diff --git a/.gitattributes b/.gitattributes index 49c0bd2f2..4dc3fad6b 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1,2 +1,3 @@ data/united-states-commutes/census_tracts_2010.csv filter=lfs diff=lfs merge=lfs -text data/united-states-commutes/commute_data.csv filter=lfs diff=lfs merge=lfs -text +packrat/lib/x86_64-pc-linux-gnu/3.6.3/arrow/libs/arrow.so filter=lfs diff=lfs merge=lfs -text diff --git a/.github/workflows/aws.yaml b/.github/workflows/aws.yaml index 2eb7a489e..d2b38fda6 100644 --- a/.github/workflows/aws.yaml +++ b/.github/workflows/aws.yaml @@ -17,6 +17,8 @@ on: - 'local_install.R' - 'Dockerfile' - 'R/pkgs/**' + - '.Rprofile' + - 'packrat/**' name: Deploy to Amazon ECR diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 1bb7f2106..d117bbe7f 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -16,11 +16,17 @@ jobs: unit-tests: runs-on: ubuntu-18.04 container: - image: docker://hopkinsidd/covidscenariopipeline:latest-dataseed + image: docker://hopkinsidd/covidscenariopipeline:latest-dev options: --user root steps: - name: Checkout uses: actions/checkout@v2 + - name: Set up Rprofile + run: cp Docker.Rprofile $HOME/.Rprofile + shell: bash + - name: Install SEIR package + run: /home/app/python_venv/bin/python setup.py install + shell: bash - name: Run pytest SEIR run: | /home/app/python_venv/bin/pytest SEIR/ @@ -35,15 +41,16 @@ jobs: setwd("R/pkgs/hospitalization") devtools::test(stop_on_failure=TRUE) shell: Rscript {0} - - name: Run report_generation tests + - name: Run report.generation tests run: | - setwd("R/pkgs/report_generation") + setwd("R/pkgs/report.generation") devtools::test(stop_on_failure=TRUE) shell: Rscript {0} - name: Run integration tests env: CENSUS_API_KEY: ${{ secrets.CENSUS_API_KEY }} run: | + git lfs pull Rscript local_install.R cd test /home/app/python_venv/bin/pytest run_tests.py diff --git a/.github/workflows/dockerhub.yaml b/.github/workflows/dockerhub.yaml index 6c7dac9e7..2df58ad8c 100644 --- a/.github/workflows/dockerhub.yaml +++ b/.github/workflows/dockerhub.yaml @@ -15,6 +15,8 @@ on: - 'local_install.R' - 'Dockerfile' - 'R/pkgs/**' + - '.Rprofile' + - 'packrat/**' name: Deploy to DockerHub diff --git a/.gitignore b/.gitignore index 46ce9c10a..c1f898e2e 100644 --- a/.gitignore +++ b/.gitignore @@ -54,3 +54,9 @@ vignettes/*.pdf # R Environment Variables .Renviron +packrat/lib*/ + +# Python build dirs +build/ +dist/ +SEIR.egg-info/ diff --git a/Docker.Rprofile b/Docker.Rprofile new file mode 100644 index 000000000..1a521a314 --- /dev/null +++ b/Docker.Rprofile @@ -0,0 +1,6 @@ +#### -- Packrat Autoloader (version 0.5.0) -- #### +working_directory <- getwd() +setwd("/home/app/") +source("/home/app/packrat/init.R") +setwd(working_directory) +#### -- End Packrat Autoloader -- #### diff --git a/Dockerfile b/Dockerfile index 43ad05613..e35bf12f1 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,7 +1,7 @@ FROM ubuntu:18.04 USER root -ENV TERM dumb +ENV TERM linux # set locale info RUN apt-get update && apt-get install -y locales && locale-gen en_US.UTF-8 @@ -31,6 +31,7 @@ RUN apt-get update && \ less \ build-essential \ git-core \ + git-lfs \ curl \ pandoc \ pandoc-citeproc \ @@ -87,13 +88,14 @@ ENV HOME /home/app ##### # TODO: use packrat (or something else) for R package management -COPY packages.R $HOME -RUN Rscript packages.R - -# install custom packages from R/pkgs/** -COPY local_install.R $HOME -COPY R/pkgs $HOME/R/pkgs -RUN Rscript local_install.R +RUN Rscript -e "install.packages('packrat',repos='https://cloud.r-project.org/')" \ + && Rscript -e "install.packages('arrow',repos='https://cloud.r-project.org/')" \ + && Rscript -e 'arrow::install_arrow()' +COPY --chown=app:app packrat $HOME/packrat +COPY --chown=app:app Docker.Rprofile $HOME/.Rprofile +COPY --chown=app:app R/pkgs $HOME/R/pkgs +RUN Rscript -e 'packrat::restore()' +RUN Rscript -e 'install.packages(list.files("R/pkgs",full.names=TRUE),type="source",repos=NULL)' ##### @@ -105,9 +107,10 @@ ENV PYTHON_VERSION 3.7.6 ENV PYTHON_VENV_DIR $HOME/python_venv ENV PATH $PYENV_ROOT/shims:$PYENV_ROOT/bin:$PATH + RUN git clone git://github.com/yyuu/pyenv.git $HOME/.pyenv \ && rm -rf $HOME/.pyenv/.git \ - && pyenv install -s $PYTHON_VERSION --verbose \ + && env PYTHON_CONFIGURE_OPTS="--enable-shared" pyenv install -s $PYTHON_VERSION --verbose \ && pyenv rehash \ && echo 'eval "$(pyenv init -)"' >> ~/.bashrc \ && echo "PS1=\"\[\e]0;\u@\h: \w\a\] \h:\w\$ \"" >> ~/.bashrc diff --git a/R/pkgs/covidcommon/R/config.R b/R/pkgs/covidcommon/R/config.R index 2e2468118..713cd7649 100644 --- a/R/pkgs/covidcommon/R/config.R +++ b/R/pkgs/covidcommon/R/config.R @@ -27,8 +27,15 @@ load_config <- function(fname) { fname <- Sys.getenv("CONFIG_PATH") } if (!missing(fname)) { - handlers <- list(map=function(x) { class(x) <- "config"; return(x) }) - return(tryCatch(yaml.load_file(fname, handlers=handlers), error = function(e) { stop(paste("Could not find file: ", fname)) })) + + if(!file.exists(fname)){ + stop(paste("Could not find file:", fname)) + } else{ + handlers <- list(map=function(x) { class(x) <- "config"; return(x) }) + return(tryCatch(yaml.load_file(fname, handlers=handlers), error = function(e) { stop(paste("The config", fname, "has an error. Run `yaml::read_yaml(", fname, ")` to identify the line where the error exists.")) })) + } + + } else { return(NA) } diff --git a/R/pkgs/covidcommon/tests/testthat/test-load_config.R b/R/pkgs/covidcommon/tests/testthat/test-load_config.R index 820ec9373..c68a0c303 100644 --- a/R/pkgs/covidcommon/tests/testthat/test-load_config.R +++ b/R/pkgs/covidcommon/tests/testthat/test-load_config.R @@ -1,6 +1,8 @@ test_that("load_config works", { fname <- tempfile() cat("yaml: TRUE\n",file=fname) + fname_bad <- tempfile() + cat("yaml: TRUE\n yaml2: FALSE\n",file=fname_bad) expect_equal( load_config(fname)$yaml, @@ -9,7 +11,7 @@ test_that("load_config works", { expect_error( load_config(";lkdjaoijdsfjoasidjfaoiwerfj q2fu8ja8erfasdiofj aewr;fj aff409a urfa8rf a';j 38i a0fuadf "), - "file" + "Could not find" ) expect_error( @@ -21,6 +23,11 @@ test_that("load_config works", { load_config(fname)$missing$badkey, "missing" ) + + expect_error( + load_config(fname_bad), + "yaml::read_yaml" + ) }) test_that("as_evaled_expression works", { diff --git a/R/pkgs/hospitalization/DESCRIPTION b/R/pkgs/hospitalization/DESCRIPTION index 6ce9629d1..75fbd295b 100644 --- a/R/pkgs/hospitalization/DESCRIPTION +++ b/R/pkgs/hospitalization/DESCRIPTION @@ -23,3 +23,4 @@ Description: Generate hospitalization scenarios corresponding to the infection s License: What license it uses Encoding: UTF-8 LazyData: true +RoxygenNote: 7.1.0 diff --git a/R/pkgs/hospitalization/NAMESPACE b/R/pkgs/hospitalization/NAMESPACE index 325e04448..3f542112c 100644 --- a/R/pkgs/hospitalization/NAMESPACE +++ b/R/pkgs/hospitalization/NAMESPACE @@ -1,4 +1,5 @@ -# Generated by roxygen2: fake comment so roxygen2 overwrites silently. -exportPattern("^[^\\.]") +# Generated by roxygen2: do not edit by hand -importFrom(foreach,"%dopar%") +export(build_hospdeath_geoid_fixedIFR_par) +export(build_hospdeath_par) +export(create_delay_frame) diff --git a/R/pkgs/hospitalization/R/hospdeath.R b/R/pkgs/hospitalization/R/hospdeath.R index fb91f6b05..97cbf0c41 100644 --- a/R/pkgs/hospitalization/R/hospdeath.R +++ b/R/pkgs/hospitalization/R/hospdeath.R @@ -108,7 +108,7 @@ create_delay_frame <- function(data, name, local_config){ geoid %in% all_geoids ) %>% dplyr::arrange(geoid,time) %>% - ungroup() + dplyr::ungroup() data <- dplyr::arrange(data,geoid,time) @@ -120,6 +120,9 @@ create_delay_frame <- function(data, name, local_config){ return(data) } + + + hosp_create_delay_frame <- function(X, p_X, data_, X_pars, varname) { X_ <- rbinom(length(data_[[X]]),data_[[X]],p_X) rc <- data.table::data.table( @@ -237,9 +240,11 @@ build_hospdeath_par <- function(p_hosp, time_ventdur_pars = log(17), cores=8, root_out_dir='hospitalization', - use_parquet = FALSE) { + use_parquet = FALSE, + start_sim = 1, + num_sims = -1) { - n_sim <- length(list.files(data_dir)) + n_sim <- ifelse(num_sims < 0, length(list.files(data_dir)), num_sims) print(paste("Creating cluster with",cores,"cores")) doParallel::registerDoParallel(cores) @@ -251,7 +256,8 @@ build_hospdeath_par <- function(p_hosp, pkgs <- c("dplyr", "readr", "data.table", "tidyr", "hospitalization") foreach::foreach(s=seq_len(n_sim), .packages=pkgs) %dopar% { - dat_ <- hosp_load_scenario_sim(data_dir,s, + sim_id <- start_sim + s - 1 + dat_ <- hosp_load_scenario_sim(data_dir,sim_id, keep_compartments = "diffI", geoid_len = 5, use_parquet = use_parquet) %>% @@ -293,24 +299,22 @@ build_hospdeath_par <- function(p_hosp, mutate(date_inds = as.integer(time - min(time) + 1), geo_ind = as.numeric(as.factor(geoid))) %>% arrange(geo_ind, date_inds) %>% - group_by(geo_ind) %>% - group_map(function(.x,.y){ + split(.$geo_ind) %>% + purrr::map_dfr(function(.x){ .x$hosp_curr <- cumsum(.x$incidH) - lag(cumsum(.x$incidH), n=R_delay_,default=0) .x$icu_curr <- cumsum(.x$incidICU) - lag(cumsum(.x$incidICU), n=ICU_dur_,default=0) .x$vent_curr <- cumsum(.x$incidVent) - lag(cumsum(.x$incidVent), n=Vent_dur_) - .x$geo_ind <- .y$geo_ind return(.x) }) %>% - do.call(what=rbind) %>% replace_na( list(vent_curr = 0, icu_curr = 0, hosp_curr = 0)) %>% arrange(date_inds, geo_ind) - write_hosp_output(root_out_dir, data_dir, dscenario_name, s, res, use_parquet) + write_hosp_output(root_out_dir, data_dir, dscenario_name, sim_id, res, use_parquet) NULL } doParallel::stopImplicitCluster() @@ -351,9 +355,11 @@ build_hospdeath_geoid_fixedIFR_par <- function( time_ventdur_pars = log(17), cores=8, root_out_dir='hospitalization', - use_parquet = FALSE + use_parquet = FALSE, + start_sim = 1, + num_sims = -1 ) { - n_sim <- length(list.files(data_dir)) + n_sim <- ifelse(num_sims < 0, length(list.files(data_dir)), num_sims) print(paste("Creating cluster with",cores,"cores")) doParallel::registerDoParallel(cores) @@ -370,7 +376,8 @@ build_hospdeath_geoid_fixedIFR_par <- function( pkgs <- c("dplyr", "readr", "data.table", "tidyr", "hospitalization") foreach::foreach(s=seq_len(n_sim), .packages=pkgs) %dopar% { - dat_I <- hosp_load_scenario_sim(data_dir,s, + sim_id <- start_sim + s - 1 + dat_I <- hosp_load_scenario_sim(data_dir, sim_id, keep_compartments = "diffI", geoid_len=5, use_parquet = use_parquet) %>% @@ -384,6 +391,11 @@ build_hospdeath_geoid_fixedIFR_par <- function( left_join(prob_dat, by="geoid") # Add time things + dat_Mild <- hosp_create_delay_frame('incidI', + dat_$p_mild_inf, + dat_, + c(-Inf, 0), # we dont want a delay here, so this is the easiest way + "Mild") dat_H <- hosp_create_delay_frame('incidI', dat_$p_hosp_inf_scaled, dat_, @@ -404,13 +416,14 @@ build_hospdeath_geoid_fixedIFR_par <- function( ICU_dur_ <- round(exp(time_ICUdur_pars[1])) Vent_dur_ <- round(exp(time_ventdur_pars[1])) - stopifnot(is.data.table(dat_I) && is.data.table(dat_H) && is.data.table(data_ICU) && is.data.table(data_Vent) && is.data.table(data_D)) + stopifnot(is.data.table(dat_I) && is.data.table(dat_Mild) && is.data.table(dat_H) && is.data.table(data_ICU) && is.data.table(data_Vent) && is.data.table(data_D)) # Using `merge` instead of full_join for performance reasons res <- Reduce(function(x, y, ...) merge(x, y, all = TRUE, ...), - list(dat_I, dat_H, data_ICU, data_Vent, data_D)) %>% + list(dat_I, dat_Mild, dat_H, data_ICU, data_Vent, data_D)) %>% replace_na( list(incidI = 0, + incidMild = 0, incidH = 0, incidICU = 0, incidVent = 0, @@ -423,25 +436,23 @@ build_hospdeath_geoid_fixedIFR_par <- function( mutate(date_inds = as.integer(time - min(time) + 1), geo_ind = as.numeric(as.factor(geoid))) %>% arrange(geo_ind, date_inds) %>% - group_by(geo_ind) %>% - group_map(function(.x,.y){ + split(.$geo_ind) %>% + purrr::map_dfr(function(.x){ .x$hosp_curr <- cumsum(.x$incidH) - lag(cumsum(.x$incidH), n=R_delay_,default=0) .x$icu_curr <- cumsum(.x$incidICU) - lag(cumsum(.x$incidICU), n=ICU_dur_,default=0) .x$vent_curr <- cumsum(.x$incidVent) - lag(cumsum(.x$incidVent), n=Vent_dur_) - .x$geo_ind <- .y$geo_ind return(.x) }) %>% - do.call(what=rbind) %>% replace_na( list(vent_curr = 0, icu_curr = 0, hosp_curr = 0)) %>% arrange(date_inds, geo_ind) - write_hosp_output(root_out_dir, data_dir, dscenario_name, s, res, use_parquet) + write_hosp_output(root_out_dir, data_dir, dscenario_name, sim_id, res, use_parquet) NULL } doParallel::stopImplicitCluster() diff --git a/R/pkgs/report_generation/DESCRIPTION b/R/pkgs/report.generation/DESCRIPTION similarity index 100% rename from R/pkgs/report_generation/DESCRIPTION rename to R/pkgs/report.generation/DESCRIPTION diff --git a/R/pkgs/report_generation/NAMESPACE b/R/pkgs/report.generation/NAMESPACE similarity index 97% rename from R/pkgs/report_generation/NAMESPACE rename to R/pkgs/report.generation/NAMESPACE index 8be994750..28a146e83 100644 --- a/R/pkgs/report_generation/NAMESPACE +++ b/R/pkgs/report.generation/NAMESPACE @@ -24,6 +24,7 @@ export(make_scn_time_summary_table) export(make_scn_time_summary_table_withVent) export(plot_event_time_by_geoid) export(plot_geounit_attack_rate_map) +export(plot_geounit_map) export(plot_hist_incidHosp_state) export(plot_line_hospPeak_time_county) export(plot_model_vs_obs) @@ -35,4 +36,3 @@ export(plot_ts_incid_inf_state_sample) export(print_pretty_date) export(print_pretty_date_short) export(reference_chunk) -export(setup_testing_environment) diff --git a/R/pkgs/report_generation/R/DataLoadFuncs.R b/R/pkgs/report.generation/R/DataLoadFuncs.R similarity index 97% rename from R/pkgs/report_generation/R/DataLoadFuncs.R rename to R/pkgs/report.generation/R/DataLoadFuncs.R index e9c98576e..a7498a9ab 100644 --- a/R/pkgs/report_generation/R/DataLoadFuncs.R +++ b/R/pkgs/report.generation/R/DataLoadFuncs.R @@ -118,7 +118,7 @@ load_scenario_sims_filtered <- function(scenario_dir, ##' with pre and post filters ##' ##' @param scenario_dir the subdirectory containing this scenario -##' @param name_filter function that +##' @param name_filter string that indicates which pdeath level to import (from the hosp filename) ##' @param post_process function that does processing after ##' @param geoid_len in defined, this we want to make geoids all the same length ##' @param padding_char character to add to the front of geoids if fixed length @@ -172,8 +172,8 @@ load_hosp_sims_filtered <- function(scenario_dir, read_file(files[i]) %>% padfn %>% - post_process(...) %>% - mutate(sim_num = i) + mutate(sim_num = i) %>% + post_process(...) } rc<- dplyr::bind_rows(rc) diff --git a/R/pkgs/report.generation/R/ReportBuildUtils-deprecated.R b/R/pkgs/report.generation/R/ReportBuildUtils-deprecated.R new file mode 100644 index 000000000..22320a446 --- /dev/null +++ b/R/pkgs/report.generation/R/ReportBuildUtils-deprecated.R @@ -0,0 +1,720 @@ +##' +##' Deprecated plot figure showing 15 random sims of incident infections +##' +##' @param hosp_state_totals totals for hospitalization related data for state for all pdeath +##' @param pdeath_level level of IFR (string: high/med/low) for filtering hospitalization data +##' @param num_sims the number of simulations to show +##' @param sim_start_date simulation start date as character string "2020-01-01" +##' @param sim_end_date simulation end date as character string +##' @param plot_intervention logical indicating whether to plot grey box over a single intervention period -- will need to adapt if we want to show multiple intervention periods +##' @param interv_start_date intervention start date as character string +##' @param interv_end_date intervention end date as character string +##' +##' @return plot with 15 random simulations of incident infection +##' +##' @export +##' +plot_ts_incid_inf_state_sample <- function (hosp_state_totals, + num_sims = 15, + pdeath_level = "high", ## doesn't really matter since data should be the same for infections + scenario_labels, + scenario_cols, + sim_start_date, + sim_end_date, + plot_intervention = FALSE, ## may not want to plot if it is too complicated + interv_start_date = NA, + interv_end_date = NA) { + + + ##TODO: Make this so each scenario does not use the same sims...though should not matter. + to_plt <- hosp_state_totals %>% + dplyr::filter(pdeath==pdeath_level, + sim_num %in% sample(unique(sim_num), + min(num_sims, length(unique(sim_num))), + replace=FALSE)) %>% + dplyr::mutate(scenario_name = factor(scenario_name, + levels = scenario_labels, + labels = scenario_labels), + sim_num = factor(sim_num)) + + rc <- ggplot(data=to_plt, + aes(x = time, color = scenario_name, + group = interaction(sim_num, scenario_name))) + + geom_line(aes(y = NincidInf), alpha=0.2, size=.75) + + scale_y_continuous("Daily incident infections", labels = scales::comma) + + scale_x_date(date_breaks = "1 month", + date_labels = "%b", + limits = c(lubridate::ymd(sim_start_date), lubridate::ymd(sim_end_date))) + + scale_color_manual("Scenario", + labels = scenario_labels, + values = scenario_cols) + + theme_minimal() + + theme(axis.title.x = element_blank(), + legend.position = "bottom", + legend.title = element_blank()) + + guides(color = guide_legend(nrow = 2, override.aes = list(alpha=1))) + + + if(plot_intervention){ + interv_dates <- data.frame(xmin = lubridate::ymd(interv_start_date), + xmax = lubridate::ymd(interv_end_date), + ymin = 0, + ymax = 1.05*max(to_plt$NincidInf)) + + rc <- rc + + geom_rect(data = interv_dates, inherit.aes = FALSE, + aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax), + color = "grey", fill = "grey", alpha = 0.33) + } + + return(rc) + +} + +##' +##' Deprecated plot figure showing 15 random sims of incident infections +##' +##' @param hosp_state_totals totals for hospitalization related data for state for all pdeath +##' @param pdeath_level level of IFR (string: high/med/low) for filtering hospitalization data +##' @param num_sims the number of simulations to show +##' @param sim_start_date simulation start date as character string "2020-01-01" +##' @param sim_end_date simulation end date as character string +##' @param plot_intervention logical indicating whether to plot grey box over a single intervention period -- will need to adapt if we want to show multiple intervention periods +##' @param interv_start_date intervention start date as character string +##' @param interv_end_date intervention end date as character string +##' +##' @return plot with 15 random simulations of incident deaths +##' +##' @export +##' +plot_ts_incid_death_state_sample_allPdeath <- function (hosp_state_totals, + num_sims = 15, + scenario_labels, + scenario_cols, + pdeath_level = "high", + pdeath_labels, + sim_start_date, + sim_end_date, + plot_intervention = FALSE, ## may not want to plot if it is too complicated + interv_start_date = NA, + interv_end_date = NA) { + + + ##TODO: Make this so each scenario does not use the same sims...though should not matter. + to_plt <- hosp_state_totals %>% + dplyr::filter(sim_num %in% sample(unique(sim_num), + min(num_sims, length(unique(sim_num))), + replace=FALSE)) %>% + dplyr::mutate(scenario_name = factor(scenario_name, + levels = scenario_labels), + pdeath = factor(pdeath, + levels = pdeath_level, + labels = pdeath_labels), + sim_num = factor(sim_num)) + + rc <- ggplot(data=to_plt, + aes(x=time, color=scenario_name, + group=interaction(sim_num, scenario_name))) + + geom_line(aes(y=NincidDeath), alpha=0.2, size=.75) + + scale_y_continuous("Daily incident deaths", labels = scales::comma) + + scale_x_date(date_breaks = "2 months", + date_labels = "%b", + limits = c(lubridate::ymd(sim_start_date), lubridate::ymd(sim_end_date))) + + scale_color_manual("Scenario", + labels = scenario_labels, + values = scenario_cols) + + theme_minimal() + + theme(axis.title.x = element_blank(), + legend.position = "bottom", + legend.title = element_blank()) + + facet_wrap(~pdeath, nrow = 1) + + guides(color = guide_legend(nrow = 2, override.aes = list(alpha=1))) + + + if(plot_intervention){ + interv_dates <- data.frame(xmin = lubridate::ymd(interv_start_date), + xmax = lubridate::ymd(interv_end_date), + ymin = 0, + ymax = 1.05*max(to_plt$NincidDeath)) + + rc <- rc + + geom_rect(data = interv_dates, inherit.aes = FALSE, + aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax), + color = "grey", fill = "grey", alpha = 0.33) + } + + return(rc) + +} + +##' +##' Plot figure showing histogram of peak hospital occupancy by a certain date +##' +##' @param hosp_cty_peaks totals for hospitalization related data for state for all pdeath +##' @param cty_names Dataframe with county geoid and county name +##' @param pdeath_level level of IFR (string: high/med/low) for filtering hospitalization data +##' @param scenario_labels scenario names from config +##' @param scenario_cols scenario colors from config +##' @param start_date date to filter to start search for peak timing (character string) +##' @param end_date date to filter to end search for peak timing (character string) +##' +##' @return plot of distribution of peak timing across simulations by county +##' +##' @export +##' +plot_line_hospPeak_time_county <- function (hosp_cty_peaks, + cty_names, + pdeath_level = "high", ## choose one to display peak + scenario_labels, + scenario_cols, + start_date, + end_date) { + pdeath_level <- match.arg(pdeath_level) + start_date <- lubridate::ymd(start_date) + end_date <- lubridate::ymd(end_date) + + ##TODO: Make this so each scenario does not use the same sims...though should not matter. + to_plt <- hosp_cty_peaks %>% + dplyr::filter(pdeath %in% pdeath_level, + scenario_name %in% scenario_labels) %>% + group_by(geoid, scenario_name) %>% + dplyr::summarise(mean_pkTime = as.Date(mean(time)), + median_pkTime = as.Date(median(time)), + low_pkTime = as.Date(quantile(time, probs=.25, type=1)), + hi_pkTime = as.Date(quantile(time, probs=.75, type=1))) %>% + ungroup %>% + dplyr::mutate(scenario_name = factor(scenario_name, + levels = scenario_labels, + labels = scenario_labels)) %>% + dplyr::left_join(cty_names, by = c("geoid")) + + if(length(scenario_labels)==1){ + rc <- ggplot(data=to_plt, + aes(x = reorder(countyname, -as.numeric(mean_pkTime)), + y = mean_pkTime, ymin = low_pkTime, ymax = hi_pkTime)) + + geom_pointrange() + + scale_y_date("Date of peak hospital occupancy", + date_breaks = "1 months", + date_labels = "%b", + # limits = c(as.Date(start_date), as.Date(end_date)) + ) + + xlab("County") + + theme_bw() + + theme(axis.text.x = element_text(angle = 90, hjust = 1), legend.position = "bottom") + + coord_flip() + } else{ + rc <- ggplot(data=to_plt, + aes(x = reorder(countyname, -as.numeric(mean_pkTime)), + y = mean_pkTime, ymin = low_pkTime, ymax = hi_pkTime, + color = scenario_name)) + + geom_pointrange() + + scale_y_date("Date of peak hospital occupancy", + date_breaks = "1 months", + date_labels = "%b", + # limits = c(as.Date(start_date), as.Date(end_date)) + ) + + xlab("County") + + scale_color_manual("Scenario", + labels = scenario_labels, + values = scenario_cols) + + theme_bw() + + theme(axis.text.x = element_text(angle = 90, hjust = 1), legend.position = "bottom") + + coord_flip() + } + + + return(rc) + +} + + +##' +##' Deprecated plot figure showing median and IQR time series for the state for one scenario +##' +##' @param hosp_state_totals totals for hospitalization related data for state for all pdeath +##' @param geodata geodata object from load_config +##' @param pdeath_level level of IFR (string: high/med/low) for filtering hospitalization data -- choose 1 +##' @param scenario_label which scenario name from config +##' @param scenario_col which scenario color from config +##' @param sim_start_date simulation start date as character string "2020-01-01" +##' @param sim_end_date simulation end date as character string +##' @param plot_intervention logical indicating whether to plot grey box over a single intervention period -- will need to adapt if we want to show multiple intervention periods +##' @param interv_start_date intervention start date as character string +##' @param interv_end_date intervention end date as character string +##' +##' @return plot state time series median and IQR +##' +##' @export +##' +plot_ts_incid_ar_state <- function (hosp_state_totals, + geodata, + pop_name, + pdeath_level = "high", ## doesn't really matter since data should be the same for infections + scenario_label, + scenario_col, + sim_start_date, + sim_end_date, + plot_intervention = FALSE, ## may not want to plot if it is too complicated + interv_start_date = NA, + interv_end_date = NA) { + + geopop <- geodata %>% + dplyr::filter(include_in_report) %>% + dplyr::select(!! pop_name) %>% + unlist %>% unname + + ##TODO: Make this so each scenario does not use the same sims...though should not matter. + to_plt <- hosp_state_totals %>% + dplyr::filter(pdeath==pdeath_level) %>% + dplyr::mutate(scenario_name = factor(scenario_name, + levels = scenario_label, + labels = scenario_label)) %>% + dplyr::filter(scenario_name == scenario_label) %>% + dplyr::group_by(time) %>% + dplyr::summarise(NincidInf_med = median(NincidInf), NincidInf_mean = mean(NincidInf), NincidInf_lo = quantile(NincidInf, .25), NincidInf_hi = quantile(NincidInf, .75)) %>% + dplyr::mutate(pop = sum(geopop)) %>% + dplyr::mutate(AR_med = NincidInf_med/pop*100000, + AR_mean = NincidInf_mean/pop*100000, + AR_lo = NincidInf_lo/pop*100000, + AR_hi = NincidInf_hi/pop*100000) + + rc <- ggplot(data=to_plt, aes(x = time)) + + geom_pointrange(aes(y = AR_med, ymin = AR_lo, ymax = AR_hi), colour = scenario_col) + + scale_y_continuous("Infections per 100K", labels = scales::comma) + + scale_x_date(date_breaks = "1 month", + date_labels = "%b", + limits = c(lubridate::ymd(sim_start_date), lubridate::ymd(sim_end_date))) + + theme_minimal() + + theme(axis.title.x = element_blank(), + legend.position = "bottom", + legend.title = element_blank()) + + + if(plot_intervention){ + interv_dates <- data.frame(xmin = lubridate::ymd(interv_start_date), + xmax = lubridate::ymd(interv_end_date), + ymin = 0, + ymax = 1.05*max(to_plt$AR_hi)) + + rc <- rc + + geom_rect(data = interv_dates, inherit.aes = FALSE, + aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax), + color = "grey", fill = "grey", alpha = 0.33) + } + + return(rc) + +} + + +##' +##' Deprecated: Make statewide table of infections, hosp, ICU, deaths for given scenario. There is a function now make_scn_state_table_withVent that replaces this one. +##' +##' @param current_scenario text string of scenario label for which to build table +##' @param hosp_state_totals totals for hospitalization related data for state for all pdeath +##' @param table_dates formatted table_dates object +##' @param pdeath_labels pdeath formatted labels +##' @param pdeath_filecode pdeath file column codes +##' +##' @return state scenario table +##' +##' @export +##' +make_scn_state_table <- function(current_scenario, + hosp_state_totals, + table_dates, + pdeath_labels, + pdeath_filecode){ + +ci_lo = 0.025 +ci_hi = 0.975 + +if (length(pdeath_filecode)==1) { + stop("Currently does not support single values of pdeath") +} + +tmp <- data.frame(name=c("INFECTIONS", + "HOSPITALIZATIONS\n total", "", "", + " daily peak admissions", "", "", + " daily peak capacity", "", "", + "ICU \n total", "", "", + " daily peak admissions", "", "", + " daily peak capacity", "", "", + "DEATHS\n total", "", "")) +tmp$name <- as.character(tmp$name) +table_dates <- as.Date(table_dates) + +for(i in 1:length(table_dates)){ + xx <- hosp_state_totals %>% + filter(!is.na(time) & scenario_name==current_scenario) %>% + filter(time <= table_dates[i]) %>% + group_by(scenario_name, pdeath, sim_num) %>% + summarize( + TotalIncidInf = sum(NincidInf, na.rm = TRUE), + TotalIncidHosp = sum(NincidHosp, na.rm = TRUE), + TotalIncidICU = sum(NincidICU, na.rm = TRUE), + TotalIncidDeath = sum(NincidDeath, na.rm = TRUE), + maxHospAdm = max(NincidHosp, na.rm=TRUE), + maxICUAdm = max(NincidICU, na.rm=TRUE), + maxHospCap = max(NhospCurr, na.rm = TRUE), + maxICUCap = max(NICUCurr, na.rm=TRUE) + ) %>% + ungroup() %>% + group_by(scenario_name, pdeath) %>% + summarize( + nIncidInf_final = mean(TotalIncidInf), + nIncidInf_lo = quantile(TotalIncidInf, ci_lo), + nIncidInf_hi = quantile(TotalIncidInf, ci_hi), + nIncidHosp_final = mean(TotalIncidHosp), + nIncidHosp_lo = quantile(TotalIncidHosp, ci_lo), + nIncidHosp_hi = quantile(TotalIncidHosp, ci_hi), + pIncidHosp_final = mean(maxHospAdm), + pIncidHosp_lo = quantile(maxHospAdm, ci_lo), + pIncidHosp_hi = quantile(maxHospAdm, ci_hi), + nIncidICU_final = mean(TotalIncidICU), + nIncidICU_lo = quantile(TotalIncidICU, ci_lo), + nIncidICU_hi = quantile(TotalIncidICU, ci_hi), + pIncidICU_final = mean(maxICUAdm), + pIncidICU_lo = quantile(maxICUAdm, ci_lo), + pIncidICU_hi = quantile(maxICUAdm, ci_hi), + nIncidDeath_final = mean(TotalIncidDeath), + nIncidDeath_lo = quantile(TotalIncidDeath, ci_lo), + nIncidDeath_hi = quantile(TotalIncidDeath, ci_hi), + nCurrHosp_final = mean(maxHospCap), + nCurrHosp_lo = quantile(maxHospCap, ci_lo), + nCurrHosp_hi = quantile(maxHospCap, ci_hi), + nCurrICU_final = mean(maxICUCap), + nCurrICU_lo = quantile(maxICUCap, ci_lo), + nCurrICU_hi = quantile(maxICUCap, ci_hi)) %>% + ungroup() %>% + mutate(pdeath = pdeath_labels[match(pdeath, pdeath_filecode)]) + + + tmp <- bind_cols(tmp, + xx %>% filter(pdeath==pdeath_labels[1]) %>% + mutate(ci = make_CI(nIncidInf_lo, nIncidInf_hi), + est = conv_round(nIncidInf_final), + lvl = paste0("total inc infections"), + pdeath = "") %>% ## infections have no pdeath + select(lvl, est, ci, pdeath) %>% + bind_rows(xx %>% + mutate(ci = make_CI(nIncidHosp_lo, nIncidHosp_hi), + est = conv_round(nIncidHosp_final), + lvl = paste0("total inc hosp", pdeath)) %>% + select(lvl, est, ci, pdeath) %>% arrange(pdeath)) %>% + bind_rows(xx %>% + mutate(ci = make_CI(pIncidHosp_lo, pIncidHosp_hi), + est = conv_round(pIncidHosp_final), + lvl = paste0("peak inc hosp", pdeath)) %>% + select(lvl, est, ci, pdeath) %>% arrange(pdeath)) %>% + bind_rows(xx %>% + mutate(ci = make_CI(nCurrHosp_lo, nCurrHosp_hi), + est = conv_round(nCurrHosp_final), + lvl = paste0("peak hosp cap", pdeath)) %>% + select(lvl, est, ci, pdeath) %>% arrange(pdeath)) %>% + bind_rows(xx %>% + mutate(ci = make_CI(nIncidICU_lo, nIncidICU_hi), + est = conv_round(nIncidICU_final), + lvl = paste0("total inc ICU", pdeath)) %>% + select(lvl, est, ci, pdeath) %>% arrange(pdeath)) %>% + bind_rows(xx %>% + mutate(ci = make_CI(pIncidICU_lo, pIncidICU_hi), + est = conv_round(pIncidICU_final), + lvl = paste0("peak inc ICU", pdeath)) %>% + select(lvl, est, ci, pdeath) %>% arrange(pdeath)) %>% + bind_rows(xx %>% + mutate(ci = make_CI(nCurrICU_lo, nCurrICU_hi), + est = conv_round(nCurrICU_final), + lvl = paste0("peak ICU cap", pdeath)) %>% + select(lvl, est, ci, pdeath) %>% arrange(pdeath)) %>% + bind_rows(xx %>% + mutate(ci = make_CI(nIncidDeath_lo, nIncidDeath_hi), + est = conv_round(nIncidDeath_final), + lvl = paste0("total inc death", pdeath)) %>% + select(lvl, est, ci, pdeath) %>% arrange(pdeath)) + ) +} + + +tlabels <- c(" ", "IFR") +nlabels <- c("name", "pdeath", "est", "ci") + +for(i in 1:length(table_dates)){ + tlabels <- c(tlabels, + paste0(print_pretty_date_short(table_dates[i]), "\nmean "), + "\n 95% PI") + if(i>1){nlabels <- c(nlabels, paste0("est", i-1), paste0("ci", i-1))} +} +names(tlabels) <- nlabels + +flextable::flextable(tmp[,nlabels]) %>% + flextable::set_header_labels(values=tlabels) %>% + flextable::valign(valign="bottom") %>% + flextable::colformat_num(digits=0) %>% + flextable::autofit() + +} + +##' +##' Deprecated function makes a summary table for an entire state. There is a function make_scn_time_summary_table_withVent that replaces this one. +##' +##' @param hosp_state_totals contains the relevant hospital data +##' @param period_breaks the dates to break up the display periods. +##' @param pi_low low side of the prediction interval +##' @param pi_high high side of the prediction interval +##' @param round_digit what level to round to +##' +##' @export +##' +make_scn_time_summary_table <- function(hosp_state_totals, + period_breaks, + pi_low = 0.025, + pi_high = 0.975, + round_digit=-2) { + ##Make the period ranges and labels + period_breaks <- sort(as.Date(period_breaks)) #out of order leads to bad things.... + period_breaks <- c(min(hosp_state_totals$time)-1, as.Date(period_breaks), max(hosp_state_totals$time)+1) + + len <- length(period_breaks) + lbls <- sprintf("%s-%s", format(period_breaks[1:(len-1)], "%b %d"), + format(period_breaks[2:len], "%b %d")) + + ## Build the table with summaries of all of the periods in it. + tbl_df <- hosp_state_totals %>% + mutate(period = cut(time, period_breaks, labels=lbls)) %>% + group_by(period, scenario_name, sim_num) %>% #summarize totals in periods by scenario + summarize(PeriodInf = sum(NincidInf), + PeriodDeath = sum(NincidDeath), + PeriodHosp = sum(NincidHosp), + PeriodPkHosp = max(NhospCurr), + PeriodICU = sum(NincidICU), + PeriodPkICU = max(NICUCurr)) %>% + ungroup %>% + group_by(period, scenario_name) %>% #now get means and prediction intervals + summarize(PeriodInfPILow = round(quantile(PeriodInf, probs = c(pi_low)),digits = round_digit), + PeriodDeathPILow = round(quantile(PeriodDeath, probs = c(pi_low)),digits = round_digit), + PeriodHospPILow = round(quantile(PeriodHosp, probs = c(pi_low)),digits = round_digit), + PeriodPkHospPILow = round(quantile(PeriodPkHosp, probs = c(pi_low)),digits = round_digit), + PeriodICUPILow = round(quantile(PeriodICU, probs = c(pi_low)),digits = round_digit), + PeriodPkICUPILow = round(quantile(PeriodPkICU, probs = c(pi_low)),digits = round_digit), + PeriodInfPIHigh = round(quantile(PeriodInf, probs = c(pi_high)),digits = round_digit), + PeriodDeathPIHigh = round(quantile(PeriodDeath, probs = c(pi_high)),digits = round_digit), + PeriodHospPIHigh = round(quantile(PeriodHosp, probs = c(pi_high)),digits = round_digit), + PeriodPkHospPIHigh = round(quantile(PeriodPkHosp, probs = c(pi_high)),digits = round_digit), + PeriodICUPIHigh = round(quantile(PeriodICU, probs = c(pi_high)),digits = round_digit), + PeriodPkICUPIHigh = round(quantile(PeriodPkICU, probs = c(pi_high)),digits = round_digit), + PeriodInf = round(mean(PeriodInf),digits = round_digit), + PeriodDeath = round(mean(PeriodDeath),digits = round_digit), + PeriodHosp = round(mean(PeriodHosp),digits = round_digit), + PeriodPkHosp = round(mean(PeriodPkHosp),digits = round_digit), + PeriodICU = round(mean(PeriodICU),digits = round_digit), + PeriodPkICU = round(mean(PeriodPkICU), digits = round_digit)) %>% + ungroup() %>% ##make hi/low into CIs + mutate(PeriodInfPI = paste(format(PeriodInfPILow,big.mark=","), format(PeriodInfPIHigh,big.mark=","), sep="-"), + PeriodDeathPI = paste(format(PeriodDeathPILow,big.mark=","), format(PeriodDeathPIHigh,big.mark=","), sep="-"), + PeriodHospPI = paste(format(PeriodHospPILow,big.mark=","), format(PeriodHospPIHigh,big.mark=","), sep="-"), + PeriodPkHospPI = paste(format(PeriodPkHospPILow,big.mark=","), format(PeriodPkHospPIHigh,big.mark=","), sep="-"), + PeriodICUPI = paste(format(PeriodICUPILow,big.mark=","), format(PeriodICUPIHigh,big.mark=","), sep="-"), + PeriodPkICUPI = paste(format(PeriodPkICUPILow,big.mark=","), format(PeriodPkICUPIHigh,big.mark=","), sep="-"),) %>% + select(-PeriodInfPILow, -PeriodInfPIHigh, + -PeriodDeathPILow, -PeriodDeathPIHigh, + -PeriodHospPILow, -PeriodHospPIHigh, + -PeriodPkHospPILow, -PeriodPkHospPIHigh, + -PeriodICUPILow, -PeriodICUPIHigh, + -PeriodPkICUPILow, -PeriodPkICUPIHigh) + + + tmp<-sprintf("%s_%s", rep(lbls, each=2),c("mean","95% PI")) + + + ##inellegant but should work + tbl_df <- + bind_rows(tbl_df%>%select(period,scenario_name, PeriodInf, PeriodInfPI)%>%mutate(outcome="Infections in Period")%>% + rename(mean=PeriodInf,`95% PI`=PeriodInfPI), + tbl_df%>%select(period,scenario_name, PeriodDeath, PeriodDeathPI)%>%mutate(outcome="Deaths in Period")%>% + rename(mean=PeriodDeath,`95% PI`=PeriodDeathPI), + tbl_df%>%select(period,scenario_name, PeriodHosp, PeriodHospPI)%>%mutate(outcome="Hospital Admissions in Period")%>% + rename(mean=PeriodHosp,`95% PI`=PeriodHospPI), + tbl_df%>%select(period,scenario_name, PeriodPkHosp, PeriodPkHospPI)%>%mutate(outcome="Peak Hospital Occupancy in Period")%>% + rename(mean=PeriodPkHosp,`95% PI`=PeriodPkHospPI), + tbl_df%>%select(period,scenario_name, PeriodICU, PeriodICUPI)%>%mutate(outcome="ICU Admissions in Period")%>% + rename(mean=PeriodICU,`95% PI`=PeriodICUPI), + tbl_df%>%select(period,scenario_name, PeriodPkICU, PeriodPkICUPI)%>%mutate(outcome="Peak ICU Occupancy in Period")%>% + rename(mean=PeriodPkICU,`95% PI`=PeriodPkICUPI)) %>% + mutate(period=as.character(period)) %>% + pivot_wider(names_from=period, values_from = c(mean,`95% PI`), names_sep=".")%>% + setNames(nm = sub("(.*)\\.(.*)", "\\2_\\1", names(.)))%>% + select(outcome,scenario_name,all_of(tmp)) + + #tells how to group columns + tbl_df <- flextable::as_grouped_data(tbl_df,groups="outcome") + tmp <- is.na(tbl_df$scenario_name) + tbl_df$scenario_name[tmp] <-tbl_df$outcome[tmp] + tbl_df <- tbl_df%>%select(-outcome) + typology<-data_frame(col_keys=colnames(tbl_df), + colA=c("",rep(lbls,each=2)), + colB=c("",rep(c("mean","95% PI"),length(lbls)))) + + + flx <- flextable::flextable(tbl_df) %>% + flextable::colformat_num(digits=0)%>% + #flextable::merge_v(j="outcome")%>% + flextable::autofit(add_w=.05)%>% + flextable::valign(valign="top") %>% + flextable::set_header_df(mapping = typology, key = "col_keys" )%>% + #flextable::merge_h(part="header")%>% + flextable::bold(j=sprintf("%s_mean",lbls))%>% + flextable::bold(part="header",bold=TRUE)%>% + flextable::bold(j = 1, i =which(tmp), bold = TRUE, part = "body" )%>% + flextable::align(i=1,align = "center", part="header") %>% + flextable::align(i=2,j=which(typology$colB=="mean"), align = "right", part="header") %>% + flextable::hline(i=2, part="header", border = officer::fp_border())%>% + flextable::hline_top(part="header", border = officer::fp_border(width=2))%>% + flextable::border(i=which(tmp), border.top = officer::fp_border(col="grey")) + + return(flx) + +} + + +##' +##' Deprecated: Returns a ggplot object giving a boxplot of the range of N +##' within each time period. +##' +##' @param hosp_state_totals, +##' +##' @param df a data frame with columns time, sim_num, scenario_name and N +##' @param period_breaks the dates to break up the display periods. +##' @param stat either "identity" or "peak" [TODO:extend options] +##' +##' @export +boxplot_by_timeperiod <- function(df, + period_breaks, + stat="identity", + scenario_labels, # TODO provide default arguments + scenario_colors # TODO provide default arguments + ) { + + period_breaks <- c(min(df$time)-1, as.Date(period_breaks), max(df$time)+1) + len <- length(period_breaks) + lbls <- sprintf("%s-%s", format(period_breaks[1:(len-1)], "%b %d"), + format(period_breaks[2:len], "%b %d")) + + if(stat=="identity") { + sum_func <- function(x){x} + } else if(stat=="peak") { + sum_func <- function (x) { + x %>% + group_by(sim_num, scenario_name, period) %>% + summarize(N=max(N)) %>% + ungroup() + } + } else { + stop("Unknown statistic") + } + + + rc <- df %>% + mutate(period = cut(time, period_breaks, labels=lbls)) %>% + sum_func %>% + ggplot(aes(x=reorder(period, desc(period)), y=N, fill=scenario_name)) + + geom_boxplot(outlier.alpha = .1, outlier.size=.2) + + facet_wrap(~scenario_name,ncol=1)+ + scale_fill_manual("Scenario", + labels = scenario_labels, + values = scenario_colors) + + coord_flip() + + return(rc) + +} + + +##' +##' Depracated: Plot heatmap of excess variables, as absolute number +##' (default), per-capita number needed, or % over threshold. There is a function +##' plot_needs_relative_to_threshold_heatmap that replaces this one. +##' +##' @param hosp_dat timeseries with incident and cumulative hospitalizations, ICU admissions, etc. +##' @param current_scenario text string of scenario label to plot +##' @param type either "absolute", for total number excess; "percent", for percent excess; or "per-capita" for number excess per 10,000 population +##' @param threshold named vector of threshold value for given variable +##' @param shp shapefile with GEOID names +##' @param varname character string of variable name to plot from hosp data +##' @param varlabel character string of variable name for plot legend +##' @param geodata geodata object from load_config; only needed if type="per-capita" +##' @param popnodes name of pop variable in geodata; only needed if type="per-capita" +##' @param trunc_value value at which to truncate values for easy plotting; if null, defaults to max +##' +##' @export +##' +make_excess_heatmap <- function(hosp_dat, + current_scenario, + type, + threshold, + shp, + varname, + varlabel, + geodata = NULL, + popnodes = config$spatial_setup$popnodes, + trunc_value = NULL){ + + shp$threshold <- threshold[match(shp$geoid, names(threshold))] + + hosp_dat <- hosp_dat %>% + dplyr::filter(scenario_name == current_scenario) %>% + rename(var = !!varname) + + if(type=="per-capita"){ + plt_dat <- as.data.frame(shp) %>% + select(geoid, name, threshold) %>% + left_join(geodata %>% dplyr::rename(pop=!!popnodes) %>% dplyr::select(geoid, pop), by="geoid") %>% + arrange(name) + + hosp_dat <- hosp_dat %>% + left_join(plt_dat, by="geoid") %>% + replace_na(list(threshold=0)) %>% + mutate(exc_raw = var - threshold, + exc_abs = ifelse(exc_raw>0, exc_raw, NA), + exc_toplot = exc_abs / pop * 10000) + } + if(type=="absolute"){ + plt_dat <- as.data.frame(shp) %>% + select(geoid, name, threshold) %>% + arrange(name) + + hosp_dat <- hosp_dat %>% + left_join(plt_dat, by="geoid") %>% + replace_na(list(threshold=0)) %>% + mutate(exc_raw = var - threshold, + exc_toplot = ifelse(exc_raw>0, exc_raw, NA)) + } + if(type=="percent"){ + plt_dat <- as.data.frame(shp) %>% + select(geoid, name, threshold) %>% + arrange(name) + + hosp_dat <- hosp_dat %>% + left_join(plt_dat, by="geoid") %>% + replace_na(list(threshold=0)) %>% + mutate(exc_raw = var - threshold, + exc_abs = ifelse(exc_raw>0, exc_raw, NA), + exc_toplot = exc_abs / threshold * 100) + } + + if(!is.null(trunc_value)){ + hosp_dat$exc_toplot <- ifelse(hosp_dat$exc_toplot>trunc_value, trunc_value, hosp_dat$exc_toplot) + } + + rc <- ggplot(hosp_dat, aes(x=time, y=name, fill=exc_toplot)) + + geom_tile() + + scale_fill_viridis_c(option = "magma", direction = -1, na.value = "white", name = varlabel) + + theme_minimal() + + xlab("") + + ylab("") + + scale_x_date(date_breaks = "2 weeks", + date_labels = "%b %d") + + theme(axis.text.x = element_text(angle=45, vjust = 0.5)) + + return(rc) +} \ No newline at end of file diff --git a/R/pkgs/report_generation/R/ReportBuildUtils.R b/R/pkgs/report.generation/R/ReportBuildUtils.R similarity index 53% rename from R/pkgs/report_generation/R/ReportBuildUtils.R rename to R/pkgs/report.generation/R/ReportBuildUtils.R index 15b8db285..704679dbb 100644 --- a/R/pkgs/report_generation/R/ReportBuildUtils.R +++ b/R/pkgs/report.generation/R/ReportBuildUtils.R @@ -168,159 +168,6 @@ plot_ts_hosp_state_sample <- function (hosp_state_totals, -##' -##' Plot figure showing 15 random sims of incident infections -##' -##' @param hosp_state_totals totals for hospitalization related data for state for all pdeath -##' @param pdeath_level level of IFR (string: high/med/low) for filtering hospitalization data -##' @param num_sims the number of simulations to show -##' @param sim_start_date simulation start date as character string "2020-01-01" -##' @param sim_end_date simulation end date as character string -##' @param plot_intervention logical indicating whether to plot grey box over a single intervention period -- will need to adapt if we want to show multiple intervention periods -##' @param interv_start_date intervention start date as character string -##' @param interv_end_date intervention end date as character string -##' -##' @return plot with 15 random simulations of incident infection -##' -##' @export -##' -plot_ts_incid_inf_state_sample <- function (hosp_state_totals, - num_sims = 15, - pdeath_level = "high", ## doesn't really matter since data should be the same for infections - scenario_labels, - scenario_cols, - sim_start_date, - sim_end_date, - plot_intervention = FALSE, ## may not want to plot if it is too complicated - interv_start_date = NA, - interv_end_date = NA) { - - - ##TODO: Make this so each scenario does not use the same sims...though should not matter. - to_plt <- hosp_state_totals %>% - dplyr::filter(pdeath==pdeath_level, - sim_num %in% sample(unique(sim_num), - min(num_sims, length(unique(sim_num))), - replace=FALSE)) %>% - dplyr::mutate(scenario_name = factor(scenario_name, - levels = scenario_labels, - labels = scenario_labels), - sim_num = factor(sim_num)) - - rc <- ggplot(data=to_plt, - aes(x = time, color = scenario_name, - group = interaction(sim_num, scenario_name))) + - geom_line(aes(y = NincidInf), alpha=0.2, size=.75) + - scale_y_continuous("Daily incident infections", labels = scales::comma) + - scale_x_date(date_breaks = "1 month", - date_labels = "%b", - limits = c(lubridate::ymd(sim_start_date), lubridate::ymd(sim_end_date))) + - scale_color_manual("Scenario", - labels = scenario_labels, - values = scenario_cols) + - theme_minimal() + - theme(axis.title.x = element_blank(), - legend.position = "bottom", - legend.title = element_blank()) + - guides(color = guide_legend(nrow = 2, override.aes = list(alpha=1))) - - - if(plot_intervention){ - interv_dates <- data.frame(xmin = lubridate::ymd(interv_start_date), - xmax = lubridate::ymd(interv_end_date), - ymin = 0, - ymax = 1.05*max(to_plt$NincidInf)) - - rc <- rc + - geom_rect(data = interv_dates, inherit.aes = FALSE, - aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax), - color = "grey", fill = "grey", alpha = 0.33) - } - - return(rc) - -} - - - -##' -##' Plot figure showing 15 random sims of incident infections -##' -##' @param hosp_state_totals totals for hospitalization related data for state for all pdeath -##' @param pdeath_level level of IFR (string: high/med/low) for filtering hospitalization data -##' @param num_sims the number of simulations to show -##' @param sim_start_date simulation start date as character string "2020-01-01" -##' @param sim_end_date simulation end date as character string -##' @param plot_intervention logical indicating whether to plot grey box over a single intervention period -- will need to adapt if we want to show multiple intervention periods -##' @param interv_start_date intervention start date as character string -##' @param interv_end_date intervention end date as character string -##' -##' @return plot with 15 random simulations of incident deaths -##' -##' @export -##' -plot_ts_incid_death_state_sample_allPdeath <- function (hosp_state_totals, - num_sims = 15, - scenario_labels, - scenario_cols, - pdeath_level = "high", - pdeath_labels, - sim_start_date, - sim_end_date, - plot_intervention = FALSE, ## may not want to plot if it is too complicated - interv_start_date = NA, - interv_end_date = NA) { - - - ##TODO: Make this so each scenario does not use the same sims...though should not matter. - to_plt <- hosp_state_totals %>% - dplyr::filter(sim_num %in% sample(unique(sim_num), - min(num_sims, length(unique(sim_num))), - replace=FALSE)) %>% - dplyr::mutate(scenario_name = factor(scenario_name, - levels = scenario_labels), - pdeath = factor(pdeath, - levels = pdeath_level, - labels = pdeath_labels), - sim_num = factor(sim_num)) - - rc <- ggplot(data=to_plt, - aes(x=time, color=scenario_name, - group=interaction(sim_num, scenario_name))) + - geom_line(aes(y=NincidDeath), alpha=0.2, size=.75) + - scale_y_continuous("Daily incident deaths", labels = scales::comma) + - scale_x_date(date_breaks = "2 months", - date_labels = "%b", - limits = c(lubridate::ymd(sim_start_date), lubridate::ymd(sim_end_date))) + - scale_color_manual("Scenario", - labels = scenario_labels, - values = scenario_cols) + - theme_minimal() + - theme(axis.title.x = element_blank(), - legend.position = "bottom", - legend.title = element_blank()) + - facet_wrap(~pdeath, nrow = 1) + - guides(color = guide_legend(nrow = 2, override.aes = list(alpha=1))) - - - if(plot_intervention){ - interv_dates <- data.frame(xmin = lubridate::ymd(interv_start_date), - xmax = lubridate::ymd(interv_end_date), - ymin = 0, - ymax = 1.05*max(to_plt$NincidDeath)) - - rc <- rc + - geom_rect(data = interv_dates, inherit.aes = FALSE, - aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax), - color = "grey", fill = "grey", alpha = 0.33) - } - - return(rc) - -} - - - ##' ##' Plot figure showing histogram of cumulative hospitalizations (or other incident outcome) by a certain date ##' @@ -379,88 +226,6 @@ plot_hist_incidHosp_state <- function (hosp_state_totals, } - -##' -##' Plot figure showing histogram of peak hospital occupancy by a certain date -##' -##' @param hosp_cty_peaks totals for hospitalization related data for state for all pdeath -##' @param cty_names Dataframe with county geoid and county name -##' @param pdeath_level level of IFR (string: high/med/low) for filtering hospitalization data -##' @param scenario_labels scenario names from config -##' @param scenario_cols scenario colors from config -##' @param start_date date to filter to start search for peak timing (character string) -##' @param end_date date to filter to end search for peak timing (character string) -##' -##' @return plot of distribution of peak timing across simulations by county -##' -##' @export -##' -plot_line_hospPeak_time_county <- function (hosp_cty_peaks, - cty_names, - pdeath_level = "high", ## choose one to display peak - scenario_labels, - scenario_cols, - start_date, - end_date) { - pdeath_level <- match.arg(pdeath_level) - start_date <- lubridate::ymd(start_date) - end_date <- lubridate::ymd(end_date) - - ##TODO: Make this so each scenario does not use the same sims...though should not matter. - to_plt <- hosp_cty_peaks %>% - dplyr::filter(pdeath %in% pdeath_level, - scenario_name %in% scenario_labels) %>% - group_by(geoid, scenario_name) %>% - dplyr::summarise(mean_pkTime = as.Date(mean(time)), - median_pkTime = as.Date(median(time)), - low_pkTime = as.Date(quantile(time, probs=.25, type=1)), - hi_pkTime = as.Date(quantile(time, probs=.75, type=1))) %>% - ungroup %>% - dplyr::mutate(scenario_name = factor(scenario_name, - levels = scenario_labels, - labels = scenario_labels)) %>% - dplyr::left_join(cty_names, by = c("geoid")) - - if(length(scenario_labels)==1){ - rc <- ggplot(data=to_plt, - aes(x = reorder(countyname, -as.numeric(mean_pkTime)), - y = mean_pkTime, ymin = low_pkTime, ymax = hi_pkTime)) + - geom_pointrange() + - scale_y_date("Date of peak hospital occupancy", - date_breaks = "1 months", - date_labels = "%b", - # limits = c(as.Date(start_date), as.Date(end_date)) - ) + - xlab("County") + - theme_bw() + - theme(axis.text.x = element_text(angle = 90, hjust = 1), legend.position = "bottom") + - coord_flip() - } else{ - rc <- ggplot(data=to_plt, - aes(x = reorder(countyname, -as.numeric(mean_pkTime)), - y = mean_pkTime, ymin = low_pkTime, ymax = hi_pkTime, - color = scenario_name)) + - geom_pointrange() + - scale_y_date("Date of peak hospital occupancy", - date_breaks = "1 months", - date_labels = "%b", - # limits = c(as.Date(start_date), as.Date(end_date)) - ) + - xlab("County") + - scale_color_manual("Scenario", - labels = scenario_labels, - values = scenario_cols) + - theme_bw() + - theme(axis.text.x = element_text(angle = 90, hjust = 1), legend.position = "bottom") + - coord_flip() - } - - - return(rc) - -} - - ##' ##' Plot map showing infections per 10K on a specific date for one scenario ##' @@ -516,286 +281,61 @@ plot_geounit_attack_rate_map <- function (cum_inf_geounit_dates, } - ##' -##' Plot figure showing median and IQR time series for the state for one scenario +##' Plot map showing chosen variable per 10K on a specific date for one scenario (blue/green color scale) ##' -##' @param hosp_state_totals totals for hospitalization related data for state for all pdeath -##' @param geodata geodata object from load_config -##' @param pdeath_level level of IFR (string: high/med/low) for filtering hospitalization data -- choose 1 -##' @param scenario_label which scenario name from config -##' @param scenario_col which scenario color from config -##' @param sim_start_date simulation start date as character string "2020-01-01" -##' @param sim_end_date simulation end date as character string -##' @param plot_intervention logical indicating whether to plot grey box over a single intervention period -- will need to adapt if we want to show multiple intervention periods -##' @param interv_start_date intervention start date as character string -##' @param interv_end_date intervention end date as character string +##' @param cum_inf_geounit_dates dataframe produced by load_cum_inf_geounit_dates, with cumulative totals/averages on a given date +##' @param plot_var name of the variable of which to plot intensity +##' @param geodata as loaded by skeleton +##' @param shp shapefile with geounits +##' @param scenariolabel scenario label character string +##' @param popnodes name of pop variable in geodata +##' @param display_date string of display date for map +##' @param viridis_palette character string of viridis palette ##' -##' @return plot state time series median and IQR +##' @return map by geounit, filled by variable per 10K at a specific date for a single scenario ##' ##' @export ##' -plot_ts_incid_ar_state <- function (hosp_state_totals, - geodata, - pop_name, - pdeath_level = "high", ## doesn't really matter since data should be the same for infections - scenario_label, - scenario_col, - sim_start_date, - sim_end_date, - plot_intervention = FALSE, ## may not want to plot if it is too complicated - interv_start_date = NA, - interv_end_date = NA) { - - geopop <- geodata %>% - dplyr::filter(include_in_report) %>% - dplyr::select(!! pop_name) %>% - unlist %>% unname - - ##TODO: Make this so each scenario does not use the same sims...though should not matter. - to_plt <- hosp_state_totals %>% - dplyr::filter(pdeath==pdeath_level) %>% - dplyr::mutate(scenario_name = factor(scenario_name, - levels = scenario_label, - labels = scenario_label)) %>% - dplyr::filter(scenario_name == scenario_label) %>% - dplyr::group_by(time) %>% - dplyr::summarise(NincidInf_med = median(NincidInf), NincidInf_mean = mean(NincidInf), NincidInf_lo = quantile(NincidInf, .25), NincidInf_hi = quantile(NincidInf, .75)) %>% - dplyr::mutate(pop = sum(geopop)) %>% - dplyr::mutate(AR_med = NincidInf_med/pop*100000, - AR_mean = NincidInf_mean/pop*100000, - AR_lo = NincidInf_lo/pop*100000, - AR_hi = NincidInf_hi/pop*100000) - - rc <- ggplot(data=to_plt, aes(x = time)) + - geom_pointrange(aes(y = AR_med, ymin = AR_lo, ymax = AR_hi), colour = scenario_col) + - scale_y_continuous("Infections per 100K", labels = scales::comma) + - scale_x_date(date_breaks = "1 month", - date_labels = "%b", - limits = c(lubridate::ymd(sim_start_date), lubridate::ymd(sim_end_date))) + - theme_minimal() + - theme(axis.title.x = element_blank(), - legend.position = "bottom", - legend.title = element_blank()) - - - if(plot_intervention){ - interv_dates <- data.frame(xmin = lubridate::ymd(interv_start_date), - xmax = lubridate::ymd(interv_end_date), - ymin = 0, - ymax = 1.05*max(to_plt$AR_hi)) - - rc <- rc + - geom_rect(data = interv_dates, inherit.aes = FALSE, - aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax), - color = "grey", fill = "grey", alpha = 0.33) +plot_geounit_map <- function(cum_inf_geounit_dates, + plot_var, + geodata, + shp, + legend_name = "Value per 10K", + scenariolabel = config$report$formatting$scenario_labels[1], + popnodes = config$spatial_setup$popnodes, + display_date, + clims = NULL){ + + display_date <- as.Date(display_date) + + shp$geoid <- as.character(shp$geoid) + to_plt <- cum_inf_geounit_dates %>% + dplyr::filter(scenario_name == scenariolabel, + time == display_date) %>% + left_join(geodata) %>% + dplyr::rename(pop = !!popnodes, plot_var = !!plot_var) %>% group_by(geoid) %>% + dplyr::summarise(geoid_rate = mean(plot_var/pop) * 10000) %>% + ungroup + + plot_shp <- left_join(shp, to_plt, by = "geoid") + + if(is.null(clims)){ + clims = range(plot_shp$geoid_rate, na.rm=TRUE) } - + + rc <- ggplot(plot_shp) + + geom_sf(aes(fill = geoid_rate)) + + theme_minimal() + + scale_fill_gradientn(name=legend_name, colors = RColorBrewer::brewer.pal(9, "YlGnBu"), limits=clims) + + ggtitle(paste0(scenariolabel, ": ", print_pretty_date_short(display_date))) + + theme(axis.title.x = element_blank(), axis.text.x = element_blank(), + axis.ticks.x = element_blank(), axis.title.y = element_blank(), + axis.text.y = element_blank(), panel.grid.major = element_blank(), + panel.grid.minor = element_blank(), panel.border = element_blank(), + axis.ticks.y = element_blank()) return(rc) - -} - - -# #### This function isn't working quite right -# ##' -# ##' Plot modeling assumption parameter distributions -# ##' -# ##' @param name parameter name -# ##' @param config config file -# ##' @return plot of distribution of peak timing across simulations by county -# ##' -# ##' @export -# ##' -# plot_model_parameter_distributions <- function(name, config){ -# dist_plot_config <- config$report$plot_settings$parameters_to_display -# local_config <- dist_plot_config[[name]] -# value <- config[[local_config$type]][['parameters']][[name]] -# if((length(value) > 1) & ("distribution" %in% names(value))){ -# if(value$distribution == 'uniform' ){ -# value <- runif(1e5,covidcommon::as_evaled_expression(value$low) , covidcommon::as_evaled_expression(value$high)) -# } -# } else { -# value <- covidcommon::as_evaled_expression(value) -# } -# if('transform' %in% names(dist_plot_config[[name]]) ){ -# if(dist_plot_config[[name]][['transform']] == 'invert'){ -# value = 1 / value -# } -# } -# rval <- NaN -# if(local_config$distribution == "lnormal"){ -# rval <- (rlnorm(1e5,meanlog= value[1], sdlog = value[2])) -# } -# if(local_config$distribution == "exp"){ -# rval <- rexp(1e5,rate=value) -# } -# if(local_config$distribution == "gamma"){ -# all_compartments <<- unique(report.generation::load_scenario_sims_filtered('mid-west-coast-AZ-NV_CaliforniaMild/',pre_process=function(x){return(x[x$time==x$time[1], ])})$comp) -# number_compartments <<- sum(grepl("I[[:digit:]]+",all_compartments)) -# if(length(value)==1){ -# value[2] <- 1/value[1] -# } -# rval <- rgamma(1e5,shape=value/number_compartments,scale=number_compartments) -# } -# if('xlim' %in% names(local_config)){ -# plt <- plot(density(rval),main = local_config$formal_name, xlab = local_config$xlab, bty='n', xlim=as.numeric(local_config$xlim)) -# } else { -# plt <- plot(density(rval),main = local_config$formal_name, xlab = local_config$xlab, bty='n') -# } -# return(plt) -# } - - - - -##' -##' Make statewide table of infections, hosp, ICU, deaths for given scenario -##' -##' @param current_scenario text string of scenario label for which to build table -##' @param hosp_state_totals totals for hospitalization related data for state for all pdeath -##' @param table_dates formatted table_dates object -##' @param pdeath_labels pdeath formatted labels -##' @param pdeath_filecode pdeath file column codes -##' -##' @return state scenario table -##' -##' @export -##' -make_scn_state_table <- function(current_scenario, - hosp_state_totals, - table_dates, - pdeath_labels, - pdeath_filecode){ - -ci_lo = 0.025 -ci_hi = 0.975 - -if (length(pdeath_filecode)==1) { - stop("Currently does not support single values of pdeath") -} - -tmp <- data.frame(name=c("INFECTIONS", - "HOSPITALIZATIONS\n total", "", "", - " daily peak admissions", "", "", - " daily peak capacity", "", "", - "ICU \n total", "", "", - " daily peak admissions", "", "", - " daily peak capacity", "", "", - "DEATHS\n total", "", "")) -tmp$name <- as.character(tmp$name) -table_dates <- as.Date(table_dates) - -for(i in 1:length(table_dates)){ - xx <- hosp_state_totals %>% - filter(!is.na(time) & scenario_name==current_scenario) %>% - filter(time <= table_dates[i]) %>% - group_by(scenario_name, pdeath, sim_num) %>% - summarize( - TotalIncidInf = sum(NincidInf, na.rm = TRUE), - TotalIncidHosp = sum(NincidHosp, na.rm = TRUE), - TotalIncidICU = sum(NincidICU, na.rm = TRUE), - TotalIncidDeath = sum(NincidDeath, na.rm = TRUE), - maxHospAdm = max(NincidHosp, na.rm=TRUE), - maxICUAdm = max(NincidICU, na.rm=TRUE), - maxHospCap = max(NhospCurr, na.rm = TRUE), - maxICUCap = max(NICUCurr, na.rm=TRUE) - ) %>% - ungroup() %>% - group_by(scenario_name, pdeath) %>% - summarize( - nIncidInf_final = mean(TotalIncidInf), - nIncidInf_lo = quantile(TotalIncidInf, ci_lo), - nIncidInf_hi = quantile(TotalIncidInf, ci_hi), - nIncidHosp_final = mean(TotalIncidHosp), - nIncidHosp_lo = quantile(TotalIncidHosp, ci_lo), - nIncidHosp_hi = quantile(TotalIncidHosp, ci_hi), - pIncidHosp_final = mean(maxHospAdm), - pIncidHosp_lo = quantile(maxHospAdm, ci_lo), - pIncidHosp_hi = quantile(maxHospAdm, ci_hi), - nIncidICU_final = mean(TotalIncidICU), - nIncidICU_lo = quantile(TotalIncidICU, ci_lo), - nIncidICU_hi = quantile(TotalIncidICU, ci_hi), - pIncidICU_final = mean(maxICUAdm), - pIncidICU_lo = quantile(maxICUAdm, ci_lo), - pIncidICU_hi = quantile(maxICUAdm, ci_hi), - nIncidDeath_final = mean(TotalIncidDeath), - nIncidDeath_lo = quantile(TotalIncidDeath, ci_lo), - nIncidDeath_hi = quantile(TotalIncidDeath, ci_hi), - nCurrHosp_final = mean(maxHospCap), - nCurrHosp_lo = quantile(maxHospCap, ci_lo), - nCurrHosp_hi = quantile(maxHospCap, ci_hi), - nCurrICU_final = mean(maxICUCap), - nCurrICU_lo = quantile(maxICUCap, ci_lo), - nCurrICU_hi = quantile(maxICUCap, ci_hi)) %>% - ungroup() %>% - mutate(pdeath = pdeath_labels[match(pdeath, pdeath_filecode)]) - - - tmp <- bind_cols(tmp, - xx %>% filter(pdeath==pdeath_labels[1]) %>% - mutate(ci = make_CI(nIncidInf_lo, nIncidInf_hi), - est = conv_round(nIncidInf_final), - lvl = paste0("total inc infections"), - pdeath = "") %>% ## infections have no pdeath - select(lvl, est, ci, pdeath) %>% - bind_rows(xx %>% - mutate(ci = make_CI(nIncidHosp_lo, nIncidHosp_hi), - est = conv_round(nIncidHosp_final), - lvl = paste0("total inc hosp", pdeath)) %>% - select(lvl, est, ci, pdeath) %>% arrange(pdeath)) %>% - bind_rows(xx %>% - mutate(ci = make_CI(pIncidHosp_lo, pIncidHosp_hi), - est = conv_round(pIncidHosp_final), - lvl = paste0("peak inc hosp", pdeath)) %>% - select(lvl, est, ci, pdeath) %>% arrange(pdeath)) %>% - bind_rows(xx %>% - mutate(ci = make_CI(nCurrHosp_lo, nCurrHosp_hi), - est = conv_round(nCurrHosp_final), - lvl = paste0("peak hosp cap", pdeath)) %>% - select(lvl, est, ci, pdeath) %>% arrange(pdeath)) %>% - bind_rows(xx %>% - mutate(ci = make_CI(nIncidICU_lo, nIncidICU_hi), - est = conv_round(nIncidICU_final), - lvl = paste0("total inc ICU", pdeath)) %>% - select(lvl, est, ci, pdeath) %>% arrange(pdeath)) %>% - bind_rows(xx %>% - mutate(ci = make_CI(pIncidICU_lo, pIncidICU_hi), - est = conv_round(pIncidICU_final), - lvl = paste0("peak inc ICU", pdeath)) %>% - select(lvl, est, ci, pdeath) %>% arrange(pdeath)) %>% - bind_rows(xx %>% - mutate(ci = make_CI(nCurrICU_lo, nCurrICU_hi), - est = conv_round(nCurrICU_final), - lvl = paste0("peak ICU cap", pdeath)) %>% - select(lvl, est, ci, pdeath) %>% arrange(pdeath)) %>% - bind_rows(xx %>% - mutate(ci = make_CI(nIncidDeath_lo, nIncidDeath_hi), - est = conv_round(nIncidDeath_final), - lvl = paste0("total inc death", pdeath)) %>% - select(lvl, est, ci, pdeath) %>% arrange(pdeath)) - ) -} - - -tlabels <- c(" ", "IFR") -nlabels <- c("name", "pdeath", "est", "ci") - -for(i in 1:length(table_dates)){ - tlabels <- c(tlabels, - paste0(print_pretty_date_short(table_dates[i]), "\nmean "), - "\n 95% PI") - if(i>1){nlabels <- c(nlabels, paste0("est", i-1), paste0("ci", i-1))} -} -names(tlabels) <- nlabels - -flextable::flextable(tmp[,nlabels]) %>% - flextable::set_header_labels(values=tlabels) %>% - flextable::valign(valign="bottom") %>% - flextable::colformat_num(digits=0) %>% - flextable::autofit() - -} - +} ##' @@ -976,127 +516,6 @@ make_scn_state_table_withVent <- function(current_scenario, } -##' -##' Function makes a summary table for an entire state. -##' -##' @param hosp_state_totals contains the relevant hospital data -##' @param period_breaks the dates to break up the display periods. -##' @param pi_low low side of the prediction interval -##' @param pi_high high side of the prediction interval -##' @param round_digit what level to round to -##' -##' @export -##' -make_scn_time_summary_table <- function(hosp_state_totals, - period_breaks, - pi_low = 0.025, - pi_high = 0.975, - round_digit=-2) { - ##Make the period ranges and labels - period_breaks <- sort(as.Date(period_breaks)) #out of order leads to bad things.... - period_breaks <- c(min(hosp_state_totals$time)-1, as.Date(period_breaks), max(hosp_state_totals$time)+1) - - len <- length(period_breaks) - lbls <- sprintf("%s-%s", format(period_breaks[1:(len-1)], "%b %d"), - format(period_breaks[2:len], "%b %d")) - - ## Build the table with summaries of all of the periods in it. - tbl_df <- hosp_state_totals %>% - mutate(period = cut(time, period_breaks, labels=lbls)) %>% - group_by(period, scenario_name, sim_num) %>% #summarize totals in periods by scenario - summarize(PeriodInf = sum(NincidInf), - PeriodDeath = sum(NincidDeath), - PeriodHosp = sum(NincidHosp), - PeriodPkHosp = max(NhospCurr), - PeriodICU = sum(NincidICU), - PeriodPkICU = max(NICUCurr)) %>% - ungroup %>% - group_by(period, scenario_name) %>% #now get means and prediction intervals - summarize(PeriodInfPILow = round(quantile(PeriodInf, probs = c(pi_low)),digits = round_digit), - PeriodDeathPILow = round(quantile(PeriodDeath, probs = c(pi_low)),digits = round_digit), - PeriodHospPILow = round(quantile(PeriodHosp, probs = c(pi_low)),digits = round_digit), - PeriodPkHospPILow = round(quantile(PeriodPkHosp, probs = c(pi_low)),digits = round_digit), - PeriodICUPILow = round(quantile(PeriodICU, probs = c(pi_low)),digits = round_digit), - PeriodPkICUPILow = round(quantile(PeriodPkICU, probs = c(pi_low)),digits = round_digit), - PeriodInfPIHigh = round(quantile(PeriodInf, probs = c(pi_high)),digits = round_digit), - PeriodDeathPIHigh = round(quantile(PeriodDeath, probs = c(pi_high)),digits = round_digit), - PeriodHospPIHigh = round(quantile(PeriodHosp, probs = c(pi_high)),digits = round_digit), - PeriodPkHospPIHigh = round(quantile(PeriodPkHosp, probs = c(pi_high)),digits = round_digit), - PeriodICUPIHigh = round(quantile(PeriodICU, probs = c(pi_high)),digits = round_digit), - PeriodPkICUPIHigh = round(quantile(PeriodPkICU, probs = c(pi_high)),digits = round_digit), - PeriodInf = round(mean(PeriodInf),digits = round_digit), - PeriodDeath = round(mean(PeriodDeath),digits = round_digit), - PeriodHosp = round(mean(PeriodHosp),digits = round_digit), - PeriodPkHosp = round(mean(PeriodPkHosp),digits = round_digit), - PeriodICU = round(mean(PeriodICU),digits = round_digit), - PeriodPkICU = round(mean(PeriodPkICU), digits = round_digit)) %>% - ungroup() %>% ##make hi/low into CIs - mutate(PeriodInfPI = paste(format(PeriodInfPILow,big.mark=","), format(PeriodInfPIHigh,big.mark=","), sep="-"), - PeriodDeathPI = paste(format(PeriodDeathPILow,big.mark=","), format(PeriodDeathPIHigh,big.mark=","), sep="-"), - PeriodHospPI = paste(format(PeriodHospPILow,big.mark=","), format(PeriodHospPIHigh,big.mark=","), sep="-"), - PeriodPkHospPI = paste(format(PeriodPkHospPILow,big.mark=","), format(PeriodPkHospPIHigh,big.mark=","), sep="-"), - PeriodICUPI = paste(format(PeriodICUPILow,big.mark=","), format(PeriodICUPIHigh,big.mark=","), sep="-"), - PeriodPkICUPI = paste(format(PeriodPkICUPILow,big.mark=","), format(PeriodPkICUPIHigh,big.mark=","), sep="-"),) %>% - select(-PeriodInfPILow, -PeriodInfPIHigh, - -PeriodDeathPILow, -PeriodDeathPIHigh, - -PeriodHospPILow, -PeriodHospPIHigh, - -PeriodPkHospPILow, -PeriodPkHospPIHigh, - -PeriodICUPILow, -PeriodICUPIHigh, - -PeriodPkICUPILow, -PeriodPkICUPIHigh) - - - tmp<-sprintf("%s_%s", rep(lbls, each=2),c("mean","95% PI")) - - - ##inellegant but should work - tbl_df <- - bind_rows(tbl_df%>%select(period,scenario_name, PeriodInf, PeriodInfPI)%>%mutate(outcome="Infections in Period")%>% - rename(mean=PeriodInf,`95% PI`=PeriodInfPI), - tbl_df%>%select(period,scenario_name, PeriodDeath, PeriodDeathPI)%>%mutate(outcome="Deaths in Period")%>% - rename(mean=PeriodDeath,`95% PI`=PeriodDeathPI), - tbl_df%>%select(period,scenario_name, PeriodHosp, PeriodHospPI)%>%mutate(outcome="Hospital Admissions in Period")%>% - rename(mean=PeriodHosp,`95% PI`=PeriodHospPI), - tbl_df%>%select(period,scenario_name, PeriodPkHosp, PeriodPkHospPI)%>%mutate(outcome="Peak Hospital Occupancy in Period")%>% - rename(mean=PeriodPkHosp,`95% PI`=PeriodPkHospPI), - tbl_df%>%select(period,scenario_name, PeriodICU, PeriodICUPI)%>%mutate(outcome="ICU Admissions in Period")%>% - rename(mean=PeriodICU,`95% PI`=PeriodICUPI), - tbl_df%>%select(period,scenario_name, PeriodPkICU, PeriodPkICUPI)%>%mutate(outcome="Peak ICU Occupancy in Period")%>% - rename(mean=PeriodPkICU,`95% PI`=PeriodPkICUPI)) %>% - mutate(period=as.character(period)) %>% - pivot_wider(names_from=period, values_from = c(mean,`95% PI`), names_sep=".")%>% - setNames(nm = sub("(.*)\\.(.*)", "\\2_\\1", names(.)))%>% - select(outcome,scenario_name,all_of(tmp)) - - #tells how to group columns - tbl_df <- flextable::as_grouped_data(tbl_df,groups="outcome") - tmp <- is.na(tbl_df$scenario_name) - tbl_df$scenario_name[tmp] <-tbl_df$outcome[tmp] - tbl_df <- tbl_df%>%select(-outcome) - typology<-data_frame(col_keys=colnames(tbl_df), - colA=c("",rep(lbls,each=2)), - colB=c("",rep(c("mean","95% PI"),length(lbls)))) - - - flx <- flextable::flextable(tbl_df) %>% - flextable::colformat_num(digits=0)%>% - #flextable::merge_v(j="outcome")%>% - flextable::autofit(add_w=.05)%>% - flextable::valign(valign="top") %>% - flextable::set_header_df(mapping = typology, key = "col_keys" )%>% - #flextable::merge_h(part="header")%>% - flextable::bold(j=sprintf("%s_mean",lbls))%>% - flextable::bold(part="header",bold=TRUE)%>% - flextable::bold(j = 1, i =which(tmp), bold = TRUE, part = "body" )%>% - flextable::align(i=1,align = "center", part="header") %>% - flextable::align(i=2,j=which(typology$colB=="mean"), align = "right", part="header") %>% - flextable::hline(i=2, part="header", border = officer::fp_border())%>% - flextable::hline_top(part="header", border = officer::fp_border(width=2))%>% - flextable::border(i=which(tmp), border.top = officer::fp_border(col="grey")) - - return(flx) - -} - ##' ##' Function makes a summary table for an entire state. @@ -1337,59 +756,6 @@ plot_event_time_by_geoid <- function(hosp_county_peaks, } -##' -##' Returns a ggplot object giving a boxplot of the range of N -##' within each time period. -##' -##' @param hosp_state_totals, -##' -##' @param df a data frame with columns time, sim_num, scenario_name and N -##' @param period_breaks the dates to break up the display periods. -##' @param stat either "identity" or "peak" [TODO:extend options] -##' -##' @export -boxplot_by_timeperiod <- function(df, - period_breaks, - stat="identity", - scenario_labels, # TODO provide default arguments - scenario_colors # TODO provide default arguments - ) { - - period_breaks <- c(min(df$time)-1, as.Date(period_breaks), max(df$time)+1) - len <- length(period_breaks) - lbls <- sprintf("%s-%s", format(period_breaks[1:(len-1)], "%b %d"), - format(period_breaks[2:len], "%b %d")) - - if(stat=="identity") { - sum_func <- function(x){x} - } else if(stat=="peak") { - sum_func <- function (x) { - x %>% - group_by(sim_num, scenario_name, period) %>% - summarize(N=max(N)) %>% - ungroup() - } - } else { - stop("Unknown statistic") - } - - - rc <- df %>% - mutate(period = cut(time, period_breaks, labels=lbls)) %>% - sum_func %>% - ggplot(aes(x=reorder(period, desc(period)), y=N, fill=scenario_name)) + - geom_boxplot(outlier.alpha = .1, outlier.size=.2) + - facet_wrap(~scenario_name,ncol=1)+ - scale_fill_manual("Scenario", - labels = scenario_labels, - values = scenario_colors) + - coord_flip() - - return(rc) - -} - - ##' ##' Compare model outputs and data from CSSE ##' @@ -1504,95 +870,6 @@ plot_model_vs_obs <- function(state_hosp_totals, } -##' -##' Plot heatmap of excess variables, as absolute number -##' (default), per-capita number needed, or % over threshold -##' -##' @param hosp_dat timeseries with incident and cumulative hospitalizations, ICU admissions, etc. -##' @param current_scenario text string of scenario label to plot -##' @param type either "absolute", for total number excess; "percent", for percent excess; or "per-capita" for number excess per 10,000 population -##' @param threshold named vector of threshold value for given variable -##' @param shp shapefile with GEOID names -##' @param varname character string of variable name to plot from hosp data -##' @param varlabel character string of variable name for plot legend -##' @param geodata geodata object from load_config; only needed if type="per-capita" -##' @param popnodes name of pop variable in geodata; only needed if type="per-capita" -##' @param trunc_value value at which to truncate values for easy plotting; if null, defaults to max -##' -##' @export -##' -make_excess_heatmap <- function(hosp_dat, - current_scenario, - type, - threshold, - shp, - varname, - varlabel, - geodata = NULL, - popnodes = config$spatial_setup$popnodes, - trunc_value = NULL){ - - shp$threshold <- threshold[match(shp$geoid, names(threshold))] - - hosp_dat <- hosp_dat %>% - dplyr::filter(scenario_name == current_scenario) %>% - rename(var = !!varname) - - if(type=="per-capita"){ - plt_dat <- as.data.frame(shp) %>% - select(geoid, name, threshold) %>% - left_join(geodata %>% dplyr::rename(pop=!!popnodes) %>% dplyr::select(geoid, pop), by="geoid") %>% - arrange(name) - - hosp_dat <- hosp_dat %>% - left_join(plt_dat, by="geoid") %>% - replace_na(list(threshold=0)) %>% - mutate(exc_raw = var - threshold, - exc_abs = ifelse(exc_raw>0, exc_raw, NA), - exc_toplot = exc_abs / pop * 10000) - } - if(type=="absolute"){ - plt_dat <- as.data.frame(shp) %>% - select(geoid, name, threshold) %>% - arrange(name) - - hosp_dat <- hosp_dat %>% - left_join(plt_dat, by="geoid") %>% - replace_na(list(threshold=0)) %>% - mutate(exc_raw = var - threshold, - exc_toplot = ifelse(exc_raw>0, exc_raw, NA)) - } - if(type=="percent"){ - plt_dat <- as.data.frame(shp) %>% - select(geoid, name, threshold) %>% - arrange(name) - - hosp_dat <- hosp_dat %>% - left_join(plt_dat, by="geoid") %>% - replace_na(list(threshold=0)) %>% - mutate(exc_raw = var - threshold, - exc_abs = ifelse(exc_raw>0, exc_raw, NA), - exc_toplot = exc_abs / threshold * 100) - } - - if(!is.null(trunc_value)){ - hosp_dat$exc_toplot <- ifelse(hosp_dat$exc_toplot>trunc_value, trunc_value, hosp_dat$exc_toplot) - } - - rc <- ggplot(hosp_dat, aes(x=time, y=name, fill=exc_toplot)) + - geom_tile() + - scale_fill_viridis_c(option = "magma", direction = -1, na.value = "white", name = varlabel) + - theme_minimal() + - xlab("") + - ylab("") + - scale_x_date(date_breaks = "2 weeks", - date_labels = "%b %d") + - theme(axis.text.x = element_text(angle=45, vjust = 0.5)) - - return(rc) -} - - ##' ##' Plot heatmap of needs relative to a threshold (e.g. bed needs) ##' diff --git a/R/pkgs/report.generation/R/ReportLoadData-deprecated.R b/R/pkgs/report.generation/R/ReportLoadData-deprecated.R new file mode 100644 index 000000000..de7d9142c --- /dev/null +++ b/R/pkgs/report.generation/R/ReportLoadData-deprecated.R @@ -0,0 +1,338 @@ +##' Deprecated convenience function to load cumulative geounit hosp outcomes at a specific date for the given scenario +##' +##' @param scn_dirs paste(config$name, config$interventions$scenarios, sep = "_") character vector of scenario directory names +##' @param scenariolabels config$report$formatting$scenario_labels character vector of scenario labels +##' @param name_filter character string that filenames should match +##' @param display_date character date string for which cumulative infections should be extracted +##' @param incl_geoids character vector of geoids that are included in the report +##' @param geoid_len in defined, this we want to make geoids all the same length +##' @param padding_char character to add to the front of geoids if fixed length +##' +##' @return a data frame with columns +##' - time +##' - comp +##' - geoid +##' - N +##' - sim_num +##' - scenario_num +##' - scenario_name +##' +##' @export +load_cum_hosp_geounit_date <- function(scn_dirs, + num_files = NA, + scenariolabels = NULL, + name_filter, + display_date=config$end_date, + incl_geoids=NULL, + geoid_len = 0, + padding_char = "0", + file_extension = 'auto'){ + + if(is.null(scenariolabels)){ + warning("You have not specified scenario labels for this function. You may encounter future errors.") + } + + display_date <- as.Date(display_date) + ##filter to munge the data at the scenario level + if (!is.null(incl_geoids)) { + hosp_post_process <- function(x) { + x %>% + dplyr::filter(!is.na(time) & geoid %in% incl_geoids, time <= display_date) %>% + group_by(geoid, sim_num) %>% + dplyr::summarize(NincidDeath = sum(incidD), + NincidInf = sum(incidI), + NincidICU=sum(incidICU), + NincidHosp=sum(incidH), + NincidVent = sum(incidVent)) %>% + ungroup() + } + } else { + hosp_post_process <- function(x) { + x %>% + dplyr::filter(!is.na(time) & time <= display_date) %>% + group_by(geoid, sim_num) %>% + dplyr::summarize(NincidDeath = sum(incidD), + NincidInf = sum(incidI), + NincidICU=sum(incidICU), + NincidHosp=sum(incidH), + NincidVent = sum(incidVent)) %>% + ungroup() + } + } + + + rc <- list(length=length(scn_dirs)) + for (i in 1:length(scn_dirs)) { + rc[[i]] <- load_hosp_sims_filtered(scn_dirs[i], + num_files = num_files, + name_filter = name_filter, + post_process = hosp_post_process, + geoid_len = geoid_len, + padding_char = padding_char, + file_extension = file_extension) + rc[[i]]$scenario_num <- i + rc[[i]]$scenario_name <- scenariolabels[[i]] + } + + return(dplyr::bind_rows(rc)) +} + + + +##' Deprecated convenience function to load timeseries current hospital outcomes +##' +##' @param scn_dirs paste(config$name, config$interventions$scenarios, sep = "_") character vector of scenario directory names +##' @param scenariolabels config$report$formatting$scenario_labels character vector of scenario labels +##' @param name_filter character string that filenames should match +##' @param end_date last date to include in timeseries +##' @param incl_geoids character vector of geoids that are included in the report +##' @param geoid_len in defined, this we want to make geoids all the same length +##' @param padding_char character to add to the front of geoids if fixed length +##' +##' @return a data frame with columns +##' - time +##' - geoid +##' - NHospCurr, NICUCurr, NVentCurr +##' - sim_num +##' - scenario_num +##' - scenario_name +##' +##' @export +load_ts_current_hosp_geounit <- function(scn_dirs, + num_files = NA, + scenariolabels = NULL, + name_filter, + end_date, + incl_geoids=NULL, + geoid_len = 0, + padding_char = "0", + qlo = 0.025, + qhi= 0.975, + file_extension = 'auto') { + + if(is.null(scenariolabels)){ + warning("You have not specified scenario labels for this function. You may encounter future errors.") + } + + + ## currently too slow including the quantiles... ## + end_date <- as.Date(end_date) + ##filter to munge the data at the scenario level + if (!is.null(incl_geoids)) { + hosp_post_process <- function(x) { + x %>% + dplyr::filter(!is.na(time) & geoid %in% incl_geoids, time <= end_date) %>% + dplyr::select(time, + geoid, + sim_num, + NHospCurr = hosp_curr, + NICUCurr = icu_curr, + NVentCurr = vent_curr) %>% + group_by(sim_num, time, geoid) %>% + mutate(#NHospCurrlo = quantile(NHospCurr, qlo), + #NHospCurrhi = quantile(NHospCurr, qhi), + NHospCurr = mean(NHospCurr), + #NICUCurrlo = quantile(NICUCurr, qlo), + #NICUCurrhi = quantile(NICUCurr, qhi), + NICUCurr = mean(NICUCurr), + #NVentCurrlo = quantile(NVentCurr, qlo), + #NVentCurrhi = quantile(NVentCurr, qhi), + NVentCurr = mean(NVentCurr)) %>% + ungroup() + } + } else { + hosp_post_process <- function(x) { + x %>% + dplyr::filter(!is.na(time) & time <= end_date) %>% + dplyr::select(time, + geoid, + sim_num, + NHospCurr = hosp_curr, + NICUCurr = icu_curr, + NVentCurr = vent_curr) %>% + group_by(sim_num, time, geoid) %>% + mutate(#NHospCurrlo = quantile(NHospCurr, qlo), + #NHospCurrhi = quantile(NHospCurr, qhi), + NHospCurr = mean(NHospCurr), + #NICUCurrlo = quantile(NICUCurr, qlo), + #NICUCurrhi = quantile(NICUCurr, qhi), + NICUCurr = mean(NICUCurr), + #NVentCurrlo = quantile(NVentCurr, qlo), + #NVentCurrhi = quantile(NVentCurr, qhi), + NVentCurr = mean(NVentCurr)) %>% + ungroup() + } + } + + + rc <- list(length=length(scn_dirs)) + for (i in 1:length(scn_dirs)) { + rc[[i]] <- load_hosp_sims_filtered(scn_dirs[i], + num_files = num_files, + name_filter = name_filter, + post_process = hosp_post_process, + geoid_len = geoid_len, + padding_char = padding_char, + file_extension = file_extension) + rc[[i]]$scenario_num <- i + rc[[i]]$scenario_name <- scenariolabels[[i]] + } + + return(dplyr::bind_rows(rc)) +} + + +##' Deprecated convenience function to load peak geounit infections before a given date for the given scenarios +##' +##' @param scn_dirs paste(config$name, config$interventions$scenarios, sep = "_") character vector of scenario directory names +##' @param display_date character string for date before which infection peak should be identified +##' @param scenariolabels config$report$formatting$scenario_labels character vector of scenario labels +##' @param incl_geoids optional character vector of geoids that are included in the report, if not included, all geoids will be used +##' @param geoid_len required length of geoid +##' @param padding_char padding +##' +##' @return a data frame with columns +##' - time +##' - comp +##' - geoid +##' - N +##' - sim_num +##' - scenario_num +##' - scenario_name +##' +##' @export +load_inf_geounit_peaks_date <- function(scn_dirs, + display_date=config$end_date, + num_files = NA, + scenariolabels=NULL, + incl_geoids=NULL, + geoid_len = 0, + padding_char = "0", + file_extension = 'auto'){ + + if(is.null(scenariolabels)){ + warning("You have not specified scenario labels for this function. You may encounter future errors.") + } + + display_date <- as.Date(display_date) + inf_pre_process <- function(x) { + x %>% + dplyr::filter(comp == "diffI" & time <= display_date) + } + + if (!is.null(incl_geoids)) { + inf_post_process <- function(x) { + x %>% + ungroup %>% + dplyr::filter(!is.na(time), geoid %in% incl_geoids) %>% + group_by(geoid) %>% + dplyr::slice(which.max(N)) %>% + ungroup() + } + } else{ + inf_post_process <- function(x) { + x %>% + ungroup %>% + dplyr::filter(!is.na(time)) %>% + group_by(geoid) %>% + dplyr::slice(which.max(N)) %>% + ungroup() + } + + } + + rc <- list() + for (i in 1:length(scn_dirs)) { + rc[[i]] <- load_scenario_sims_filtered(scn_dirs[i], + num_files = num_files, + pre_process = inf_pre_process, + post_process = inf_post_process, + geoid_len = geoid_len, + padding_char = padding_char, + file_extension = file_extension) + rc[[i]]$scenario_num <- i + rc[[i]]$scenario_name <- scenariolabels[[i]] + + } + + return(dplyr::bind_rows(rc)) + +} + + +##' Deprecated convenience function to load peak geounit hospitalizations (or any other variable) by a specific date for the given scenarios +##' +##' @param scn_dirs paste(config$name, config$interventions$scenarios, sep = "_") character vector of scenario directory names +##' @param max_var character string of variable that will be maximized per geoid +##' @param display_date date before which we should search for peaks +##' @param name_filter character string that filenames should match +##' @param incl_geoids optional character vector of geoids that are included in the report, if not included, all geoids will be used +##' @param scenariolabels config$report$formatting$scenario_labels character vector of scenario labels +##' @param incl_geoids optional character vector of geoids that are included in the report, if not included, all geoids will be used +##' @param geoid_len required length of geoid +##' @param padding_char padding +##' +##' @return a data frame with columns +##' - sim_num +##' - Pk_[variableName] variable that was maximized by geoid +##' - NhospCurr number of people in hospital on a day +##' - NICUCurr number of people in ICU on a day +##' - NincidDeath number of incidence deaths on a day +##' - NincidInf number of incident infections on a day +##' - NincidICH number of incident ICUs on a day +##' @export +### all of the peak times for each sim and each county so we can make a figure for when things peak +load_hosp_geounit_peak_date <- function(scn_dirs, + max_var, + display_date = config$end_date, + num_files = NA, + name_filter, + incl_geoids = NULL, + scenariolabels = NULL, + geoid_len = 0, + padding_char = "0", + file_extension = 'auto'){ + + if(is.null(scenariolabels)){ + warning("You have not specified scenario labels for this function. You may encounter future errors.") + } + + display_date <- as.Date(display_date) + if (!is.null(incl_geoids)) { + hosp_post_process <- function(x) { + x %>% + dplyr::rename(mx_var = !!max_var) %>% + dplyr::filter(!is.na(time), geoid %in% incl_geoids, time <= display_date) %>% + group_by(geoid) %>% + dplyr::slice(which.max(mx_var)) %>% + ungroup() + } + } else { + hosp_post_process <- function(x) { + x %>% + dplyr::rename(mx_var = !!max_var) %>% + dplyr::filter(!is.na(time), time <= display_date) %>% + group_by(geoid) %>% + dplyr::slice(which.max(mx_var)) %>% + ungroup() + } + } + rc <- list(length=length(scn_dirs)) + for (i in 1:length(scn_dirs)) { + rc[[i]] <- load_hosp_sims_filtered(scn_dirs[i], + num_files = num_files, + name_filter = name_filter, + post_process = hosp_post_process, + geoid_len = geoid_len, + padding_char = padding_char, + file_extension = file_extension) %>% + dplyr::select(time, geoid, sim_num, mx_var) + rc[[i]]$scenario_num <- i + rc[[i]]$scenario_name <- scenariolabels[[i]] + } + + rc %>% + dplyr::bind_rows() %>% + dplyr::rename(!!paste0("Pk_", max_var) := mx_var) %>% ## notate the column that was maximized with "Pk_" + return() +} diff --git a/R/pkgs/report_generation/R/ReportLoadData.R b/R/pkgs/report.generation/R/ReportLoadData.R similarity index 54% rename from R/pkgs/report_generation/R/ReportLoadData.R rename to R/pkgs/report.generation/R/ReportLoadData.R index 65fc8247f..1e74d08a7 100644 --- a/R/pkgs/report_generation/R/ReportLoadData.R +++ b/R/pkgs/report.generation/R/ReportLoadData.R @@ -7,15 +7,17 @@ ##' @param incl_geoids character vector of geoids that are included in the report ##' @param geoid_len in defined, this we want to make geoids all the same length ##' @param padding_char character to add to the front of geoids if fixed length +##' @param file_extension string indicating type of model output files (parquet or csv or auto) +##' @param name_filter string that indicates which pdeath level to import for the source files (from the hosp file name) ##' ##' @return a data frame with columns ##' - time -##' - comp ##' - geoid -##' - N ##' - sim_num +##' - N ##' - scenario_num ##' - scenario_name +##' - pdeath ##' ##' @export load_cum_inf_geounit_dates <- function(scn_dirs, @@ -25,234 +27,57 @@ load_cum_inf_geounit_dates <- function(scn_dirs, incl_geoids=NULL, geoid_len = 0, padding_char = "0", - file_extension = 'auto'){ - + file_extension = 'auto', + name_filter) +{ if(is.null(scenariolabels)){ warning("You have not specified scenario labels for this function. You may encounter future errors.") } - + warning("This function loads infection data from hospitalization outputs. Only one IFR scenario is needed to load these data for a given set of model outputs because infection counts will be the same across IFR scenarios.") + display_dates <- as.Date(display_dates) - inf_pre_process <- function(x) { - x %>% - dplyr::filter(comp == "cumI") %>% - dplyr::filter(time %in% display_dates) - } + max_date <- max(display_dates) + ##filter to munge the data at the scenario level if (!is.null(incl_geoids)) { - inf_post_process <- function(x) { + hosp_post_process <- function(x) { x %>% - ungroup %>% - dplyr::filter(!is.na(time), geoid %in% incl_geoids) + dplyr::filter(!is.na(time) & geoid %in% incl_geoids, time <= max_date) %>% + group_by(geoid, sim_num) %>% + dplyr::mutate(N = cumsum(incidI)) %>% + ungroup() %>% + dplyr::filter(time %in% display_dates) } } else { - inf_post_process <- function(x) { + hosp_post_process <- function(x) { x %>% - ungroup %>% - dplyr::filter(!is.na(time)) + dplyr::filter(!is.na(time) & time <= max_date) %>% + group_by(geoid, sim_num) %>% + dplyr::mutate(N = cumsum(incidI)) %>% + ungroup() %>% + dplyr::filter(time %in% display_dates) } } - + rc <- list() for (i in 1:length(scn_dirs)) { - rc[[i]] <- load_scenario_sims_filtered(scn_dirs[i], - num_files = num_files, - pre_process = inf_pre_process, - post_process = inf_post_process, - geoid_len = geoid_len, - padding_char = padding_char, - file_extension = file_extension) - + rc[[i]] <- load_hosp_sims_filtered(scn_dirs[i], + num_files = num_files, + name_filter = name_filter, + post_process = hosp_post_process, + geoid_len = geoid_len, + padding_char = padding_char, + file_extension = file_extension) rc[[i]]$scenario_num <- i rc[[i]]$scenario_name <- scenariolabels[[i]] } - return(dplyr::bind_rows(rc)) - } -##' Convenience function to load cumulative geounit hosp outcomes at a specific date for the given scenario -##' -##' @param scn_dirs paste(config$name, config$interventions$scenarios, sep = "_") character vector of scenario directory names -##' @param scenariolabels config$report$formatting$scenario_labels character vector of scenario labels -##' @param name_filter character string that filenames should match -##' @param display_date character date string for which cumulative infections should be extracted -##' @param incl_geoids character vector of geoids that are included in the report -##' @param geoid_len in defined, this we want to make geoids all the same length -##' @param padding_char character to add to the front of geoids if fixed length -##' -##' @return a data frame with columns -##' - time -##' - comp -##' - geoid -##' - N -##' - sim_num -##' - scenario_num -##' - scenario_name -##' -##' @export -load_cum_hosp_geounit_date <- function(scn_dirs, - num_files = NA, - scenariolabels = NULL, - name_filter, - display_date=config$end_date, - incl_geoids=NULL, - geoid_len = 0, - padding_char = "0", - file_extension = 'auto'){ - - if(is.null(scenariolabels)){ - warning("You have not specified scenario labels for this function. You may encounter future errors.") - } - - display_date <- as.Date(display_date) - ##filter to munge the data at the scenario level - if (!is.null(incl_geoids)) { - hosp_post_process <- function(x) { - x %>% - dplyr::filter(!is.na(time) & geoid %in% incl_geoids, time <= display_date) %>% - group_by(geoid, sim_num) %>% - dplyr::summarize(NincidDeath = sum(incidD), - NincidInf = sum(incidI), - NincidICU=sum(incidICU), - NincidHosp=sum(incidH), - NincidVent = sum(incidVent)) %>% - ungroup() - } - } else { - hosp_post_process <- function(x) { - x %>% - dplyr::filter(!is.na(time) & time <= display_date) %>% - group_by(geoid, sim_num) %>% - dplyr::summarize(NincidDeath = sum(incidD), - NincidInf = sum(incidI), - NincidICU=sum(incidICU), - NincidHosp=sum(incidH), - NincidVent = sum(incidVent)) %>% - ungroup() - } - } - - - rc <- list(length=length(scn_dirs)) - for (i in 1:length(scn_dirs)) { - rc[[i]] <- load_hosp_sims_filtered(scn_dirs[i], - num_files = num_files, - name_filter = name_filter, - post_process = hosp_post_process, - geoid_len = geoid_len, - padding_char = padding_char, - file_extension = file_extension) - rc[[i]]$scenario_num <- i - rc[[i]]$scenario_name <- scenariolabels[[i]] - } - return(dplyr::bind_rows(rc)) -} -##' Convenience function to load timeseries current hospital outcomes -##' -##' @param scn_dirs paste(config$name, config$interventions$scenarios, sep = "_") character vector of scenario directory names -##' @param scenariolabels config$report$formatting$scenario_labels character vector of scenario labels -##' @param name_filter character string that filenames should match -##' @param end_date last date to include in timeseries -##' @param incl_geoids character vector of geoids that are included in the report -##' @param geoid_len in defined, this we want to make geoids all the same length -##' @param padding_char character to add to the front of geoids if fixed length -##' -##' @return a data frame with columns -##' - time -##' - geoid -##' - NHospCurr, NICUCurr, NVentCurr -##' - sim_num -##' - scenario_num -##' - scenario_name -##' -##' @export -load_ts_current_hosp_geounit <- function(scn_dirs, - num_files = NA, - scenariolabels = NULL, - name_filter, - end_date, - incl_geoids=NULL, - geoid_len = 0, - padding_char = "0", - qlo = 0.025, - qhi= 0.975, - file_extension = 'auto') { - - if(is.null(scenariolabels)){ - warning("You have not specified scenario labels for this function. You may encounter future errors.") - } - - - ## currently too slow including the quantiles... ## - end_date <- as.Date(end_date) - ##filter to munge the data at the scenario level - if (!is.null(incl_geoids)) { - hosp_post_process <- function(x) { - x %>% - dplyr::filter(!is.na(time) & geoid %in% incl_geoids, time <= end_date) %>% - dplyr::select(time, - geoid, - sim_num, - NHospCurr = hosp_curr, - NICUCurr = icu_curr, - NVentCurr = vent_curr) %>% - group_by(sim_num, time, geoid) %>% - mutate(#NHospCurrlo = quantile(NHospCurr, qlo), - #NHospCurrhi = quantile(NHospCurr, qhi), - NHospCurr = mean(NHospCurr), - #NICUCurrlo = quantile(NICUCurr, qlo), - #NICUCurrhi = quantile(NICUCurr, qhi), - NICUCurr = mean(NICUCurr), - #NVentCurrlo = quantile(NVentCurr, qlo), - #NVentCurrhi = quantile(NVentCurr, qhi), - NVentCurr = mean(NVentCurr)) %>% - ungroup() - } - } else { - hosp_post_process <- function(x) { - x %>% - dplyr::filter(!is.na(time) & time <= end_date) %>% - dplyr::select(time, - geoid, - sim_num, - NHospCurr = hosp_curr, - NICUCurr = icu_curr, - NVentCurr = vent_curr) %>% - group_by(sim_num, time, geoid) %>% - mutate(#NHospCurrlo = quantile(NHospCurr, qlo), - #NHospCurrhi = quantile(NHospCurr, qhi), - NHospCurr = mean(NHospCurr), - #NICUCurrlo = quantile(NICUCurr, qlo), - #NICUCurrhi = quantile(NICUCurr, qhi), - NICUCurr = mean(NICUCurr), - #NVentCurrlo = quantile(NVentCurr, qlo), - #NVentCurrhi = quantile(NVentCurr, qhi), - NVentCurr = mean(NVentCurr)) %>% - ungroup() - } - } - - - rc <- list(length=length(scn_dirs)) - for (i in 1:length(scn_dirs)) { - rc[[i]] <- load_hosp_sims_filtered(scn_dirs[i], - num_files = num_files, - name_filter = name_filter, - post_process = hosp_post_process, - geoid_len = geoid_len, - padding_char = padding_char, - file_extension = file_extension) - rc[[i]]$scenario_num <- i - rc[[i]]$scenario_name <- scenariolabels[[i]] - } - - return(dplyr::bind_rows(rc)) -} - ##' ##' Convenience function to allow us to load hospital totals for the combined geounits quickly for ##' the given scenarios. @@ -341,161 +166,6 @@ load_hosp_geocombined_totals <- function(scn_dirs, - -##' Convenience function to load peak geounit infections before a given date for the given scenarios -##' -##' @param scn_dirs paste(config$name, config$interventions$scenarios, sep = "_") character vector of scenario directory names -##' @param display_date character string for date before which infection peak should be identified -##' @param scenariolabels config$report$formatting$scenario_labels character vector of scenario labels -##' @param incl_geoids optional character vector of geoids that are included in the report, if not included, all geoids will be used -##' @param geoid_len required length of geoid -##' @param padding_char padding -##' -##' @return a data frame with columns -##' - time -##' - comp -##' - geoid -##' - N -##' - sim_num -##' - scenario_num -##' - scenario_name -##' -##' @export -load_inf_geounit_peaks_date <- function(scn_dirs, - display_date=config$end_date, - num_files = NA, - scenariolabels=NULL, - incl_geoids=NULL, - geoid_len = 0, - padding_char = "0", - file_extension = 'auto'){ - - if(is.null(scenariolabels)){ - warning("You have not specified scenario labels for this function. You may encounter future errors.") - } - - display_date <- as.Date(display_date) - inf_pre_process <- function(x) { - x %>% - dplyr::filter(comp == "diffI" & time <= display_date) - } - - if (!is.null(incl_geoids)) { - inf_post_process <- function(x) { - x %>% - ungroup %>% - dplyr::filter(!is.na(time), geoid %in% incl_geoids) %>% - group_by(geoid) %>% - dplyr::slice(which.max(N)) %>% - ungroup() - } - } else{ - inf_post_process <- function(x) { - x %>% - ungroup %>% - dplyr::filter(!is.na(time)) %>% - group_by(geoid) %>% - dplyr::slice(which.max(N)) %>% - ungroup() - } - - } - - rc <- list() - for (i in 1:length(scn_dirs)) { - rc[[i]] <- load_scenario_sims_filtered(scn_dirs[i], - num_files = num_files, - pre_process = inf_pre_process, - post_process = inf_post_process, - geoid_len = geoid_len, - padding_char = padding_char, - file_extension = file_extension) - rc[[i]]$scenario_num <- i - rc[[i]]$scenario_name <- scenariolabels[[i]] - - } - - return(dplyr::bind_rows(rc)) - -} - -##' Convenience function to load peak geounit hospitalizations (or any other variable) by a specific date for the given scenarios -##' -##' @param scn_dirs paste(config$name, config$interventions$scenarios, sep = "_") character vector of scenario directory names -##' @param max_var character string of variable that will be maximized per geoid -##' @param display_date date before which we should search for peaks -##' @param name_filter character string that filenames should match -##' @param incl_geoids optional character vector of geoids that are included in the report, if not included, all geoids will be used -##' @param scenariolabels config$report$formatting$scenario_labels character vector of scenario labels -##' @param incl_geoids optional character vector of geoids that are included in the report, if not included, all geoids will be used -##' @param geoid_len required length of geoid -##' @param padding_char padding -##' -##' @return a data frame with columns -##' - sim_num -##' - Pk_[variableName] variable that was maximized by geoid -##' - NhospCurr number of people in hospital on a day -##' - NICUCurr number of people in ICU on a day -##' - NincidDeath number of incidence deaths on a day -##' - NincidInf number of incident infections on a day -##' - NincidICH number of incident ICUs on a day -##' @export -### all of the peak times for each sim and each county so we can make a figure for when things peak -load_hosp_geounit_peak_date <- function(scn_dirs, - max_var, - display_date = config$end_date, - num_files = NA, - name_filter, - incl_geoids = NULL, - scenariolabels = NULL, - geoid_len = 0, - padding_char = "0", - file_extension = 'auto'){ - - if(is.null(scenariolabels)){ - warning("You have not specified scenario labels for this function. You may encounter future errors.") - } - - display_date <- as.Date(display_date) - if (!is.null(incl_geoids)) { - hosp_post_process <- function(x) { - x %>% - dplyr::rename(mx_var = !!max_var) %>% - dplyr::filter(!is.na(time), geoid %in% incl_geoids, time <= display_date) %>% - group_by(geoid) %>% - dplyr::slice(which.max(mx_var)) %>% - ungroup() - } - } else { - hosp_post_process <- function(x) { - x %>% - dplyr::rename(mx_var = !!max_var) %>% - dplyr::filter(!is.na(time), time <= display_date) %>% - group_by(geoid) %>% - dplyr::slice(which.max(mx_var)) %>% - ungroup() - } - } - rc <- list(length=length(scn_dirs)) - for (i in 1:length(scn_dirs)) { - rc[[i]] <- load_hosp_sims_filtered(scn_dirs[i], - num_files = num_files, - name_filter = name_filter, - post_process = hosp_post_process, - geoid_len = geoid_len, - padding_char = padding_char, - file_extension = file_extension) %>% - dplyr::select(time, geoid, sim_num, mx_var) - rc[[i]]$scenario_num <- i - rc[[i]]$scenario_name <- scenariolabels[[i]] - } - - rc %>% - dplyr::bind_rows() %>% - dplyr::rename(!!paste0("Pk_", max_var) := mx_var) %>% ## notate the column that was maximized with "Pk_" - return() -} - ##' Convenience function to load the slice for each geoid where the value of an outcome exceeds a given threshold ##' ##' @param scn_dirs paste(config$name, config$interventions$scenarios, sep = "_") character vector of scenario directory names @@ -539,6 +209,10 @@ load_hosp_geounit_threshold <- function( warning("You have not specified scenario labels for this function. You may encounter future errors.") } + if(!variable %in% c("incidI", "incidH", "hosp_curr", "incidICU", "icu_curr", "incidVent", "vent_curr", "incidD")){ + warning("You have specified a variable name that may not be supported in the current output. You may encounter future errors") + } + end_date <- as.Date(end_date) if (!is.null(incl_geoids)) { hosp_post_process <- function(x) { @@ -691,7 +365,7 @@ load_jhu_csse_for_report <- function(jhu_data_dir = "JHU_CSSE_Data", states, updateJHUData = TRUE, ...) { - if(!dir.exists(jhu_data_dir)) { + if(!(dir.exists(jhu_data_dir) & length(list.files(jhu_data_dir) > 0))) { ### Download JHU data pull_JHUCSSE_github_data(jhu_data_dir) } else { diff --git a/R/pkgs/report_generation/inst/rmarkdown/chunks/DevelopmentTeam.Rmd b/R/pkgs/report.generation/inst/rmarkdown/chunks/DevelopmentTeam.Rmd similarity index 91% rename from R/pkgs/report_generation/inst/rmarkdown/chunks/DevelopmentTeam.Rmd rename to R/pkgs/report.generation/inst/rmarkdown/chunks/DevelopmentTeam.Rmd index f479e12de..8191a2f0b 100644 --- a/R/pkgs/report_generation/inst/rmarkdown/chunks/DevelopmentTeam.Rmd +++ b/R/pkgs/report.generation/inst/rmarkdown/chunks/DevelopmentTeam.Rmd @@ -1,44 +1,45 @@ - -This report would not be possible without the work of the **COVID-19 Scenario Modeling Pipeline -Working Group**: - -**EPFL** - -* Joseph C. Lemaitre - -**Johns Hopkins Infectious Disease Dynamics** - -* Qifang Bi -* Jacob Fiksel -* M. Kate Grabowski -* Kyra H. Grantz -* Joshua Kaminsky -* Stephen A. Lauer -* Elizabeth C. Lee -* Justin Lessler -* Hannah R. Meredith -* Javier Perez-Saez -* Shaun A. Truelove - - -**University of Utah** - -* Lindsay T. Keegan - -**Developers Without Affiliation** - -* Ian Chamberlain -* Kathryn Kaminsky -* Sam Shah -* Josh Wills - - -**Amazon Web Services** - -* Pierre-Yves Aquilanti -* Karthik Raman -* Arun Subramaniyan -* Greg Thursam -* Anh Tran - - + +This report would not be possible without the work of the **COVID-19 Scenario Modeling Pipeline +Working Group**: + +**EPFL** + +* Joseph C. Lemaitre + +**Johns Hopkins Infectious Disease Dynamics** + +* Qifang Bi +* Juan Dent Hulse +* Jacob Fiksel +* M. Kate Grabowski +* Kyra H. Grantz +* Joshua Kaminsky +* Stephen A. Lauer +* Elizabeth C. Lee +* Justin Lessler +* Hannah R. Meredith +* Javier Perez-Saez +* Shaun A. Truelove + + +**University of Utah** + +* Lindsay T. Keegan + +**Developers Without Affiliation** + +* Ian Chamberlain +* Kathryn Kaminsky +* Sam Shah +* Josh Wills + + +**Amazon Web Services** + +* Pierre-Yves Aquilanti +* Karthik Raman +* Arun Subramaniyan +* Greg Thursam +* Anh Tran + + diff --git a/R/pkgs/report.generation/inst/rmarkdown/chunks/HospModelDesc.Rmd b/R/pkgs/report.generation/inst/rmarkdown/chunks/HospModelDesc.Rmd new file mode 100644 index 000000000..11b7ade9e --- /dev/null +++ b/R/pkgs/report.generation/inst/rmarkdown/chunks/HospModelDesc.Rmd @@ -0,0 +1,23 @@ +##### Health outcomes + +We use a statistical model to calculate several key health outcomes, including number of individuals who are hospitalized, admitted to the ICU, ventilatied, and who die, from transmission model output. + +Briefly, we assume some probabilty of hospitalization among all incident infections, $\mathbb{P}(hosp \mid infected)$ and a fixed average time from symptom onset to hospitalization, $d_{inf -> hosp}$. The number of hospitalizations that were infected at time $t_{inf}$ and hospitalized at time $t_{hosp}$ is denoted $n^{hosp}_{t_{inf},t_{hosp}}$, where + +\begin{eqnarray} +n^{hosp}_{t_{inf},\cdot} &\sim Binomial(n^{inf}_{t_{inf}}, \mathbb{P}(hosp \mid infected)) \\ +t_{hosp} &= t_{inf} + d_{inf -> hosp} +\end{eqnarray} + +In the absence of clear data on the overall risk of hospitalization and the asymptomatic fraction, we assumed that the risk of hospitalization is 10 times the risk of death among all infections (the infection fatality ratio, IFR), such that $\mathbb{P}(hosp \mid infected) = 10\cdot\mathbb{P}(death \mid infected)$. Here, we use IFR estimates: `r paste(config$report$formatting$pdeath_labels, sep=", ")`. Those who are hospitalized are at risk of ICU admission ($\mathbb{P}(ICU \mid hosp) =$ `r paste(config$hospitalization$parameters$p_ICU)`), and those admitted to the ICU are at risk of ventilation ($\mathbb{P}(vent \mid ICU) =$ `r paste(config$hospitalization$parameters$p_vent)`). + +\begin{eqnarray} +n^{ICU}_{t_{hosp},\cdot} &\sim Binomial(n^{hosp}_{t_{hosp}}, \mathbb{P}(ICU \mid hosp)) \\ +t_{ICU} &= t_{hosp} + d_{hosp -> ICU} \\ +\\ +n^{vent}_{t_{ICU},\cdot} &\sim Binomial(n^{ICU}_{t_{ICU}}, \mathbb{P}(vent \mid ICU)) \\ +t_{vent} &= t_{ICU} + d_{ICU -> vent} +\\ +n^{death}_{t_{hosp},\cdot} &\sim Binomial(n^{hosp}_{t_{hosp}}, 0.1) \\ +t_{death} &= t_{hosp} + d_{hosp -> death} +\end{eqnarray} \ No newline at end of file diff --git a/R/pkgs/report.generation/inst/rmarkdown/chunks/HospModelDesc_AgeAdjusted.Rmd b/R/pkgs/report.generation/inst/rmarkdown/chunks/HospModelDesc_AgeAdjusted.Rmd new file mode 100644 index 000000000..2676e9b8a --- /dev/null +++ b/R/pkgs/report.generation/inst/rmarkdown/chunks/HospModelDesc_AgeAdjusted.Rmd @@ -0,0 +1,25 @@ +##### Health outcomes + +We use a statistical model to calculate several key health outcomes, including number of individuals who are hospitalized, admitted to the ICU, ventilatied, and who die, from transmission model output. These calculations account for the population age distribution in each location and differences in the risk of these health outcomes by age. + +Briefly, we assume some probabilty of death among all incident infections, $\mathbb{P}(death \mid infected)$, known as the infection fatality ratio, and a fixed average time from symptom onset to death, $d_{inf -> death}$. Here, we use IFR estimates: `r paste(config$report$formatting$pdeath_labels, sep=", ")`. The number of deaths that were infected at time $t_{inf}$ and died at time $t_{death}$ is denoted $n^{death}_{t_{inf},t_{death}}$, where + +\begin{eqnarray} +n^{death}_{t_{inf},\cdot} &\sim Binomial(n^{inf}_{t_{inf}}, \mathbb{P}(death \mid infected)) \\ +t_{death} &= t_{inf} + d_{inf -> death} +\end{eqnarray} + +Similarly, those who are infected are at risk of hospitalization, those who are hospitalized are at risk of ICU admission, and those admitted to the ICU are at risk of ventilation. + +\begin{eqnarray} +n^{hosp}_{t_{inf},\cdot} &\sim Binomial(n^{inf}_{t_{inf}}, \mathbb{P}(hosp \mid inf)) \\ +t_{hosp} &= t_{inf} + d_{inf -> hosp} \\ +\\ +n^{ICU}_{t_{hosp},\cdot} &\sim Binomial(n^{hosp}_{t_{hosp}}, \mathbb{P}(ICU \mid hosp)) \\ +t_{ICU} &= t_{hosp} + d_{hosp -> ICU} \\ +\\ +n^{vent}_{t_{ICU},\cdot} &\sim Binomial(n^{ICU}_{t_{ICU}}, \mathbb{P}(vent \mid ICU)) \\ +t_{vent} &= t_{ICU} + d_{ICU -> vent} +\end{eqnarray} + +We estimate age-standardized probabilities of death, hospitalization, and ICU admission; there is currently limited data on the age-specific risk of ventilation among ICU patients, and thus a single, average estimate is used across all locations. We reviewed the literature for relevant age-specific estimates of risk of each health outcome, and use a logistic GAM with penalized cubic spline for age and random effect for study to estimate the risk for 10-year, aggregated age categories. We then apply these age-specific estimates to the population age distribution in each location to get location-specific, age-adjusted estimates. We assume that individuals of all ages are at equal risk of infection. \ No newline at end of file diff --git a/R/pkgs/report_generation/inst/rmarkdown/chunks/PipelineDescription.Rmd b/R/pkgs/report.generation/inst/rmarkdown/chunks/PipelineDescription.Rmd similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/chunks/PipelineDescription.Rmd rename to R/pkgs/report.generation/inst/rmarkdown/chunks/PipelineDescription.Rmd diff --git a/R/pkgs/report_generation/inst/rmarkdown/chunks/SEIRModelDesc.Rmd b/R/pkgs/report.generation/inst/rmarkdown/chunks/SEIRModelDesc.Rmd similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/chunks/SEIRModelDesc.Rmd rename to R/pkgs/report.generation/inst/rmarkdown/chunks/SEIRModelDesc.Rmd diff --git a/R/pkgs/report_generation/inst/rmarkdown/chunks/importation_seeding.Rmd b/R/pkgs/report.generation/inst/rmarkdown/chunks/importation_seeding.Rmd similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/chunks/importation_seeding.Rmd rename to R/pkgs/report.generation/inst/rmarkdown/chunks/importation_seeding.Rmd diff --git a/R/pkgs/report_generation/inst/rmarkdown/chunks/key_sources.Rmd b/R/pkgs/report.generation/inst/rmarkdown/chunks/key_sources.Rmd similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/chunks/key_sources.Rmd rename to R/pkgs/report.generation/inst/rmarkdown/chunks/key_sources.Rmd diff --git a/R/pkgs/report_generation/inst/rmarkdown/chunks/limitations.Rmd b/R/pkgs/report.generation/inst/rmarkdown/chunks/limitations.Rmd similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/chunks/limitations.Rmd rename to R/pkgs/report.generation/inst/rmarkdown/chunks/limitations.Rmd diff --git a/R/pkgs/report_generation/inst/rmarkdown/chunks/limitations_AgeAdjusted.Rmd b/R/pkgs/report.generation/inst/rmarkdown/chunks/limitations_AgeAdjusted.Rmd similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/chunks/limitations_AgeAdjusted.Rmd rename to R/pkgs/report.generation/inst/rmarkdown/chunks/limitations_AgeAdjusted.Rmd diff --git a/R/pkgs/report_generation/inst/rmarkdown/chunks/planning_models.Rmd b/R/pkgs/report.generation/inst/rmarkdown/chunks/planning_models.Rmd similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/chunks/planning_models.Rmd rename to R/pkgs/report.generation/inst/rmarkdown/chunks/planning_models.Rmd diff --git a/R/pkgs/report_generation/inst/rmarkdown/chunks/poisson_seeding.Rmd b/R/pkgs/report.generation/inst/rmarkdown/chunks/poisson_seeding.Rmd similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/chunks/poisson_seeding.Rmd rename to R/pkgs/report.generation/inst/rmarkdown/chunks/poisson_seeding.Rmd diff --git a/R/pkgs/report_generation/inst/rmarkdown/templates/state_report/skeleton/ReportReferences.bib b/R/pkgs/report.generation/inst/rmarkdown/templates/country_report/skeleton/ReportReferences.bib similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/templates/state_report/skeleton/ReportReferences.bib rename to R/pkgs/report.generation/inst/rmarkdown/templates/country_report/skeleton/ReportReferences.bib diff --git a/R/pkgs/report.generation/inst/rmarkdown/templates/country_report/skeleton/skeleton.Rmd b/R/pkgs/report.generation/inst/rmarkdown/templates/country_report/skeleton/skeleton.Rmd new file mode 100644 index 000000000..8690289b5 --- /dev/null +++ b/R/pkgs/report.generation/inst/rmarkdown/templates/country_report/skeleton/skeleton.Rmd @@ -0,0 +1,388 @@ +--- +title: "[COUNTRY] Scenario Report" +author: "" +output: + html_document: + df_print: paged + fig_caption: true + theme: journal +bibliography: ReportReferences.bib +params: + continue_on_error: TRUE + config_file: "config.yml" + country_iso3: "[COUNTRY ISO3]" #country ISO3...must provided + +--- + +Prepared by [Johns Hopkins ID Dynamics](https://iddynamics.jhsph.edu/) Working Group +Updated `r Sys.Date()` + +**FOR PLANNING PURPOSES ONLY: NOT A FORECAST** + +```{r setup, include=F} + +nfiles <- NA ## set to a number for test reports. +ncores <- 25 ## number of cores to use for loading data + + + +## Block with general knitr options, libray load, etc. Nothing specific to the project. +knitr::opts_knit$set(root.dir = "..") ##Assumes we are in the notebook directory +knitr::opts_chunk$set( + echo = FALSE, + fig.align = "center", + message = FALSE, + warning = FALSE, + error = params$continue_on_error, + cache.lazy = FALSE, + bitmapType = "cairo" + ) +knitr::opts_knit$set(eval.after = 'fig.cap') ##Allows us to set a variable to figure caption in the block + +options(scipen=999) + +#Preamble +library(tidyverse) +library(covidcommon) +library(report.generation) +library(covidImportation) +library(doParallel) +library(ggpubr) +library(tidyselect) +library(ISOcodes) + +nfiles2 <- ifelse(nfiles >= 50, nfiles, 50) ## for plotting + +if (params$country_iso3=="[COUNTRY ISO3]") {stop("Must define a target country by ISO3 code.")} + +``` + +```{r load_config} +reportCountryISO3 <- params$country_iso3 + +## Block loads the config file and geodata +config <- covidcommon:::load_config(params$config_file) +geodata <- load_geodata_file(file.path(config$spatial_setup$base_path, config$spatial_setup$geodata), + geoid_len=config$spatial_setup$geoid_len) +included_geoids <- (geodata %>% filter(admin0==reportCountryISO3))$geoid + +scn_dirs <- paste(config$name,config$interventions$scenarios,sep='_') + +``` + +```{r load_shapefile} +## Load shapefile +shp <- load_shape_file(filename = file.path(config$spatial_setup$base_path, config$spatial_setup$shapefile_name), + to_lower = TRUE, + geoid_len = 5) +``` + +```{r config_vals} +nscenarios <- length(config$interventions$scenarios) +sim_start_date <- config$start_date +sim_end_date <- config$end_date +report_loc <- config$report_location_name +modeled_loc <- paste(config$spatial_setup$modeled_states, collapse = ", ") +census_year <- config$spatial_setup$census_year +incub_period <- 1/eval(parse(text=config$seir$parameters$sigma)) +infect_period <- c(1/(eval(parse(text=config$seir$parameters$gamma$high))), + 1/(eval(parse(text=config$seir$parameters$gamma$low)))) +R0_range <- c(config$seir$parameters$R0s$low, config$seir$parameters$R0s$high) + +# use the ISOcodes package to get the correct name for each country +modeled_states <- ISOcodes::ISO_3166_1$Name[which(ISOcodes::ISO_3166_1$Alpha_3 %in% config$spatial_setup$modeled_states)] +``` + +We compared `r nscenarios` intervention scenarios for model simulations from `r print_pretty_date(sim_start_date)` through `r print_pretty_date(sim_end_date)`: + +[CHANGE BELOW DETAILS ABOUT INTERVENTIONS] + +1. *Lockdown followed by Worst-Case Uncontrolled Spread:* This scenario has country-wide school closures from March 13-19 followed by a country-wide stay-at-home policy from March 19 through May 14. All interventions are then removed (back to worst-case uncontrolled transmission) starting May 15. + +1. *Lockdown followed by Test and Isolate:* This scenario has country-wide school closures from March 13-19 followed by a country-wide stay-at-home policy from March 19 through May 14. From May 15 through December 31, there is a targeted test and isolate strategy similar to that implemented in South Korea. + +1. *Lockdown followed by Moderate Social Distancing:* This scenario has country-wide school closures from March 13-19 followed by a country-wide stay-at-home policy from March 19 through May 14. From May 15 through December 31, there is moderately restrictive social distancing similar to that in US cities during the 1918 influenza pandemic. + +[MAYBE WE SHOULD THEN ADD SOME SUMMARY STATEMENTS ABOUT OUR FINDINGS?] + +[ALTER BELOW DESCRIPTIVE STRING FOR SCENARIO CAPTIONS] + +```{r rmd_formatting} +scen_desc_str <- "three scenarios with 8-week lockdown followed by 1) worst-case uncontrolled spread, 2) targeted testing and isolation, and 3) moderately restrictive social distancing" +fig_counter <- 1 +tab_counter <- 1 +``` + +```{r load_hosp_geocombined_totals} + +doParallel::registerDoParallel(ncores) + +country_hosp_totals <- list() +for (i in 1:length(config$hospitalization$parameters$p_death_names)) { + country_hosp_totals[[i]] <- load_hosp_geocombined_totals(scn_dirs, + num_files = nfiles, + scenariolabels = config$report$formatting$scenario_labels, + name_filter= config$hospitalization$parameters$p_death_names[i], + incl_geoids = included_geoids, + geoid_len = 5, + file_extension="auto") %>% + mutate(pdeath=config$hospitalization$parameters$p_death[i]) +} + +country_hosp_totals <- dplyr::bind_rows(country_hosp_totals) + +doParallel::stopImplicitCluster() +registerDoSEQ() +``` + +```{r summary_fig, fig.cap = cap} +plot_ts_hosp_state_sample(country_hosp_totals, + varname = "NhospCurr", + varlabel = "Daily hospital occupancy", + scenario_labels = config$report$formatting$scenario_labels, + scenario_cols = config$report$formatting$scenario_colors, + sim_start_date = config$start_date, + sim_end_date = config$end_date, + pdeath_level = 0.01) + +cap <- paste0("**Fig. ", fig_counter, "**: Daily hospital occupancy for 15 simulation realizations for ", scen_desc_str, "at 1 % IFR assumptions.") +``` + +```{r load_cum_inf_geounit_dates} +###Load cumulative infections on specific dates +doParallel::registerDoParallel(ncores) + +cum_inf_dates <- load_cum_inf_geounit_dates(scn_dirs, + num_files = nfiles, + display_dates = config$report$formatting$display_dates, + scenariolabels = config$report$formatting$scenario_labels, + incl_geoids = included_geoids, + geoid_len = 5, + file_extension="auto") + +doParallel::stopImplicitCluster() +registerDoSEQ() +``` + +```{r load_csse_data} +## load CSSE data +jhu_dat <- load_jhu_csse_for_report(states = modeled_states, update=TRUE) ## change to update=FALSE after the data is pulled for the first time +``` + + +```{r, child=reference_chunk("planning_models.Rmd")} +``` + +## Country Level Results + +### Summary + +`r paste0("**Tab.", tab_counter, "**: Summary across", scen_desc_str, ". Estimates are presented across", length(config$report$formatting$display_dates)+1, "time periods for 1% infection fatality ratio (IFR) assumptions.")` + +```{r scn_time_sum} +make_scn_time_summary_table_withVent(country_hosp_totals %>% dplyr::filter(pdeath==.01), + config$report$formatting$display_dates, + pi_low = 0.025, + pi_high = 0.975, + round_digit = -1) +tab_counter <- tab_counter+1 +``` + + +### Diversity of Possible Outcomes + +```{r death_histograms, fig.cap = cap, fig.width = 12} +##Chunk plots the distribution of hospitalizations at multiple time points + +show_dates <- config$report$formatting$display_dates +hist_plts <- list() + +for (i in 1:length(show_dates)) { + hist_plts[[i]] <- plot_hist_incidHosp_state(country_hosp_totals, + var_name = "NincidHosp", + scenario_labels = config$report$formatting$scenario_labels, + scenario_cols = config$report$formatting$scenario_colors, + sim_start_date = config$start_date, + summary_date = show_dates[i], + pdeath_level = 0.01) +} + +ggpubr::ggarrange(plotlist=hist_plts, nrow=1) + + +cap <- paste("**Fig.", fig_counter, "**: Distribution of cumulative hospital admissions for", scen_desc_str, "at 1% IFR assumptions. Each bar represents a bin of 2,000 hospitalizations.") +fig_counter <- fig_counter+1 +``` + +## Scenario Summaries + +[IF AVAILABLE, LOAD BED DATA AS IN THE EXAMPLE THAT FOLLOWS] +```{r load_special_data} + +## source("R/load_beds_by_county_[COUNTRY].R") ## R/load_beds_by_county_early_march.R +## bedtype <- "staffed ICU" +## vname <- "n_icu_bed_staffed" +## hosp_vname <- "icu_curr" +## occup_assum <- 0.68 ## assumes ICU occupancy is 68% per county over time on non-COVID patients +## bedtype_label <- paste("Available", bedtype, "ICU beds, calculated as", (1-occup_assum)*100, "% of", bedtype, "Beds") + +## beddata <- load_beds_by_county_md(filename = "data/east-coast/md_hospbeddata.csv", ## "data/DPH/GACH ICU Beds By County Early March.xlsx" +## shapefile = shp, +## varname = vname, +## bed_percentage = 1-occup_assum) + + +``` + +```{r load_hosp_geounit_threshold} +## doParallel::registerDoParallel(ncores) + +## ## dataframe to show when hosp_curr exceeds bed data by county +## thresholddat <- load_hosp_geounit_threshold(scn_dirs, +## num_files = nfiles, +## threshold = beddata, +## name_filter = "high", +## variable = hosp_vname, +## end_date = config$end_date, +## incl_geoids = included_geoids, +## scenario_labels = config$report$formatting$scenario_labels, +## geoid_len = 5) +## doParallel::stopImplicitCluster() +## registerDoSEQ() +``` + +### Scenario 1: [Scenario Name] + +1. *Lockdown followed by Worst-Case Uncontrolled Spread:* This scenario has country-wide school closures from March 13-19 followed by a country-wide stay-at-home policy from March 19 through May 14. All interventions are then removed (back to worst-case uncontrolled transmission) starting May 15. + + +`r paste("**Tab.", tab_counter, "** Country-level summary for", config$report$formatting$scenario_labels[1], "scenario reported for the period from", sim_start_date, "through the dates specified by the column headers.")` + +```{r scn_state_table1} +make_scn_state_table(config$report$formatting$scenario_labels[1], + country_hosp_totals, + table_dates = config$report$formatting$display_dates, + pdeath_labels = config$report$formatting$pdeath_labels, + pdeath_filecode = config$hospitalization$parameters$p_death) + +tab_counter <- tab_counter+1 +``` + + +```{r ARmaps1, fig.cap = cap} +ARmap1 <- plot_geounit_attack_rate_map(cum_inf_dates, + geodata, + shp, + scenariolabel = config$report$formatting$scenario_labels[1], + display_date = config$report$formatting$display_dates[1], + viridis_palette = "plasma", + popnodes = config$spatial_setup$popnodes) + +ARmap2 <- plot_geounit_attack_rate_map(cum_inf_dates, + geodata, + shp, + scenariolabel = config$report$formatting$scenario_labels[1], + display_date = config$report$formatting$display_dates[2], + viridis_palette = "viridis", + popnodes = config$spatial_setup$popnodes) + +ARmap3 <- plot_geounit_attack_rate_map(cum_inf_dates, + geodata, + shp, + scenariolabel = config$report$formatting$scenario_labels[1], + display_date = config$report$formatting$display_dates[3], + viridis_palette = "cividis") +cowplot::plot_grid(ARmap1, ARmap2, ARmap3, ncol=3) + +cap <- paste("**Fig.", fig_counter, "** County-level map of infections per 10,000 for", config$report$formatting$scenario_labels[1], " strategy.") +fig_counter <- fig_counter+1 +``` + + +[UNCOMMENT THIS IF THE BEDDATA EXISTS] +```{r plot_threshold1, fig.cap = cap, fig.height = 7} +# plot_event_time_by_geoid( +# hosp_county_peaks = thresholddat, +# shapefile = shp %>% mutate(name=as.character(name)), +# scenario_labels = config$report$formatting$scenario_labels[1], +# scenario_colors = config$report$formatting$scenario_colors[1], +# time_caption = paste("Time when", bedtype, "occupancy exceeds", bedtype, "bed capacity"), +# geoid_caption = "County", +# value_name = "threshold_value", +# value_label = bedtype_label, +# start_date = config$start_date, +# end_date = config$end_date +# ) +# cap <- paste("**Fig.", fig_counter, "** Time when COVID-19", bedtype, "occupancy exceeds in-county", bedtype, "bed capacity for", config$report$formatting$scenario_labels[1], "scenario at 1% IFR assumptions. We assume that occupancy is", occup_assum*100, "% over time for non-COVID patients. Points indicate the median and lines indicate the interquartile range of model estimates. Counties which never exceed capacity will have no estimate plotted.") +# fig_counter <- fig_counter+1 +``` + + + +## Appendix 1: Methods + +### Pipeline Overview + +```{r, child=reference_chunk("PipelineDescription.Rmd")} +``` + +### Technical Details + +#### Data Sources + +* County-level confirmed SARS-COV-2 infections: [JHU CSSE COVID-19 Data Portal](https://coronavirus.jhu.edu/map.html) + + +* US Census Bureau 2010 county commuting flows and `r census_year` population data + +Our model and report make the following key assumptions: + +* Mean incubation period: `r incub_period` days + +* Infectious period: ranges from `r paste(infect_period, collapse = "-")` days + +* R0: `r paste(R0_range, collapse = "-")` + +* We examine 3 infection fatality rates (IFR) throughout our report: `r paste0(config$hospitalization$parameters$p_death * 100, collapse = ", ")`%. + +* We assume that `r paste0(config$hospitalization$parameters$p_death_rate * 100, "%")` of all hospitalized patients will die and adjust overall hospitalization rates to match the given IFR for a scenario. + +* Hospitalizations admitted to the ICU: `r paste0(config$hospitalization$parameters$p_ICU*100, "%")` + +* ICU admissions that are ventilated: `r paste0(config$hospitalization$parameters$p_vent*100, "%")` + + + +#### Epidemic Simulation + +[CHOOSE ONE OF THESE CHUNKS DEPENDING ON SEEDING. POISSON SEEDING TEXT SAYS 10X] + + +#### SEIR Model + +```{r, child=reference_chunk("SEIRModelDesc.Rmd")} +``` + +### Limitations + +```{r, child=reference_chunk("limitations.Rmd")} +``` + +### Key Sources + +```{r, child=reference_chunk("key_sources.Rmd")} +``` + +## Development Team + +[ADD NAMES AND RECOMPILE PACKAGE AS NECESSARY] +```{r, child=reference_chunk("DevelopmentTeam.Rmd")} +``` + +## Bibliography diff --git a/R/pkgs/report.generation/inst/rmarkdown/templates/country_report/template.yaml b/R/pkgs/report.generation/inst/rmarkdown/templates/country_report/template.yaml new file mode 100644 index 000000000..b870cb408 --- /dev/null +++ b/R/pkgs/report.generation/inst/rmarkdown/templates/country_report/template.yaml @@ -0,0 +1,2 @@ +name: Multi scenario country report +description: Basic templage for making a multi-scenario country report. diff --git a/R/pkgs/report_generation/inst/rmarkdown/templates/county_report/skeleton/ReportReferences.bib b/R/pkgs/report.generation/inst/rmarkdown/templates/county_report/skeleton/ReportReferences.bib similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/templates/county_report/skeleton/ReportReferences.bib rename to R/pkgs/report.generation/inst/rmarkdown/templates/county_report/skeleton/ReportReferences.bib diff --git a/R/pkgs/report_generation/inst/rmarkdown/templates/county_report/skeleton/skeleton.Rmd b/R/pkgs/report.generation/inst/rmarkdown/templates/county_report/skeleton/skeleton.Rmd similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/templates/county_report/skeleton/skeleton.Rmd rename to R/pkgs/report.generation/inst/rmarkdown/templates/county_report/skeleton/skeleton.Rmd diff --git a/R/pkgs/report_generation/inst/rmarkdown/templates/county_report/template.yaml b/R/pkgs/report.generation/inst/rmarkdown/templates/county_report/template.yaml similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/templates/county_report/template.yaml rename to R/pkgs/report.generation/inst/rmarkdown/templates/county_report/template.yaml diff --git a/R/pkgs/report.generation/inst/rmarkdown/templates/integration_testing_report/skeleton/ReportReferences.bib b/R/pkgs/report.generation/inst/rmarkdown/templates/integration_testing_report/skeleton/ReportReferences.bib new file mode 100644 index 000000000..6f3940375 --- /dev/null +++ b/R/pkgs/report.generation/inst/rmarkdown/templates/integration_testing_report/skeleton/ReportReferences.bib @@ -0,0 +1,142 @@ +% Encoding: UTF-8 + +@Article{Bootsma2007, + author = {Martin C. J. Bootsma and Neil M. Ferguson}, + journal = {Proceedings of the National Academy of Sciences}, + title = {The effect of public health measures on the 1918 influenza pandemic in U.S. cities}, + year = {2007}, + month = {apr}, + number = {18}, + pages = {7588--7593}, + volume = {104}, + doi = {10.1073/pnas.0611071104}, + publisher = {Proceedings of the National Academy of Sciences}, +} + +@Article{Jackson2020, + author = {Michael L Jackson and Gregory R Hart and Denise J McCulloch and Amanda Adler and Elisabeth Brandstetter and Kairsten Fay and Peter Han and Kirsten Lacombe and Jover Lee and Thomas Sibley and Deborah A Nickerson and Mark Rieder and Lea Starita and Janet A Englund and Trevor Bedford and Helen Chu and Michael Famulare and}, + title = {Effects of weather-related social distancing on city-scale transmission of respiratory viruses}, + year = {2020}, + month = {mar}, + doi = {10.1101/2020.03.02.20027599}, + publisher = {Cold Spring Harbor Laboratory}, +} + +@Article{Cauchemez2008, + author = {Simon Cauchemez and Alain-Jacques Valleron and Pierre-Yves Boëlle and Antoine Flahault and Neil M. Ferguson}, + journal = {Nature}, + title = {Estimating the impact of school closure on influenza transmission from Sentinel data}, + year = {2008}, + month = {apr}, + number = {7188}, + pages = {750--754}, + volume = {452}, + doi = {10.1038/nature06732}, + publisher = {Springer Science and Business Media {LLC}}, +} + +@Article{Litvinova2019, + author = {Maria Litvinova and Quan-Hui Liu and Evgeny S. Kulikov and Marco Ajelli}, + journal = {Proceedings of the National Academy of Sciences}, + title = {Reactive school closure weakens the network of social interactions and reduces the spread of influenza}, + year = {2019}, + month = {jun}, + number = {27}, + pages = {13174--13181}, + volume = {116}, + doi = {10.1073/pnas.1821298116}, + publisher = {Proceedings of the National Academy of Sciences}, +} + +@Article{Bi2020, + author = {Qifang Bi and Yongsheng Wu and Shujiang Mei and Chenfei Ye and Xuan Zou and Zhen Zhang and Xiaojian Liu and Lan Wei and Shaun A Truelove and Tong Zhang and Wei Gao and Cong Cheng and Xiujuan Tang and Xiaoliang Wu and Yu Wu and Binbin Sun and Suli Huang and Yu Sun and Juncen Zhang and Ting Ma and Justin Lessler and Teijian Feng}, + title = {Epidemiology and Transmission of {COVID}-19 in Shenzhen China: Analysis of 391 cases and 1,286 of their close contacts}, + year = {2020}, + month = {mar}, + doi = {10.1101/2020.03.03.20028423}, + publisher = {Cold Spring Harbor Laboratory}, +} + +@Article{Riou2020, + author = {Julien Riou and Christian L. Althaus}, + title = {Pattern of early human-to-human transmission of Wuhan 2019-{nCoV}}, + year = {2020}, + month = {jan}, + doi = {10.1101/2020.01.23.917351}, + publisher = {Cold Spring Harbor Laboratory}, +} + +@Article{Majumder2020, + author = {Maimuna Majumder and Kenneth D. Mandl}, + journal = {{SSRN} Electronic Journal}, + title = {Early Transmissibility Assessment of a Novel Coronavirus in Wuhan, China}, + year = {2020}, + doi = {10.2139/ssrn.3524675}, + publisher = {Elsevier {BV}}, +} + +@Article{Zhao2020, + author = {Shi Zhao and Qianyin Lin and Jinjun Ran and Salihu S. Musa and Guangpu Yang and Weiming Wang and Yijun Lou and Daozhou Gao and Lin Yang and Daihai He and Maggie H. Wang}, + journal = {International Journal of Infectious Diseases}, + title = {Preliminary estimation of the basic reproduction number of novel coronavirus (2019-{nCoV}) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak}, + year = {2020}, + month = {mar}, + pages = {214--217}, + volume = {92}, + doi = {10.1016/j.ijid.2020.01.050}, + publisher = {Elsevier {BV}}, +} + +@Article{Halpern2015, + author = {Neil A. Halpern and Stephen M. Pastores}, + journal = {Critical Care Medicine}, + title = {Critical care medicine beds, use, occupancy and costs in the United States: a methodological review}, + year = {2015}, + month = {nov}, + number = {11}, + pages = {2452-2459}, + volume = {43}, + doi = {10.1097/CCM.0000000000001227}, + publisher = {Critical Care Medicine}, +} + +@Article{Metcalf2011, + author = {C.J.E. Metcalf and C. V. Munayco and C. Viboud and G. Chowell and B.T. Grenfell and O.N. Bjornstad}, + journal = {Journal of the Royal Society Interface}, + title = {Rubella metapopulation dynamics and importance of spatial coupling to the risk of congenital rubella syndrome in Peru}, + year = {2011}, + pages = {369-376}, + volume = {8}, + issue = {56}, +} + +@Article{Word2012, + author = {D.P. Word and D.A. Cummings and D.S. Burke and S. Iamsirithaworn and C.D. Laird}, + journal = {Journal of the Royal Society Interface}, + title = {A nonlinear programming approach for estimation of transmission parameters in childhood infectious disease using a continuous time model}, + year = {2012}, + pages = {1983-1997}, + volume = {9}, + issue = {73}, +} + +@Article{Finkenstadt2002, + author = {B.F. Finkenstadt and O.N. Bjornstad and B.T. Grenfell}, + journal = {Biostatistics}, + title = {A stochastic model for extinction and recurrennce of epidemics: estimation and inference for measles outbreaks}, + year = {2002}, + pages = {493-510}, + volume = {3}, + issue = {4}, +} + +@Article{Becker2017, + author = {A.D. Becker and B.T. Grenfell}, + journal = {PLOS One}, + title = {tSIR: An R package for time-series Susceptible-Infected-Recovered models of epidemics}, + year = {2017}, + volume = {12}, + issue = {9}, +} + +@Comment{jabref-meta: databaseType:bibtex;} diff --git a/R/pkgs/report.generation/inst/rmarkdown/templates/integration_testing_report/skeleton/skeleton.Rmd b/R/pkgs/report.generation/inst/rmarkdown/templates/integration_testing_report/skeleton/skeleton.Rmd new file mode 100644 index 000000000..699d5b8a1 --- /dev/null +++ b/R/pkgs/report.generation/inst/rmarkdown/templates/integration_testing_report/skeleton/skeleton.Rmd @@ -0,0 +1,368 @@ +--- +title: "Integration testing report" +author: "" +output: + html_document: + df_print: paged + fig_caption: true + theme: journal +bibliography: ReportReferences.bib +params: + continue_on_error: TRUE + config_file: "config.yml" + state_usps: "[STATE USPS]" #state USPS...must provided + +--- + +Prepared by [Johns Hopkins ID Dynamics](https://iddynamics.jhsph.edu/) Working Group +Updated `r Sys.Date()` + +**FOR PLANNING PURPOSES ONLY: NOT A FORECAST** + +```{r setup, include=F} +## Block with general knitr options, libray load, etc. Nothing specific to the project. +knitr::opts_knit$set(root.dir = "../..") ##Assumes we are in a subdirectory of notebooks +knitr::opts_chunk$set( + echo = FALSE, + fig.align = "center", + message = FALSE, + warning = FALSE, + error = params$continue_on_error, + cache.lazy = FALSE, + bitmapType = "cairo" + ) +knitr::opts_knit$set(eval.after = 'fig.cap') ##Allows us to set a variable to figure caption in the block + +options(scipen=999) + +#Preamble +library(tidyverse) +library(covidcommon) +library(report.generation) +library(covidImportation) +library(doParallel) + +nfiles <- 2 ## set to a number for test reports. +nfiles2 <- ifelse(nfiles <= 50, nfiles, 50) ## for plotting + +if (params$state_usps=="[STATE USPS]") {stop("Must define a target state by USPS code.")} +ncores <- 1 ## number of cores to use for loading data + +``` + +```{r load_config} +reportStateUSPS <- params$state_usps + +## Block loads the config file and geodata +config <- covidcommon:::load_config(params$config_file) +geodata <- load_geodata_file(file.path(config$spatial_setup$base_path, config$spatial_setup$geodata), + geoid_len=5) +included_geoids <- (geodata %>% filter(USPS==reportStateUSPS))$geoid + +scn_dirs <- paste(config$name,config$interventions$scenarios,sep='_') + +``` + +```{r load_shapefile} +## Load shapefile +shp <- load_shape_file(filename = file.path(config$spatial_setup$base_path, config$spatial_setup$shapefile_name), + to_lower = TRUE, + geoid_len = 5) +``` + +```{r config_vals} +nscenarios <- length(config$interventions$scenarios) +sim_start_date <- config$start_date +sim_end_date <- config$end_date +report_loc <- config$report_location_name +modeled_loc <- paste(config$spatial_setup$modeled_states, collapse = ", ") +census_year <- config$spatial_setup$census_year +incub_period <- 1/eval(parse(text=config$seir$parameters$sigma)) +infect_period <- c(1/(eval(parse(text=config$seir$parameters$gamma$high))), + 1/(eval(parse(text=config$seir$parameters$gamma$low)))) +R0_range <- c(config$seir$parameters$R0s$low, config$seir$parameters$R0s$high) +modeled_states <- state.name[which(state.abb %in% config$spatial_setup$modeled_states)] +``` + +We compared `r nscenarios` intervention scenarios for model simulations from `r print_pretty_date(sim_start_date)` through `r print_pretty_date(sim_end_date)`: + + +```{r rmd_formatting} +scen_desc_str <- "scenario description" +fig_counter <- 1 +tab_counter <- 1 +``` + + +## Load the data + +```{r load_cum_inf_geounit_dates} +###Load cumulative infections on specific dates +doParallel::registerDoParallel(ncores) +cum_inf_dates <- load_cum_inf_geounit_dates(scn_dirs, + num_files = nfiles, + scenariolabels = config$report$formatting$scenario_labels, + name_filter= config$hospitalization$parameters$p_death_names[1], ## includes only one pdeath because interest is only in infections here + incl_geoids = included_geoids, + geoid_len = 5, + file_extension="auto") %>% + mutate(pdeath=config$hospitalization$parameters$p_death[1]) + +doParallel::stopImplicitCluster() +registerDoSEQ() +``` + +```{r load_hosp_geocombined_totals} + +doParallel::registerDoParallel(ncores) + +state_hosp_totals <- list() +for (i in 1:length(config$hospitalization$parameters$p_death_names)) { + state_hosp_totals[[i]] <- load_hosp_geocombined_totals(scn_dirs, + num_files = nfiles, + scenariolabels = config$report$formatting$scenario_labels, + name_filter= config$hospitalization$parameters$p_death_names[i], + incl_geoids = included_geoids, + geoid_len = 5, + file_extension="auto") %>% + mutate(pdeath=config$hospitalization$parameters$p_death[i]) +} + +state_hosp_totals <- dplyr::bind_rows(state_hosp_totals) + +doParallel::stopImplicitCluster() +registerDoSEQ() +``` + +[THE COMMENTED LOAD FUNCTIONS ARE DEPENDENT ON LOCATION-SPECIFIC DATA INPUTS] + +```{r load_special_data} + +## source("R/load_beds_by_county_[STATE].R") ## R/load_beds_by_county_early_march.R +## bedtype <- "staffed ICU" +## vname <- "n_icu_bed_staffed" +## hosp_vname <- "icu_curr" +## occup_assum <- 0.68 ## assumes ICU occupancy is 68% per county over time on non-COVID patients +## bedtype_label <- paste("Available", bedtype, "ICU beds, calculated as", (1-occup_assum)*100, "% of", bedtype, "Beds") + +## beddata <- load_beds_by_county_md(filename = "data/east-coast/md_hospbeddata.csv", ## "data/DPH/GACH ICU Beds By County Early March.xlsx" +## shapefile = shp, +## varname = vname, +## bed_percentage = 1-occup_assum) + + +``` + +```{r load_hosp_geounit_threshold} +## doParallel::registerDoParallel(ncores) + +## ## dataframe to show when hosp_curr exceeds bed data by county +## thresholddat <- load_hosp_geounit_threshold(scn_dirs, +## num_files = nfiles, +## threshold = beddata, +## name_filter = "high", +## variable = hosp_vname, +## end_date = config$end_date, +## incl_geoids = included_geoids, +## scenario_labels = config$report$formatting$scenario_labels, +## geoid_len = 5) +## doParallel::stopImplicitCluster() +## registerDoSEQ() +``` + +```{r load_hosp_geounit_relative_to_threshold} +## doParallel::registerDoParallel(ncores) + +## ## dataframe to show when hosp_curr exceeds bed data by county +## hosp_geounit_relative <- load_hosp_geounit_relative_to_threshold(scn_dirs, +## num_files = nfiles, +## threshold = beddata, +## name_filter = "high", +## variable = hosp_vname, +## end_date = config$end_date, +## incl_geoids = included_geoids, +## scenario_labels = config$report$formatting$scenario_labels, +## geoid_len = 5) +## doParallel::stopImplicitCluster() +## registerDoSEQ() +``` + +[TRYING TO DEPRECATE LOAD CSSE DATA] + +```{r load_csse_data} +## load CSSE data +jhu_dat <- load_jhu_csse_for_report(states = modeled_states, update=TRUE) ## change to update=FALSE after the data is pulled for the first time +``` + +## Plot Things + +```{r summary_fig, fig.cap = cap} +plot_ts_hosp_state_sample(state_hosp_totals, + varname = "NhospCurr", + varlabel = "Daily hospital occupancy", + scenario_labels = config$report$formatting$scenario_labels, + scenario_cols = config$report$formatting$scenario_colors, + sim_start_date = config$start_date, + sim_end_date = config$end_date, + pdeath_level = 0.01) + +cap <- paste0("**Fig. ", fig_counter, "**: Daily hospital occupancy for 15 simulation realizations for ", scen_desc_str, "at 1 % IFR assumptions.") +``` + +```{r death_histograms, fig.cap = cap, fig.width = 12} +##Chunk plots the distribution of hospitalizations at multiple time points + +show_dates <- config$report$formatting$display_dates +hist_plts <- list() + +for (i in 1:length(show_dates)) { + hist_plts[[i]] <- plot_hist_incidHosp_state(state_hosp_totals, + var_name = "NincidHosp", + scenario_labels = config$report$formatting$scenario_labels, + scenario_cols = config$report$formatting$scenario_colors, + sim_start_date = config$start_date, + summary_date = show_dates[i], + pdeath_level = 0.01) +} + +ggpubr::ggarrange(plotlist=hist_plts, nrow=1) + + +cap <- paste("**Fig.", fig_counter, "**: Distribution of cumulative hospital admissions for", scen_desc_str, "at 1% IFR assumptions. Each bar represents a bin of 2,000 hospitalizations.") +fig_counter <- fig_counter+1 +``` + +```{r ARmaps1, fig.cap = cap} +ARmap1 <- plot_geounit_attack_rate_map(cum_inf_dates, + geodata, + shp, + scenariolabel = config$report$formatting$scenario_labels[1], + display_date = config$report$formatting$display_dates[1], + viridis_palette = "plasma", + popnodes = config$spatial_setup$popnodes) + +cowplot::plot_grid(ARmap1, ncol=1) + +cap <- paste("**Fig.", fig_counter, "** County-level map of infections per 10,000 for", config$report$formatting$scenario_labels[1], " strategy.") +fig_counter <- fig_counter+1 +``` + +```{r maps2, fig.cap = cap} +map2 <- plot_geounit_map(cum_inf_dates, + plot_var = "N", + geodata, + shp, + scenariolabel = config$report$formatting$scenario_labels[1], + display_date = config$report$formatting$display_dates[1], + popnodes = config$spatial_setup$popnodes) + +cowplot::plot_grid(map3, ncol=1) + +cap <- paste("**Fig.", fig_counter, "** Second county-level map of infections per 10,000 for", config$report$formatting$scenario_labels[1], " strategy.") +fig_counter <- fig_counter+1 +``` + +```{r plot_modelVsObs_all, fig.height = 7} +compare_plts <- plot_model_vs_obs(state_hosp_totals = state_hosp_totals, + jhu_obs_dat = jhu_dat, + scenario_labels = config$report$formatting$scenario_labels, + scenario_cols = config$report$formatting$scenario_colors, + pdeath_level = params$pdeath_default, + obs_data_col = 'black', + ci.L = 0.025, + ci.U = 0.975, + sim_start_date = sim_start_date, + sim_end_date = "2020-05-14", + assumed_reporting_rate = 0.2) +ggpubr::ggarrange(plotlist=compare_plts, ncol=1) +``` + + +[UNCOMMENT THESE IF THE BEDDATA EXISTS] + +```{r plot_threshold1, fig.cap = cap, fig.height = 7} +# plot_event_time_by_geoid( +# hosp_county_peaks = thresholddat, +# shapefile = shp %>% mutate(name=as.character(name)), +# scenario_labels = config$report$formatting$scenario_labels[1], +# scenario_colors = config$report$formatting$scenario_colors[1], +# time_caption = paste("Time when", bedtype, "occupancy exceeds", bedtype, "bed capacity"), +# geoid_caption = "County", +# value_name = "threshold_value", +# value_label = bedtype_label, +# start_date = config$start_date, +# end_date = config$end_date +# ) +# cap <- paste("**Fig.", fig_counter, "** Time when COVID-19", bedtype, "occupancy exceeds in-county", bedtype, "bed capacity for", config$report$formatting$scenario_labels[1], "scenario at 1% IFR assumptions. We assume that occupancy is", occup_assum*100, "% over time for non-COVID patients. Points indicate the median and lines indicate the interquartile range of model estimates. Counties which never exceed capacity will have no estimate plotted.") +# fig_counter <- fig_counter+1 +``` + +```{r plot_hosp_threshold_comparisons, fig.width = 10, fig.cap = cap, fig.height = 9} +# fig_label <- c("**Continued lockdown**", "**Slow**-paced reopening", "**Moderate**-paced reopening", "**Fast**-paced reopening") +# hosp_geounit_relative <- hosp_geounit_relative %>% +# mutate(scenario_label = case_when(scenario_label == "Continued lockdown" ~ "**Continued lockdown**", +# scenario_label == "Slow-paced reopening" ~ "**Slow**-paced reopening", +# scenario_label == "Moderate-paced reopening" ~ "**Moderate**-paced reopening", +# scenario_label == "Fast-paced reopening" ~ "**Fast**-paced reopening")) +# +# plot <- plot_needs_relative_to_threshold_heatmap(hosp_geounit_relative, +# shapefile = shp, +# scenario_labels = fig_label, +# legend_title = "excess hospital \nbeds needed", +# value_name = "threshold_value", +# value_label = "total hospital bed capacity", +# start_date = "2020-04-01", +# end_date = sim_end_date, +# incl_geoids = included_geoids) + +# scale_x_date(date_breaks = "8 weeks") + +# theme(strip.text = ggtext::element_markdown()) +# +# plot$data <- plot$data %>% +# mutate(name = factor(name, levels = sort(unique(geo_names$name), decreasing=TRUE))) +# +# plot +# +# cap <- paste("**Fig.", fig_counter, " **: County-level hospital bed needs, as log proportion of total non-surge hospital bed capacity, for", scen_desc_str, "at 1% IFR assumptions. We assume that occupancy is 0% over time for non-COVID patients") +# +# +# fig_counter <- fig_counter+1 + +``` + + + +## Some tables + +```{r scn_state_table1} +make_scn_state_table_withVent(config$report$formatting$scenario_labels[1], + state_hosp_totals, + table_dates = config$report$formatting$display_dates, + pdeath_labels = config$report$formatting$pdeath_labels, + pdeath_filecode = config$hospitalization$parameters$p_death) + +tab_counter <- tab_counter+1 +``` + + +```{r scn_time_sum} +make_scn_time_summary_table_withVent(state_hosp_totals %>% dplyr::filter(pdeath==.01), + config$report$formatting$display_dates, + pi_low = 0.025, + pi_high = 0.975, + round_digit = -1) +tab_counter <- tab_counter+1 +``` + + + +## Reference chunks + +```{r, child=reference_chunk("planning_models.Rmd")} +``` + +```{r, child=reference_chunk("PipelineDescription.Rmd")} +``` + +```{r, child=reference_chunk("poisson_seeding.Rmd")} +``` + diff --git a/R/pkgs/report.generation/inst/rmarkdown/templates/integration_testing_report/template.yaml b/R/pkgs/report.generation/inst/rmarkdown/templates/integration_testing_report/template.yaml new file mode 100644 index 000000000..cf3633a2d --- /dev/null +++ b/R/pkgs/report.generation/inst/rmarkdown/templates/integration_testing_report/template.yaml @@ -0,0 +1,2 @@ +name: Integration testing report +description: Basic template with all active functions for integration testing diff --git a/R/pkgs/report_generation/inst/rmarkdown/templates/multi_county_report/skeleton/ReportReferences.bib b/R/pkgs/report.generation/inst/rmarkdown/templates/multi_county_report/skeleton/ReportReferences.bib similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/templates/multi_county_report/skeleton/ReportReferences.bib rename to R/pkgs/report.generation/inst/rmarkdown/templates/multi_county_report/skeleton/ReportReferences.bib diff --git a/R/pkgs/report_generation/inst/rmarkdown/templates/multi_county_report/skeleton/skeleton.Rmd b/R/pkgs/report.generation/inst/rmarkdown/templates/multi_county_report/skeleton/skeleton.Rmd similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/templates/multi_county_report/skeleton/skeleton.Rmd rename to R/pkgs/report.generation/inst/rmarkdown/templates/multi_county_report/skeleton/skeleton.Rmd diff --git a/R/pkgs/report_generation/inst/rmarkdown/templates/multi_county_report/template.yaml b/R/pkgs/report.generation/inst/rmarkdown/templates/multi_county_report/template.yaml similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/templates/multi_county_report/template.yaml rename to R/pkgs/report.generation/inst/rmarkdown/templates/multi_county_report/template.yaml diff --git a/R/pkgs/report.generation/inst/rmarkdown/templates/state_report/skeleton/ReportReferences.bib b/R/pkgs/report.generation/inst/rmarkdown/templates/state_report/skeleton/ReportReferences.bib new file mode 100644 index 000000000..6f3940375 --- /dev/null +++ b/R/pkgs/report.generation/inst/rmarkdown/templates/state_report/skeleton/ReportReferences.bib @@ -0,0 +1,142 @@ +% Encoding: UTF-8 + +@Article{Bootsma2007, + author = {Martin C. J. Bootsma and Neil M. Ferguson}, + journal = {Proceedings of the National Academy of Sciences}, + title = {The effect of public health measures on the 1918 influenza pandemic in U.S. cities}, + year = {2007}, + month = {apr}, + number = {18}, + pages = {7588--7593}, + volume = {104}, + doi = {10.1073/pnas.0611071104}, + publisher = {Proceedings of the National Academy of Sciences}, +} + +@Article{Jackson2020, + author = {Michael L Jackson and Gregory R Hart and Denise J McCulloch and Amanda Adler and Elisabeth Brandstetter and Kairsten Fay and Peter Han and Kirsten Lacombe and Jover Lee and Thomas Sibley and Deborah A Nickerson and Mark Rieder and Lea Starita and Janet A Englund and Trevor Bedford and Helen Chu and Michael Famulare and}, + title = {Effects of weather-related social distancing on city-scale transmission of respiratory viruses}, + year = {2020}, + month = {mar}, + doi = {10.1101/2020.03.02.20027599}, + publisher = {Cold Spring Harbor Laboratory}, +} + +@Article{Cauchemez2008, + author = {Simon Cauchemez and Alain-Jacques Valleron and Pierre-Yves Boëlle and Antoine Flahault and Neil M. Ferguson}, + journal = {Nature}, + title = {Estimating the impact of school closure on influenza transmission from Sentinel data}, + year = {2008}, + month = {apr}, + number = {7188}, + pages = {750--754}, + volume = {452}, + doi = {10.1038/nature06732}, + publisher = {Springer Science and Business Media {LLC}}, +} + +@Article{Litvinova2019, + author = {Maria Litvinova and Quan-Hui Liu and Evgeny S. Kulikov and Marco Ajelli}, + journal = {Proceedings of the National Academy of Sciences}, + title = {Reactive school closure weakens the network of social interactions and reduces the spread of influenza}, + year = {2019}, + month = {jun}, + number = {27}, + pages = {13174--13181}, + volume = {116}, + doi = {10.1073/pnas.1821298116}, + publisher = {Proceedings of the National Academy of Sciences}, +} + +@Article{Bi2020, + author = {Qifang Bi and Yongsheng Wu and Shujiang Mei and Chenfei Ye and Xuan Zou and Zhen Zhang and Xiaojian Liu and Lan Wei and Shaun A Truelove and Tong Zhang and Wei Gao and Cong Cheng and Xiujuan Tang and Xiaoliang Wu and Yu Wu and Binbin Sun and Suli Huang and Yu Sun and Juncen Zhang and Ting Ma and Justin Lessler and Teijian Feng}, + title = {Epidemiology and Transmission of {COVID}-19 in Shenzhen China: Analysis of 391 cases and 1,286 of their close contacts}, + year = {2020}, + month = {mar}, + doi = {10.1101/2020.03.03.20028423}, + publisher = {Cold Spring Harbor Laboratory}, +} + +@Article{Riou2020, + author = {Julien Riou and Christian L. Althaus}, + title = {Pattern of early human-to-human transmission of Wuhan 2019-{nCoV}}, + year = {2020}, + month = {jan}, + doi = {10.1101/2020.01.23.917351}, + publisher = {Cold Spring Harbor Laboratory}, +} + +@Article{Majumder2020, + author = {Maimuna Majumder and Kenneth D. Mandl}, + journal = {{SSRN} Electronic Journal}, + title = {Early Transmissibility Assessment of a Novel Coronavirus in Wuhan, China}, + year = {2020}, + doi = {10.2139/ssrn.3524675}, + publisher = {Elsevier {BV}}, +} + +@Article{Zhao2020, + author = {Shi Zhao and Qianyin Lin and Jinjun Ran and Salihu S. Musa and Guangpu Yang and Weiming Wang and Yijun Lou and Daozhou Gao and Lin Yang and Daihai He and Maggie H. Wang}, + journal = {International Journal of Infectious Diseases}, + title = {Preliminary estimation of the basic reproduction number of novel coronavirus (2019-{nCoV}) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak}, + year = {2020}, + month = {mar}, + pages = {214--217}, + volume = {92}, + doi = {10.1016/j.ijid.2020.01.050}, + publisher = {Elsevier {BV}}, +} + +@Article{Halpern2015, + author = {Neil A. Halpern and Stephen M. Pastores}, + journal = {Critical Care Medicine}, + title = {Critical care medicine beds, use, occupancy and costs in the United States: a methodological review}, + year = {2015}, + month = {nov}, + number = {11}, + pages = {2452-2459}, + volume = {43}, + doi = {10.1097/CCM.0000000000001227}, + publisher = {Critical Care Medicine}, +} + +@Article{Metcalf2011, + author = {C.J.E. Metcalf and C. V. Munayco and C. Viboud and G. Chowell and B.T. Grenfell and O.N. Bjornstad}, + journal = {Journal of the Royal Society Interface}, + title = {Rubella metapopulation dynamics and importance of spatial coupling to the risk of congenital rubella syndrome in Peru}, + year = {2011}, + pages = {369-376}, + volume = {8}, + issue = {56}, +} + +@Article{Word2012, + author = {D.P. Word and D.A. Cummings and D.S. Burke and S. Iamsirithaworn and C.D. Laird}, + journal = {Journal of the Royal Society Interface}, + title = {A nonlinear programming approach for estimation of transmission parameters in childhood infectious disease using a continuous time model}, + year = {2012}, + pages = {1983-1997}, + volume = {9}, + issue = {73}, +} + +@Article{Finkenstadt2002, + author = {B.F. Finkenstadt and O.N. Bjornstad and B.T. Grenfell}, + journal = {Biostatistics}, + title = {A stochastic model for extinction and recurrennce of epidemics: estimation and inference for measles outbreaks}, + year = {2002}, + pages = {493-510}, + volume = {3}, + issue = {4}, +} + +@Article{Becker2017, + author = {A.D. Becker and B.T. Grenfell}, + journal = {PLOS One}, + title = {tSIR: An R package for time-series Susceptible-Infected-Recovered models of epidemics}, + year = {2017}, + volume = {12}, + issue = {9}, +} + +@Comment{jabref-meta: databaseType:bibtex;} diff --git a/R/pkgs/report_generation/inst/rmarkdown/templates/state_report/skeleton/skeleton.Rmd b/R/pkgs/report.generation/inst/rmarkdown/templates/state_report/skeleton/skeleton.Rmd similarity index 94% rename from R/pkgs/report_generation/inst/rmarkdown/templates/state_report/skeleton/skeleton.Rmd rename to R/pkgs/report.generation/inst/rmarkdown/templates/state_report/skeleton/skeleton.Rmd index 2594bff24..151db8c49 100644 --- a/R/pkgs/report_generation/inst/rmarkdown/templates/state_report/skeleton/skeleton.Rmd +++ b/R/pkgs/report.generation/inst/rmarkdown/templates/state_report/skeleton/skeleton.Rmd @@ -142,14 +142,14 @@ cap <- paste0("**Fig. ", fig_counter, "**: Daily hospital occupancy for 15 simul ```{r load_cum_inf_geounit_dates} ###Load cumulative infections on specific dates doParallel::registerDoParallel(ncores) - cum_inf_dates <- load_cum_inf_geounit_dates(scn_dirs, - num_files = nfiles, - display_dates = config$report$formatting$display_dates, - scenariolabels = config$report$formatting$scenario_labels, - incl_geoids = included_geoids, - geoid_len = 5, - file_extension="auto") + num_files = nfiles, + scenariolabels = config$report$formatting$scenario_labels, + name_filter= config$hospitalization$parameters$p_death_names[1], ## includes only one pdeath because interest is only in infections here + incl_geoids = included_geoids, + geoid_len = 5, + file_extension="auto") %>% + mutate(pdeath=config$hospitalization$parameters$p_death[1]) doParallel::stopImplicitCluster() registerDoSEQ() @@ -250,7 +250,7 @@ fig_counter <- fig_counter+1 `r paste("**Tab.", tab_counter, "** State-level summary for", config$report$formatting$scenario_labels[1], "scenario reported for the period from", sim_start_date, "through the dates specified by the column headers.")` ```{r scn_state_table1} -make_scn_state_table(config$report$formatting$scenario_labels[1], +make_scn_state_table_withVent(config$report$formatting$scenario_labels[1], state_hosp_totals, table_dates = config$report$formatting$display_dates, pdeath_labels = config$report$formatting$pdeath_labels, @@ -282,7 +282,8 @@ ARmap3 <- plot_geounit_attack_rate_map(cum_inf_dates, shp, scenariolabel = config$report$formatting$scenario_labels[1], display_date = config$report$formatting$display_dates[3], - viridis_palette = "cividis") + viridis_palette = "cividis", + popnodes = config$spatial_setup$popnodes) cowplot::plot_grid(ARmap1, ARmap2, ARmap3, ncol=3) cap <- paste("**Fig.", fig_counter, "** County-level map of infections per 10,000 for", config$report$formatting$scenario_labels[1], " strategy.") diff --git a/R/pkgs/report_generation/inst/rmarkdown/templates/state_report/template.yaml b/R/pkgs/report.generation/inst/rmarkdown/templates/state_report/template.yaml similarity index 100% rename from R/pkgs/report_generation/inst/rmarkdown/templates/state_report/template.yaml rename to R/pkgs/report.generation/inst/rmarkdown/templates/state_report/template.yaml diff --git a/R/pkgs/report_generation/tests/testthat.R b/R/pkgs/report.generation/tests/testthat.R similarity index 100% rename from R/pkgs/report_generation/tests/testthat.R rename to R/pkgs/report.generation/tests/testthat.R diff --git a/R/pkgs/report_generation/tests/testthat/test-load_shape_file.R b/R/pkgs/report.generation/tests/testthat/test-load_shape_file.R similarity index 100% rename from R/pkgs/report_generation/tests/testthat/test-load_shape_file.R rename to R/pkgs/report.generation/tests/testthat/test-load_shape_file.R diff --git a/R/pkgs/report_generation/tests/testthat/test-test_loading.R b/R/pkgs/report.generation/tests/testthat/test-test_loading.R similarity index 100% rename from R/pkgs/report_generation/tests/testthat/test-test_loading.R rename to R/pkgs/report.generation/tests/testthat/test-test_loading.R diff --git a/R/pkgs/report_generation/R/setup_testing_environment.R b/R/pkgs/report_generation/R/setup_testing_environment.R deleted file mode 100644 index c2ea2c20e..000000000 --- a/R/pkgs/report_generation/R/setup_testing_environment.R +++ /dev/null @@ -1,221 +0,0 @@ -#' @export -setup_testing_environment <- function(cf = "config.yml"){ - params = list(config_file = cf) - library(tidyverse) - library(covidcommon) - library(report.generation) - - LOADED_CONFIG <<- FALSE - LOADED_GEOIDS <<- FALSE - LOADED_HOSP_STATE_TOTALS <<- FALSE - LOADED_INF_CTY_PEAKS <<- FALSE - LOADED_HOSP_CTY_PEAKS <<- FALSE - LOADED_HOSP_CTY_TOTALS <<- FALSE - LOADED_INF_CTY_TOTALS <<- FALSE - LOADED_SHAPEFILES <<- FALSE - LOADED_POPULATION <<- FALSE - - - if(! LOADED_CONFIG){ - if(is.null(params$config_file)){ - stop("A document parameter `config_file` is required to load the config file") - } - config <- covidcommon:::load_config(params$config_file) - LOADED_CONFIG <<- TRUE - } - - ## Code loads the state geodata if it has not yet been loaded - if(!LOADED_GEOIDS){ - geodata <<- read.csv(file.path(config$spatial_setup$base_path, config$spatial_setup$geodata)) - geodata$geoid <<- ifelse(nchar(geodata$geoid)==4, paste0("0", geodata$geoid), as.character(geodata$geoid)) - included_geoids <<- geodata[["geoid"]][geodata[[config$spatial_setup$include_in_report]]] - LOADED_GEOIDS <<- TRUE - } - - - if (!LOADED_CONFIG) { stop("This chunk requires the config to be loaded")} - ## Code loads the state hospitalization totals if it has not yet been loaded - if (!LOADED_HOSP_CTY_PEAKS) { - hosp_post_process <- function(x) { - x %>% - ungroup %>% - filter(!is.na(time)) %>% - group_by(geoid) %>% - dplyr::slice(which.max(hosp_curr)) %>% - ungroup - } - - scn_dirs <- paste(config$name,config$interventions$scenarios,sep='_') - hosp_cty_peaks <<- NULL - - for (i in 1:length(scn_dirs)) { - for (pdeath in config$hospitalization$parameters$p_death_names) { - hosp_cty_peaks <<- dplyr::bind_rows(hosp_cty_peaks, load_hosp_sims_filtered(scn_dirs[i], - name_filter = pdeath, - post_process = hosp_post_process) %>% - mutate(scenario_num=i, scenario_name=config$report$formatting$scenario_labels[i], pdeath=pdeath)) - } - } - - - LOADED_HOSP_CTY_PEAKS <<- TRUE - } - - - if (!LOADED_CONFIG){stop("This chunk requires the config to be loaded")} - ## Code loads the state hospitalization totals if it has not yet been loaded - if (!LOADED_HOSP_CTY_TOTALS) { - hosp_post_process <- function(x) { - x %>% - dplyr::filter(!is.na(time)) %>% - dplyr::filter(geoid %in% included_geoids) %>% - group_by(geoid, time, sim_num) %>% - summarize(NhospCurr = sum(hosp_curr), - NICUCurr = sum(icu_curr), - NincidDeath = sum(incidD), - NincidInf = sum(incidI), - NincidICU=sum(incidICU), - NincidHosp=sum(incidH)) %>% - ungroup() - - } - - scn_dirs <<- paste(config$name,config$interventions$scenarios,sep='_') - hosp_cty_totals <<- NULL - - for (i in 1:length(scn_dirs)) { - for (pdeath in config$hospitalization$parameters$p_death_names) { - hosp_cty_totals <<- dplyr::bind_rows(hosp_cty_totals, load_hosp_sims_filtered(scn_dirs[i], - name_filter = pdeath, - post_process = hosp_post_process) %>% - mutate(scenario_num=i, scenario_name=config$report$formatting$scenario_labels[i], pdeath=pdeath)) - } - } - - - LOADED_HOSP_CTY_TOTALS <<- TRUE - } - - - - if (!LOADED_CONFIG){stop("This chunk requires the config to be loaded")} - - if (!LOADED_HOSP_STATE_TOTALS) { - hosp_post_process <- function(x) { - x %>% - dplyr::filter(!is.na(time)) %>% - group_by(time, sim_num) %>% - dplyr::summarize(NhospCurr = sum(hosp_curr), - NICUCurr = sum(icu_curr), - NincidDeath = sum(incidD), - NincidInf = sum(incidI), - NincidICU=sum(incidICU), - NincidHosp=sum(incidH)) %>% - ungroup() - } - - scn_dirs <<- paste(config$name,config$interventions$scenarios,sep='_') - hosp_state_totals <<- NULL - - for (i in 1:length(scn_dirs)) { - for (pdeath in config$hospitalization$parameters$p_death_names) { - hosp_state_totals <<- dplyr::bind_rows(hosp_state_totals, load_hosp_sims_filtered(scn_dirs[i], - name_filter = pdeath, - post_process = hosp_post_process) %>% - mutate(scenario_num = i, scenario_name = config$report$formatting$scenario_labels[i], pdeath=pdeath)) - } - } - - - LOADED_HOSP_STATE_TOTALS <- TRUE - } - - - - if(!LOADED_CONFIG){stop("This chunk requires the config to be loaded")} - ## Code loads the county infection peaks if it has not yet been loaded - if (!LOADED_INF_CTY_PEAKS) { - - inf_pre_process <- function(x) { - x %>% - dplyr::filter(comp == "diffI") - } - - inf_post_process <- function(x) { - x %>% - ungroup %>% - dplyr::filter(!is.na(time)) %>% - dplyr::mutate(geoid=ifelse(nchar(geoid)==4, paste0("0",geoid),geoid)) %>% - dplyr::filter(geoid %in% included_geoids) %>% - group_by(geoid) %>% - dplyr::slice(which.max(N)) %>% - ungroup - } - - scn_dirs <<- paste(config$name,config$interventions$scenarios,sep='_') - inf_cty_peaks <<- NULL - - for (i in 1:length(scn_dirs)) { - inf_cty_peaks <<- dplyr::bind_rows(inf_cty_peaks, load_scenario_sims_filtered(scn_dirs[i], - pre_process = inf_pre_process, - post_process = inf_post_process) %>% - mutate(scenario_num=i, - scenario_name=config$report$formatting$scenario_labels[i])) - - } - - - LOADED_INF_CTY_PEAKS <<- TRUE - } - - - if(!LOADED_CONFIG){stop("This chunk requires the config to be loaded")} - ## Code loads the county infection peaks if it has not yet been loaded - if (!LOADED_INF_CTY_TOTALS) { - - inf_pre_process <- function(x) { - x %>% - dplyr::filter(comp == "cumI") - } - - inf_post_process <- function(x) { - x %>% - ungroup %>% - dplyr::mutate(geoid=ifelse(nchar(geoid)==4, paste0("0",geoid),geoid)) %>% - dplyr::filter(!is.na(time), geoid %in% included_geoids) - } - - scn_dirs <<- paste(config$name,config$interventions$scenarios,sep='_') - inf_cty_totals <<- NULL - - for (i in 1:length(scn_dirs)) { - inf_cty_totals <<- inf_cty_totals %>% - dplyr::bind_rows(load_scenario_sims_filtered(scn_dirs[i], - pre_process = inf_pre_process, - post_process = inf_post_process) %>% - mutate(scenario_num=i, - scenario_name=config$report$formatting$scenario_labels[i]) %>% - group_by(geoid, time, scenario_num, scenario_name) %>% - dplyr::summarize(Nincid=mean(N)) %>% - ungroup() - ) - } - - LOADED_INF_CTY_TOTALS <<- TRUE - } - - if (!LOADED_CONFIG){stop("This chunk requires loading the config")} - - if (!LOADED_SHAPEFILES | !LOADED_POPULATION){ - shp <<- suppressMessages(sf::st_read(paste(config$spatial_setup$base_path,config$spatial_setup$shapefile_name,sep='/'), quiet=TRUE) %>% - dplyr::rename(geoid = GEOID, countyname = NAME)) - shp <- shp[shp[["geoid"]] %in% included_geoids,] - LOADED_SHAPEFILES <<- TRUE - - cty_names <<- shp %>% - sf::st_drop_geometry() %>% - dplyr::select(geoid, countyname) - LOADED_POPULATION <<- TRUE - } - -} diff --git a/R/scripts/build_US_setup.R b/R/scripts/build_US_setup.R index 47ed3703f..532d6cb4c 100644 --- a/R/scripts/build_US_setup.R +++ b/R/scripts/build_US_setup.R @@ -1,5 +1,38 @@ +## +# @file +# @brief Creates mobility and geodata for US +# +# @details +# +# ## Configuration Items +# +# ```yaml +# spatial_setup: +# base_path: +# modeled_states: e.g. MD, CA, NY +# mobility: optional; default is 'mobility.csv' +# geodata: optional; default is 'geodata.csv' +# popnodes: optional; default is 'population' +# +# importation: +# census_api_key: default is environment variable CENSUS_API_KEY. Environment variable is preferred so you don't accidentally commit your key. +# ``` +# +# ## Input Data +# +# None +# +# ## Output Data +# +# * {spatial_setup::base_path}/{spatial_setup::mobility} +# * {spatial_setup::base_path}/{spatial_setup::geodata} +# + +## @cond + library(dplyr) library(tidyr) +library(tidycensus) option_list = list( optparse::make_option(c("-c", "--config"), action="store", default=Sys.getenv("CONFIG_PATH"), type='character', help="path to the config file"), @@ -9,49 +42,102 @@ option_list = list( opt = optparse::parse_args(optparse::OptionParser(option_list=option_list)) config <- covidcommon::load_config(opt$c) -if (is.na(config)) { +if (length(config) == 0) { stop("no configuration found -- please set CONFIG_PATH environment variable or use the -c command flag") } outdir <- config$spatial_setup$base_path filterUSPS <- config$spatial_setup$modeled_states -commute_data <- readr::read_csv(paste(opt$p,"sample_data","united-states-commutes","commute_data.csv",sep='/')) -census_data <- readr::read_csv(paste(opt$p,"sample_data","united-states-commutes","census_tracts_2010.csv", sep = '/')) +dir.create(outdir, showWarnings = FALSE, recursive = TRUE) +# commute_data <- readr::read_csv(paste(opt$p,"sample_data","united-states-commutes","commute_data.csv",sep='/')) +# census_data <- readr::read_csv(paste(opt$p,"sample_data","united-states-commutes","census_tracts_2010.csv", sep = '/')) + + +# Get census key +census_key = Sys.getenv("CENSUS_API_KEY") +if(length(config$importation$census_api_key) != 0) +{ + census_key = config$importation$census_api_key +} +if(census_key == "") +{ + stop("no census key found -- please set CENSUS_API_KEY environment variable or specify importation::census_api_key in config file") +} +tidycensus::census_api_key(key = census_key) +# CENSUS DATA +census_data <- tidycensus::get_acs(geography="county", state=filterUSPS, + variables="B01003_001", year=config$spatial_setup$census_year, + keep_geo_vars=TRUE, geometry=FALSE, show_call=TRUE) census_data <- census_data %>% - filter(USPS %in% filterUSPS) %>% - select(USPS,GEOID,POP10) %>% - mutate(GEOID = substr(GEOID,1,5)) + rename(population=estimate, geoid=GEOID) %>% + select(geoid, population) %>% + mutate(geoid = substr(geoid,1,5)) +# Add USPS column +data(fips_codes) +fips_geoid_codes <- mutate(fips_codes, geoid=paste0(state_code,county_code)) %>% + group_by(geoid) %>% + summarize(USPS=unique(state)) +census_data <- census_data %>% left_join(fips_geoid_codes, by="geoid") + +# Make each territory one county. +# Puerto Rico is the only one in the 2018 ACS estimates right now. Aggregate it. +# Keeping the other territories in the aggregation just in case they're there in the future. name_changer <- setNames( - unique(census_data$GEOID), - unique(census_data$GEOID) + unique(census_data$geoid), + unique(census_data$geoid) ) -name_changer[grepl("^60",name_changer)] <- "60000" -name_changer[grepl("^66",name_changer)] <- "66000" -name_changer[grepl("^69",name_changer)] <- "69000" -name_changer[grepl("^72",name_changer)] <- "72000" -name_changer[grepl("^78",name_changer)] <- "78000" +name_changer[grepl("^60",name_changer)] <- "60000" # Amerian Samoa +name_changer[grepl("^66",name_changer)] <- "66000" # Guam +name_changer[grepl("^69",name_changer)] <- "69000" # Northern Mariana Islands +name_changer[grepl("^72",name_changer)] <- "72000" # Puerto Rico +name_changer[grepl("^78",name_changer)] <- "78000" # Virgin Islands + +census_data <- census_data %>% + mutate(geoid = name_changer[geoid]) %>% + group_by(geoid) %>% + summarize(USPS = unique(USPS), population = sum(population)) +# Territory populations (except Puerto Rico) taken from from https://www.census.gov/prod/cen2010/cph-2-1.pdf +terr_census_data <- readr::read_csv(paste(opt$p,"sample_data","united-states-commutes","census_tracts_island_areas_2010.csv",sep='/')) + +census_data <- terr_census_data %>% + filter(length(filterUSPS) == 0 | ((USPS %in% filterUSPS) & !(USPS %in% census_data)))%>% + rbind(census_data) + +# Sort by population census_data <- census_data %>% - mutate(GEOID = name_changer[GEOID]) %>% - group_by(GEOID) %>% - summarize(USPS = unique(USPS),POP10 = sum(POP10)) %>% - arrange(POP10) + arrange(population) + +if (!is.null(config$spatial_setup$popnodes)) { + names(census_data)[names(census_data) == "population"] <- config$spatial_setup$popnodes +} + +if (length(config$spatial_setup$geodata) > 0) { + geodata_file <- config$spatial_setup$geodata +} else { + geodata_file <- 'geodata.csv' +} +write.csv(file = file.path(outdir, geodata_file), census_data, row.names=FALSE) +print(paste("Wrote geodata file:", file.path(outdir, geodata_file))) + +# COMMUTE DATA +commute_data <- readr::read_csv(paste(opt$p,"sample_data","united-states-commutes","commute_data.csv",sep='/')) commute_data <- commute_data %>% mutate(OFIPS = substr(OFIPS,1,5), DFIPS = substr(DFIPS,1,5)) %>% mutate(OFIPS = name_changer[OFIPS], DFIPS = name_changer[DFIPS]) %>% - filter(OFIPS %in% census_data$GEOID, DFIPS %in% census_data$GEOID) %>% + filter(OFIPS %in% census_data$geoid, DFIPS %in% census_data$geoid) %>% group_by(OFIPS,DFIPS) %>% summarize(FLOW = sum(FLOW)) %>% filter(OFIPS != DFIPS) padding_table <- tibble( - OFIPS = census_data$GEOID, - DFIPS = census_data$GEOID, + OFIPS = census_data$geoid, + DFIPS = census_data$geoid, FLOW = 0 ) @@ -62,20 +148,31 @@ t_commute_table <- tibble( ) rc <- padding_table %>% bind_rows(commute_data) %>% bind_rows(t_commute_table) + if(opt$w){ - rc <- rc %>%pivot_wider(OFIPS,names_from=DFIPS,values_from=FLOW, values_fill=c("FLOW"=0),values_fn = list(FLOW=sum)) + mobility_file <- 'mobility.txt' +} else if (length(config$spatial_setup$mobility) > 0) { + mobility_file <- config$spatial_setup$mobility +} else { + mobility_file <- 'mobility.csv' } -print(outdir) -if(opt$w){ - if(!isTRUE(all(rc$OFIPS == census_data$GEOID))){ +if(endsWith(mobility_file, '.txt')) { + rc <- rc %>% pivot_wider(OFIPS,names_from=DFIPS,values_from=FLOW, values_fill=c("FLOW"=0),values_fn = list(FLOW=sum)) + if(!isTRUE(all(rc$OFIPS == census_data$geoid))){ + print(rc$OFIPS) + print(census_data$geoid) stop("There was a problem generating the mobility matrix") } - write.table(file = file.path(outdir,'mobility.txt'), as.matrix(rc[,-1]), row.names=FALSE, col.names = FALSE, sep = " ") -} else { + write.table(file = file.path(outdir, mobility_file), as.matrix(rc[,-1]), row.names=FALSE, col.names = FALSE, sep = " ") +} else if(endsWith(mobility_file, '.csv')) { names(rc) <- c("ori","dest","amount") rc <- rc[rc$ori != rc$dest,] - write.csv(file = file.path(outdir,'mobility.csv'), rc, row.names=FALSE) + write.csv(file = file.path(outdir, mobility_file), rc, row.names=FALSE) +} else { + stop("Only .txt and .csv extensions supported for mobility matrix. Please check config's spatial_setup::mobility.") } -names(census_data) <- c("geoid","USPS","pop2010") -write.csv(file = file.path(outdir,'geodata.csv'), census_data,row.names=FALSE) + +print(paste("Wrote mobility file:", file.path(outdir, mobility_file))) + +## @endcond diff --git a/R/scripts/build_nonUS_setup.R b/R/scripts/build_nonUS_setup.R new file mode 100644 index 000000000..bc4d0360b --- /dev/null +++ b/R/scripts/build_nonUS_setup.R @@ -0,0 +1,120 @@ +## +# @file +# @brief Creates mobility and geodata for non-US location +# +# @details +# +# ## Configuration Items +# +# ```yaml +# spatial_setup: +# base_path: +# modeled_states: e.g. ZMB, BGD, CAN +# mobility: optional; default is 'mobility.csv' +# geodata: optional; default is 'geodata.csv' +# popnodes: optional; default is 'pop' +# +# +# ## Input Data +# +# None +# +# ## Output Data +# +# * {spatial_setup::base_path}/{spatial_setup::mobility} +# * {spatial_setup::base_path}/{spatial_setup::geodata} +# + +## @cond + +library(dplyr) +library(tidyr) + +option_list = list( + optparse::make_option(c("-c", "--config"), action="store", default="config.yml", type='character', help="path to the config file"), + optparse::make_option(c("-w", "--wide_form"), action="store",default=FALSE,type='logical',help="Whether to generate the old wide format mobility or the new long format"), + optparse::make_option(c("-n", "--population"), action="store",default="population_data.csv",type='character',help="Name of the popultion data file"), + optparse::make_option(c("-m", "--mobility"), action="store",default="mobility_data.csv",type='character',help="Name of the mobility data file") +) +opt = optparse::parse_args(optparse::OptionParser(option_list=option_list)) + +config <- covidcommon::load_config(opt$config) +if (length(config) == 0) { + stop("no configuration found -- please set CONFIG_PATH environment variable or use the -c command flag") +} + +outdir <- config$spatial_setup$base_path +filterADMIN0 <- config$spatial_setup$modeled_states + +dir.create(outdir, showWarnings = FALSE, recursive = TRUE) + +# Read in needed data +commute_data <- readr::read_csv(file.path(config$spatial_setup$base_path, "geodata", opt$mobility)) %>% + mutate(OGEOID = as.character(OGEOID), + DGEOID = as.character(DGEOID)) +census_data <- readr::read_csv(file.path(config$spatial_setup$base_path, "geodata", opt$population)) %>% + mutate(GEOID = as.character(GEOID)) + +# Filter if needed +if (!(is.null(filterADMIN0) || is.na(filterADMIN0))){ + census_data <- census_data %>% + dplyr::filter(ADMIN0 %in% filterADMIN0) +} + +census_data <- census_data %>% + dplyr::select(ADMIN0,GEOID,ADMIN2,POP) %>% + dplyr::group_by(GEOID,ADMIN2) %>% + dplyr::summarize(ADMIN0 = unique(ADMIN0), POP = sum(POP)) %>% + dplyr::arrange(POP) + +commute_data <- commute_data %>% + dplyr::filter(OGEOID %in% census_data$GEOID, DGEOID %in% census_data$GEOID) %>% + dplyr::group_by(OGEOID, DGEOID) %>% + dplyr::summarize(FLOW = sum(FLOW)) %>% + dplyr::filter(OGEOID != DGEOID) + +padding_table <- tibble::tibble( + OGEOID = census_data$GEOID, + DGEOID = census_data$GEOID, + FLOW = 0 +) + +t_commute_table <- tibble::tibble( + OGEOID = commute_data$DGEOID, + DGEOID = commute_data$OGEOID, + FLOW = commute_data$FLOW +) + +rc <- padding_table %>% + dplyr::bind_rows(commute_data) %>% + dplyr::bind_rows(t_commute_table) + +# Make wide if specified +if(opt$w){ + rc <- rc %>% tidyr::pivot_wider(OGEOID, names_from=DGEOID, values_from=FLOW, values_fill=c("FLOW"=0), values_fn = list(FLOW=sum)) +} + + +if(opt$w){ + if(!isTRUE(all(rc$OGEOID == census_data$GEOID))){ + stop("There was a problem generating the mobility matrix") + } + write.table(file = file.path(outdir,'mobility.txt'), as.matrix(rc[,-1]), row.names=FALSE, col.names = FALSE, sep = " ") +} else { + names(rc) <- c("ori","dest","amount") + rc <- rc[rc$ori != rc$dest,] + write.csv(file = file.path(outdir,'mobility.csv'), rc, row.names=FALSE) +} + +# Save population geodata +names(census_data) <- c("geoid","admin2","admin0","pop") +write.csv(file = file.path(outdir,'geodata.csv'), census_data,row.names=FALSE) + +print("Census Data Check (up to 6 rows)") +print(head(census_data)) +print("Commute Data Check (up to 6 rows)") +print(head(commute_data)) + +print(paste0("mobility.csv/.txt and geodata.csv saved to: ", outdir)) + + diff --git a/R/scripts/create_seeding.R b/R/scripts/create_seeding.R index 9d79f3e84..9a8d6029c 100644 --- a/R/scripts/create_seeding.R +++ b/R/scripts/create_seeding.R @@ -1,6 +1,6 @@ ## # @file -# @brief Creates a filter file +# @brief Creates a seeding file # # @details # @@ -8,7 +8,6 @@ # ## Configuration Items # # ```yaml -# dynfilter_path: # start_date: # end_date: # @@ -17,6 +16,8 @@ # base_path: # geodata: # nodenames: +# lambda_file: + # ``` # # ## Input Data @@ -26,7 +27,7 @@ # ## Output Data # # * importation/{spatial_setup::setup_name}/case_data/jhucsse_case_data.csv is a csv with case data from JHU CSSE -# * {dynfilter_path}: filter file +# * {spatial_setup::lambda_file}: seeding file # ## @cond @@ -38,61 +39,146 @@ library(tidyr) library(purrr) option_list = list( - optparse::make_option(c("-c", "--config"), action="store", default=Sys.getenv("CONFIG_PATH"), type='character', help="path to the config file") + optparse::make_option(c("-c", "--config"), action="store", default=Sys.getenv("CONFIG_PATH"), type='character', help="path to the config file"), + optparse::make_option(c("-s", "--source"), action="store", default="CSSE", type='character', help="source of case data: USAFacts or CSSE"), + optparse::make_option(c("-d", "--data"), action="store", default=file.path("data","case_data","case_data.csv"), type='character', help="path to the case data file") ) -opts = optparse::parse_args(optparse::OptionParser(option_list=option_list)) +opt = optparse::parse_args(optparse::OptionParser(option_list=option_list)) -config <- covidcommon::load_config(opts$c) +print(paste0("Using config file: ", opt$config)) +config <- covidcommon::load_config(opt$config) if (length(config) == 0) { stop("no configuration found -- please set CONFIG_PATH environment variable or use the -c command flag") } -jhucsse <- covidImportation::get_clean_JHUCSSE_data(aggr_level = "UID", - last_date = as.POSIXct(lubridate::ymd(config$end_date)), - case_data_dir = file.path('importation',config$spatial_setup$setup_name,"case_data"), - save_raw_data=TRUE, - us_data_only=FALSE) - -print("Successfully pulled JHU CSSE data for seeding.") - all_times <- lubridate::ymd(config$start_date) + seq_len(lubridate::ymd(config$end_date) - lubridate::ymd(config$start_date)) -geodata <- report.generation:::load_geodata_file(file.path(config$spatial_setup$base_path, config$spatial_setup$geodata),5,'0',TRUE) -all_geoids <- geodata[[config$spatial_setup$nodenames]] -incident_cases <- jhucsse %>% - dplyr::filter(FIPS %in% all_geoids) %>% - dplyr::select(Update, FIPS, incidI) -incident_cases$Update <- as.Date(incident_cases$Update) +# Get the data + + +# get data if a US model --------------------------------- + +if (is.null(config$spatial_setup$us_model) || config$spatial_setup$us_model==TRUE){ + + # Load either JHUCSSE or USAFacts data + if (tolower(opt$source) %in% c("csse", "jhucsse", "jhu csse")){ + + dir.create(file.path('importation',config$spatial_setup$setup_name,"case_data"), showWarnings = FALSE, recursive = TRUE) + + print("Pulling case data from JHU CSSE for US seeding.") + cases_deaths <- covidImportation::get_clean_JHUCSSE_data(aggr_level = "UID", + last_date = as.POSIXct(lubridate::ymd(config$end_date)), + case_data_dir = file.path('importation',config$spatial_setup$setup_name,"case_data"), + save_raw_data=TRUE, + us_data_only=FALSE) + print("Successfully pulled JHU CSSE data for seeding.") + + } else if (tolower(opt$source) %in% c("usafacts", "usa facts", "usa")){ + print("Pulling case data from USA Facts for US seeding.") + cases_deaths <- covidcommon::get_USAFacts_data() + print("Successfully pulled USAFacts data for seeding.") + } else { + stop(paste(opt$source,"is not a recognized source of case data")) + } + + geodata <- report.generation::load_geodata_file(filename = file.path(config$spatial_setup$base_path, config$spatial_setup$geodata), + geoid_len = 5, geoid_pad = '0', to_lower = TRUE) + + + all_geoids <- geodata[[config$spatial_setup$nodenames]] + + incident_cases <- cases_deaths %>% + dplyr::filter(FIPS %in% all_geoids) %>% + dplyr::select(Update, FIPS, incidI) + + incident_cases$Update <- as.Date(incident_cases$Update) + + if(is.null(config$seeding$delay_incidC)){ + config$seeding$delay_incidC <- 5 + } + if(is.null(config$seeding$ratio_incidC)){ + config$seeding$ratio_incidC <- 10 + } + + incident_cases <- incident_cases %>% + dplyr::group_by(FIPS) %>% + dplyr::group_modify(function(.x,.y){ + .x %>% + dplyr::arrange(Update) %>% + dplyr::filter(incidI > 0) %>% + .[seq_len(min(nrow(.x),5)),] %>% + dplyr::mutate( + Update = Update - lubridate::days(config$seeding$delay_incidC), + incidI = config$seeding$ratio_incidC * incidI + .05 + ) + }) + + + +# from file --------------------------------- + +} else { + + print(paste0("Using case data from ", opt$data, "for seeding ", config$spatial_setup$setup_name)) + + case_data <- readr::read_csv(opt$data) + if (!exists("case_data") || is.null(case_data)){ + stop(paste0("ERROR: ", opt$data, "does not exist!")) + } + + geodata <- report.generation::load_geodata_file(filename = file.path(config$spatial_setup$base_path, config$spatial_setup$geodata), + geoid_len = config$spatial_setup$geoid_len, geoid_pad = '0', to_lower = TRUE) + + all_geoids <- geodata[[config$spatial_setup$nodenames]] + + incident_cases <- case_data %>% + dplyr::filter(geoid %in% all_geoids) %>% + dplyr::select(date, geoid, incidI) + + incident_cases$date <- as.Date(incident_cases$date) + + if(is.null(config$seeding$delay_incidC)){ + config$seeding$delay_incidC <- 5 + } + if(is.null(config$seeding$ratio_incidC)){ + config$seeding$ratio_incidC <- 10 + } + + incident_cases <- incident_cases %>% + dplyr::group_by(geoid) %>% + dplyr::group_modify(function(.x,.y){ + .x %>% + dplyr::arrange(date) %>% + dplyr::filter(incidI > 0) %>% + .[seq_len(min(nrow(.x),5)),] %>% + dplyr::mutate( + date = date - lubridate::days(config$seeding$delay_incidC), + incidI = config$seeding$ratio_incidC * incidI + .05 + ) + }) +} -incident_cases <- incident_cases %>% - group_by(FIPS) %>% - group_modify(function(.x,.y){ - .x %>% - arrange(Update) %>% - filter(incidI > 0) %>% - .[seq_len(min(nrow(.x),5)),] %>% - mutate( - Update = Update - lubridate::days(5), - incidI = 10 * incidI + .05 - ) - - }) names(incident_cases) <- c('place','date','amount') incident_cases <- incident_cases %>% dplyr::filter(!is.na(amount) | !is.na(date)) -write.csv( +lambda_dir <- dirname(config$seeding$lambda_file) +if(!dir.exists(lambda_dir)){ + suppressWarnings(dir.create(lambda_dir,recursive=TRUE)) +} + +readr::write_csv( incident_cases, - file=file.path(config$seeding$lambda_file), - row.names=FALSE, - col.names=TRUE, + file.path(config$seeding$lambda_file) ) +print(paste("Saved seeding to",config$seeding$lambda_file)) + ## @endcond diff --git a/R/scripts/hosp_run.R b/R/scripts/hosp_run.R index b2e7acfb1..bf2d2ea14 100644 --- a/R/scripts/hosp_run.R +++ b/R/scripts/hosp_run.R @@ -9,6 +9,12 @@ # ```yaml # name # +# spatial_setup: +# us_model: [Defaults to TRUE if not specified] +# base_path: +# geodata: +# nodenames: +# # interventions: # scenarios: # - @@ -53,6 +59,7 @@ # * model\_output/{name}\_[scenario] is a directory of csv's. # + Each csv must have columns: "time", "comp", and each geoid of interest. # + The "comp" column must have a value of "diffI" in at least one row. +# * {spatial_setup::base_path}/{spatial_setup::geodata} is a csv with columns {spatial_setup::nodenames} and {spatial_setup::popnodes} # # ## Output Data # @@ -78,6 +85,7 @@ library(devtools) library(covidcommon) library(hospitalization) +library(report.generation) library(readr) library(dplyr) library(tidyr) @@ -85,6 +93,7 @@ library(magrittr) library(data.table) library(parallel) library(stringr) +library(doParallel) option_list = list( @@ -101,13 +110,19 @@ option_list = list( optparse::make_option(c("-j", "--jobs"), action="store", default=detectCores(), type='numeric', help="number of cores used"), #' @param -p The path to COVIDScenarioPipeline - optparse::make_option(c("-p", "--path"), action="store", default="COVIDScenarioPipeline", type='character', help="path to the COVIDScenarioPipeline directory") + optparse::make_option(c("-p", "--path"), action="store", default="COVIDScenarioPipeline", type='character', help="path to the COVIDScenarioPipeline directory"), + + #' @param -i The index of the first simulation to run against + optparse::make_option(c("-i", "--index-from-sim"), action="store", default=1, type='numeric', help="The index of the first simulation to run against"), + + #' @param -n The number of simulations to run + optparse::make_option(c("-n", "--num-sims"), action="store", default=-1, type='numeric', help="number of simulations to run") ) opt = optparse::parse_args(optparse::OptionParser(option_list=option_list)) #' @description Run the hospitalization results. #' @importFrom covidcommon load_config -config <- covidcommon::load_config(opt$c) +config <- covidcommon::load_config(opt$config) if (length(config) == 0) { stop("no configuration found -- please set CONFIG_PATH environment variable or use the -c command flag") } @@ -136,6 +151,8 @@ names(p_death) = hosp_parameters$p_death_names cmd <- opt$d scenario <- opt$s ncore <- opt$j +start_sim <- opt$i +num_sims <- opt$n # Verify that the cmd maps to a known p_death value if (cmd == "all") { @@ -151,13 +168,40 @@ if (scenario == "all" ) { quit("yes", status=1) } +is_international <- config$spatial_setup$us_model +if(is.null(is_international)){ + is_international <- FALSE +} + ## Running age-adjusted script if(run_age_adjust){ - + # Specified geoparams or not (data for US model is included in CSP and does not need to be specified) + if (is.null(config$spatial_setup$geoid_params_file)){ + if(is_international) stop("International models require spatial_setup::geoid_params_file specified in the config") + config$spatial_setup$geoid_params_file <- paste(opt$p,"sample_data","geoid-params.csv",sep='/') + } + if (is.null(config$spatial_setup$geoid_len)){ + if(is_international) stop("International models require spatial_setup::geoid_len specified in the config") + config$spatial_setup$geoid_len <- 5 + } + + # Throw some warnings and errors. + print(paste0("Using ", config$spatial_setup$geoid_params_file, " for geounit-specific outcomes.")) + if (!file.exists(config$spatial_setup$geoid_params_file)){ + stop(paste0("ERROR: ", config$spatial_setup$geoid_params_file, " does not exist.")) + } + # read in probability file - # NOTE(jwills): this file would ideally live inside of the hospitalization package as an .Rdata object - prob_dat <- readr::read_csv(paste(opt$p,"sample_data","geoid-params.csv",sep='/')) + prob_dat <- readr::read_csv(config$spatial_setup$geoid_params_file) + prob_dat <- prob_dat %>% mutate(geoid = as.character(geoid)) # so it matches + + geodata <- report.generation:::load_geodata_file(file.path(config$spatial_setup$base_path, config$spatial_setup$geodata),config$spatial_setup$geoid_len,'0',TRUE) + in_geoids <- geodata[[config$spatial_setup$nodenames]] + missing_geoids <- setdiff(in_geoids, prob_dat$geoid) + if(length(missing_geoids) > 0) { + warning(paste("The hospitalization outcomes will not be calculated for geoids not present in geoid-params.csv:", missing_geoids)) + } time_onset_death_pars <- as_evaled_expression(hosp_parameters$time_onset_death) p_hosp_inf <- as_evaled_expression(hosp_parameters$p_hosp_inf) @@ -166,7 +210,7 @@ if(run_age_adjust){ if (length(p_death)!=length(p_hosp_inf)) { stop("Number of IFR and p_hosp_inf values do not match") } - + for (scn0 in scenario) { data_dir <- paste0("model_output/",config$name,"_",scn0) cat(paste(data_dir, "\n")) @@ -185,7 +229,9 @@ if(run_age_adjust){ cores = ncore, data_dir = data_dir, dscenario_name = cmd0, - use_parquet = TRUE + use_parquet = TRUE, + start_sim = start_sim, + num_sims = num_sims ) } } @@ -229,7 +275,9 @@ if(run_age_adjust){ cores = ncore, data_dir = data_dir, dscenario_name = cmd0, - use_parquet = TRUE + use_parquet = TRUE, + start_sim = start_sim, + num_sims = num_sims ) } } diff --git a/R/scripts/make_makefile.R b/R/scripts/make_makefile.R index b724198c3..2b18e8355 100644 --- a/R/scripts/make_makefile.R +++ b/R/scripts/make_makefile.R @@ -3,7 +3,8 @@ option_list = list( optparse::make_option(c("-c", "--config"), action="store", default=Sys.getenv("CONFIG_PATH"), type='character', help="path to the config file"), optparse::make_option(c("-p", "--pipepath"), action="store", default="COVIDScenarioPipeline", type='character', help="path to the COVIDScenarioPipeline directory"), optparse::make_option(c("-n", "--ncoreper"), action="store", default="1", type='character', help="Number of CPUS/jobs for pipeline"), - optparse::make_option(c("-y", "--python"), action="store", default="python3", type='character', help="path to python executable") + optparse::make_option(c("-y", "--python"), action="store", default="python3", type='character', help="path to python executable"), + optparse::make_option(c("-f", "--file_prefix"), action="store", default=FALSE, type='logical', help="whether to use the config$spatial_setup$setup_name as the file prefix") ) parser=optparse::OptionParser(option_list=option_list) @@ -28,7 +29,8 @@ if(isTRUE(config$this_file_is_unedited)){ simulations = config$nsimulations scenarios = config$interventions$scenarios deathrates = config$hospitalization$parameters$p_death_names - +use_file_prefix = opt$file_prefix + cat(simulations) cat("\n") cat(scenarios) @@ -38,11 +40,19 @@ cat("\n") using_importation <- ("importation" %in% names(config)) generating_report <- ("report" %in% names(config)) +if(is.null(config$spatial_setup$us_model)) { + config$spatial_setup$us_model <- FALSE + if("modeled_states" %in% names(config$spatial_setup)){ + config$spatial_setup$us_model <- TRUE + } +} +building_US_setup <- config$spatial_setup$us_model +file_prefix <- ifelse(use_file_prefix, config$spatial_setup$setup_name, "") # prefix of file names if(generating_report) { # Create report name (no suffix) for the .Rmd and .html - report_name = "" + report_name <- "" if(length(config$report_location_name) != 0){ report_name = config$report_location_name } else if(length(config$name) != 0){ @@ -50,7 +60,7 @@ if(generating_report) } else { stop(paste("Please specify report_location_name or name in the config")) } - report_name = paste0(report_name, "_", format(Sys.Date(), format="%Y%m%d")) + report_name <- paste0(report_name, "_", format(Sys.Date(), format="%Y%m%d")) } importation_target_name <- function(simulation, prefix = ""){ @@ -60,7 +70,7 @@ importation_target_name <- function(simulation, prefix = ""){ importation_make_command <- function(simulation,prefix=""){ target_name <- importation_target_name(simulation,prefix) dependency_name <- "" - command_name <- paste0("$(RSCRIPT) $(PIPELINE)/R/scripts/importation.R -c $(CONFIG) -j $(NCOREPER)") + command_name <- "$(RSCRIPT) $(PIPELINE)/R/scripts/importation.R -c $(CONFIG) -j $(NCOREPER)" touch_name <- paste0("touch ",target_name) return(paste0( target_name, ": ", @@ -70,21 +80,58 @@ importation_make_command <- function(simulation,prefix=""){ )) } -filter_target_name <- function(simulation, prefix = "" ){ - paste0(".files/",prefix,simulation,"_filter") +build_location_setup_target_name <- function() { + return(file.path(config$spatial_setup$base_path, config$spatial_setup$mobility)) } -filter_make_command <- function(simulation,prefix=""){ - target_name <- filter_target_name(simulation,prefix) - dependency_name <- importation_target_name(simulation, prefix=prefix) - command_name<- paste0("$(RSCRIPT) $(PIPELINE)/R/scripts/create_filter.R -c $(CONFIG)") - touch_name <- paste0("touch ",target_name) - return(paste0( - target_name, ": .files/directory_exists ", - dependency_name, "\n", - "\t",command_name, "\n", - "\t",touch_name, "\n" - )) +geodata_name <- function() { + return(file.path(config$spatial_setup$base_path, config$spatial_setup$geodata)) +} + +build_US_setup_make_command <- function() { + command_name <- paste0(build_location_setup_target_name(),":\n") + command_name <- paste0(command_name, "\tmkdir -p ", config$spatial_setup$base_path, "\n") + command_name <- paste0(command_name, "\t$(RSCRIPT) $(PIPELINE)/R/scripts/build_US_setup.R -c $(CONFIG) -p $(PIPELINE)") + return(command_name) +} + +build_nonUS_pop_setup_name <- function() { + return(file.path(config$spatial_setup$base_path, config$spatial_setup$nonUS_pop_setup)) +} + +build_nonUS_mobility_setup_name <- function() { + return(file.path(config$spatial_setup$base_path, config$spatial_setup$nonUS_mobility_setup)) +} + +build_nonUS_setup_make_command <- function() { + command_name <- paste0(build_location_setup_target_name(),":\n") + command_name <- paste0(command_name, "\tmkdir -p ", config$spatial_setup$base_path, "\n") + command_name <- paste0(command_name, "\t$(RSCRIPT) $(PIPELINE)/R/scripts/build_nonUS_setup.R -c $(CONFIG) -p $(PIPELINE) -n ", build_nonUS_pop_setup_name(), " -m ", build_nonUS_mobility_setup_name()) + return(command_name) +} + +create_seeding_target_name <- function() { + return(file.path(config$seeding$lambda_file)) +} + +create_US_seeding_make_command <- function() { + command_name <- paste0(create_seeding_target_name(),":\n") + command_name <- paste0(command_name, "\t$(RSCRIPT) $(PIPELINE)/R/scripts/create_seeding.R -c $(CONFIG)") + return(command_name) +} + +create_nonUS_seeding_casedata_name <- function() { + return(file.path(config$seeding$casedata_file)) +} + +create_US_seeding_casedata_name <- function() { + return(file.path("data/case_data/case_data.csv")) +} + +create_nonUS_seeding_make_command <- function() { + command_name <- paste0(create_seeding_target_name(),":\n") + command_name <- paste0(command_name, "\t$(RSCRIPT) $(PIPELINE)/R/scripts/create_seeding.R -c $(CONFIG) -d ", create_nonUS_seeding_casedata_name()) + return(command_name) } hospitalization_target_name <- function(simulation,scenario,deathrate, prefix = ''){ @@ -118,9 +165,11 @@ simulation_make_command <- function(simulation,scenario,previous_simulation, pre previous_simulation <- 0 } if(using_importation){ - dependency_name <- paste(dependency_name,filter_target_name(simulation,prefix),importation_target_name(simulation,prefix)) + dependency_name <- paste(dependency_name,importation_target_name(simulation,prefix)) } - command_name <- paste0("$(PYTHON) $(PIPELINE)/simulate.py -c $(CONFIG) -s ",scenario," -n ",simulation - previous_simulation," -j $(NCOREPER)") + dependency_name <- paste(dependency_name, build_location_setup_target_name()) + dependency_name <- paste(dependency_name, create_seeding_target_name()) + command_name <- paste0("$(PYTHON) -m SEIR -c $(CONFIG) -s ",scenario," -n ",simulation - previous_simulation," -j $(NCOREPER)") touch_name <- paste0("touch ",target_name) return(paste0( target_name, ": .files/directory_exists ", @@ -130,6 +179,52 @@ simulation_make_command <- function(simulation,scenario,previous_simulation, pre )) } +report_html_target_name <- function(report_name) { + return(sprintf("notebooks/%s/%s_report.html", report_name, report_name)) +} + +report_html_make_command <- function(report_name, scenarios, simulations, deathrates, config) { + rmd_file = report_rmd_target_name(report_name) + s <- run_dependencies(scenarios, simulations, deathrates) + s <- paste0(s, " ", rmd_file,"\n") + + renderCmd = sprintf("\t$(RSCRIPT) -e 'rmarkdown::render(\"%s\"", rmd_file) + renderCmd = paste0(renderCmd, sprintf(", params=list(state_usps=\"%s\"", config$report$state_usps)) + if(length(config$report$continue_on_error) != 0) + { + renderCmd = paste0(renderCmd, + sprintf(", continue_on_error=%s", config$report$continue_on_error)) + } + renderCmd = paste0(renderCmd, "))'") + + s <- paste0(s, renderCmd, "\n") + return(s) +} + +report_rmd_target_name <- function(report_name) { + return(sprintf("notebooks/%s/%s_report.Rmd", report_name, report_name)) +} + +report_rmd_make_command <- function(report_name) { + return(sprintf("%s: +\tmkdir -p notebooks/%s +\t$(RSCRIPT) -e 'rmarkdown::draft(\"$@\",template=\"state_report\",package=\"report.generation\",edit=FALSE)'\n", +report_rmd_target_name(report_name), report_name)) +} + +run_dependencies <- function(scenarios, simulations, deathrates, prefix="") { + s <- ":" + for(scenario in scenarios) + { + s <- paste0(s, " ", simulation_target_name(simulations, scenario, prefix = prefix)) + for(deathrate in deathrates) + { + s <- paste0(s, " ", hospitalization_target_name(simulations, scenario, deathrate, prefix=prefix)) + } + } + return(s) +} + sink("Makefile") @@ -147,54 +242,35 @@ cat(paste0("CONFIG=",opt$config,"\n\n")) # If generating report, first target is the html file. # Otherwise, first target is run. # For both, the dependencies include all the simulation targets. -if(generating_report) -{ - rmd_file = sprintf("notebooks/%s/%s_report.Rmd", report_name, report_name) - report_html_target_name = sprintf("notebooks/%s/%s_report.html", report_name, report_name) - cat(paste0(report_html_target_name,":")) +if(generating_report) { + cat(report_html_target_name(report_name)) + cat(report_html_make_command(report_name, scenarios, simulations, deathrates, config)) + cat(report_rmd_make_command(report_name)) } else { - cat("run:") + cat("run") + cat(run_dependencies(scenarios, simulations, deathrates, prefix = file_prefix)) } -for(scenario in scenarios) -{ - cat(" ") - cat(simulation_target_name(simulations,scenario)) - for(deathrate in deathrates) - { - cat(" ") - cat(hospitalization_target_name(simulations,scenario,deathrate)) - } -} +cat("\n") -if(generating_report) -{ - # final target dependency for .html is the Rmd - cat(sprintf(" %s\n", rmd_file)) +if(building_US_setup){ + cat(build_US_setup_make_command()) +} else{ + cat(build_nonUS_setup_make_command()) +} - renderCmd = sprintf("\t$(RSCRIPT) -e 'rmarkdown::render(\"%s\"", rmd_file) - renderCmd = paste0(renderCmd, sprintf(", params=list(state_usps=\"%s\"", config$report$state_usps)) - if(length(config$report$continue_on_error) != 0) - { - renderCmd = paste0(renderCmd, - sprintf(", continue_on_error=%s", config$report$continue_on_error)) - } - renderCmd = paste0(renderCmd, "))'") - cat(renderCmd) +cat("\n") - rmd_target = sprintf(" -%s: -\tmkdir -p notebooks/%s -\t$(RSCRIPT) -e 'rmarkdown::draft(\"$@\",template=\"state_report\",package=\"report.generation\",edit=FALSE)'", -rmd_file, report_name) - cat(rmd_target) +if(building_US_setup){ + cat(create_US_seeding_make_command()) +} else{ + cat(create_nonUS_seeding_make_command()) } + cat("\n") if(using_importation){ for(sim_idx in seq_len(length(simulations))){ - - cat(filter_make_command(simulations[sim_idx])) cat(importation_make_command(simulations[sim_idx])) } } @@ -203,51 +279,68 @@ for(sim_idx in seq_len(length(simulations))){ sim <- simulations[sim_idx] prev_sim <- dplyr::lag(simulations)[sim_idx] for(scenario in scenarios){ - cat(simulation_make_command(sim,scenario,prev_sim)) + cat(simulation_make_command(sim,scenario,prev_sim, prefix = file_prefix)) for(deathrate in deathrates){ - cat(hospitalization_make_command(sim,scenario,deathrate)) + cat(hospitalization_make_command(sim,scenario,deathrate, prefix = file_prefix)) } } } cat(" .files/directory_exists: -\tmkdir .files +\tmkdir -p .files \ttouch .files/directory_exists ") -cat(paste0(" +cat("\n\nrerun: rerun_simulations rerun_hospitalization") -rerun: rerun_simulations rerun_hospitalization" -)) +if(using_importation){ + cat(" rerun_importation") +} +cat("\n") if(using_importation){ - cat(paste0("rerun_importation rerun_filter -clean_filter: rerun_filter -\trm -rf ",config$dynfilter_path," +cat(paste0(" clean_importation: rerun_importation \trm -rf data/case_data \trm -rf importation +rerun_importation: +\trm -f .files/*_importation ")) } +if(use_file_prefix){ +cat(paste0(" +rerun_simulations: clean_simulations +\trm -f .files/*", file_prefix, scenario, "_simulation* +rerun_hospitalization: +\trm -f .files/*", file_prefix, simulations, "_hospitalization* +clean: clean_simulations clean_hospitalization" +)) +}else{ cat(paste0(" -rerun_filter: -\trm -f .files/1*_filter -rerun_importation: -\trm -f .files/1*_importation rerun_simulations: clean_simulations -\trm -f .files/1*_simulation* +\trm -f .files/*_simulation* rerun_hospitalization: -\trm -f .files/1*_hospitalization* -clean: clean_simulations clean_hospitalization")) +\trm -f .files/*_hospitalization* +clean: clean_simulations clean_hospitalization clean_location_setup" +)) +} if(using_importation){ - cat(" clean_importation clean_filter") + cat(" clean_importation") } if(generating_report) { cat(" clean_reports") } +if(use_file_prefix){ +cat(" +\trm -rf .files +clean_simulations: rerun_simulations +\trm -rf model_output/", file_prefix, +"clean_hospitalization: rerun_hospitalization +\trm -rf hospitalization/", file_prefix) +}else{ cat(" \trm -rf .files clean_simulations: rerun_simulations @@ -255,11 +348,24 @@ clean_simulations: rerun_simulations clean_hospitalization: rerun_hospitalization \trm -rf hospitalization ") +} if(generating_report) { - cat(paste0(" +cat(paste0(" clean_reports: -\trm -f ",report_html_target_name)) +\trm -f ",report_html_target_name(report_name))) +} +if(building_US_setup) +{ +cat(paste0(" +clean_location_setup: +\trm -f ", build_location_setup_target_name(), " ", geodata_name(), " ", create_US_seeding_casedata_name() +)) +}else{ +cat(paste0(" +clean_location_setup: +\techo 'NOT REMOVING ANYTHING'" +)) } diff --git a/R/scripts/setup_initial_nonUS_data.R b/R/scripts/setup_initial_nonUS_data.R new file mode 100644 index 000000000..659a2af9e --- /dev/null +++ b/R/scripts/setup_initial_nonUS_data.R @@ -0,0 +1,281 @@ +## +# @file +# @brief Creates a filter file +# +# @details +# +# +# ## Configuration Items +# +# ```yaml +# dynfilter_path: +# start_date: +# end_date: +# +# spatial_setup: +# setup_name: +# base_path: +# geodata: +# nodenames: +# ``` +# +# ## Input Data +# +# * {spatial_setup::base_path}/{spatial_setup::geodata} is a csv with column {spatial_setup::nodenames} that denotes the geoids +# +# ## Output Data +# +# * importation/{spatial_setup::setup_name}/case_data/jhucsse_case_data.csv is a csv with case data from JHU CSSE +# * {dynfilter_path}: filter file +# + +## @cond + +# SETUP ------------------------------------------------------------------- + +library(tidyverse) +library(covidSeverity) +library(sf) +library(globaltoolboxlite) +library(foreach) + + + +#................................................................. + +# Pulling arguments from command line (comment out if using the next section) + +option_list = list( + optparse::make_option(c("-c", "--config"), action="store", default=Sys.getenv("CONFIG_PATH"), type='character', help="path to the config file"), + optparse::make_option(c("-w", "--worldpop"), action="store", default=FALSE, type='logical', help="whether to download worldpop data"), # should be set to TRUE for first run, then FALSE after that + optparse::make_option(c("-v", "--varname"), action="store", default="ADMIN2", type='character', help="variable name of geounits in shapefile. this is changed by this script to 'ADMIN2'"), + optparse::make_option(c("-j", "--jobs"), action="store", default="4", type='integer', help="Number of cores (jobs) to run in parallel") +) +opts = optparse::parse_args(optparse::OptionParser(option_list=option_list)) + +# Variables defined by the command line arguments +config <- covidcommon::load_config(opts$config) +cores <- opts$jobs +shp_loc_var <- opts$varname # Admin2 variable name in the shapefile +download_worldpop <- opts$worldpop # Set to TRUE for the first run. Otherwise false as this takes a while + + +#................................................................. + +# ## IF RUNNING FROM THE SCRIPT AND NOT COMMAND LINE, UNCOMMENT THIS SECTION, COMMENT OUT THE ABOVE SECTION, AND SET THESE PARAMETERS +# config <- covidcommon::load_config("config.yml") +# cores <- 4 +# shp_loc_var <- "ADMIN2" # Admin2 variable name in the shapefile +# download_worldpop <- TRUE # Set to TRUE for the first run. Otherwise false as this takes a while + +#................................................................. + + + +if (length(config) == 0) { + stop("no configuration found -- please set CONFIG_PATH environment variable or use the -c command flag") +} + + + + +# Pull variables from config +base_data_path <- config$spatial_setup$base_path +country_code <- config$spatial_setup$modeled_states +country_name <- globaltoolboxlite::get_country_name_ISO3(country_code) +# check that the codes is valid +if(any(is.na(country_name))){ + # In case we are using fake countries + if (exists(config$spatial_setup$modeled_states_names) & exists(config$spatial_setup$modeled_states_nums)){ + country_name <- config$spatial_setup$modeled_states_names + country_num <- stringr::str_pad(config$spatial_setup$modeled_states_nums, 3, "left", 0) + } else { + stop(paste0("Country code(s): [", paste(country_code, collapse = ", "), "] not recognized as an official ISO-3 code. Please revise in the config.")) + } +} else { + country_num <- stringr::str_pad(globaltoolboxlite::get_UNcode_from_ISO3(country_code), 3, "left", 0) +} + +census_year <- config$spatial_setup$census_year +geoid_len <- config$spatial_setup$geoid_len +shp <- file.path(base_data_path, config$spatial_setup$shapefile) + +# OD matrix of mobility with row +mobility_od_matrix <- file.path(base_data_path, "geodata/mobility_data_counts.csv") + + + + +# SEVERITY ---------------------------------------------------------- + +#devtools::install_github(repo='HopkinsIDD/covidSeverity') + +# Download the geotiffs +if (download_worldpop){ + filenames <- NULL + for (c in seq_len(length(country_code))){ + filenames_ <- globaltoolboxlite::download_worldpop_agetifs(country=country_code[c], + year=census_year, + save_dir=file.path(base_data_path, "worldpop"), + cores=cores) + filenames_ <- c(filenames, filenames_) + } +} else { + # if not downloading, check that these files exist + all_wp_files_downloaded <- NULL + for (c in seq_len(length(country_code))){ + all_wp_files_downloaded_ <- length(list.files(file.path(base_data_path, "worldpop", country_code[c]))) == 36 # should be 36 files for every country + all_wp_files_downloaded <- c(all_wp_files_downloaded, all_wp_files_downloaded_) + } + if (!all(all_wp_files_downloaded)){ + stop(cat(paste( + paste0("ERROR: Worldpop geotiffs were not completely downloaded for: ", paste(country_code[!all_wp_files_downloaded], collapse = ", "), "."), + "Please set command line argument of '-w TRUE' and rerun to download all files", sep="\n"))) + } +} + + +# Combine data and consolidate to districts + +age_pop_data <- NULL +age_pop_10yr <- NULL + + +for (c in seq_len(length(country_code))){ + + age_pop_data_ <- globaltoolboxlite::load_worldpop_age(shp=shp, + country=country_code[c], + year=census_year, + loc_var=shp_loc_var, + save_dir=file.path(base_data_path,"worldpop"), + add_pop_to_shapefile = TRUE, + cores=cores) + + # Setup geoids + age_pop_data_ <- age_pop_data_ %>% + tibble::as_tibble() %>% + dplyr::rename(setNames(shp_loc_var, "adm2")) %>% # Rename + dplyr::arrange(as.numeric(age_l), adm2) %>% + dplyr::mutate(geoid = as.character(paste0(country_num, stringr::str_pad(as.integer(as.factor(adm2)), geoid_len-3, "left", 0))), + adm0 = country_code[c]) + + # Convert to 10-year age groups + age_pop_10yr_ <- globaltoolboxlite::convert_wp_10yr(age_pop_data_) %>% + mutate(adm0 = country_code[c]) %>% + left_join(age_pop_data_ %>% dplyr::select(adm2, geoid, adm0) %>% + dplyr::distinct(), + by=c("adm2", "adm0")) + + # Get proportions + age_pop_10yr_ <- age_pop_10yr_ %>% + dplyr::group_by(adm2, adm0, geoid) %>% + dplyr::mutate(prop = pop / sum(pop)) %>% + dplyr::ungroup() + + ## Save individual countries (not sure if needed right now) + # dir.create(file.path(base_data_path, country_code[c]), recursive = TRUE) + # readr::write_csv(age_pop_10yr_, file.path(base_data_path, country_code[c], paste0(country_code[c], "_age_pop_10yr.csv"))) + # readr::write_csv(age_pop_data_, file.path(base_data_path, country_code[c], paste0(country_code[c], "_age_pop_data.csv"))) + + age_pop_data <- dplyr::bind_rows(age_pop_data, age_pop_data_) + age_pop_10yr <- dplyr::bind_rows(age_pop_10yr, age_pop_10yr_) + +} + +readr::write_csv(age_pop_10yr, file.path(base_data_path, paste0("age_pop_10yr.csv"))) +readr::write_csv(age_pop_data, file.path(base_data_path, paste0("age_pop_data.csv"))) + + +# Estimate parameters - All included countries done at once +geo_age_params <- covidSeverity::get_ageadjustments(age_pop_10yr, + cores=cores, + n_sims=40, + n_preds=1000, + age_grps=c(seq(0,80,by=10),100), + googlesheet_access=FALSE, + output_dir=base_data_path, + pop_name=NULL) + + + + +# POPULATION_DATA.CSV ----------------------------------------------------- +# Use WorldPop data to get total population by geounit -- this is used by the mobility component + +age_pop_data <- readr::read_csv(file.path(base_data_path, paste0("age_pop_data.csv"))) + +population_data <- age_pop_data %>% + dplyr::group_by(geoid, adm2, adm0) %>% + dplyr::summarise(POP = round(sum(pop))) %>% + dplyr::select(ADMIN0=adm0, ADMIN2=adm2, GEOID=geoid, POP) + +dir.create(file.path(base_data_path, "geodata"), recursive = TRUE, showWarnings = FALSE) +readr::write_csv(population_data, file.path(base_data_path, "geodata/population_data.csv")) + + + + + +# SHAPEFILE --------------------------------------------------------------- +# This section verifies that the shapefile has a variable `GEOID` +# that matches with the other data + +# Read +adm2 <- sf::read_sf(shp) %>% dplyr::rename(setNames(shp_loc_var, "ADMIN2")) +population_data <- readr::read_csv(file.path(base_data_path, "geodata/population_data.csv")) + +# Add population +if ("pop" %in% colnames(adm2)){ + adm2 <- adm2 %>% dplyr::select(-pop) +} +adm2 <- adm2 %>% + dplyr::left_join(population_data %>% dplyr::select(POP, GEOID, ADMIN0, ADMIN2), + by=c("ADMIN2")) +adm2 <- adm2 %>% dplyr::rename(pop=POP, geoid=GEOID) + + +# Save it back in the same name +sf::st_write(adm2, shp, delete_layer=TRUE) + + + +# mobility_data.csv ------------------------------------------------------------ + +mobility <- readr::read_csv(mobility_od_matrix) %>% as.data.frame() +rownames_ <- as.character(mobility[,1]) +mobility <- as.matrix(mobility[,-1]) +row.names(mobility) <- rownames_ + +# Get names and geoids from the shapefile +geoid_info <- adm2 %>% + dplyr::select(geoid, ADMIN0, ADMIN2) %>% + sf::st_set_geometry(NULL) %>% + dplyr::arrange(geoid, ADMIN0) + +# first check that the names match those of the population data +if(all.equal(sort(colnames(mobility)), sort(geoid_info$ADMIN2))==TRUE){ + mobility <- mobility %>% + tibble::as_tibble(rownames = NA) %>% + tibble::rownames_to_column(var="origin") %>% + tidyr::pivot_longer(cols = -origin, names_to = "destination", values_to = "FLOW") + + mobility <- mobility %>% + dplyr::full_join(population_data %>% dplyr::select(ADMIN2, POP, GEOID), by = c("origin"="ADMIN2")) %>% + rename(pop_orig = POP, + OGEOID = GEOID) %>% + dplyr::full_join(population_data %>% dplyr::select(ADMIN2, POP, GEOID), by = c("destination"="ADMIN2")) %>% + rename(pop_dest = POP, + DGEOID = GEOID) + + readr::write_csv(mobility, file.path(base_data_path, "geodata/mobility_data.csv")) + + print(paste0("SUCCESS: Mobility data saved to ", file.path(base_data_path, "geodata/mobility_data.csv"))) + +} else { + + print(paste0("ERROR: Location names not equal between ", mobility_od_matrix, " and population_data.csv. Please check and re-run MOBILITY setup.")) + +} + + + diff --git a/README.md b/README.md index 251a4393b..82a4ea538 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,9 @@ Welcome to the Johns Hopkins University Infectious Disease Dynamics COVID-19 Wor We recommend that most new users use the code from the stable `master` branch. Please post questions to GitHub issues with the `question` tag. We are prioritizing direct support for individuals engaged in public health planning and emergency response. -For more information on getting started, please visit our [Getting Started wiki](https://github.com/HopkinsIDD/COVID19_Minimal/wiki/Getting-Started) at [HopkinsIDD/COVID19_Minimal](https://github.com/HopkinsIDD/COVID19_Minimal). We are trying to keep this page up-to-date for use with the `master` branch. +For more information on getting started, please visit our [wiki](https://github.com/HopkinsIDD/COVID19_Minimal/wiki) at [HopkinsIDD/COVID19_Minimal](https://github.com/HopkinsIDD/COVID19_Minimal). We are trying to keep this page up-to-date for use with the `master` branch. + +For more details on the methods and features of our model, visit our [preprint on medRxiv](https://www.medrxiv.org/content/10.1101/2020.06.11.20127894v1). This open-source project is licensed under GPL v3.0. @@ -30,7 +32,7 @@ To start the container: docker run -v ~/mysrcdir:/home/app/src -it hopkinsidd/covidscenariopipeline:latest ``` -Replace `mysrcdir` with where the code is mounted on your machine; it will +replacing `mysrcdir` with the path where the code is mounted on your machine. This code will then be available in the `/home/app/src` directory inside the container. You'll be dropped to the bash prompt where you can run the Python or diff --git a/SEIR/NPI/Reduce.py b/SEIR/NPI/Reduce.py new file mode 100644 index 000000000..d0ba9c951 --- /dev/null +++ b/SEIR/NPI/Reduce.py @@ -0,0 +1,106 @@ +import pandas as pd +import pyarrow as pa +import numpy as np + +from .base import NPIBase + +REDUCE_PARAMS = ["alpha", "r0", "gamma", "sigma"] + +class Reduce(NPIBase): + def __init__(self, *, npi_config, global_config, geoids): + self.start_date = global_config["start_date"].as_date() + self.end_date = global_config["end_date"].as_date() + + self.geoids = geoids + + # Optional config fields "period_start_date" and "period_end_date" + # If unspecified, runs from global start_date to end_date + self.period_start_date = npi_config["period_start_date"].as_date() \ + if npi_config["period_start_date"].exists() else self.start_date + self.period_end_date = npi_config["period_end_date"].as_date() \ + if npi_config["period_end_date"].exists() else self.end_date + + if not (self.start_date <= self.period_start_date <= self.end_date): + raise ValueError(f"period_start_date ({self.period_start_date}) is not between global dates [{self.start_date}, {self.end_date}]") + if not (self.start_date <= self.period_end_date <= self.end_date): + raise ValueError(f"period_end_date ({self.period_end_date}) is not between global dates [{self.start_date}, {self.end_date}]") + if self.period_end_date < self.start_date: + raise ValueError(f"period_end_date ({self.period_end_date}) is less than period_start_date ({self.period_start_date})") + + # Optional config field "affected_geoids" + # If values of "affected_geoids" is "all" or unspecified, run on all geoids. + # Otherwise, run only on geoids specified. + affected = geoids + if "affected_geoids" in npi_config and npi_config["affected_geoids"].get() != "all": + affected = [] + for n in npi_config["affected_geoids"]: + node = str(n.get()) # because confuse may read as an int + if node not in geoids: + raise ValueError(f"Invalid config value {n.name} ({node}) not in geoids") + affected.append(node) + + # Get name of the parameter to reduce + param_name = npi_config["parameter"].as_str().lower() + if param_name not in REDUCE_PARAMS: + raise ValueError(f"Invalid parameter name: {param_name}. Must be one of {REDUCE_PARAMS}") + self.reduced_param = param_name + + # Create reduction + self.npi = pd.DataFrame(0.0, index=self.geoids, + columns=pd.date_range(self.start_date, self.end_date)) + self.dist = npi_config["value"].as_random_distribution() + period_range = pd.date_range(self.period_start_date, self.period_end_date) + npi_draw = np.tile(self.dist(size=len(affected)), (len(period_range), 1)).T + self.npi.loc[affected, period_range] = npi_draw + + if "fatigue_rate" in npi_config: + self.fatig_rate = npi_config["fatigue_rate"].as_random_distribution() + if "fatigue_min" in npi_config: + self.fatig_min = npi_config["fatigue_min"].as_evaled_expression() + else: + self.fatig_min = 0 + + self.fatig_freq = npi_config["fatigue_frequency_days"].as_evaled_expression() + if ("fatigue_type" in npi_config) and (npi_config["fatigue_type"].as_str() == 'geometric'): + self.fatig_rate = 1 - self.fatig_rate(size=len(affected)) + self.npi.loc[affected, period_range] =( npi_draw * \ + np.tile(self.fatig_rate, (len(period_range), 1)).T ** \ + (np.arange(0,len(period_range))/self.fatig_freq) \ + ).clip(self.fatig_min) + + else: + self.fatig_rate = self.fatig_rate(size=len(affected)) + self.npi.loc[affected, period_range] =(npi_draw - \ + np.tile(self.dist(size=len(affected)), (len(period_range), 1)).T * \ + np.tile(self.fatig_rate, (len(period_range), 1)).T * \ + (np.arange(0,len(period_range))/self.fatig_freq)).clip(self.fatig_min) + + if "fatigue_min_relative" in npi_config: + fatig_relmin = npi_config["fatigue_min_relative"].as_evaled_expression() + self.npi.loc[affected, period_range] = self.npi.loc[affected, period_range].clip(npi_draw*fatig_relmin) + + # Validate + if (self.npi == 0).all(axis=None): + print(f"Warning: The intervention in config: {npi_config.name} does nothing.") + + if (self.npi > 1).all(axis=None): + raise ValueError(f"The intervention in config: {npi_config.name} has reduction of {param_name} is greater than 1") + + def getReduction(self, param): + if param == self.reduced_param: + return self.npi + return pd.DataFrame(0.0, index=self.geoids, + columns=pd.date_range(self.start_date, self.end_date)) + + def writeReductions(self, fname, extension): + out_df = self.npi.T.assign(parameter=self.reduced_param) + + if extension == "csv": + out_df.to_csv(f"{fname}.{extension}", index_label="time") + elif extension == "parquet": + out_df["parameter"] = out_df.index + out_df = pa.Table.from_pandas(out_df, preserve_index = False) + pa.parquet.write_table(out_df,f"{fname}.{extension}") + else: + raise NotImplementedError(f"Invalid extension {extension}. Must be 'csv' or 'parquet'") + diff --git a/SEIR/NPI/ReduceR0.py b/SEIR/NPI/ReduceR0.py index 29b978564..79fc0e270 100644 --- a/SEIR/NPI/ReduceR0.py +++ b/SEIR/NPI/ReduceR0.py @@ -1,14 +1,21 @@ import pandas as pd import numpy as np +import pyarrow as pa from .base import NPIBase +# ReduceR0 is redundant with the newer Reduce NPI configured with parameter: 'r0' +# Kept for backwards compatibility class ReduceR0(NPIBase): def __init__(self, *, npi_config, global_config, geoids): self.start_date = global_config["start_date"].as_date() self.end_date = global_config["end_date"].as_date() + self.geoids = geoids + + # Optional config fields "period_start_date" and "period_end_date" + # If unspecified, runs from global start_date to end_date self.period_start_date = npi_config["period_start_date"].as_date() \ if npi_config["period_start_date"].exists() else self.start_date self.period_end_date = npi_config["period_end_date"].as_date() \ @@ -23,7 +30,7 @@ def __init__(self, *, npi_config, global_config, geoids): self.dist = npi_config["value"].as_random_distribution() - # Optional "affected_geoids" config field. + # Optional config field "affected_geoids" # If values of "affected_geoids" is "all" or unspecified, run on all geoids. # Otherwise, run only on geoids specified. affected = geoids @@ -38,10 +45,55 @@ def __init__(self, *, npi_config, global_config, geoids): self.npi = pd.DataFrame(0.0, index=geoids, columns=pd.date_range(self.start_date, self.end_date)) period_range = pd.date_range(self.period_start_date, self.period_end_date) - self.npi.loc[affected, period_range] = np.tile(self.dist(size=len(affected)), (len(period_range), 1)).T + npi_draw = np.tile(self.dist(size=len(affected)), (len(period_range), 1)).T + self.npi.loc[affected, period_range] = npi_draw + + if "fatigue_rate" in npi_config: + self.fatig_rate = npi_config["fatigue_rate"].as_random_distribution() + if "fatigue_min" in npi_config: + self.fatig_min = npi_config["fatigue_min"].as_evaled_expression() + else: + self.fatig_min = 0 + + self.fatig_freq = npi_config["fatigue_frequency_days"].as_evaled_expression() + if ("fatigue_type" in npi_config) and (npi_config["fatigue_type"].as_str() == 'geometric'): + self.fatig_rate = 1 - self.fatig_rate(size=len(affected)) + self.npi.loc[affected, period_range] =( npi_draw * \ + np.tile(self.fatig_rate, (len(period_range), 1)).T ** \ + (np.arange(0,len(period_range))/self.fatig_freq) \ + ).clip(self.fatig_min) - if self.npi.to_numpy(copy=True).nonzero()[0].size == 0: + else: + self.fatig_rate = self.fatig_rate(size=len(affected)) + self.npi.loc[affected, period_range] =(npi_draw - \ + np.tile(self.dist(size=len(affected)), (len(period_range), 1)).T * \ + np.tile(self.fatig_rate, (len(period_range), 1)).T * \ + (np.arange(0,len(period_range))/self.fatig_freq)).clip(self.fatig_min) + + if "fatigue_min_relative" in npi_config: + fatig_relmin = npi_config["fatigue_min_relative"].as_evaled_expression() + self.npi.loc[affected, period_range] = self.npi.loc[affected, period_range].clip(npi_draw*fatig_relmin) + + if (self.npi == 0).all(axis=None): print(f"Warning: The intervention in config: {npi_config.name} does nothing.") - def get(self): - return self.npi + print("Warning: The ReduceR0 is redundant with the newer Reduce NPI template configured with parameter: r0") + + def getReduction(self, param): + if param == 'r0': + return self.npi + return pd.DataFrame(0.0, index=self.geoids, + columns=pd.date_range(self.start_date, self.end_date)) + + def writeReductions(self, fname, extension): + out_df = self.npi.T.assign(parameter="r0") + + if extension == "csv": + out_df.to_csv(f"{fname}.{extension}", index_label="time") + elif extension == "parquet": + out_df["parameter"] = out_df.index + out_df = pa.Table.from_pandas(out_df, preserve_index = False) + pa.parquet.write_table(out_df,f"{fname}.{extension}") + else: + raise NotImplementedError(f"Invalid extension {extension}. Must be 'csv' or 'parquet'") + diff --git a/SEIR/NPI/Stacked.py b/SEIR/NPI/Stacked.py index a1aff0654..a21744abf 100644 --- a/SEIR/NPI/Stacked.py +++ b/SEIR/NPI/Stacked.py @@ -1,11 +1,21 @@ import functools +import pandas as pd +import pyarrow as pa from .base import NPIBase +REDUCE_PARAMS = ["alpha", "r0", "gamma", "sigma"] class Stacked(NPIBase): def __init__(self, *, npi_config, global_config, geoids): - npis = [] + self.start_date = global_config["start_date"].as_date() + self.end_date = global_config["end_date"].as_date() + + # Gather parameter reductions + reduction_lists = {} + for param in REDUCE_PARAMS: + reduction_lists[param] = [] + for scenario in npi_config["scenarios"]: # if it's a string, look up the scenario name's config if isinstance(scenario.get(), str): @@ -16,10 +26,32 @@ def __init__(self, *, npi_config, global_config, geoids): # otherwise use the specified map as the config scenario_npi_config = scenario - npi = NPIBase.execute(npi_config=scenario_npi_config, global_config=global_config, geoids=geoids) - npis.append(npi.get()) + sub_npi = NPIBase.execute(npi_config=scenario_npi_config, global_config=global_config, geoids=geoids) + + for p in REDUCE_PARAMS: + reduction_lists[p].append(sub_npi.getReduction(p)) + + # Calculate reductions + self.reductions = {} + for param, reduction_list in reduction_lists.items(): + self.reductions[param] = 1 - functools.reduce(lambda a,b : a * (1-b) , reduction_list, 1) + + def getReduction(self, param): + return self.reductions[param] + + def writeReductions(self, fname, extension): + p_dfs = [] + for p_name, p_df in self.reductions.items(): + if (p_df == 0.0).all(axis=None): + continue + p_dfs.append(p_df.T.assign(parameter=p_name)) + out_df = pd.concat(p_dfs) - #self.npi = 1 - functools.reduce(lambda a, b: a * (1 - b), npis) - self.npi = 1 - functools.reduce(lambda a,b : a * (1-b) , npis, 1) - def get(self): - return self.npi + if extension == "csv": + out_df.to_csv(f"{fname}.{extension}", index_label="time") + elif extension == "parquet": + out_df["parameter"] = out_df.index + out_df = pa.Table.from_pandas(out_df, preserve_index = False) + pa.parquet.write_table(out_df,f"{fname}.{extension}") + else: + raise NotImplementedError(f"Invalid extension {extension}. Must be 'csv' or 'parquet'") diff --git a/SEIR/NPI/base.py b/SEIR/NPI/base.py index fa68cbfc2..71cffc597 100644 --- a/SEIR/NPI/base.py +++ b/SEIR/NPI/base.py @@ -9,7 +9,11 @@ def __init_subclass__(cls, **kwargs): NPIBase.__plugins__[cls.__name__] = cls @abc.abstractmethod - def get(self): + def getReduction(self, param): + pass + + @abc.abstractmethod + def writeReductions(self, fname, extension): pass def execute(*, npi_config, global_config, geoids): diff --git a/SEIR/__main__.py b/SEIR/__main__.py new file mode 100644 index 000000000..883ce106a --- /dev/null +++ b/SEIR/__main__.py @@ -0,0 +1,4 @@ +from . import simulate + +if __name__ == "__main__": + simulate.simulate() diff --git a/SEIR/seir.py b/SEIR/seir.py index 816e74e2b..75414e27a 100644 --- a/SEIR/seir.py +++ b/SEIR/seir.py @@ -1,12 +1,10 @@ import itertools import time -import uuid +import warnings -from numba import jit import numpy as np import pandas as pd import scipy -import os import tqdm.contrib.concurrent from . import NPI, setup @@ -14,6 +12,15 @@ import pyarrow.parquet as pq import pyarrow as pa +try: + # ignore DeprecationWarning inside numba + with warnings.catch_warnings() as w: + warnings.simplefilter("ignore") + + from steps import steps_SEIR_nb +except ModuleNotFoundError as e: + raise RuntimeError("Missing compiled module, please run `python setup.py install`") from e + ncomp = 7 S, E, I1, I2, I3, R, cumI = np.arange(ncomp) @@ -21,19 +28,17 @@ def onerun_SEIR(sim_id, s): scipy.random.seed() - sim_id_str = str(sim_id).zfill(9) - npi = NPI.NPIBase.execute(npi_config=s.npi_config, global_config=config, geoids=s.spatset.nodenames) - npi = npi.get().T seeding = setup.seeding_draw(s, sim_id) mobility_geoid_indices = s.mobility.indices mobility_data_indices = s.mobility.indptr mobility_data = s.mobility.data - parameters = setup.parameters_quick_draw(config["seir"]["parameters"], len(s.t_inter), s.nnodes, s.dt, npi) + p_draw = setup.parameters_quick_draw(config["seir"]["parameters"], len(s.t_inter), s.nnodes) + parameters = setup.parameters_reduce(p_draw, npi, s.dt) - states = steps_SEIR_nb(parameters, + states = steps_SEIR_nb(*parameters, seeding, s.dt, s.t_inter, s.nnodes, s.popnodes, mobility_geoid_indices, mobility_data_indices, mobility_data, s.dynfilter) @@ -64,19 +69,18 @@ def onerun_SEIR(sim_id, s): out_df['comp'].replace(R, 'R', inplace=True) out_df['comp'].replace(cumI, 'cumI', inplace=True) out_df['comp'].replace(ncomp, 'diffI', inplace=True) + sim_id_str = str(sim_id + s.first_sim_index - 1).zfill(9) if s.write_csv: - npi.to_csv(f"{s.paramdir}{sim_id}.snpi.csv", index_label="time") - setup.parameters_write(parameters, f"{s.paramdir}{sim_id_str}.spar","csv") + npi.writeReductions(f"{s.paramdir}{sim_id_str}.snpi","csv") + setup.parameters_write(parameters, f"{s.paramdir}{sim_id_str}.spar", "csv") + out_df.to_csv( f"{s.datadir}{sim_id}.seir.csv", index='time', index_label='time') if s.write_parquet: - npi['time'] = npi.index - pa_npi = pa.Table.from_pandas(npi,preserve_index = False) - pa.parquet.write_table(pa_npi,f"{s.paramdir}{sim_id_str}.snpi.parquet") - - setup.parameters_write(parameters, f"{s.paramdir}{sim_id_str}.spar","parquet") + npi.writeReductions(f"{s.paramdir}{sim_id_str}.snpi", "parquet") + setup.parameters_write(p_draw, f"{s.paramdir}{sim_id_str}.spar", "parquet") out_df['time'] = out_df.index pa_df = pa.Table.from_pandas(out_df, preserve_index = False) @@ -99,71 +103,3 @@ def run_parallel(s, *, n_jobs=1): >> {s.nsim} simulations completed in {time.monotonic()-start:.1f} seconds """) - -@jit(nopython=True) -def steps_SEIR_nb(p_vec, seeding, dt, t_inter, nnodes, popnodes, - mobility_row_indices, mobility_data_indices, mobility_data, dynfilter): - """ - Made to run just-in-time-compiled by numba, hence very descriptive and using loop, - because loops are expanded by the compiler hence not a problem. - as there is very few authorized function. Needs the nopython option to be fast. - """ - alpha, beta, sigma, gamma = p_vec - t = 0 - - y = np.zeros((ncomp, nnodes)) - y[S, :] = popnodes - states = np.zeros((ncomp, nnodes, len(t_inter))) - - exposeCases = np.empty(nnodes) - incidentCases = np.empty(nnodes) - incident2Cases = np.empty(nnodes) - incident3Cases = np.empty(nnodes) - recoveredCases = np.empty(nnodes) - - p_infect = 1 - np.exp(-dt * sigma) - p_recover = 1 - np.exp(-dt * gamma) - - percent_who_move = np.zeros(nnodes) - percent_day_away = 0.5 - for j in range(nnodes): - percent_who_move[j] = mobility_data[mobility_data_indices[j]:mobility_data_indices[j+1] ].sum() / popnodes[j] - - for it, t in enumerate(t_inter): - if (it % int(1 / dt) == 0): - y[E] = y[E] + seeding[int(t)] - y[S] = y[S] - seeding[int(t)] - y[S] = y[S] * (y[S] > 0) - - for i in range(nnodes): - p_expose = 1.0 - np.exp(-dt * ( - ((1 - percent_day_away * percent_who_move[i] ) * beta[it][i] * (y[I1][i] + y[I2][i] + y[I3][i])**alpha / popnodes[i] ) + # Staying at home FoI - ( - percent_day_away * mobility_data[mobility_data_indices[i]:mobility_data_indices[i+1] ] / popnodes[i] * # Probability of going there - beta[it][mobility_row_indices[mobility_data_indices[i]:mobility_data_indices[i+1] ] ] * # The beta for there - ( # num infected tehre - y[I1][mobility_row_indices[mobility_data_indices[i]:mobility_data_indices[i+1] ] ] + - y[I2][mobility_row_indices[mobility_data_indices[i]:mobility_data_indices[i+1] ] ] + - y[I3][mobility_row_indices[mobility_data_indices[i]:mobility_data_indices[i+1] ] ] - )**alpha / popnodes[mobility_row_indices[mobility_data_indices[i]:mobility_data_indices[i+1] ] ] # population there - ).sum() - )) - - exposeCases[i] = np.random.binomial(y[S][i], p_expose) - incidentCases[i] = np.random.binomial(y[E][i], p_infect) - incident2Cases[i] = np.random.binomial(y[I1][i], p_recover) - incident3Cases[i] = np.random.binomial(y[I2][i], p_recover) - recoveredCases[i] = np.random.binomial(y[I3][i], p_recover) - - y[S] += -exposeCases - y[E] += exposeCases - incidentCases - y[I1] += incidentCases - incident2Cases - y[I2] += incident2Cases - incident3Cases - y[I3] += incident3Cases - recoveredCases - y[R] += recoveredCases - y[cumI] += incidentCases - states[:, :, it] = y - if (it%(1/dt) == 0 and (y[cumI] < dynfilter[int(it%(1/dt))]).any()): - return -np.ones((ncomp, nnodes, len(t_inter))) - - return states diff --git a/SEIR/setup.py b/SEIR/setup.py index cdee4cc4a..ca2ee8f00 100644 --- a/SEIR/setup.py +++ b/SEIR/setup.py @@ -26,6 +26,8 @@ def __init__(self, *, setup_name, geodata_file, mobility_file, popnodes_key, nod if popnodes_key not in self.data: raise ValueError(f"popnodes_key: {popnodes_key} does not correspond to a column in geodata."); self.popnodes = self.data[popnodes_key].to_numpy() # population + if len(np.argwhere(self.popnodes == 0)): + raise ValueError(f"There are {len(np.argwhere(self.popnodes == 0))} nodes with population zero, this is not supported.") # nodenames_key is the name of the column in geodata_file with geoids if nodenames_key not in self.data: @@ -53,9 +55,6 @@ def __init__(self, *, setup_name, geodata_file, mobility_file, popnodes_key, nod else: raise ValueError(f"Mobility data must either be a .csv file in longform (recommended) or a .txt matrix file. Got {mobility_file}") - # if (self.mobility - self.mobility.T).nnz != 0: - # raise ValueError(f"mobility data is not symmetric.") - # Make sure mobility values <= the population of src node tmp = (self.mobility.T - self.popnodes).T tmp[tmp < 0] = 0 @@ -65,9 +64,18 @@ def __init__(self, *, setup_name, geodata_file, mobility_file, popnodes_key, nod for r,c,v in zip(rows, cols, values): errmsg += f"\n({r}, {c}) = {self.mobility[r,c]} > population of '{self.nodenames[r]}' = {self.popnodes[r]}" raise ValueError(f"The following entries in the mobility data exceed the source node populations in geodata:{errmsg}") + + tmp = self.popnodes - np.squeeze(np.asarray(self.mobility.sum(axis=1))) + tmp[tmp > 0] = 0 + if tmp.any(): + row, = np.where(tmp) + errmsg = "" + for r in row: + errmsg += f"\n sum accross row {r} exceed population of node '{self.nodenames[r]}' ({self.popnodes[r]}), by {-tmp[r]}" + raise ValueError(f'The following rows in the mobility data exceed the source node populations in geodata:{errmsg}') -class Setup(): +class Setup: """ This class hold a setup model setup. """ @@ -84,7 +92,8 @@ def __init__(self, *, write_csv=False, write_parquet=False, dt=1 / 6, # step size, in days - nbetas=None): # # of betas, which are rates of infection + nbetas=None, + first_sim_index = 1): # # of betas, which are rates of infection self.setup_name = setup_name self.nsim = nsim self.dt = dt @@ -98,6 +107,7 @@ def __init__(self, *, self.interactive = interactive self.write_csv = write_csv self.write_parquet = write_parquet + self.first_sim_index = first_sim_index if nbetas is None: nbetas = nsim @@ -133,6 +143,22 @@ def load_filter(self, dynfilter_path): def seeding_draw(s, sim_id): importation = np.zeros((s.t_span+1, s.nnodes)) method = s.seeding_config["method"].as_str() + if (method == 'NegativeBinomialDistributed'): + seeding = pd.read_csv(s.seeding_config["lambda_file"].as_str(), + converters={'place': lambda x: str(x)}, + parse_dates=['date']) + + dupes = seeding[seeding.duplicated(['place', 'date'])].index + 1 + if not dupes.empty: + raise ValueError(f"Repeated place-date in rows {dupes.tolist()} of seeding::lambda_file.") + + for _, row in seeding.iterrows(): + if row['place'] not in s.spatset.nodenames: + raise ValueError(f"Invalid place '{row['place']}' in row {_ + 1} of seeding::lambda_file. Not found in geodata.") + + importation[(row['date'].date()-s.ti).days][s.spatset.nodenames.index(row['place'])] = \ + np.random.negative_binomial(n= 5, p = 5/(row['amount'] + 5)) + if (method == 'PoissonDistributed'): seeding = pd.read_csv(s.seeding_config["lambda_file"].as_str(), converters={'place': lambda x: str(x)}, @@ -160,38 +186,69 @@ def seeding_draw(s, sim_id): raise NotImplementedError(f"unknown seeding method [got: {method}]") return importation -# Returns alpha, beta, sigma, and gamma parameters in a tuple -# alpha, sigma and gamma are scalars -# alpha is percentage of day spent commuting -# beta is an array of shape (nt_inter, nnodes) -def parameters_quick_draw(p_config, nt_inter, nnodes, dt, npi): - if nnodes <= 0 or nt_inter <= 0: - raise ValueError("Invalid nt_inter or nnodes") - +# Returns alpha, beta, sigma, and gamma parameters in a tuple. +# All parameters are arrays of shape (nt_inter, nnodes). +# They are returned as a tuple because it is numba-friendly for steps_SEIR_nb(). +# +# These are drawn based on the seir::parameters section of the config, passed in as p_config. +# In the config, alpha is optional with a default of 1.0. +# The other parameters sigma, gamma, and R0s are required. +def parameters_quick_draw(p_config, nt_inter, nnodes): alpha = 1.0 if "alpha" in p_config: alpha = p_config["alpha"].as_evaled_expression() + alpha = np.full((nt_inter, nnodes), alpha) sigma = p_config["sigma"].as_evaled_expression() + sigma = np.full((nt_inter, nnodes), sigma) + gamma = p_config["gamma"].as_random_distribution()() * n_Icomp - R0s = p_config["R0s"].as_random_distribution()() + gamma = np.full((nt_inter, nnodes), gamma) + R0s = p_config["R0s"].as_random_distribution()() beta = R0s * gamma / n_Icomp + beta = np.full((nt_inter, nnodes), beta) + + return (alpha, beta, sigma, gamma) + +# Returns alpha, beta, sigma, and gamma parameters in a tuple. +# All parameters are arrays of shape (nt_inter, nnodes). +# They are returned as a tuple because it is numba-friendly for steps_SEIR_nb(). +# +# They are reduced according to the NPI provided. +def parameters_reduce(p_draw, npi, dt): + alpha, beta, sigma, gamma = p_draw # tuple of dataframes - beta = np.full((nnodes, nt_inter), beta) + alpha = _parameter_reduce(alpha, npi.getReduction("alpha"), dt) + beta = _parameter_reduce(beta, npi.getReduction("r0"), dt) + sigma = _parameter_reduce(sigma, npi.getReduction("sigma"), dt) + gamma = _parameter_reduce(gamma, npi.getReduction("gamma"), dt) - npi.index = pd.to_datetime(npi.index.astype(str)) - npi = npi.resample(str(dt * 24) + 'H').ffill() - beta = np.multiply(beta, np.ones_like(beta) - npi.to_numpy().T) + return (alpha, beta, sigma, gamma) - return (alpha, beta.T, sigma, gamma) +# Helper function +def _parameter_reduce(parameter, reduction, dt): + reduction = reduction.T + reduction.index = pd.to_datetime(reduction.index.astype(str)) + reduction = reduction.resample(str(dt * 24) + 'H').ffill().to_numpy() + return parameter * (1 - reduction) +# Write parameters generated by parameters_quick_draw() to file def parameters_write(parameters, fname, extension): - out_df = pd.DataFrame([parameters[0], parameters[1][0][0]*n_Icomp / parameters[3], parameters[2], parameters[3]], index = ["alpha","R0","sigma","gamma"], columns = ["value"]) + alpha, beta, sigma, gamma = parameters + out_df = pd.DataFrame([alpha[0][0], + beta[0][0] * n_Icomp / gamma[0][0], + sigma[0][0], + gamma[0][0]], \ + index = ["alpha","R0","sigma","gamma"], columns = ["value"]) + if extension == "csv": - out_dict.to_csv(f"{fname}.{extension}", index_label="parameter") - if extension == "parquet": + out_df.to_csv(f"{fname}.{extension}", index_label="parameter") + elif extension == "parquet": out_df["parameter"] = out_df.index pa_df = pa.Table.from_pandas(out_df, preserve_index = False) pa.parquet.write_table(pa_df,f"{fname}.{extension}") + else: + raise NotImplementedError(f"Invalid extension {extension}. Must be 'csv' or 'parquet'") + diff --git a/simulate.py b/SEIR/simulate.py similarity index 80% rename from simulate.py rename to SEIR/simulate.py index 5d519c5dd..f6cf8b1a5 100755 --- a/simulate.py +++ b/SEIR/simulate.py @@ -37,10 +37,10 @@ # - ... # settings: # : -# template: choose one - "ReduceR0", "Stacked" +# template: choose one - "Reduce", ReduceR0", "Stacked" # ... # : -# template: choose one - "Reduce R0", "Stacked" +# template: choose one - "Reduce", "ReduceR0", "Stacked" # ... # # seeding: @@ -54,6 +54,19 @@ # interventions: # scenarios: # : +# template: Reduce +# parameter: choose one - "alpha, sigma, gamma, r0" +# period_start_date: +# period_end_date: +# value: +# affected_geoids: optional +# ``` +# +# If {template} is ReduceR0 +# ```yaml +# interventions: +# scenarios: +# : # template: ReduceR0 # period_start_date: # period_end_date: @@ -101,7 +114,7 @@ # # * model_output/{spatial_setup::setup_name}_[scenario]/[simulation ID].seir.[csv/parquet] # * model_parameters/{spatial_setup::setup_name}_[scenario]/[simulation ID].spar.[csv/parquet] -# * model_parameters/{spatial_setup::setup_name}_[scenario]/[simulation ID].npi.[csv/parquet] +# * model_parameters/{spatial_setup::setup_name}_[scenario]/[simulation ID].snpi.[csv/parquet] ## @cond @@ -124,6 +137,9 @@ help="override the scenario(s) run for this simulation [supports multiple scenarios: `-s Wuhan -s None`]") @click.option("-n", "--nsim", type=click.IntRange(min=1), help="override the # of simulation runs in the config file") +@click.option("-i", "--index", type=click.IntRange(min=1), + default=1, show_default=True, + help="The index of the first simulation") @click.option("-j", "--jobs", type=click.IntRange(min=1), default=multiprocessing.cpu_count(), show_default=True, help="the parallelization factor") @@ -134,7 +150,7 @@ @click.option("--write-parquet/--no-write-parquet", default=True, show_default=True, help="write parquet file output at end of simulation") @profile_options -def simulate(config_file, scenarios, nsim, jobs, interactive, write_csv, write_parquet): +def simulate(config_file, scenarios, nsim, jobs, interactive, write_csv, write_parquet,index): config.set_file(config_file) spatial_config = config["spatial_setup"] @@ -147,16 +163,17 @@ def simulate(config_file, scenarios, nsim, jobs, interactive, write_csv, write_p if not nsim: nsim = config["nsimulations"].as_number() + spatial_setup = setup.SpatialSetup( + setup_name=spatial_config["setup_name"].get(), + geodata_file=spatial_base_path / spatial_config["geodata"].get(), + mobility_file=spatial_base_path / spatial_config["mobility"].get(), + popnodes_key=spatial_config["popnodes"].get(), + nodenames_key=spatial_config["nodenames"].get()) + start = time.monotonic() for scenario in scenarios: s = setup.Setup(setup_name=config["name"].get() + "_" + str(scenario), - spatial_setup=setup.SpatialSetup( - setup_name=spatial_config["setup_name"].get(), - geodata_file=spatial_base_path / spatial_config["geodata"].get(), - mobility_file=spatial_base_path / spatial_config["mobility"].get(), - popnodes_key=spatial_config["popnodes"].get(), - nodenames_key=spatial_config["nodenames"].get() - ), + spatial_setup=spatial_setup, nsim=nsim, npi_scenario=scenario, npi_config=config["interventions"]["settings"][scenario], @@ -166,7 +183,8 @@ def simulate(config_file, scenarios, nsim, jobs, interactive, write_csv, write_p interactive=interactive, write_csv=write_csv, write_parquet=write_parquet, - dt=config["dt"].as_number()) + dt=config["dt"].as_number(), + first_sim_index = index) try: s.load_filter(config["dynfilter_path"].get()) print(' We are using a filter') @@ -175,7 +193,7 @@ def simulate(config_file, scenarios, nsim, jobs, interactive, write_csv, write_p print(f""" >> Scenario: {scenario} ->> Starting {s.nsim} model runs on {jobs} processes +>> Starting {s.nsim} model runs beginning from {s.first_sim_index} on {jobs} processes >> Setup *** {s.setup_name} *** from {s.ti} to {s.tf} >> writing to folder : {s.datadir}{s.setup_name} """) diff --git a/SEIR/steps_source.py b/SEIR/steps_source.py new file mode 100644 index 000000000..9f2c34b48 --- /dev/null +++ b/SEIR/steps_source.py @@ -0,0 +1,84 @@ +from numba.pycc import CC +import numpy as np + +cc = CC("steps") +cc.verbose = True + +ncomp = 7 +S, E, I1, I2, I3, R, cumI = np.arange(ncomp) + + +@cc.export( + "steps_SEIR_nb", + "float64[:,:,:](float64[:,:], float64[:,:], float64[:,:], float64[:,:], float64[:,:]," + "float64, float64[:], int64, int64[:], int32[:], int32[:], float64[:], float64[:,:])" +) +def steps_SEIR_nb(alpha, beta, sigma, gamma, seeding, dt, t_inter, nnodes, popnodes, + mobility_row_indices, mobility_data_indices, mobility_data, dynfilter): + """ + Made to run just-in-time-compiled by numba, hence very descriptive and using loop, + because loops are expanded by the compiler hence not a problem. + as there is very few authorized function. Needs the nopython option to be fast. + """ + y = np.zeros((ncomp, nnodes)) + y[S, :] = popnodes + states = np.zeros((ncomp, nnodes, len(t_inter))) + + exposeCases = np.empty(nnodes) + incidentCases = np.empty(nnodes) + incident2Cases = np.empty(nnodes) + incident3Cases = np.empty(nnodes) + recoveredCases = np.empty(nnodes) + + percent_who_move = np.zeros(nnodes) + percent_day_away = 0.5 + for j in range(nnodes): + percent_who_move[j] = mobility_data[mobility_data_indices[j]:mobility_data_indices[j+1]].sum() / popnodes[j] + + for it, t in enumerate(t_inter): + if (it % int(1 / dt) == 0): + y[E] = y[E] + seeding[int(t)] + y[S] = y[S] - seeding[int(t)] + y[S] = y[S] * (y[S] > 0) + + for i in range(nnodes): + index = np.arange(mobility_data_indices[i], mobility_data_indices[i+1]) + row_index = mobility_row_indices[index] + p_expose = 1.0 - np.exp(-dt * ( + ((1 - percent_day_away * percent_who_move[i]) * beta[it][i] * + (y[I1][i] + y[I2][i] + y[I3][i]) ** alpha[it][i] / popnodes[i]) + # Staying at home FoI + ( + percent_day_away * mobility_data[index] / popnodes[i] * # Probability of going there + beta[it][row_index] * # The beta for there + ( # num infected there + y[I1][row_index] + + y[I2][row_index] + + y[I3][row_index] + ) ** alpha[it][i] / popnodes[row_index] # population there + ).sum() + )) + + exposeCases[i] = np.random.binomial(y[S][i], p_expose) + p_infect = 1 - np.exp(-dt * sigma[it][i]) + incidentCases[i] = np.random.binomial(y[E][i], p_infect) + p_recover = 1 - np.exp(-dt * gamma[it][i]) + incident2Cases[i] = np.random.binomial(y[I1][i], p_recover) + incident3Cases[i] = np.random.binomial(y[I2][i], p_recover) + recoveredCases[i] = np.random.binomial(y[I3][i], p_recover) + + y[S] += -exposeCases + y[E] += exposeCases - incidentCases + y[I1] += incidentCases - incident2Cases + y[I2] += incident2Cases - incident3Cases + y[I3] += incident3Cases - recoveredCases + y[R] += recoveredCases + y[cumI] += incidentCases + states[:, :, it] = y + if (it % (1/dt) == 0 and (y[cumI] < dynfilter[int(it % (1/dt))]).any()): + return -np.ones((ncomp, nnodes, len(t_inter))) + + return states + + +if __name__ == "__main__": + cc.compile() diff --git a/SEIR/test/data/config.yml b/SEIR/test/data/config.yml index 5d5320063..599001810 100644 --- a/SEIR/test/data/config.yml +++ b/SEIR/test/data/config.yml @@ -13,14 +13,6 @@ spatial_setup: popnodes: population nodenames: geoid -seeding: ## If removing the importation, comment out this seeding block - method: FolderDraw - folder_path: importation/minimal/ - -# seeding: ## If removing importation, uncomment this seeding block -# method: PoissonDistributed -# lambda_file: data/minimal/seeding.csv - seir: parameters: alpha: 0.5 @@ -39,14 +31,16 @@ interventions: - None settings: None: - template: ReduceR0 + template: Reduce + parameter: r0 period_start_date: 2020-04-01 period_end_date: 2020-05-15 value: distribution: fixed value: 0 Wuhan: - template: ReduceR0 + template: Reduce + parameter: r0 period_start_date: 2020-04-01 period_end_date: 2020-05-15 value: @@ -55,6 +49,7 @@ interventions: high: .33 KansasCity: template: ReduceR0 + parameter: r0 period_start_date: 2020-04-01 period_end_date: 2020-05-15 value: diff --git a/SEIR/test/data/test_ReduceR0_trivial.yml b/SEIR/test/data/test_ReduceR0_trivial.yml index 08b9a5a00..a14901658 100644 --- a/SEIR/test/data/test_ReduceR0_trivial.yml +++ b/SEIR/test/data/test_ReduceR0_trivial.yml @@ -1,20 +1,81 @@ -trivial: +# Global Configs +trivial_global: start_date: 2020-01-01 end_date: 2020-01-01 - interventions: - settings: - Test: - template: ReduceR0 - value: - distribution: fixed - value: 1 -daterange: + +month_global: start_date: 2020-01-01 - end_date: 2020-01-31 - interventions: - settings: - Test: - template: ReduceR0 - value: - distribution: fixed - value: 1 + end_date: 2020-02-01 + + +# NPI Configs +trivial: + value: + distribution: fixed + value: 1 + parameter: gamma + value: + distribution: fixed + value: 0.5 + +bad_geoid: + parameter: gamma + value: + distribution: fixed + value: 0.5 + affected_geoids: + - does_not_exit + +geoidrange: + parameter: gamma + value: + distribution: fixed + value: 0.5 + affected_geoids: + - 10001 + - 2020 + +invalid_parameter: + parameter: NOT_A_PARAMETER + value: + distribution: fixed + value: 0.5 + +bad_start_date: + period_start_date: 2019-12-31 # period_start_date before global start date + period_end_date: 2020-01-31 + value: + distribution: fixed + value: 1 + +bad_end_date: + period_start_date: 2019-01-31 + period_end_date: 2020-02-23 # period_end_date after global end date + value: + distribution: fixed + value: 1 + +daterange: + period_start_date: 2020-01-05 + period_end_date: 2020-01-20 + parameter: gamma + value: + distribution: fixed + value: 0.5 + +fullrange: + parameter: gamma + value: + distribution: fixed + value: 0.5 + period_start_date: 2020-01-31 + period_end_date: 2020-01-20 + affected_geoids: + - 10001 + - 2020 + +toobig: + parameter: gamma + value: + distribution: fixed + value: 1.1 diff --git a/SEIR/test/test_npi.py b/SEIR/test/test_npi.py index fb27cbc5d..d8b980a75 100644 --- a/SEIR/test/test_npi.py +++ b/SEIR/test/test_npi.py @@ -5,7 +5,7 @@ import pytest import confuse -from SEIR.NPI import ReduceR0 +from SEIR.NPI import ReduceR0, Reduce from ..utils import config @@ -14,29 +14,168 @@ class TestInterventionsReduceR0: def test_ReduceR0_constructor_trivial(self): config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") - test_result = ReduceR0(global_config = config["trivial"],npi_config = config["trivial"]["interventions"]["settings"]["Test"],geoids = ["10001"]) - assert type(test_result.get()).__module__ == 'pandas.core.frame' - assert test_result.get().shape == (1,1) - assert (test_result.get().keys() == [config["trivial"]["start_date"].as_date()]).all() - assert (test_result.get().index.values == ["10001"]).all() - def test_ReduceR0_constructor_geoidrage(self): - config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") - test_result = ReduceR0(global_config = config["trivial"],npi_config = config["trivial"]["interventions"]["settings"]["Test"],geoids = ["10001","2020","40"]) - assert type(test_result.get()).__module__ == 'pandas.core.frame' - assert test_result.get().shape == (3,1) - assert (test_result.get().keys() == [config["trivial"]["start_date"].as_date()]).all() - assert (test_result.get().index.values == ["10001","2020","40"]).all() + global_config = config["trivial_global"] + test_result = ReduceR0(global_config = global_config, + npi_config = config["trivial"], + geoids = ["10001"]) + assert type(test_result.getReduction('r0')).__module__ == 'pandas.core.frame' + assert test_result.getReduction('r0').shape == (1,1) + assert (test_result.getReduction('r0').keys() == [global_config["start_date"].as_date()]).all() + assert (test_result.getReduction('r0').index.values == ["10001"]) + + def test_ReduceR0_constructor_geoidrange(self): + config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") + global_config = config["trivial_global"] + test_result = ReduceR0(global_config = global_config, + npi_config = config["geoidrange"], + geoids = ["10001","2020","40"]) + + reduction = test_result.getReduction('r0') + assert type(reduction).__module__ == 'pandas.core.frame' + assert reduction.shape == (3,1) + assert (reduction.keys() == [global_config["start_date"].as_date()]).all() + assert (reduction.index.values == ["10001","2020","40"]).all() + assert (reduction.index.values == ["10001", "2020", "40"]).all() + assert (reduction.loc[["10001", "2020"]] == 0.5).all(axis=None) + assert (reduction.loc["40"] == 0).all() + def test_ReduceR0_constructor_daterange(self): + # Test period date range config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") - test_result = ReduceR0(global_config = config["trivial"],npi_config = config["daterange"]["interventions"]["settings"]["Test"],geoids = ["10001"]) - assert type(test_result.get()).__module__ == 'pandas.core.frame' - assert test_result.get().shape == (1,1) - assert (test_result.get().keys() == pd.date_range(config["trivial"]["start_date"].as_date(), config["trivial"]["end_date"].as_date())).all() - assert (test_result.get().index.values == ["10001"]).all() + global_config = config["month_global"] + npi_config = config["daterange"] + test_result = ReduceR0(global_config = global_config, + npi_config = npi_config, + geoids = ["10001"]) + reduction = test_result.getReduction('r0') + + global_start_date = global_config["start_date"].as_date() + global_end_date = global_config["end_date"].as_date() + period_start_date = npi_config["period_start_date"].as_date() + period_end_date = npi_config["period_end_date"].as_date() + assert type(reduction).__module__ == 'pandas.core.frame' + assert reduction.shape == (1,32) + assert (reduction.keys() == pd.date_range(global_start_date, global_end_date)).all() + assert (reduction.index.values == ["10001"]) + + # Test values in date ranges + assert (reduction[pd.date_range(global_start_date, period_start_date, closed="left")] == 0).all(axis=None) + assert (reduction[pd.date_range(period_start_date, period_end_date)] == 0.5).all(axis=None) + assert (reduction[pd.date_range(period_end_date, global_end_date, closed="right")] == 0).all(axis=None) + def test_ReduceR0_constructor_fullrange(self): + # Test affected geoids and period date range + config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") + global_config = config["month_global"] + npi_config = config["fullrange"] + test_result = ReduceR0(global_config = global_config, + npi_config = npi_config, + geoids = ["10001","2020","40"]) + reduction = test_result.getReduction('r0') + + assert type(reduction).__module__ == 'pandas.core.frame' + assert reduction.shape == (3,32) + assert (reduction.keys() == pd.date_range(global_config["start_date"].as_date(), + global_config["end_date"].as_date())).all() + assert (reduction.index.values == ["10001","2020","40"]).all() + assert (reduction.loc[["10001","2020"],pd.date_range(npi_config["period_start_date"].as_date(), + npi_config["period_end_date"].as_date())] == 0.5).all(axis=None) + +class TestInterventionsReduce: + def test_Reduce_constructor_trivial(self): + config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") + global_config = config["trivial_global"] + test_result = Reduce(global_config = global_config, + npi_config = config["trivial"], + geoids = ["10001"]) + reduction = test_result.getReduction('gamma') + + assert type(reduction).__module__ == 'pandas.core.frame' + assert reduction.shape == (1,1) + assert (reduction.keys() == [global_config["start_date"].as_date()]) + assert (reduction.index.values == ["10001"]).all() + assert (reduction == 0.5).all(axis=None) + + def test_Reduce_constructor_geoidrange(self): + config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") + test_result = Reduce(global_config = config["trivial_global"], + npi_config = config["geoidrange"], + geoids = ["10001","2020","40"]) + reduction = test_result.getReduction('gamma') + + assert reduction.shape == (3,1) + assert (reduction.index.values == ["10001", "2020", "40"]).all() + assert (reduction.loc[["10001", "2020"]] == 0.5).all(axis=None) + assert (reduction.loc["40"] == 0).all() + + def test_Reduce_constructor_daterange(self): config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") - test_result = ReduceR0(global_config = config["trivial"],npi_config = config["daterange"]["interventions"]["settings"]["Test"],geoids = ["10001","2020","40"]) - assert type(test_result.get()).__module__ == 'pandas.core.frame' - assert test_result.get().shape == (3,1) - assert (test_result.get().keys() == pd.date_range(config["trivial"]["start_date"].as_date(), config["trivial"]["end_date"].as_date())).all() - assert (test_result.get().index.values == ["10001","2020","40"]).all() + global_config = config["month_global"] + npi_config = config["daterange"] + test_result = Reduce(global_config = global_config, + npi_config = npi_config, + geoids = ["10001"]) + reduction = test_result.getReduction('gamma') + + global_start_date = global_config["start_date"].as_date() + global_end_date = global_config["end_date"].as_date() + period_start_date = npi_config["period_start_date"].as_date() + period_end_date = npi_config["period_end_date"].as_date() + + assert type(reduction).__module__ == 'pandas.core.frame' + assert reduction.shape == (1,32) + assert (reduction.keys() == pd.date_range(global_start_date, global_end_date)).all() + assert (reduction.index.values == ["10001"]) + + # Test values in date ranges + assert (reduction[pd.date_range(global_start_date, period_start_date, closed="left")] == 0).all(axis=None) + assert (reduction[pd.date_range(period_start_date, period_end_date)] == 0.5).all(axis=None) + assert (reduction[pd.date_range(period_end_date, global_end_date, closed="right")] == 0).all(axis=None) + + def test_Reduce_constructor_fullrange(self): + config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") + global_config = config["month_global"] + npi_config = config["fullrange"] + test_result = Reduce(global_config = global_config, + npi_config = npi_config, + geoids = ["10001","2020","40"]) + reduction = test_result.getReduction('gamma') + + assert type(reduction).__module__ == 'pandas.core.frame' + assert reduction.shape == (3,32) + assert (reduction.keys() == pd.date_range(global_config["start_date"].as_date(), + global_config["end_date"].as_date())).all() + assert (reduction.index.values == ["10001","2020","40"]).all() + assert (reduction.loc[["10001","2020"],pd.date_range(npi_config["period_start_date"].as_date(), + npi_config["period_end_date"].as_date())] == 0.5).all(axis=None) + + def test_Reduce_constructor_toobig(self): + config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") + with pytest.raises(ValueError, match=r'.*greater than.*'): + test_result = Reduce(global_config = config["trivial_global"], + npi_config = config["toobig"], + geoids = ["10001","2020","40"]) + + def test_Reduce_invalid_parameter(self): + config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") + with pytest.raises(ValueError, match=r'Invalid parameter name.*'): + test_result = Reduce(global_config = config["trivial_global"], + npi_config = config["invalid_parameter"], + geoids = ["10001","2020","40"]) + + def test_Reduce_bad_start_date(self): + config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") + with pytest.raises(ValueError, match=r'.*not between global dates.*'): + test_result = Reduce(global_config = config["trivial_global"], + npi_config = config["bad_start_date"], + geoids = ["10001","2020","40"]) + + def test_Reduce_bad_end_date(self): + config.set_file(f"{DATA_DIR}/test_ReduceR0_trivial.yml") + with pytest.raises(ValueError, match=r'.*not between global dates.*'): + test_result = Reduce(global_config = config["trivial_global"], + npi_config = config["bad_end_date"], + geoids = ["10001","2020","40"]) + + +# TODO Stacked Tests diff --git a/SEIR/test/test_seir.py b/SEIR/test/test_seir.py index d879da373..9e0abaa23 100644 --- a/SEIR/test/test_seir.py +++ b/SEIR/test/test_seir.py @@ -88,11 +88,11 @@ def test_constant_population(): mobility_data = s.mobility.data npi = NPI.NPIBase.execute(npi_config=s.npi_config, global_config=config, geoids=s.spatset.nodenames) - npi = npi.get().T - parameters = setup.parameters_quick_draw(config["seir"]["parameters"], len(s.t_inter), s.nnodes, s.dt, npi) + parameters = setup.parameters_quick_draw(config["seir"]["parameters"], len(s.t_inter), s.nnodes) + parameters = setup.parameters_reduce(parameters, npi, s.dt) - states = seir.steps_SEIR_nb(parameters, + states = seir.steps_SEIR_nb(*parameters, seeding, s.dt, s.t_inter, s.nnodes, s.popnodes, mobility_geoid_indices, mobility_data_indices, mobility_data, s.dynfilter) @@ -135,12 +135,12 @@ def test_steps_SEIR_nb_simple_spread(): mobility_data = s.mobility.data npi = NPI.NPIBase.execute(npi_config=s.npi_config, global_config=config, geoids=s.spatset.nodenames) - npi = npi.get().T - parameters = setup.parameters_quick_draw(config["seir"]["parameters"], len(s.t_inter), s.nnodes, s.dt, npi) + parameters = setup.parameters_quick_draw(config["seir"]["parameters"], len(s.t_inter), s.nnodes) + parameters = setup.parameters_reduce(parameters, npi, s.dt) for i in range(100): - states = seir.steps_SEIR_nb(parameters, + states = seir.steps_SEIR_nb(*parameters, seeding, s.dt, s.t_inter, s.nnodes, s.popnodes, mobility_geoid_indices, mobility_data_indices, mobility_data, s.dynfilter) @@ -175,12 +175,12 @@ def test_steps_SEIR_no_spread(): mobility_data = s.mobility.data * 0 npi = NPI.NPIBase.execute(npi_config=s.npi_config, global_config=config, geoids=s.spatset.nodenames) - npi = npi.get().T - parameters = setup.parameters_quick_draw(config["seir"]["parameters"], len(s.t_inter), s.nnodes, s.dt, npi) + parameters = setup.parameters_quick_draw(config["seir"]["parameters"], len(s.t_inter), s.nnodes) + parameters = setup.parameters_reduce(parameters, npi, s.dt) for i in range(100): - states = seir.steps_SEIR_nb(parameters, + states = seir.steps_SEIR_nb(*parameters, seeding, s.dt, s.t_inter, s.nnodes, s.popnodes, mobility_geoid_indices, mobility_data_indices, mobility_data, s.dynfilter) diff --git a/SEIR/test/test_setup.py b/SEIR/test/test_setup.py index f66ab15a1..8eaafa38d 100644 --- a/SEIR/test/test_setup.py +++ b/SEIR/test/test_setup.py @@ -46,15 +46,6 @@ def test_mobility_dimensions_fail(self): popnodes_key="population", nodenames_key="geoid") - ## I think we're not requiring this for now. - ## def test_mobility_unsymmetric_fail(self): - ## with pytest.raises(ValueError, match=r".*mobility.*symmetric.*"): - ## setup.SpatialSetup(setup_name=TEST_SETUP_NAME, - ## geodata_file=f"{DATA_DIR}/geodata.csv", - ## mobility_file=f"{DATA_DIR}/mobility_unsymmetric.txt", - ## popnodes_key="population", - ## nodenames_key="geoid") - def test_mobility_too_big_fail(self): with pytest.raises(ValueError, match=r".*mobility.*population.*"): setup.SpatialSetup(setup_name=TEST_SETUP_NAME, @@ -96,14 +87,18 @@ def test_parameters_quick_draw(): npi = pd.DataFrame(0.0, index=date_range, columns=range(nnodes)) - alpha, beta, sigma, gamma = setup.parameters_quick_draw(config, nt_inter, nnodes, dt, npi) + alpha, beta, sigma, gamma = setup.parameters_quick_draw(config, nt_inter, nnodes) - assert alpha == 0.5 + assert alpha.shape == (nt_inter, nnodes) + assert (alpha == 0.5).all() assert beta.shape == (nt_inter, nnodes) + assert (len(np.unique(beta)) == 1) assert (((1/6. * 2) <= beta) & (beta <= (1./2.6 * 3))).all() - assert (beta == beta[0][0]).all() - assert (sigma == config["sigma"].as_evaled_expression()) + assert sigma.shape == (nt_inter, nnodes) + assert (sigma == config["sigma"].as_evaled_expression()).all() - assert (setup.n_Icomp * (1./6)) <= gamma <= (setup.n_Icomp * (1/2.6)) + assert gamma.shape == (nt_inter, nnodes) + assert (len(np.unique(gamma)) == 1) + assert (((setup.n_Icomp * (1./6)) <= gamma) & (gamma <= (setup.n_Icomp * (1/2.6)))).all() diff --git a/batch/launch_job.py b/batch/launch_job.py new file mode 100755 index 000000000..72284e4da --- /dev/null +++ b/batch/launch_job.py @@ -0,0 +1,140 @@ +#!/usr/bin/env python + +import boto3 +import click +import glob +import os +import re +import subprocess +import tarfile +import time +import yaml + +@click.command() +@click.option("-c", "--config", "config_file", envvar="CONFIG_PATH", type=click.Path(exists=True), required=True, + help="configuration file for this run") +@click.option("-j", "--num-jobs", "num_jobs", type=click.IntRange(min=1), required=True, + help="total number of jobs to run in this batch") +@click.option("-l", "--slots-per-job", "slots_per_job", type=click.IntRange(min=1), required=True, + help="how many slots each job should run") +@click.option("-t", "--dvc-target", "dvc_target", type=click.Path(exists=True), required=True, + help="name of the .dvc file that is the last step in the dvc run pipeline") +@click.option("-i", "--s3-input-bucket", "s3_input_bucket", type=str, default="idd-input-data-sets", show_default=True, + help="The S3 bucket to use for uploading the code and configuration used by the batch job") +@click.option("-o", "--s3-output-bucket", "s3_output_bucket", type=str, default="idd-pipeline-results", show_default=True, + help="The S3 bucket for storing the job's outputs") +@click.option("-d", "--job-definition", "batch_job_definition", type=str, default="Batch-CovidPipeline-Job", show_default=True, + help="The name of the AWS Batch Job Definition to use for the job") +@click.option("-q", "--job-queue", "batch_job_queue", type=str, default="Batch-CovidPipeline", show_default=True, + help="The name of the AWS Batch Job Queue to use for the job") +@click.option("-p", "--parallelize-scenarios", "parallelize_scenarios", is_flag=True, default=False, show_default=True, + help="Launch a different batch job for each scenario") +@click.option("-v", "--vcpu", "vcpu", type=click.IntRange(min=2, max=96), default=72, show_default=True, + help="The number of vCPU cores each job should have") +@click.option("-m", "--memory", "memory", type=click.IntRange(min=1000, max=6000), default=4000, show_default=True, + help="The amount of RAM in megabytes needed per CPU running simulations") +def launch_batch(config_file, num_jobs, slots_per_job, dvc_target, s3_input_bucket, s3_output_bucket, batch_job_definition, batch_job_queue, parallelize_scenarios, vcpu, memory): + + config = None + with open(config_file) as f: + config = yaml.full_load(f) + + # A unique name for this job run, based on the config name and current time + job_name = f"{config['name']}-{int(time.time())}" + + # Update and save the config file with the number of sims to run + print(f"Updating {config_file} to run {slots_per_job} slots...") + config['nsimulations'] = slots_per_job + + if parallelize_scenarios: + scenarios = config['interventions']['scenarios'] + for s in scenarios: + scenario_job_name = f"{job_name}_{s}" + config['interventions']['scenarios'] = [s] + with open(config_file, "w") as f: + yaml.dump(config, f, sort_keys=False) + launch_job_inner(scenario_job_name, config_file, num_jobs, slots_per_job, dvc_target, s3_input_bucket, s3_output_bucket, batch_job_definition, batch_job_queue, vcpu, memory) + config['interventions']['scenarios'] = scenarios + with open(config_file, "w") as f: + yaml.dump(config, f, sort_keys=False) + else: + with open(config_file, "w") as f: + yaml.dump(config, f, sort_keys=False) + launch_job_inner(job_name, config_file, num_jobs, slots_per_job, dvc_target, s3_input_bucket, s3_output_bucket, batch_job_definition, batch_job_queue, vcpu, memory) + + (rc, txt) = subprocess.getstatusoutput(f"git checkout -b run_{job_name}") + print(txt) + return rc + + +def launch_job_inner(job_name, config_file, num_jobs, slots_per_job, dvc_target, s3_input_bucket, s3_output_bucket, batch_job_definition, batch_job_queue, vcpu, memory): + + # Prepare to tar up the current directory, excluding any dvc outputs, so it + # can be shipped to S3 + dvc_outputs = get_dvc_outputs() + tarfile_name = f"{job_name}.tar.gz" + tar = tarfile.open(tarfile_name, "w:gz") + for p in os.listdir('.'): + if not (p.startswith(".") or p.endswith("tar.gz") or p in dvc_outputs or p == "batch"): + tar.add(p, filter=lambda x: None if x.name.startswith('.') else x) + tar.close() + + # Upload the tar'd contents of this directory and the runner script to S3 + runner_script_name = f"{job_name}-runner.sh" + local_runner_script = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'runner.sh') + s3_client = boto3.client('s3') + s3_client.upload_file(local_runner_script, s3_input_bucket, runner_script_name) + s3_client.upload_file(tarfile_name, s3_input_bucket, tarfile_name) + os.remove(tarfile_name) + + # Prepare and launch the num_jobs via AWS Batch. + model_data_path = f"s3://{s3_input_bucket}/{tarfile_name}" + results_path = f"s3://{s3_output_bucket}/{job_name}" + env_vars = [ + {"name": "CONFIG_PATH", "value": config_file}, + {"name": "S3_MODEL_DATA_PATH", "value": model_data_path}, + {"name": "DVC_TARGET", "value": dvc_target}, + {"name": "DVC_OUTPUTS", "value": " ".join(dvc_outputs)}, + {"name": "S3_RESULTS_PATH", "value": results_path}, + {"name": "SLOTS_PER_JOB", "value": str(slots_per_job)} + ] + s3_cp_run_script = f"aws s3 cp s3://{s3_input_bucket}/{runner_script_name} $PWD/run-covid-pipeline" + command = ["sh", "-c", f"{s3_cp_run_script}; /bin/bash $PWD/run-covid-pipeline"] + container_overrides = { + 'vcpus': vcpu, + 'memory': vcpu * memory, + 'environment': env_vars, + 'command': command + } + + print("Preparing to run job: %s" % job_name) + batch_client = boto3.client('batch') + if num_jobs > 1: + resp = batch_client.submit_job( + jobName=job_name, + jobQueue=batch_job_queue, + arrayProperties={'size': num_jobs}, + jobDefinition=batch_job_definition, + containerOverrides=container_overrides) + else: + resp = batch_client.submit_job( + jobName=job_name, + jobQueue=batch_job_queue, + jobDefinition=batch_job_definition, + containerOverrides=container_overrides) + + print(f"Batch job with id {resp['jobId']} launched; output will be written to {results_path}") + + +def get_dvc_outputs(): + ret = [] + for dvc_file in glob.glob("*.dvc"): + with open(dvc_file) as df: + d = yaml.full_load(df) + if 'cmd' in d and 'outs' in d: + ret.extend([x['path'] for x in d['outs'] if x['path']]) + return ret + + +if __name__ == '__main__': + launch_batch() diff --git a/batch/runner.sh b/batch/runner.sh new file mode 100755 index 000000000..c20211119 --- /dev/null +++ b/batch/runner.sh @@ -0,0 +1,59 @@ +#!/bin/bash + +set -x + +# Expected environment variables from AWS Batch env +# S3_MODEL_DATA_PATH location in S3 with the code, data, and dvc pipeline to run +# DVC_TARGET the name of the dvc file in the model that should be reproduced locally. +# DVC_OUTPUTS the names of the directories with outputs to save in S3, separated by a space +# S3_RESULTS_PATH location in S3 to store the results + +# setup the python environment +HOME=/home/app +PYENV_ROOT=$HOME/.pyenv +PYTHON_VERSION=3.7.6 +PYTHON_VENV_DIR=$HOME/python_venv +PATH=$PYENV_ROOT/shims:$PYENV_ROOT/bin:$PATH +. $PYTHON_VENV_DIR/bin/activate + +# set optimized S3 configuration +aws configure set default.s3.max_concurrent_requests 100 +aws configure set default.s3.max_queue_size 100 +aws configure set default.s3.multipart_threshold 8MB +aws configure set default.s3.multipart_chunksize 8MB + +# Copy the complete model + data package from S3 and +# install the local R packages +aws s3 cp --quiet $S3_MODEL_DATA_PATH model_data.tar.gz +mkdir model_data +tar -xvzf model_data.tar.gz -C model_data +cd model_data + +# Optional tracking variable to use to write unique output files +export AWS_BATCH_SIM_OFFSET=$((${AWS_BATCH_JOB_ARRAY_INDEX:-0} * ${SLOTS_PER_JOB:-0})) + +# Initialize dvc and run the pipeline to re-create the +# dvc target +dvc init --no-scm +dvc repro $DVC_TARGET + +DVC_OUTPUTS_ARRAY=($DVC_OUTPUTS) +if [ -z "$AWS_BATCH_JOB_ARRAY_INDEX" ]; then + for output in "${DVC_OUTPUTS_ARRAY[@]}" + do + if [ -d "$output" ]; then + tar cv --use-compress-program=pbzip2 -f $output.tar.bz2 $output + aws s3 cp --quiet $output.tar.bz2 $S3_RESULTS_PATH/ + fi + done +else + echo "Saving outputs from array batch job" + for output in "${DVC_OUTPUTS_ARRAY[@]}" + do + if [ -d "$output" ]; then + aws s3 cp --quiet --recursive $output $S3_RESULTS_PATH/$AWS_BATCH_JOB_ID/$output/ + fi + done +fi + +echo "Done" diff --git a/local_install.R b/local_install.R index 613543b41..f5fb8296d 100644 --- a/local_install.R +++ b/local_install.R @@ -3,8 +3,6 @@ library(devtools) initial.options <- commandArgs(trailingOnly = FALSE) file.arg.name <- "--file=" script.name <- sub(file.arg.name, "", initial.options[grep(file.arg.name, initial.options)]) -pkg.dir <- paste0(dirname(script.name), "/R/pkgs/") -install_local(paste0(pkg.dir, "covidcommon"), force=TRUE, upgrade="always") -install_local(paste0(pkg.dir, "hospitalization"), force=TRUE, upgrade="always") -install_local(paste0(pkg.dir, "report_generation"), force=TRUE, upgrade="always") +pkg.dir <- paste0(dirname(script.name), "/R/pkgs/") +install.packages(list.files(pkg.dir,full.names=TRUE),type='source',repos=NULL) diff --git a/packages.R b/packages.R index d17a5da2b..657b212f6 100644 --- a/packages.R +++ b/packages.R @@ -34,7 +34,7 @@ install_version("splines2", version = "0.2.8", repos = repo_url) install_version("nnls", version = "1.4", repos = repo_url) install_github("HopkinsIDD/globaltoolboxlite") -install_github("HopkinsIDD/covidImportation", ref = "1.6.1") +install_github("HopkinsIDD/covidImportation", ref = "v1.6.1") # Install arrow and it's extra dependencies install_version("arrow", version = "0.16.0.2", repos = repo_url) diff --git a/packrat/init.R b/packrat/init.R new file mode 100644 index 000000000..5901a3312 --- /dev/null +++ b/packrat/init.R @@ -0,0 +1,226 @@ +local({ + + ## Helper function to get the path to the library directory for a + ## given packrat project. + getPackratLibDir <- function(projDir = NULL) { + path <- file.path("packrat", "lib", R.version$platform, getRversion()) + + if (!is.null(projDir)) { + + ## Strip trailing slashes if necessary + projDir <- sub("/+$", "", projDir) + + ## Only prepend path if different from current working dir + if (!identical(normalizePath(projDir), normalizePath(getwd()))) + path <- file.path(projDir, path) + } + + path + } + + ## Ensure that we set the packrat library directory relative to the + ## project directory. Normally, this should be the working directory, + ## but we also use '.rs.getProjectDirectory()' if necessary (e.g. we're + ## rebuilding a project while within a separate directory) + libDir <- if (exists(".rs.getProjectDirectory")) + getPackratLibDir(.rs.getProjectDirectory()) + else + getPackratLibDir() + + ## Unload packrat in case it's loaded -- this ensures packrat _must_ be + ## loaded from the private library. Note that `requireNamespace` will + ## succeed if the package is already loaded, regardless of lib.loc! + if ("packrat" %in% loadedNamespaces()) + try(unloadNamespace("packrat"), silent = TRUE) + + if (suppressWarnings(requireNamespace("packrat", quietly = TRUE, lib.loc = libDir))) { + + # Check 'print.banner.on.startup' -- when NA and RStudio, don't print + print.banner <- packrat::get_opts("print.banner.on.startup") + if (print.banner == "auto" && is.na(Sys.getenv("RSTUDIO", unset = NA))) { + print.banner <- TRUE + } else { + print.banner <- FALSE + } + return(packrat::on(print.banner = print.banner)) + } + + ## Escape hatch to allow RStudio to handle bootstrapping. This + ## enables RStudio to provide print output when automagically + ## restoring a project from a bundle on load. + if (!is.na(Sys.getenv("RSTUDIO", unset = NA)) && + is.na(Sys.getenv("RSTUDIO_PACKRAT_BOOTSTRAP", unset = NA))) { + Sys.setenv("RSTUDIO_PACKRAT_BOOTSTRAP" = "1") + setHook("rstudio.sessionInit", function(...) { + # Ensure that, on sourcing 'packrat/init.R', we are + # within the project root directory + if (exists(".rs.getProjectDirectory")) { + owd <- getwd() + setwd(.rs.getProjectDirectory()) + on.exit(setwd(owd), add = TRUE) + } + source("packrat/init.R") + }) + return(invisible(NULL)) + } + + ## Bootstrapping -- only performed in interactive contexts, + ## or when explicitly asked for on the command line + if (interactive() || "--bootstrap-packrat" %in% commandArgs(TRUE)) { + + needsRestore <- "--bootstrap-packrat" %in% commandArgs(TRUE) + + message("Packrat is not installed in the local library -- ", + "attempting to bootstrap an installation...") + + ## We need utils for the following to succeed -- there are calls to functions + ## in 'restore' that are contained within utils. utils gets loaded at the + ## end of start-up anyhow, so this should be fine + library("utils", character.only = TRUE) + + ## Install packrat into local project library + packratSrcPath <- list.files(full.names = TRUE, + file.path("packrat", "src", "packrat") + ) + + ## No packrat tarballs available locally -- try some other means of installation + if (!length(packratSrcPath)) { + + message("> No source tarball of packrat available locally") + + ## There are no packrat sources available -- try using a version of + ## packrat installed in the user library to bootstrap + if (requireNamespace("packrat", quietly = TRUE) && packageVersion("packrat") >= "0.2.0.99") { + message("> Using user-library packrat (", + packageVersion("packrat"), + ") to bootstrap this project") + } + + ## Couldn't find a user-local packrat -- try finding and using devtools + ## to install + else if (requireNamespace("devtools", quietly = TRUE)) { + message("> Attempting to use devtools::install_github to install ", + "a temporary version of packrat") + library(stats) ## for setNames + devtools::install_github("rstudio/packrat") + } + + ## Try downloading packrat from CRAN if available + else if ("packrat" %in% rownames(available.packages())) { + message("> Installing packrat from CRAN") + install.packages("packrat") + } + + ## Fail -- couldn't find an appropriate means of installing packrat + else { + stop("Could not automatically bootstrap packrat -- try running ", + "\"'install.packages('devtools'); devtools::install_github('rstudio/packrat')\"", + "and restarting R to bootstrap packrat.") + } + + # Restore the project, unload the temporary packrat, and load the private packrat + if (needsRestore) + packrat::restore(prompt = FALSE, restart = TRUE) + + ## This code path only reached if we didn't restart earlier + unloadNamespace("packrat") + requireNamespace("packrat", lib.loc = libDir, quietly = TRUE) + return(packrat::on()) + + } + + ## Multiple packrat tarballs available locally -- try to choose one + ## TODO: read lock file and infer most appropriate from there; low priority because + ## after bootstrapping packrat a restore should do the right thing + if (length(packratSrcPath) > 1) { + warning("Multiple versions of packrat available in the source directory;", + "using packrat source:\n- ", shQuote(packratSrcPath)) + packratSrcPath <- packratSrcPath[[1]] + } + + + lib <- file.path("packrat", "lib", R.version$platform, getRversion()) + if (!file.exists(lib)) { + dir.create(lib, recursive = TRUE) + } + + message("> Installing packrat into project private library:") + message("- ", shQuote(lib)) + + surround <- function(x, with) { + if (!length(x)) return(character()) + paste0(with, x, with) + } + + + ## Invoke install.packages() in clean R session + peq <- function(x, y) paste(x, y, sep = " = ") + installArgs <- c( + peq("pkgs", surround(packratSrcPath, with = "'")), + peq("lib", surround(lib, with = "'")), + peq("repos", "NULL"), + peq("type", surround("source", with = "'")) + ) + + fmt <- "utils::install.packages(%s)" + installCmd <- sprintf(fmt, paste(installArgs, collapse = ", ")) + + ## Write script to file (avoid issues with command line quoting + ## on R 3.4.3) + installFile <- tempfile("packrat-bootstrap", fileext = ".R") + writeLines(installCmd, con = installFile) + on.exit(unlink(installFile), add = TRUE) + + fullCmd <- paste( + surround(file.path(R.home("bin"), "R"), with = "\""), + "--vanilla", + "--slave", + "-f", + surround(installFile, with = "\"") + ) + system(fullCmd) + + ## Tag the installed packrat so we know it's managed by packrat + ## TODO: should this be taking information from the lockfile? this is a bit awkward + ## because we're taking an un-annotated packrat source tarball and simply assuming it's now + ## an 'installed from source' version + + ## -- InstallAgent -- ## + installAgent <- "InstallAgent: packrat 0.5.0" + + ## -- InstallSource -- ## + installSource <- "InstallSource: source" + + packratDescPath <- file.path(lib, "packrat", "DESCRIPTION") + DESCRIPTION <- readLines(packratDescPath) + DESCRIPTION <- c(DESCRIPTION, installAgent, installSource) + cat(DESCRIPTION, file = packratDescPath, sep = "\n") + + # Otherwise, continue on as normal + message("> Attaching packrat") + library("packrat", character.only = TRUE, lib.loc = lib) + + message("> Restoring library") + if (needsRestore) + packrat::restore(prompt = FALSE, restart = FALSE) + + # If the environment allows us to restart, do so with a call to restore + restart <- getOption("restart") + if (!is.null(restart)) { + message("> Packrat bootstrap successfully completed. ", + "Restarting R and entering packrat mode...") + return(restart()) + } + + # Callers (source-erers) can define this hidden variable to make sure we don't enter packrat mode + # Primarily useful for testing + if (!exists(".__DONT_ENTER_PACKRAT_MODE__.") && interactive()) { + message("> Packrat bootstrap successfully completed. Entering packrat mode...") + packrat::on() + } + + Sys.unsetenv("RSTUDIO_PACKRAT_BOOTSTRAP") + + } + +}) diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/KernSmooth b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/KernSmooth new file mode 120000 index 000000000..e4284919b --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/KernSmooth @@ -0,0 +1 @@ +/usr/lib/R/library/KernSmooth \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/MASS b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/MASS new file mode 120000 index 000000000..e498a42ec --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/MASS @@ -0,0 +1 @@ +/usr/lib/R/library/MASS \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/Matrix b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/Matrix new file mode 120000 index 000000000..44e20eeb2 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/Matrix @@ -0,0 +1 @@ +/usr/lib/R/library/Matrix \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/base b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/base new file mode 120000 index 000000000..03718b113 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/base @@ -0,0 +1 @@ +/usr/lib/R/library/base \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/boot b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/boot new file mode 120000 index 000000000..5e6dd3900 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/boot @@ -0,0 +1 @@ +/usr/lib/R/library/boot \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/class b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/class new file mode 120000 index 000000000..6dcb8895f --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/class @@ -0,0 +1 @@ +/usr/lib/R/library/class \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/cluster b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/cluster new file mode 120000 index 000000000..cd45bb8ba --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/cluster @@ -0,0 +1 @@ +/usr/lib/R/library/cluster \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/codetools b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/codetools new file mode 120000 index 000000000..aef161591 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/codetools @@ -0,0 +1 @@ +/usr/lib/R/library/codetools \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/compiler b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/compiler new file mode 120000 index 000000000..a2b59c968 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/compiler @@ -0,0 +1 @@ +/usr/lib/R/library/compiler \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/datasets b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/datasets new file mode 120000 index 000000000..d8ac61e45 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/datasets @@ -0,0 +1 @@ +/usr/lib/R/library/datasets \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/foreign b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/foreign new file mode 120000 index 000000000..f96dfcfb8 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/foreign @@ -0,0 +1 @@ +/usr/lib/R/library/foreign \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/grDevices b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/grDevices new file mode 120000 index 000000000..eeef200bf --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/grDevices @@ -0,0 +1 @@ +/usr/lib/R/library/grDevices \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/graphics b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/graphics new file mode 120000 index 000000000..a35f21b20 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/graphics @@ -0,0 +1 @@ +/usr/lib/R/library/graphics \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/grid b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/grid new file mode 120000 index 000000000..148524369 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/grid @@ -0,0 +1 @@ +/usr/lib/R/library/grid \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/lattice b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/lattice new file mode 120000 index 000000000..f79cfb726 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/lattice @@ -0,0 +1 @@ +/usr/lib/R/library/lattice \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/methods b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/methods new file mode 120000 index 000000000..b4dc58eac --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/methods @@ -0,0 +1 @@ +/usr/lib/R/library/methods \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/mgcv b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/mgcv new file mode 120000 index 000000000..ed41fe593 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/mgcv @@ -0,0 +1 @@ +/usr/lib/R/library/mgcv \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/nlme b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/nlme new file mode 120000 index 000000000..0fd0ffa6b --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/nlme @@ -0,0 +1 @@ +/usr/lib/R/library/nlme \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/nnet b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/nnet new file mode 120000 index 000000000..75aed7cdd --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/nnet @@ -0,0 +1 @@ +/usr/lib/R/library/nnet \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/parallel b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/parallel new file mode 120000 index 000000000..8ecaa6e9e --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/parallel @@ -0,0 +1 @@ +/usr/lib/R/library/parallel \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/rpart b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/rpart new file mode 120000 index 000000000..35eb4d28e --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/rpart @@ -0,0 +1 @@ +/usr/lib/R/library/rpart \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/spatial b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/spatial new file mode 120000 index 000000000..4c4b26fe7 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/spatial @@ -0,0 +1 @@ +/usr/lib/R/library/spatial \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/splines b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/splines new file mode 120000 index 000000000..9762ac81e --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/splines @@ -0,0 +1 @@ +/usr/lib/R/library/splines \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/stats b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/stats new file mode 120000 index 000000000..3b5ff65e0 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/stats @@ -0,0 +1 @@ +/usr/lib/R/library/stats \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/stats4 b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/stats4 new file mode 120000 index 000000000..8b44254de --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/stats4 @@ -0,0 +1 @@ +/usr/lib/R/library/stats4 \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/survival b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/survival new file mode 120000 index 000000000..042ccbcc4 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/survival @@ -0,0 +1 @@ +/usr/lib/R/library/survival \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/tcltk b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/tcltk new file mode 120000 index 000000000..3f77dd967 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/tcltk @@ -0,0 +1 @@ +/usr/lib/R/library/tcltk \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/tools b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/tools new file mode 120000 index 000000000..8a54f0270 --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/tools @@ -0,0 +1 @@ +/usr/lib/R/library/tools \ No newline at end of file diff --git a/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/utils b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/utils new file mode 120000 index 000000000..ed5b2d42f --- /dev/null +++ b/packrat/lib-R/x86_64-pc-linux-gnu/3.6.3/utils @@ -0,0 +1 @@ +/usr/lib/R/library/utils \ No newline at end of file diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/DESCRIPTION b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/DESCRIPTION new file mode 100644 index 000000000..34a0a0d90 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/DESCRIPTION @@ -0,0 +1,28 @@ +Package: covidImportation +Title: Estimating the Number of Imported COVID-19 Cases +Version: 1.6.1 +Authors@R: c(person(given = c("Shaun", "A."), family = "Truelove", role + = c("aut", "cre"), email = "shauntruelove@jhu.edu"), + person(given=c("Stephen", "A."), family="Lauer", + email="slauer5@jh.edu", role = c("ctb"))) +Description: What the package does (one paragraph). +Depends: R (>= 3.5), dplyr, tidyr +Imports: doParallel, httr, lubridate, countrycode, globaltoolboxlite, + fitdistrplus, data.table, abind, reshape2, arrayhelpers, truncnorm, + geosphere, ggvoronoi, gpclib, igraph, magrittr, maptools, raster, + rgdal, rlist, sf, tidycensus, purrr, readr, tibble, ggplot2, + parallel, tidyverse +License: What license it uses +Encoding: UTF-8 +LazyData: true +RoxygenNote: 7.1.0 +GithubRepo: covidImportation +GithubUsername: HopkinsIDD +GithubRef: v1.8 +GithubSHA1: 3cf2341907d23e1b19a3a3190dfca29b50d22218 +Author: Shaun A. Truelove [aut, cre], Stephen A. Lauer [ctb] +Maintainer: Shaun A. Truelove +Built: R 3.6.3; ; 2020-09-09 13:56:26 UTC; unix +InstallAgent: packrat 0.5.0 +InstallSource: github +Hash: 19ccb07938df6c97b7397e7a0493b818 diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/INDEX b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/INDEX new file mode 100644 index 000000000..92bc5c8a4 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/INDEX @@ -0,0 +1,89 @@ +airport_attribution Airport attribution data for China +airport_data Airport data +apply_travel_restrictions + Apply a set of travel restrictions to the + travel data, reducing or increasing to a + proportion of the average travel. +calc_nb_import_pars Get negative binomial estimates for each time + and destination +correct_for_Hubei_reporting + Function to correct for the changes in + reporting in Hubei +distrib_county_imports + distrib_county_imports +do_airport_attribution + do_airport_attribution +est_daily_incidence Function to extract approximate epidemic curves + from the cumulative case data. +est_daily_incidence_corrected + Wrapper function to correct for the changes in + reporting in Hubei and merge with data for all + incidence +est_import_detect_dates + Estimate the detection dates of importations +est_imports_base Estimate imports base +expand_travel_restrict + Expand the travel restrictions to include every + date, to allow for merging with travel data. +find_recent_file find_recent_file +fit_ispline Function to fit monotonically increasing + spline. Returns a function that can be used to + predict the spline for each date. +get_CA_metro_labels Get Metro Areas for CA +get_JHUCSSE_data Pull JHU CSSE GitHub data +get_JHUCSSE_deaths Pull JHU CSSE GitHub data +get_airport_city Get airport city +get_airport_country Get airport country +get_airport_state Get airport state +get_airports_to_consider + get_airports_to_consider +get_clean_JHUCSSE_data + Clean crude data from JHUCSSE and aggregated it + to state or county level +get_clean_JHUCSSE_deaths + Clean crude data from JHUCSSE and aggregated it + to state or county level +get_county_pops get_county_pops +get_global_cum Get cumulative case counts by Province_state +get_incidence_data Get incidence data from JHUCSSE +get_incidence_fits Get incidence data from JHUCSSE +get_mean_imports Get mean importations across geoids +get_oag_travel Get OAG travel data +get_oag_travel_fulldata + Get OAG travel data +imports_airport_clustering + imports_airport_clustering +make_daily_travel Create Daily Travel +make_daily_travel_faster + Convert monthly travel to daily travel data - + fast - When we have already built the daily + data, we reuse that and just fill in the new + daily volume each time +make_input_data Make input data +make_meanD Make MeanD Matrix +plot_imports_stackeddest + Barchart plot of importations stacked by source +plot_incidence_ests_report + Function to plot the estimated and reported + case counts +plot_rep_cases Facet plot of cumulative and incident cases at + locations desired +pop_data Population data +pull_JHUCSSE_github_data + Pull JHU CSSE GitHub data +read_JHUCSSE_cases Reads in the JHUCSSE total case count data up + until (and including) a given dat. +run_daily_import_model + Run the full simulation of daily importations +run_daily_import_model_par + Run the full simulation of daily importations +run_full_distrib_imports + run_distrib_imports +run_importations Run importation sims +setup_and_run_importations + Set up and run importation sims +setup_importations Set up importation sims +travel_restrictions Travel restrictions data +underreporting Underreporting data +update_JHUCSSE_github_data + Pull JHU CSSE GitHub data diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/LICENSE b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/LICENSE new file mode 100644 index 000000000..f288702d2 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/LICENSE @@ -0,0 +1,674 @@ + GNU GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. 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If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/Meta/Rd.rds b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/Meta/Rd.rds new file mode 100644 index 000000000..a8ca8bac4 Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/Meta/Rd.rds differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/Meta/data.rds b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/Meta/data.rds new file mode 100644 index 000000000..8e70abf63 Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/Meta/data.rds differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/Meta/features.rds b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/Meta/features.rds new file mode 100644 index 000000000..772f787fd Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/Meta/features.rds differ diff --git 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a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/Meta/package.rds b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/Meta/package.rds new file mode 100644 index 000000000..4aa9e0f6a Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/Meta/package.rds differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/NAMESPACE b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/NAMESPACE new file mode 100644 index 000000000..c89c88f4f --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/NAMESPACE @@ -0,0 +1,88 @@ +# Generated by roxygen2: do not edit by hand + +export(calc_nb_import_pars) +export(correct_for_Hubei_reporting) +export(distrib_county_imports) +export(do_airport_attribution) +export(est_daily_incidence) +export(est_daily_incidence_corrected) +export(fit_ispline) +export(get_JHUCSSE_data) +export(get_JHUCSSE_deaths) +export(get_clean_JHUCSSE_data) +export(get_clean_JHUCSSE_deaths) +export(get_county_pops) +export(get_global_cum) +export(get_incidence_data) +export(get_incidence_fits) +export(get_mean_imports) +export(get_oag_travel_fulldata) +export(imports_airport_clustering) +export(plot_imports_stackeddest) +export(plot_incidence_ests_report) +export(plot_rep_cases) +export(pull_JHUCSSE_github_data) +export(read_JHUCSSE_cases) +export(run_daily_import_model) +export(run_daily_import_model_par) +export(run_full_distrib_imports) +export(run_importations) +export(setup_and_run_importations) +export(setup_importations) +export(update_JHUCSSE_github_data) +import(doParallel) +import(dplyr) +import(foreach) +import(ggplot2) +import(globaltoolboxlite) +import(httr) +import(parallel) +import(readr) +import(sf) +import(tibble) +import(tidyr) +importFrom(abind,abind) +importFrom(arrayhelpers,array2df) +importFrom(countrycode,countrycode) +importFrom(data.table,fread) +importFrom(data.table,rbindlist) +importFrom(fitdistrplus,fitdist) +importFrom(geosphere,distHaversine) +importFrom(ggvoronoi,voronoi_polygon) +importFrom(globaltoolboxlite,get_country_name_ISO3) +importFrom(globaltoolboxlite,get_iso) +importFrom(igraph,as_edgelist) +importFrom(igraph,make_full_graph) +importFrom(igraph,set_vertex_attr) +importFrom(lubridate,as_date) +importFrom(lubridate,day) +importFrom(lubridate,days_in_month) +importFrom(lubridate,epiweek) +importFrom(lubridate,mdy) +importFrom(lubridate,month) +importFrom(lubridate,parse_date_time) +importFrom(lubridate,ydm) +importFrom(lubridate,year) +importFrom(lubridate,ymd_hms) +importFrom(maptools,unionSpatialPolygons) +importFrom(nnls,nnls) +importFrom(purrr,flatten) +importFrom(purrr,map) +importFrom(purrr,map2) +importFrom(purrr,map_dfr) +importFrom(purrr,reduce) +importFrom(raster,crs) +importFrom(raster,intersect) +importFrom(raster,projection) +importFrom(readr,read_csv) +importFrom(readr,write_csv) +importFrom(reshape2,acast) +importFrom(rgdal,readOGR) +importFrom(rgeos,gBuffer) +importFrom(rlist,list.remove) +importFrom(splines2,iSpline) +importFrom(stringr,str_pad) +importFrom(tibble,as_tibble) +importFrom(tidycensus,get_acs) +importFrom(tidyr,replace_na) +importFrom(truncnorm,rtruncnorm) diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/R/covidImportation b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/R/covidImportation new file mode 100644 index 000000000..3b65e3cbb --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/R/covidImportation @@ -0,0 +1,27 @@ +# File share/R/nspackloader.R +# Part of the R package, http://www.R-project.org +# +# Copyright (C) 1995-2012 The R Core Team +# +# This program is free software; you can redistribute it and/or modify +# it under the terms of the GNU General Public License as published by +# the Free Software Foundation; either version 2 of the License, or +# (at your option) any later version. +# +# This program is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +# GNU General Public License for more details. +# +# A copy of the GNU General Public License is available at +# http://www.r-project.org/Licenses/ + +local({ + info <- loadingNamespaceInfo() + pkg <- info$pkgname + ns <- .getNamespace(as.name(pkg)) + if (is.null(ns)) + stop("cannot find namespace environment for ", pkg, domain = NA); + dbbase <- file.path(info$libname, pkg, "R", pkg) + lazyLoad(dbbase, ns, filter = function(n) n != ".__NAMESPACE__.") +}) diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/R/covidImportation.rdb b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/R/covidImportation.rdb new file mode 100644 index 000000000..48c3848f6 Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/R/covidImportation.rdb differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/R/covidImportation.rdx b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/R/covidImportation.rdx new file mode 100644 index 000000000..5619eccbe Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/R/covidImportation.rdx differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/ResultsUtils.R b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/ResultsUtils.R new file mode 100644 index 000000000..fecfc1a2c --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/ResultsUtils.R @@ -0,0 +1,238 @@ + +library(tidyverse) + +states_of_interest=c("NY","NJ","CT") + +regioncode="NYC" +dest=c("JFK","BUF","LGA") +output_dir=file.path("model_output", "importation",regioncode) + + + + +##' +##' Sum importation counts to airport attribution clusters +##' Airport clusters are generated using `do_airport_attribution` for aiports in close proximity to +##' each other e.g. ORD/MDY, DCA/IAD, SFO/OAK +##' +##' +##' @title run_distrib_imports +##' +##' @param states_of_interest single simulation result from importation model +##' @param regioncode Region/project name +##' @param yr Year of county population data +##' @param mean_travel_file Filename of monthly mean travelers into each airport in the region +##' @param states_of_interest States for which to get county populations +##' @param travelers_threshold Minimum monthly average travel volume to be included +##' @param airport_cluster_threshold Distance by which airports can be separated to be in the same cluster, in km; Haversine distance. +##' @param imports_sim_file file name root for each importation simulation. +##' @param local_dir local data directory +##' +##' @return A data.frame of clustered airports, dates, and nmber of importations +##' +##' @import doParallel +##' +##' +##' +examine_single_dest <- function(dests=NULL, output_dir=file.path("model_output", "importation",regioncode)){ + + # input data + input_data <- readr::read_csv(file.path(output_dir,"input_data.csv")) + input_data_dest <- input_data %>% dplyr::filter(destination %in% dest) + + # travel data + travel_data <- readr::read_csv(file.path(output_dir,"travel_data_monthly.csv")) + travel_data_dest <- input_data %>% dplyr::filter(destination %in% dest) + + + # Pull importation results and combine them + import_files <- list.files(output_dir, "imports_sim") + + # get the first one + imports <- readr::read_csv(file.path(output_dir,paste0("imports_sim", 1, ".csv"))) + if (!is.null(dests)){ + imports <- imports %>% dplyr::filter(destination %in% dest) + } + imports <- imports %>% dplyr::group_by(destination, source, t) %>% + dplyr::summarise(imports = sum(this.sim, na.rm = TRUE)) + n_dest <- length(unique(imports$destination)) + n_source <- length(unique(imports$source)) + n_t <- length(unique(imports$t)) + n_sim <- length(import_files) + + #imports_res <- list() + import_array <- array(0, dim=c(n_source, n_dest, n_t, n_sim), + dimnames = list(sort(unique(imports$source)), + sort(unique(imports$destination)), + sort(unique(imports$t)), + seq_len(n_sim))) + + + for (n in seq_len(length(import_files))){ + + # import results + imports <- readr::read_csv(file.path(output_dir,paste0("imports_sim", n, ".csv"))) + + if (!is.null(dests)){ + imports <- imports %>% dplyr::filter(destination %in% dest) + } + + imports <- imports %>% dplyr::group_by(destination, source, t) %>% + dplyr::summarise(imports = sum(this.sim, na.rm = TRUE)) + + #imports_res[[n]] <- imports %>% mutate(sim=n) + import_array[,,,n] <- reshape2::acast(imports %>% dplyr::group_by(source, destination, t), + source ~ destination ~ t, value.var = "imports", + fill=0) + } + #imports_res <- data.table::rbindlist(imports_res) + + #format(object.size(imports_res), "Mb") + format(object.size(import_array), "Mb") + + + # imports_sum_dest <- imports_res %>% + # dplyr::group_by(destination, t) %>% + # dplyr::summarise(sim_mean = mean(imports), + # sim_ll = min(imports), + # sim_ul = max(imports)) + # + # imports_sum <- imports_res %>% + # dplyr::group_by(destination, source, t) %>% + # dplyr::summarise(sim_mean = mean(imports), + # sim_ll = min(imports), + # sim_ul = max(imports)) + + + dest_ <- apply(import_array, c(2:4), sum) + + + dest_mean <- apply(dest_, c(1:2), mean) + + summarize_dests <- function(data=dest_, ){ + dest_res <- apply(dest_, c(1:2), quantile, prob=0.025) + dest_res <- dest_res %>% as_tibble() %>% + mutate(destination = row.names(dest_res)) %>% + pivot_longer(-destination, + names_to = "t", + values_to = "imports") + dest_res <- dest_res %>% mutate(t = as.Date(as.integer(t), origin="1970-01-01")) + + return(dest_res) + } + + + + dest_ul <- apply(dest_, c(1:2), quantile, prob=0.975) + + + + + + source_ <- apply(import_array, c(1,3:4), sum) + + + + + dest_cum <- apply(dest_, c(4), sum) + + + dest_ll <- apply(import_array, c(2:4), quantile, probs=.025) + + dest_cum <- apply(import_array, c(4), sum) + + + + + + ggplot() + + + + + + + +} + + + + + + + + + + + +#### DEAL WITH THIS BELOW LATER + + + +##' +##' Get negative binomial estimates for each time and destination +##' +##' @param importation_sim 4D array outputted from the importation model +##' @param cores number of cores to use in parallel. if not parallel, specify 1. +##' +##' @import doParallel +##' +##' @export +##' +calc_nb_import_pars <- function(importation_sim, cores=4){ + + # aggregate to just destination + import_sim_dests <- apply(importation_sim, 2:4, sum, na.rm=TRUE) + + dests <- dimnames(import_sim_dests)[[1]] + t <- dimnames(import_sim_dests)[[2]] + n_t <- length(t) + n_dest <- length(dests) + + # Make the blank parameter data.frame + #import_pars_df <- tidyr::expand_grid(destination=dests, t=t, size=1, mu=0) + + + # Set up the cluster for parallelization + library(doParallel) + print(paste0("Making a cluster of ", cores," for parallelization.")) + cl <- parallel::makeCluster(cores) + doParallel::registerDoParallel(cl) + + # Suppress errors for this loop + options(show.error.messages = FALSE) + + import_pars_df_all <- foreach(t_=seq_len(length(t)), + .packages = "fitdistrplus", + .combine = "rbind") %dopar% { + + import_pars_df <- data.frame(destination=dests, t=t_, size=1, mu=0) + + for (d_ in seq_len(length(dests))){ + + pars_ <- tryCatch ( { + fitdistrplus::fitdist(import_sim_dests[d_, t_, ], distr="nbinom", method="mle")$estimate + }, + #warning = function(w) { }, + error = function(e) { + c(1,0) + }) + + import_pars_df[d_, 3:4] <- pars_ + + } + import_pars_df + } + + # Un-suppress errors + options(show.error.messages = TRUE) + + parallel::stopCluster(cl) + + + # write_csv(import_pars_df, file.path("output",project_name, sprintf("covid_importation_nb_params_%s_batch_v%s.csv", batch, version))) + return(import_pars_df_all) +} + + + diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/data/Rdata.rdb b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/data/Rdata.rdb new file mode 100644 index 000000000..7e458addb Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/data/Rdata.rdb differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/data/Rdata.rds b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/data/Rdata.rds new file mode 100644 index 000000000..95451500e Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/data/Rdata.rds differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/data/Rdata.rdx b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/data/Rdata.rdx new file mode 100644 index 000000000..26e1ff692 Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/data/Rdata.rdx differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/data/datalist b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/data/datalist new file mode 100644 index 000000000..947d5e85c --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/data/datalist @@ -0,0 +1,10 @@ +airport_attribution +airport_data +jhucsse_case_data +pop_data +travel_restrictions +tsa_throughput +underreporting +us_counties +usa_oag_aggr_travel +wikipedia_cases diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/get_case_data.R b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/get_case_data.R new file mode 100644 index 000000000..b7eb62f58 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/get_case_data.R @@ -0,0 +1,32 @@ + +#Required package +devtools::install_github("HopkinsIDD/globaltoolboxlite") +#Installation +devtools::install_github("HopkinsIDD/covidImportation") + +library(covidImportation) + + +## ~ Incidence data +incid_data_list <- get_incidence_data(first_date = ISOdate(2019,12,1), + last_date = Sys.time(), + update_case_data = TRUE, + case_data_dir = "data/case_data", + check_saved_data = TRUE, + save_data = TRUE) + +#Smoothed data -- currently smoothed for Chinese Province, US State, and otherwise country +incid_data <- incid_data_list$incid_data %>% dplyr::filter(source != "USA") +incid_data <- incid_data %>% rename(incid_est = cases_incid) + +#Cleaned JHU CSSE data +jhucsse <- incid_data_list$jhucsse_case_data + +#Cleaned JHU CSSE data, with cumulative cases and incident cases aggregated to State level for the US +jhucsse_state <- incid_data_list$jhucsse_case_data_state + + + +# To look at the functions doing smoothing within the `get_incidence_data` function, look at: +# -- est_daily_incidence_corrected() + diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/help/AnIndex b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/help/AnIndex new file mode 100644 index 000000000..7b012014f --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/help/AnIndex @@ -0,0 +1,50 @@ +airport_attribution airport_attribution +airport_data airport_data +apply_travel_restrictions apply_travel_restrictions +calc_nb_import_pars calc_nb_import_pars +correct_for_Hubei_reporting correct_for_Hubei_reporting +distrib_county_imports distrib_county_imports +do_airport_attribution do_airport_attribution +est_daily_incidence est_daily_incidence +est_daily_incidence_corrected est_daily_incidence_corrected +est_imports_base est_imports_base +est_import_detect_dates est_import_detect_dates +expand_travel_restrict expand_travel_restrict +find_recent_file find_recent_file +fit_ispline fit_ispline +get_airports_to_consider get_airports_to_consider +get_airport_city get_airport_city +get_airport_country get_airport_country +get_airport_state get_airport_state +get_CA_metro_labels get_CA_metro_labels +get_clean_JHUCSSE_data get_clean_JHUCSSE_data +get_clean_JHUCSSE_deaths get_clean_JHUCSSE_deaths +get_county_pops get_county_pops +get_global_cum get_global_cum +get_incidence_data get_incidence_data +get_incidence_fits get_incidence_fits +get_JHUCSSE_data get_JHUCSSE_data +get_JHUCSSE_deaths get_JHUCSSE_deaths +get_mean_imports get_mean_imports +get_oag_travel get_oag_travel +get_oag_travel_fulldata get_oag_travel_fulldata +imports_airport_clustering imports_airport_clustering +make_daily_travel make_daily_travel +make_daily_travel_faster make_daily_travel_faster +make_input_data make_input_data +make_meanD make_meanD +plot_imports_stackeddest plot_imports_stackeddest +plot_incidence_ests_report plot_incidence_ests_report +plot_rep_cases plot_rep_cases +pop_data pop_data +pull_JHUCSSE_github_data pull_JHUCSSE_github_data +read_JHUCSSE_cases read_JHUCSSE_cases +run_daily_import_model run_daily_import_model +run_daily_import_model_par run_daily_import_model_par +run_full_distrib_imports run_full_distrib_imports +run_importations run_importations +setup_and_run_importations setup_and_run_importations +setup_importations setup_importations +travel_restrictions travel_restrictions +underreporting underreporting +update_JHUCSSE_github_data update_JHUCSSE_github_data diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/help/aliases.rds 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Estimating the Number of Imported COVID-19 Cases + +

+
+
+[Up] +[Top] +

Documentation for package ‘covidImportation’ version 1.6.1

+ + + +

Help Pages

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
airport_attributionAirport attribution data for China
airport_dataAirport data
apply_travel_restrictionsApply a set of travel restrictions to the travel data, reducing or increasing to a proportion of the average travel.
calc_nb_import_parsGet negative binomial estimates for each time and destination
correct_for_Hubei_reportingFunction to correct for the changes in reporting in Hubei
distrib_county_importsdistrib_county_imports
do_airport_attributiondo_airport_attribution
est_daily_incidenceFunction to extract approximate epidemic curves from the cumulative case data.
est_daily_incidence_correctedWrapper function to correct for the changes in reporting in Hubei and merge with data for all incidence
est_imports_baseEstimate imports base
est_import_detect_datesEstimate the detection dates of importations
expand_travel_restrictExpand the travel restrictions to include every date, to allow for merging with travel data.
find_recent_filefind_recent_file
fit_isplineFunction to fit monotonically increasing spline. Returns a function that can be used to predict the spline for each date.
get_airports_to_considerget_airports_to_consider
get_airport_cityGet airport city
get_airport_countryGet airport country
get_airport_stateGet airport state
get_CA_metro_labelsGet Metro Areas for CA
get_clean_JHUCSSE_dataClean crude data from JHUCSSE and aggregated it to state or county level
get_clean_JHUCSSE_deathsClean crude data from JHUCSSE and aggregated it to state or county level
get_county_popsget_county_pops
get_global_cumGet cumulative case counts by Province_state
get_incidence_dataGet incidence data from JHUCSSE
get_incidence_fitsGet incidence data from JHUCSSE
get_JHUCSSE_dataPull JHU CSSE GitHub data
get_JHUCSSE_deathsPull JHU CSSE GitHub data
get_mean_importsGet mean importations across geoids
get_oag_travelGet OAG travel data
get_oag_travel_fulldataGet OAG travel data
imports_airport_clusteringimports_airport_clustering
make_daily_travelCreate Daily Travel
make_daily_travel_fasterConvert monthly travel to daily travel data - fast - When we have already built the daily data, we reuse that and just fill in the new daily volume each time
make_input_dataMake input data
make_meanDMake MeanD Matrix
plot_imports_stackeddestBarchart plot of importations stacked by source
plot_incidence_ests_reportFunction to plot the estimated and reported case counts
plot_rep_casesFacet plot of cumulative and incident cases at locations desired
pop_dataPopulation data
pull_JHUCSSE_github_dataPull JHU CSSE GitHub data
read_JHUCSSE_casesReads in the JHUCSSE total case count data up until (and including) a given dat.
run_daily_import_modelRun the full simulation of daily importations
run_daily_import_model_parRun the full simulation of daily importations
run_full_distrib_importsrun_distrib_imports
run_importationsRun importation sims
setup_and_run_importationsSet up and run importation sims
setup_importationsSet up importation sims
travel_restrictionsTravel restrictions data
underreportingUnderreporting data
update_JHUCSSE_github_dataPull JHU CSSE GitHub data
+ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/html/R.css b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/html/R.css new file mode 100644 index 000000000..f10f5ea66 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/html/R.css @@ -0,0 +1,97 @@ +body { + background: white; + color: black; +} + +a:link { + background: white; + color: blue; +} + +a:visited { + background: white; + color: rgb(50%, 0%, 50%); +} + +h1 { + background: white; + color: rgb(55%, 55%, 55%); + font-family: monospace; + font-size: x-large; + text-align: center; +} + +h2 { + background: white; + color: rgb(40%, 40%, 40%); + font-family: monospace; + font-size: large; + text-align: center; +} + +h3 { + background: white; + color: rgb(40%, 40%, 40%); + font-family: monospace; + font-size: large; +} + +h4 { + background: white; + color: rgb(40%, 40%, 40%); + font-family: monospace; + font-style: italic; + font-size: large; +} + +h5 { + background: white; + color: rgb(40%, 40%, 40%); + font-family: monospace; +} + +h6 { + background: white; + color: rgb(40%, 40%, 40%); + font-family: monospace; + font-style: italic; +} + +img.toplogo { + width: 4em; + vertical-align: middle; +} + +img.arrow { + width: 30px; + height: 30px; + border: 0; +} + +span.acronym { + font-size: small; +} + +span.env { + font-family: monospace; +} + +span.file { + font-family: monospace; +} + +span.option{ + font-family: monospace; +} + +span.pkg { + font-weight: bold; +} + +span.samp{ + font-family: monospace; +} + +div.vignettes a:hover { + background: rgb(85%, 85%, 85%); +} diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/importation_analysis.R b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/importation_analysis.R new file mode 100644 index 000000000..aeac2db42 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/importation_analysis.R @@ -0,0 +1,562 @@ +##::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: +##' nCoV Importation Analyses -- Risk Analyses #### +##' +##::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: + +if (!exists("version") | is.list(version)){ version <- "1" } +if (!exists("batch") | is.list(batch)){ batch <- "1st" } +if (!exists("project_name")){ project_name <- "california_import" } +if (!exists("start_date")){ start_date <- "2020-01-01" } +if (!exists("na_to_zero")){ na_to_zero <- TRUE } + +print(project_name) +print(version) +print(batch) + +dir.create(file.path("results", project_name), recursive = TRUE) +import_sim_file <- file.path("output",project_name, sprintf("covid_importation_sim_%s_batch_v%s.RData", batch, version)) + + + +# SETUP ------------------------------------------------------------------- + +options(scipen=999) +if(!require('tidyverse')) install.packages('tidyverse'); library(tidyverse) +if(!require('reshape2')) install.packages('reshape2'); library(reshape2) +if(!require('abind')) install.packages('abind'); library(abind) + + + +# IMPORT DATA ------------------------------------------------------------- + +load(import_sim_file) # load importation_sim +Sys.sleep(5) # pause to let the computer catch up +#format(object.size(importation_sim),"Mb") + +sources_ <- dimnames(importation_sim)[[1]] +dests_ <- dimnames(importation_sim)[[2]] +t_ <- dimnames(importation_sim)[[3]] +sims_ <- dimnames(importation_sim)[[4]] + + +# Check range of sims +range(sims_) +tmp <- apply(importation_sim, c(3,4), sum, na.rm=TRUE) +rowMeans(tmp) + + + +# ~ Convert to Long Form -------------------------------------------------- + +# Convert raw data array into long format +import_data_long <- arrayhelpers::array2df(importation_sim) +Sys.sleep(5) # pause to let the computer catch up + +colnames(import_data_long) <- c("imports","source","destination","t","sim") +import_data_long <- import_data_long %>% mutate(t = lubridate::ymd(t)) %>% as.data.frame() + +# Remove time prior to start_date +min((import_data_long %>% filter(!is.na(imports)))$t) +import_data_long <- import_data_long %>% filter(t>=start_date) + + +#write_csv(import_data_long, paste0("data/est_imports_long_ver",version,".csv")) +import_data_long$imports <- as.integer(as.character(import_data_long$imports)) +dims_import_data <- dim(importation_sim) +n_sim <- dims_import_data[4] +format(object.size(import_data_long), "Mb") + +# # Add reported +# import_data_long <- left_join(import_data_long, imports_reported_bydestination) + +# Make NAs into 0 if desired +if (na_to_zero){ + import_data_long <- import_data_long %>% mutate(imports = ifelse(is.na(imports), 0, imports)) +} + +# ~ Summarize imporations in long data ------------------------------------ + +# Get mean and medians for ea/ch sim +import_data_long <- import_data_long %>% group_by(sim) %>% + mutate(mean_sim=mean(imports, na.rm=T), + median_sim=median(imports, na.rm=T)) %>% ungroup() + +# Get RR compared to the mean and median +import_data_long$RR.vs.sim.mean <- import_data_long$imports / import_data_long$mean_sim +import_data_long$RR.vs.sim.median <- import_data_long$imports / import_data_long$median_sim + +# Get RR compared to the destination mean +import_data_long <- import_data_long %>% group_by(destination, sim) %>% + mutate(destination_sim_mean = mean(imports, na.rm=TRUE)) %>% ungroup() +import_data_long$RR.vs.destination.mean <- import_data_long$imports / import_data_long$destination_sim_mean +import_data_long$RR.vs.destination.mean[import_data_long$destination_sim_mean==0] <- 1 + + +# Save it +dir.create(file.path("results", project_name), recursive = TRUE, showWarnings = FALSE) +write_csv(import_data_long, file.path("results", project_name, sprintf("import_data_long_v%s.csv", version))) + + +# # Load it +import_data_long <- read_csv(file.path("results", project_name, sprintf("import_data_long_v%s.csv", version))) %>% as.data.frame() + +cols.numeric <- c("mean_sim", "RR.vs.sim.mean", "RR.vs.sim.median", "destination_sim_mean", "RR.vs.destination.mean") +cols.integer <- c("imports", "sim", "median_sim") +#"rep_imports", "rep_imports_orig", "missing_data_count", "available_data_count","mean_travel", "mean_population", +import_data_long[cols.numeric] <- sapply(import_data_long[cols.numeric], as.numeric) +import_data_long[cols.integer] <- sapply(import_data_long[cols.integer], as.integer) +sapply(import_data_long, class) + +n_sim <- max(import_data_long$sim) + + + + + + + +# SUMMARIZE RESULTS ------------------------------------------------------- + + +# ~ import_results_dest -------------------------------------------------------- + +# Get RR mean and CIs +import_results_dest <- import_data_long %>% group_by(destination, sim) %>% + mutate(imports = sum(imports, na.rm = TRUE)) %>% ungroup() %>% group_by(destination) %>% + summarize( + import_mean=mean(imports, na.rm=T), + import_sd=sd(imports, na.rm=T), + import_ll=quantile(imports, probs=.025, na.rm=T), + import_ul=quantile(imports, probs=.975, na.rm=T), + import_median=median(imports, na.rm=T), + import_min=min(imports, na.rm=T), + import_max=max(imports, na.rm=T), + import_25pt=quantile(imports, probs=.25, na.rm=T), + import_75pt=quantile(imports, probs=.75, na.rm=T), + + RR_mean=mean(RR.vs.sim.mean, na.rm=T), + RR_ll=quantile(RR.vs.sim.mean, probs=.025, na.rm=T), + RR_ul=quantile(RR.vs.sim.mean, probs=.975, na.rm=T), + RR_sd=sd(RR.vs.sim.mean, na.rm=T), + RR_median=median(RR.vs.sim.mean, na.rm=T), + + RR_destination_mean=mean(RR.vs.destination.mean, na.rm=T), + RR_destination_ll=quantile(RR.vs.destination.mean, probs=.025, na.rm=T), + RR_destination_ul=quantile(RR.vs.destination.mean, probs=.975, na.rm=T), + RR_destination_sd=sd(RR.vs.destination.mean, na.rm=T), + RR_destination_median=median(RR.vs.destination.mean, na.rm=T)#, + #rep_imports = mean(rep_imports, na.rm = T) + ) + +write_csv(import_results_dest, file.path("results",project_name,sprintf("import_results_dest_v%s.csv", version))) + + + +# ~ import_results_desttime -------------------------------------------------------- + + + +# Get RR mean and CIs +import_results_desttime <- import_data_long %>% group_by(destination, t, sim) %>% + mutate(imports = sum(imports, na.rm = TRUE)) %>% ungroup() %>% group_by(destination, t) %>% + summarize( + import_mean=mean(imports, na.rm=T), + import_sd=sd(imports, na.rm=T), + import_ll=quantile(imports, probs=.025, na.rm=T), + import_ul=quantile(imports, probs=.975, na.rm=T), + import_median=median(imports, na.rm=T), + import_min=min(imports, na.rm=T), + import_max=max(imports, na.rm=T), + import_25pt=quantile(imports, probs=.25, na.rm=T), + import_75pt=quantile(imports, probs=.75, na.rm=T), + + RR_mean=mean(RR.vs.sim.mean, na.rm=T), + RR_ll=quantile(RR.vs.sim.mean, probs=.025, na.rm=T), + RR_ul=quantile(RR.vs.sim.mean, probs=.975, na.rm=T), + RR_sd=sd(RR.vs.sim.mean, na.rm=T), + RR_median=median(RR.vs.sim.mean, na.rm=T), + + RR_destination_mean=mean(RR.vs.destination.mean, na.rm=T), + RR_destination_ll=quantile(RR.vs.destination.mean, probs=.025, na.rm=T), + RR_destination_ul=quantile(RR.vs.destination.mean, probs=.975, na.rm=T), + RR_destination_sd=sd(RR.vs.destination.mean, na.rm=T), + RR_destination_median=median(RR.vs.destination.mean, na.rm=T)#, + #rep_imports = mean(rep_imports, na.rm = T) + ) + +# Get the probability of >0 imports +prob_any_import <- import_data_long %>% group_by(destination, t, sim) %>% + summarise(imports = sum(imports)) %>% group_by(destination, t) %>% + summarize(n_import = sum(imports>0)) %>% mutate(prob_import=n_import/(n_sim)) + +# Add Probability +import_results_desttime$prob_any_import <- prob_any_import$prob_import +import_results_desttime <- import_results_desttime %>% dplyr::select(1,2,prob_any_import, everything()) +rm(prob_any_import) + +write_csv(import_results_desttime, file.path("results",project_name,sprintf("import_results_desttime_v%s.csv", version))) + + +# # ADD REPORTED TO ESTIMATED +# #source("Source/clean_reported_importations.R") +# reported_file_path <- paste0("Results/",results_folder,"/import_reported_long_matched.csv") +# +# if (file.exists(reported_file_path)){ +# # load reported imports summed by destination +# imports_reported_long <- read_csv(reported_file_path) %>% as.data.frame() %>% +# rename(rep_imports=imports) +# +# # merge with import_results +# import_results <- left_join(import_results, imports_reported_long) +# import_data_long <- left_join(import_data_long, imports_reported_long) +# +# } else { +# import_results$rep_imports <- NA +# import_data_long$rep_imports <- NA +# } + + + + + + + +# ~ import_results_desttime_cum -------------------------------------------------------- +# Cumulate importations into destination + +# Add up importations by location by simulation +import_data_long <- import_data_long %>% group_by(sim, source, destination) %>% + mutate(imports_cum = cumsum(imports)) %>% ungroup() + +# Get RR mean and CIs +import_results_desttime_cum <- import_data_long %>% group_by(destination, t, sim) %>% + mutate(imports_cum = sum(imports_cum, na.rm = TRUE)) %>% ungroup() %>% group_by(destination, t) %>% + summarize( + cum_import_mean=mean(imports_cum, na.rm=T), + cum_import_sd=sd(imports_cum, na.rm=T), + cum_import_ll=quantile(imports_cum, probs=.025, na.rm=T), + cum_import_ul=quantile(imports_cum, probs=.975, na.rm=T), + cum_import_median=median(imports_cum, na.rm=T), + cum_import_min=min(imports_cum, na.rm=T), + cum_import_max=max(imports_cum, na.rm=T), + cum_import_25pt=quantile(imports_cum, probs=.25, na.rm=T), + cum_import_75pt=quantile(imports_cum, probs=.75, na.rm=T), + ) + +# Get the probability of >0 imports +prob_any_import <- import_data_long %>% group_by(destination, t, sim) %>% + summarise(imports_cum = sum(imports_cum)) %>% group_by(destination, t) %>% + summarize(n_import = sum(imports_cum>0)) %>% mutate(prob_import=n_import/(n_sim)) + +# Add Probability +import_results_desttime_cum$cum_prob_any_import <- prob_any_import$prob_import +import_results_desttime_cum <- import_results_desttime_cum %>% dplyr::select(1,2,cum_prob_any_import, everything()) +rm(prob_any_import) + +write_csv(import_results_desttime_cum, file.path("results",project_name,sprintf("import_results_desttime_cumulative_v%s.csv", version))) + + + + + +# ~ import_results_desttime_overall -------------------------------------------------------- + + +# Get RR mean and CIs +import_results_desttime_overall <- import_data_long %>% group_by(t, sim) %>% + mutate(imports = sum(imports, na.rm = TRUE)) %>% ungroup() %>% group_by(t) %>% + summarize( + import_mean=mean(imports, na.rm=T), + import_sd=sd(imports, na.rm=T), + import_ll=quantile(imports, probs=.025, na.rm=T), + import_ul=quantile(imports, probs=.975, na.rm=T), + import_median=median(imports, na.rm=T), + import_min=min(imports, na.rm=T), + import_max=max(imports, na.rm=T), + import_25pt=quantile(imports, probs=.25, na.rm=T), + import_75pt=quantile(imports, probs=.75, na.rm=T), + + RR_mean=mean(RR.vs.sim.mean, na.rm=T), + RR_ll=quantile(RR.vs.sim.mean, probs=.025, na.rm=T), + RR_ul=quantile(RR.vs.sim.mean, probs=.975, na.rm=T), + RR_sd=sd(RR.vs.sim.mean, na.rm=T), + RR_median=median(RR.vs.sim.mean, na.rm=T), + + RR_destination_mean=mean(RR.vs.destination.mean, na.rm=T), + RR_destination_ll=quantile(RR.vs.destination.mean, probs=.025, na.rm=T), + RR_destination_ul=quantile(RR.vs.destination.mean, probs=.975, na.rm=T), + RR_destination_sd=sd(RR.vs.destination.mean, na.rm=T), + RR_destination_median=median(RR.vs.destination.mean, na.rm=T)#, + #rep_imports = mean(rep_imports, na.rm = T) + ) + +# Get the probability of >0 imports +prob_any_import <- import_data_long %>% group_by(t, sim) %>% + summarise(imports = sum(imports)) %>% group_by(t) %>% + summarize(n_import = sum(imports>0)) %>% mutate(prob_import=n_import/(n_sim)) + +# Add Probability +import_results_desttime_overall$prob_any_import <- prob_any_import$prob_import +import_results_desttime_overall <- import_results_desttime_overall %>% dplyr::select(1,2,prob_any_import, everything()) +rm(prob_any_import) + +write_csv(import_results_desttime_overall, file.path("results",project_name,sprintf("import_results_desttime_overall_v%s.csv", version))) + + +# # ADD REPORTED TO ESTIMATED +# #source("Source/clean_reported_importations.R") +# reported_file_path <- paste0("Results/",results_folder,"/import_reported_long_matched.csv") +# +# if (file.exists(reported_file_path)){ +# # load reported imports summed by destination +# imports_reported_long <- read_csv(reported_file_path) %>% as.data.frame() %>% +# rename(rep_imports=imports) +# +# # merge with import_results +# import_results <- left_join(import_results, imports_reported_long) +# import_data_long <- left_join(import_data_long, imports_reported_long) +# +# } else { +# import_results$rep_imports <- NA +# import_data_long$rep_imports <- NA +# } + + + + + + + +# ~ import_results_desttime_overall_cum -------------------------------------------------------- +# Cumulate importations into overall destination (i.e., a state) + +# Get RR mean and CIs +import_results_desttime_overall_cum <- import_data_long %>% + group_by(t, sim) %>% summarise(imports = sum(imports, na.rm = TRUE)) %>% as.data.frame() %>% + group_by(sim) %>% mutate(imports_cum = cumsum(imports)) %>% ungroup(sim) %>% + group_by(t) %>% + summarize( + cum_import_mean=mean(imports_cum, na.rm=T), + cum_import_sd=sd(imports_cum, na.rm=T), + cum_import_ll=quantile(imports_cum, probs=.025, na.rm=T), + cum_import_ul=quantile(imports_cum, probs=.975, na.rm=T), + cum_import_median=median(imports_cum, na.rm=T), + cum_import_min=min(imports_cum, na.rm=T), + cum_import_max=max(imports_cum, na.rm=T), + cum_import_25pt=quantile(imports_cum, probs=.25, na.rm=T), + cum_import_75pt=quantile(imports_cum, probs=.75, na.rm=T), + ) + +# Get the probability of >0 imports +prob_any_import <- import_data_long %>% group_by(t, sim) %>% + summarise(imports = sum(imports, na.rm = TRUE)) %>% as.data.frame() %>% + group_by(sim) %>% mutate(imports_cum = cumsum(imports)) %>% ungroup(sim) %>% + group_by(t) %>% + summarize(n_import = sum(imports_cum>0)) %>% + mutate(prob_import=n_import/(n_sim)) + +# Add Probability +import_results_desttime_overall_cum$cum_prob_any_import <- prob_any_import$prob_import +import_results_desttime_overall_cum <- import_results_desttime_overall_cum %>% dplyr::select(1,2,cum_prob_any_import, everything()) +rm(prob_any_import) + +write_csv(import_results_desttime_overall_cum, file.path("results",project_name,sprintf("import_results_desttime_overall_cumulative_v%s.csv", version))) + + + + + +# ~ import_results_sources --------------------------------------------------- +# -- SUMMARIZE IMPORTATION FROM PROVINCES - FROM LONG DATA + +head(import_data_long) + +# long source year +import_data_sourcesday_long <- import_data_long %>% + group_by(source, t, sim) %>% + summarize(imports=sum(imports, na.rm=T)) +head(import_data_sourcesday_long) + +# long source +import_data_sources_long <- import_data_long %>% group_by(source, sim) %>% + summarize(imports=sum(imports, na.rm=T)) +head(import_data_sources_long) + +# Get mean and medians for each sim +import_data_sources_long <- import_data_sources_long %>% group_by(sim) %>% + mutate(mean_sim=mean(imports, na.rm=T), median_sim=median(imports, na.rm=T)) %>% ungroup() + +# Get the probability of >0 imports +prob_any_import <- import_data_sources_long %>% group_by(source) %>% + summarize(n_anyimport=sum(imports>0)) %>% mutate(prob_import=n_anyimport/n_sim) + +# Get RR compared to the mean +import_data_sources_long <- import_data_sources_long %>% mutate(RR.vs.sim.mean = imports / mean_sim) + +# Get RR mean and CIs +import_results_sources <- import_data_sources_long %>% group_by(source) %>% + summarize( + import_mean=mean(imports, na.rm=T), + import_sd=sd(imports, na.rm=T), + import_ll=quantile(imports, probs=.025, na.rm=T), + import_ul=quantile(imports, probs=.975, na.rm=T), + import_median=median(imports, na.rm=T), + import_min=min(imports, na.rm=T), + import_max=max(imports, na.rm=T), + + RR_mean=mean(RR.vs.sim.mean, na.rm=T), + RR_ll=quantile(RR.vs.sim.mean, probs=.025, na.rm=T), + RR_ul=quantile(RR.vs.sim.mean, probs=.975, na.rm=T), + RR_sd=sd(RR.vs.sim.mean, na.rm=T), + RR_median=median(RR.vs.sim.mean, na.rm=T)) %>% as.data.frame() + +import_results_sources <- left_join(import_results_sources, prob_any_import %>% select(-n_anyimport), by=c("source"="source")) +head(import_results_sources) +rm(prob_any_import) + +write_csv(import_results_sources, file.path("results",project_name,sprintf("import_results_sources_v%s.csv", version))) + + + + + +# ~ import_results_sourcetime --------------------------------------- + +# SUMMARIZE IMPORTATIONS BY STATE AND YEAR + +# Sum up by t +import_sourcetime_long <- import_data_long %>% as.data.frame() %>% + group_by(source, t, sim) %>% + summarise(imports=sum(imports)) +import_sourcetime_long <- import_sourcetime_long %>% + group_by(sim) %>% mutate(mean_sim=mean(imports, na.rm=T)) %>% ungroup() %>% + mutate(RR.vs.sim.mean=imports/mean_sim) + +# Get RR mean and CIs +import_results_sourcetime <- import_sourcetime_long %>% group_by(source, t) %>% + summarize( + import_mean=mean(imports, na.rm=T), + import_sd=sd(imports, na.rm=T), + import_ll=quantile(imports, probs=.025, na.rm=T), + import_ul=quantile(imports, probs=.975, na.rm=T), + import_ll_pois = NA, + import_ul_pois = NA, + import_median=median(imports, na.rm=T), + import_min=min(imports, na.rm=T), + import_max=max(imports, na.rm=T), + + #rep_import=mean(rep_imports, na.rm=T), + + RR_mean=mean(RR.vs.sim.mean, na.rm=T), + RR_ll=quantile(RR.vs.sim.mean, probs=.025, na.rm=T), + RR_ul=quantile(RR.vs.sim.mean, probs=.975, na.rm=T), + RR_sd=sd(RR.vs.sim.mean, na.rm=T), + RR_median=median(RR.vs.sim.mean, na.rm=T) + ) + +import_results_sourcetime <- import_results_sourcetime %>% + mutate(import_ll_pois = import_mean - 1.96 * sqrt(import_mean/10000), + import_ul_pois = import_mean + 1.96 * sqrt(import_mean/10000)) + + +# Get the probability of >0 imports +prob_any_import <- import_data_long %>% group_by(source, t, sim) %>% + summarise(imports = sum(imports)) %>% group_by(source, t) %>% + summarize(n_import = sum(imports>0)) %>% mutate(prob_import=n_import/(n_sim)) + + +prob_for_cis <- prob_any_import %>% filter(!is.na(n_import)) %>% + mutate(n = n_sim) +cis <- Hmisc::binconf(prob_for_cis$n_import, prob_for_cis$n, + alpha=0.05, + method=c("wilson"), + include.x=FALSE, include.n=FALSE, return.df=TRUE) +prob_for_cis <- data.frame(prob_for_cis, cis) +prob_for_cis <- prob_for_cis %>% mutate(Lower=round(Lower, 3), Upper=round(Upper, 3)) +prob_any_import <- left_join(prob_any_import, prob_for_cis %>% + select(source, t, prob_ll=Lower, prob_ul=Upper)) +rm(prob_for_cis) + +t_meanprob <- prob_any_import %>% group_by(source) %>% + summarise(mean = round(mean(prob_import, na.rm=TRUE), 3), + mean_ll = round(mean(prob_ll, na.rm=TRUE), 3), + mean_ul = round(mean(prob_ul, na.rm=TRUE), 3), + probyr_sd = sd(prob_import, na.rm=TRUE), + n_samp = sum(!is.na(prob_import))) %>% + mutate(probyr_ll = round(mean - 1.96*probyr_sd/sqrt(n_samp), 3), + probyr_ul = round(mean + 1.96*probyr_sd/sqrt(n_samp), 3)) + + +import_results_sourcetime$prob_any_import <- prob_any_import$prob_import +import_results_sourcetime <- import_results_sourcetime %>% dplyr::select(1,2,prob_any_import, everything()) +rm(prob_any_import) + +import_results_sourcetime <- import_results_sourcetime %>% + dplyr::select(source, t, everything()) +# +# # Add travel and population adjustment +# Travelers.source.t <- read_csv("Data/travel_t_sources.csv") +# import_results_sourcetime <- add_t_pop_and_travel(import_results_sourcetime) +# import_results_sourcetime <- import_results_sourcetime %>% +# mutate(exp_per_100000trav = import_mean / (travelers/100000), +# exp_per_100000trav_ll = import_ll / (travelers/100000), +# exp_per_100000trav_ul = import_ul / (travelers/100000)) + +write_csv(import_results_sourcetime, file.path("results",project_name,sprintf("import_results_sourcetime_v%s.csv", version))) +#import_results_sourcetime <- read_csv(paste0("Results/",results_folder,"/import_results_sourcetime_summary.csv")) %>% as.data.frame() + + + + + +# ~ import_results_sourcetime_cum -------------------------------------------------------- +# Cumulate importations into source + + +# Get RR mean and CIs +import_results_sourcetime_cum <- import_data_long %>% group_by(source, t, sim) %>% + mutate(imports_cum = sum(imports_cum, na.rm = TRUE)) %>% ungroup() %>% group_by(source, t) %>% + summarize( + cum_import_mean=mean(imports_cum, na.rm=T), + cum_import_sd=sd(imports_cum, na.rm=T), + cum_import_ll=quantile(imports_cum, probs=.025, na.rm=T), + cum_import_ul=quantile(imports_cum, probs=.975, na.rm=T), + cum_import_median=median(imports_cum, na.rm=T), + cum_import_min=min(imports_cum, na.rm=T), + cum_import_max=max(imports_cum, na.rm=T), + cum_import_25pt=quantile(imports_cum, probs=.25, na.rm=T), + cum_import_75pt=quantile(imports_cum, probs=.75, na.rm=T), + ) + +# Get the probability of >0 imports +prob_any_import <- import_data_long %>% group_by(source, t, sim) %>% + summarise(imports_cum = sum(imports_cum)) %>% group_by(source, t) %>% + summarize(n_import = sum(imports_cum>0)) %>% mutate(prob_import=n_import/(n_sim)) + +# Add Probability +import_results_sourcetime_cum$cum_prob_any_import <- prob_any_import$prob_import +import_results_sourcetime_cum <- import_results_sourcetime_cum %>% dplyr::select(1,2,cum_prob_any_import, everything()) +rm(prob_any_import) + +write_csv(import_results_sourcetime_cum, file.path("results",project_name,sprintf("import_results_sourcetime_cumulative_v%s.csv", version))) + + + + + + + + + + + + + + + + + +# REMOVE EVERYTHING FROM THE CURRENT WORKSPACE +#rm(list = ls()); gc() + + diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/importation_analysis_detection.R b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/importation_analysis_detection.R new file mode 100644 index 000000000..d625f441e --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/importation_analysis_detection.R @@ -0,0 +1,559 @@ +##::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: +##' nCoV Importation Analyses -- Risk Analyses #### +##' +##::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: + +if (!exists("version") | is.list(version)){ version <- "1" } +if (!exists("batch") | is.list(batch)){ batch <- "1st" } +if (!exists("project_name")){ project_name <- "shenzhen_import" } +if (!exists("start_date")){ start_date <- "2020-01-21" } +if (!exists("na_to_zero")){ na_to_zero <- TRUE } + +dir.create(file.path("results", project_name), recursive = TRUE) +import_detect_file <- file.path("output",project_name, sprintf("covid_importation_detect_%s_batch_v%s.RData", batch, version)) + +# +# print(project_name) +# print(version) +# print(batch) + +# SETUP ------------------------------------------------------------------- + +options(scipen=999) +if(!require('tidyverse')) install.packages('tidyverse'); library(tidyverse) +if(!require('reshape2')) install.packages('reshape2'); library(reshape2) +if(!require('abind')) install.packages('abind'); library(abind) + + + +# IMPORT DATA ------------------------------------------------------------- + +load(import_detect_file) # load importation_sim +Sys.sleep(5) # pause to let the computer catch up + + +sources_ <- dimnames(importation_detect)[[1]] +dests_ <- dimnames(importation_detect)[[2]] +t_ <- dimnames(importation_detect)[[3]] +sims_ <- dimnames(importation_detect)[[4]] + + +# Check range of sims +range(sims_) +tmp <- apply(importation_detect, c(3,4), sum, na.rm=TRUE) +rowMeans(tmp) + + + + +# ~ Convert to Long Form -------------------------------------------------- + +# Convert raw data array into long format +import_data_long <- arrayhelpers::array2df(importation_detect) +Sys.sleep(5) # pause to let the computer catch up + +colnames(import_data_long) <- c("imports","source","destination","t","sim") +import_data_long <- import_data_long %>% mutate(t = lubridate::ymd(t)) %>% as.data.frame() + +# Remove time prior to start_date +min((import_data_long %>% filter(!is.na(imports)))$t) +import_data_long <- import_data_long %>% filter(t>=start_date) + + +#write_csv(import_data_long, paste0("data/est_imports_long_ver",version,".csv")) +import_data_long$imports <- as.integer(as.character(import_data_long$imports)) +dims_import_data <- dim(importation_detect) +n_sim <- dims_import_data[4] +format(object.size(import_data_long), "Mb") + +# # Add reported +# import_data_long <- left_join(import_data_long, imports_reported_bydestination) + +# Make NAs into 0 if desired +if (na_to_zero){ + import_data_long <- import_data_long %>% mutate(imports = ifelse(is.na(imports), 0, imports)) +} + + +# ~ Summarize imporations in long data ------------------------------------ + +# Get mean and medians for ea/ch sim +import_data_long <- import_data_long %>% group_by(sim) %>% + mutate(mean_sim=mean(imports, na.rm=T), + median_sim=median(imports, na.rm=T)) %>% ungroup() + +# Get RR compared to the mean and median +import_data_long$RR.vs.sim.mean <- import_data_long$imports / import_data_long$mean_sim +import_data_long$RR.vs.sim.median <- import_data_long$imports / import_data_long$median_sim + +# Get RR compared to the destination mean +import_data_long <- import_data_long %>% group_by(destination, sim) %>% + mutate(destination_sim_mean = mean(imports, na.rm=TRUE)) %>% ungroup() +import_data_long$RR.vs.destination.mean <- import_data_long$imports / import_data_long$destination_sim_mean +import_data_long$RR.vs.destination.mean[import_data_long$destination_sim_mean==0] <- 1 + + +# Save it +dir.create(file.path("results", project_name), recursive = TRUE) +write_csv(import_data_long, file.path("results", project_name, sprintf("import_data_detected_long_v%s.csv", version))) + + +# # Load it +#import_data_long <- read_csv(file.path("results", project_name, sprintf("import_data_detected_long_v%s.csv", version))) %>% as.data.frame() + +cols.numeric <- c("mean_sim", "RR.vs.sim.mean", "RR.vs.sim.median", "destination_sim_mean", "RR.vs.destination.mean") +cols.integer <- c("imports", "sim", "median_sim") +#"rep_imports", "rep_imports_orig", "missing_data_count", "available_data_count","mean_travel", "mean_population", +import_data_long[cols.numeric] <- sapply(import_data_long[cols.numeric], as.numeric) +import_data_long[cols.integer] <- sapply(import_data_long[cols.integer], as.integer) +sapply(import_data_long, class) + +n_sim <- max(import_data_long$sim) + + + + +# SUMMARIZE RESULTS ------------------------------------------------------- + + +# ~ import_results_dest -------------------------------------------------------- + +# Get RR mean and CIs +import_results_dest <- import_data_long %>% group_by(destination, sim) %>% + mutate(imports = sum(imports, na.rm = TRUE)) %>% ungroup() %>% group_by(destination) %>% + summarize( + import_mean=mean(imports, na.rm=T), + import_sd=sd(imports, na.rm=T), + import_ll=quantile(imports, probs=.025, na.rm=T), + import_ul=quantile(imports, probs=.975, na.rm=T), + import_median=median(imports, na.rm=T), + import_min=min(imports, na.rm=T), + import_max=max(imports, na.rm=T), + import_25pt=quantile(imports, probs=.25, na.rm=T), + import_75pt=quantile(imports, probs=.75, na.rm=T), + + RR_mean=mean(RR.vs.sim.mean, na.rm=T), + RR_ll=quantile(RR.vs.sim.mean, probs=.025, na.rm=T), + RR_ul=quantile(RR.vs.sim.mean, probs=.975, na.rm=T), + RR_sd=sd(RR.vs.sim.mean, na.rm=T), + RR_median=median(RR.vs.sim.mean, na.rm=T), + + RR_destination_mean=mean(RR.vs.destination.mean, na.rm=T), + RR_destination_ll=quantile(RR.vs.destination.mean, probs=.025, na.rm=T), + RR_destination_ul=quantile(RR.vs.destination.mean, probs=.975, na.rm=T), + RR_destination_sd=sd(RR.vs.destination.mean, na.rm=T), + RR_destination_median=median(RR.vs.destination.mean, na.rm=T)#, + #rep_imports = mean(rep_imports, na.rm = T) + ) + +write_csv(import_results_dest, file.path("results",project_name,sprintf("import_results_dest_detect_v%s.csv", version))) + + + +# ~ import_results_desttime -------------------------------------------------------- + +# Get RR mean and CIs +import_results_desttime <- import_data_long %>% group_by(destination, t, sim) %>% + mutate(imports = sum(imports, na.rm = TRUE)) %>% ungroup() %>% group_by(destination, t) %>% + summarize( + import_mean=mean(imports, na.rm=T), + import_sd=sd(imports, na.rm=T), + import_ll=quantile(imports, probs=.025, na.rm=T), + import_ul=quantile(imports, probs=.975, na.rm=T), + import_median=median(imports, na.rm=T), + import_min=min(imports, na.rm=T), + import_max=max(imports, na.rm=T), + import_25pt=quantile(imports, probs=.25, na.rm=T), + import_75pt=quantile(imports, probs=.75, na.rm=T), + + RR_mean=mean(RR.vs.sim.mean, na.rm=T), + RR_ll=quantile(RR.vs.sim.mean, probs=.025, na.rm=T), + RR_ul=quantile(RR.vs.sim.mean, probs=.975, na.rm=T), + RR_sd=sd(RR.vs.sim.mean, na.rm=T), + RR_median=median(RR.vs.sim.mean, na.rm=T), + + RR_destination_mean=mean(RR.vs.destination.mean, na.rm=T), + RR_destination_ll=quantile(RR.vs.destination.mean, probs=.025, na.rm=T), + RR_destination_ul=quantile(RR.vs.destination.mean, probs=.975, na.rm=T), + RR_destination_sd=sd(RR.vs.destination.mean, na.rm=T), + RR_destination_median=median(RR.vs.destination.mean, na.rm=T)#, + #rep_imports = mean(rep_imports, na.rm = T) + ) + +# Get the probability of >0 imports +prob_any_import <- import_data_long %>% group_by(destination, t, sim) %>% + summarise(imports = sum(imports)) %>% group_by(destination, t) %>% + summarize(n_import = sum(imports>0)) %>% mutate(prob_import=n_import/(n_sim)) + +# Add Probability +import_results_desttime$prob_any_import <- prob_any_import$prob_import +import_results_desttime <- import_results_desttime %>% dplyr::select(1,2,prob_any_import, everything()) +rm(prob_any_import) + +write_csv(import_results_desttime, file.path("results",project_name,sprintf("import_results_desttime_detect_v%s.csv", version))) + + +# # ADD REPORTED TO ESTIMATED +# #source("Source/clean_reported_importations.R") +# reported_file_path <- paste0("Results/",results_folder,"/import_reported_long_matched.csv") +# +# if (file.exists(reported_file_path)){ +# # load reported imports summed by destination +# imports_reported_long <- read_csv(reported_file_path) %>% as.data.frame() %>% +# rename(rep_imports=imports) +# +# # merge with import_results +# import_results <- left_join(import_results, imports_reported_long) +# import_data_long <- left_join(import_data_long, imports_reported_long) +# +# } else { +# import_results$rep_imports <- NA +# import_data_long$rep_imports <- NA +# } + + + + + + + +# ~ import_results_desttime_cum -------------------------------------------------------- +# Cumulate importations into destination + +# Add up importations by location by simulation +import_data_long <- import_data_long %>% group_by(sim, source, destination) %>% + mutate(imports_cum = cumsum(imports)) %>% ungroup() + +# Get RR mean and CIs +import_results_desttime_cum <- import_data_long %>% group_by(destination, t, sim) %>% + mutate(imports_cum = sum(imports_cum, na.rm = TRUE)) %>% ungroup() %>% group_by(destination, t) %>% + summarize( + cum_import_mean=mean(imports_cum, na.rm=T), + cum_import_sd=sd(imports_cum, na.rm=T), + cum_import_ll=quantile(imports_cum, probs=.025, na.rm=T), + cum_import_ul=quantile(imports_cum, probs=.975, na.rm=T), + cum_import_median=median(imports_cum, na.rm=T), + cum_import_min=min(imports_cum, na.rm=T), + cum_import_max=max(imports_cum, na.rm=T), + cum_import_25pt=quantile(imports_cum, probs=.25, na.rm=T), + cum_import_75pt=quantile(imports_cum, probs=.75, na.rm=T), + ) + +# Get the probability of >0 imports +prob_any_import <- import_data_long %>% group_by(destination, t, sim) %>% + summarise(imports_cum = sum(imports_cum)) %>% group_by(destination, t) %>% + summarize(n_import = sum(imports_cum>0)) %>% mutate(prob_import=n_import/(n_sim)) + +# Add Probability +import_results_desttime_cum$cum_prob_any_import <- prob_any_import$prob_import +import_results_desttime_cum <- import_results_desttime_cum %>% dplyr::select(1,2,cum_prob_any_import, everything()) +rm(prob_any_import) + +write_csv(import_results_desttime_cum, file.path("results",project_name,sprintf("import_results_desttime_cumulative_detect_v%s.csv", version))) + + + + + + +# ~ import_results_desttime_overall -------------------------------------------------------- + + +# Get RR mean and CIs +import_results_desttime_overall <- import_data_long %>% group_by(t, sim) %>% + mutate(imports = sum(imports, na.rm = TRUE)) %>% ungroup() %>% group_by(t) %>% + summarize( + import_mean=mean(imports, na.rm=T), + import_sd=sd(imports, na.rm=T), + import_ll=quantile(imports, probs=.025, na.rm=T), + import_ul=quantile(imports, probs=.975, na.rm=T), + import_median=median(imports, na.rm=T), + import_min=min(imports, na.rm=T), + import_max=max(imports, na.rm=T), + import_25pt=quantile(imports, probs=.25, na.rm=T), + import_75pt=quantile(imports, probs=.75, na.rm=T), + + RR_mean=mean(RR.vs.sim.mean, na.rm=T), + RR_ll=quantile(RR.vs.sim.mean, probs=.025, na.rm=T), + RR_ul=quantile(RR.vs.sim.mean, probs=.975, na.rm=T), + RR_sd=sd(RR.vs.sim.mean, na.rm=T), + RR_median=median(RR.vs.sim.mean, na.rm=T), + + RR_destination_mean=mean(RR.vs.destination.mean, na.rm=T), + RR_destination_ll=quantile(RR.vs.destination.mean, probs=.025, na.rm=T), + RR_destination_ul=quantile(RR.vs.destination.mean, probs=.975, na.rm=T), + RR_destination_sd=sd(RR.vs.destination.mean, na.rm=T), + RR_destination_median=median(RR.vs.destination.mean, na.rm=T)#, + #rep_imports = mean(rep_imports, na.rm = T) + ) + +# Get the probability of >0 imports +prob_any_import <- import_data_long %>% group_by(t, sim) %>% + summarise(imports = sum(imports)) %>% group_by(t) %>% + summarize(n_import = sum(imports>0)) %>% mutate(prob_import=n_import/(n_sim)) + +# Add Probability +import_results_desttime_overall$prob_any_import <- prob_any_import$prob_import +import_results_desttime_overall <- import_results_desttime_overall %>% dplyr::select(1,2,prob_any_import, everything()) +rm(prob_any_import) + +write_csv(import_results_desttime_overall, file.path("results",project_name,sprintf("import_results_desttime_overall_detect_v%s.csv", version))) + + +# # ADD REPORTED TO ESTIMATED +# #source("Source/clean_reported_importations.R") +# reported_file_path <- paste0("Results/",results_folder,"/import_reported_long_matched.csv") +# +# if (file.exists(reported_file_path)){ +# # load reported imports summed by destination +# imports_reported_long <- read_csv(reported_file_path) %>% as.data.frame() %>% +# rename(rep_imports=imports) +# +# # merge with import_results +# import_results <- left_join(import_results, imports_reported_long) +# import_data_long <- left_join(import_data_long, imports_reported_long) +# +# } else { +# import_results$rep_imports <- NA +# import_data_long$rep_imports <- NA +# } + + + + + + + +# ~ import_results_desttime_overall_cum -------------------------------------------------------- +# Cumulate importations into overall destination (i.e., a state) + +# Add up importations by location by simulation +import_data_overall_long <- import_data_long %>% group_by(sim, source) %>% + mutate(imports_cum = cumsum(imports)) %>% ungroup() + +# Get RR mean and CIs +import_results_desttime_overall_cum <- import_data_overall_long %>% group_by(t, sim) %>% + mutate(imports_cum = sum(imports_cum, na.rm = TRUE)) %>% ungroup() %>% group_by(t) %>% + summarize( + cum_import_mean=mean(imports_cum, na.rm=T), + cum_import_sd=sd(imports_cum, na.rm=T), + cum_import_ll=quantile(imports_cum, probs=.025, na.rm=T), + cum_import_ul=quantile(imports_cum, probs=.975, na.rm=T), + cum_import_median=median(imports_cum, na.rm=T), + cum_import_min=min(imports_cum, na.rm=T), + cum_import_max=max(imports_cum, na.rm=T), + cum_import_25pt=quantile(imports_cum, probs=.25, na.rm=T), + cum_import_75pt=quantile(imports_cum, probs=.75, na.rm=T), + ) + +# Get the probability of >0 imports +prob_any_import <- import_data_overall_long %>% group_by(t, sim) %>% + summarise(imports_cum = sum(imports_cum)) %>% group_by(t) %>% + summarize(n_import = sum(imports_cum>0)) %>% mutate(prob_import=n_import/(n_sim)) + +# Add Probability +import_results_desttime_overall_cum$cum_prob_any_import <- prob_any_import$prob_import +import_results_desttime_overall_cum <- import_results_desttime_overall_cum %>% dplyr::select(1,2,cum_prob_any_import, everything()) +rm(prob_any_import) + +write_csv(import_results_desttime_overall_cum, file.path("results",project_name,sprintf("import_results_desttime_overall_cumulative_detect_v%s.csv", version))) + + + + + + + + + + + + + + + + + +# ~ import_results_sources --------------------------------------------------- +# -- SUMMARIZE IMPORTATION FROM PROVINCES - FROM LONG DATA + +head(import_data_long) + +# long source year +import_data_sourcesday_long <- import_data_long %>% + group_by(source, t, sim) %>% + summarize(imports=sum(imports, na.rm=T)) +head(import_data_sourcesday_long) + +# long source +import_data_sources_long <- import_data_long %>% group_by(source, sim) %>% + summarize(imports=sum(imports, na.rm=T)) +head(import_data_sources_long) + +# Get mean and medians for each sim +import_data_sources_long <- import_data_sources_long %>% group_by(sim) %>% + mutate(mean_sim=mean(imports, na.rm=T), median_sim=median(imports, na.rm=T)) %>% ungroup() + +# Get the probability of >0 imports +prob_any_import <- import_data_sources_long %>% group_by(source) %>% + summarize(n_anyimport=sum(imports>0)) %>% mutate(prob_import=n_anyimport/n_sim) + +# Get RR compared to the mean +import_data_sources_long <- import_data_sources_long %>% mutate(RR.vs.sim.mean = imports / mean_sim) + +# Get RR mean and CIs +import_results_sources <- import_data_sources_long %>% group_by(source) %>% + summarize( + import_mean=mean(imports, na.rm=T), + import_sd=sd(imports, na.rm=T), + import_ll=quantile(imports, probs=.025, na.rm=T), + import_ul=quantile(imports, probs=.975, na.rm=T), + import_median=median(imports, na.rm=T), + import_min=min(imports, na.rm=T), + import_max=max(imports, na.rm=T), + + RR_mean=mean(RR.vs.sim.mean, na.rm=T), + RR_ll=quantile(RR.vs.sim.mean, probs=.025, na.rm=T), + RR_ul=quantile(RR.vs.sim.mean, probs=.975, na.rm=T), + RR_sd=sd(RR.vs.sim.mean, na.rm=T), + RR_median=median(RR.vs.sim.mean, na.rm=T)) %>% as.data.frame() + +import_results_sources <- left_join(import_results_sources, prob_any_import %>% select(-n_anyimport), by=c("source"="source")) +head(import_results_sources) +rm(prob_any_import) + +write_csv(import_results_sources, file.path("results",project_name,sprintf("import_results_sources_detect_v%s.csv", version))) + + + + + +# ~ import_results_sourcetime --------------------------------------- + +# SUMMARIZE IMPORTATIONS BY STATE AND YEAR + +# Sum up by t +import_sourcetime_long <- import_data_long %>% as.data.frame() %>% + group_by(source, t, sim) %>% + summarise(imports=sum(imports)) +import_sourcetime_long <- import_sourcetime_long %>% + group_by(sim) %>% mutate(mean_sim=mean(imports, na.rm=T)) %>% ungroup() %>% + mutate(RR.vs.sim.mean=imports/mean_sim) + +# Get RR mean and CIs +import_results_sourcetime <- import_sourcetime_long %>% group_by(source, t) %>% + summarize( + import_mean=mean(imports, na.rm=T), + import_sd=sd(imports, na.rm=T), + import_ll=quantile(imports, probs=.025, na.rm=T), + import_ul=quantile(imports, probs=.975, na.rm=T), + import_ll_pois = NA, + import_ul_pois = NA, + import_median=median(imports, na.rm=T), + import_min=min(imports, na.rm=T), + import_max=max(imports, na.rm=T), + + #rep_import=mean(rep_imports, na.rm=T), + + RR_mean=mean(RR.vs.sim.mean, na.rm=T), + RR_ll=quantile(RR.vs.sim.mean, probs=.025, na.rm=T), + RR_ul=quantile(RR.vs.sim.mean, probs=.975, na.rm=T), + RR_sd=sd(RR.vs.sim.mean, na.rm=T), + RR_median=median(RR.vs.sim.mean, na.rm=T) + ) + +import_results_sourcetime <- import_results_sourcetime %>% + mutate(import_ll_pois = import_mean - 1.96 * sqrt(import_mean/10000), + import_ul_pois = import_mean + 1.96 * sqrt(import_mean/10000)) + + +# Get the probability of >0 imports +prob_any_import <- import_data_long %>% group_by(source, t, sim) %>% + summarise(imports = sum(imports)) %>% group_by(source, t) %>% + summarize(n_import = sum(imports>0)) %>% mutate(prob_import=n_import/(n_sim)) + + +prob_for_cis <- prob_any_import %>% filter(!is.na(n_import)) %>% + mutate(n = n_sim) +cis <- Hmisc::binconf(prob_for_cis$n_import, prob_for_cis$n, + alpha=0.05, + method=c("wilson"), + include.x=FALSE, include.n=FALSE, return.df=TRUE) +prob_for_cis <- data.frame(prob_for_cis, cis) +prob_for_cis <- prob_for_cis %>% mutate(Lower=round(Lower, 3), Upper=round(Upper, 3)) +prob_any_import <- left_join(prob_any_import, prob_for_cis %>% + select(source, t, prob_ll=Lower, prob_ul=Upper)) +rm(prob_for_cis) + +t_meanprob <- prob_any_import %>% group_by(source) %>% + summarise(mean = round(mean(prob_import, na.rm=TRUE), 3), + mean_ll = round(mean(prob_ll, na.rm=TRUE), 3), + mean_ul = round(mean(prob_ul, na.rm=TRUE), 3), + probyr_sd = sd(prob_import, na.rm=TRUE), + n_samp = sum(!is.na(prob_import))) %>% + mutate(probyr_ll = round(mean - 1.96*probyr_sd/sqrt(n_samp), 3), + probyr_ul = round(mean + 1.96*probyr_sd/sqrt(n_samp), 3)) + + +import_results_sourcetime$prob_any_import <- prob_any_import$prob_import +import_results_sourcetime <- import_results_sourcetime %>% dplyr::select(1,2,prob_any_import, everything()) +rm(prob_any_import) + +import_results_sourcetime <- import_results_sourcetime %>% + dplyr::select(source, t, everything()) +# +# # Add travel and population adjustment +# Travelers.source.t <- read_csv("Data/travel_t_sources.csv") +# import_results_sourcetime <- add_t_pop_and_travel(import_results_sourcetime) +# import_results_sourcetime <- import_results_sourcetime %>% +# mutate(exp_per_100000trav = import_mean / (travelers/100000), +# exp_per_100000trav_ll = import_ll / (travelers/100000), +# exp_per_100000trav_ul = import_ul / (travelers/100000)) + +write_csv(import_results_sourcetime, file.path("results",project_name,sprintf("import_results_sourcetime_detect_v%s.csv", version))) +#import_results_sourcetime <- read_csv(paste0("Results/",results_folder,"/import_results_sourcetime_summary.csv")) %>% as.data.frame() + + + + + +# ~ import_results_sourcetime_cum -------------------------------------------------------- +# Cumulate importations into source + + +# Get RR mean and CIs +import_results_sourcetime_cum <- import_data_long %>% group_by(source, t, sim) %>% + mutate(imports_cum = sum(imports_cum, na.rm = TRUE)) %>% ungroup() %>% group_by(source, t) %>% + summarize( + cum_import_mean=mean(imports_cum, na.rm=T), + cum_import_sd=sd(imports_cum, na.rm=T), + cum_import_ll=quantile(imports_cum, probs=.025, na.rm=T), + cum_import_ul=quantile(imports_cum, probs=.975, na.rm=T), + cum_import_median=median(imports_cum, na.rm=T), + cum_import_min=min(imports_cum, na.rm=T), + cum_import_max=max(imports_cum, na.rm=T), + cum_import_25pt=quantile(imports_cum, probs=.25, na.rm=T), + cum_import_75pt=quantile(imports_cum, probs=.75, na.rm=T), + ) + +# Get the probability of >0 imports +prob_any_import <- import_data_long %>% group_by(source, t, sim) %>% + summarise(imports_cum = sum(imports_cum)) %>% group_by(source, t) %>% + summarize(n_import = sum(imports_cum>0)) %>% mutate(prob_import=n_import/(n_sim)) + +# Add Probability +import_results_sourcetime_cum$cum_prob_any_import <- prob_any_import$prob_import +import_results_sourcetime_cum <- import_results_sourcetime_cum %>% dplyr::select(1,2,cum_prob_any_import, everything()) +rm(prob_any_import) + +write_csv(import_results_sourcetime_cum, file.path("results",project_name,sprintf("import_results_sourcetime_cumulative_detect_v%s.csv", version))) + + + + + + +# REMOVE EVERYTHING FROM THE CURRENT WORKSPACE +#rm(list = ls()); gc() + + diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/make-other-data.R b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/make-other-data.R new file mode 100644 index 000000000..499ba0c03 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/make-other-data.R @@ -0,0 +1,361 @@ + + +library(tidyverse) + + +## make underreporting data +source("https://raw.githubusercontent.com/salauer/CFR_calculation/master/global_estimates/scripts/main_script_clean.R") +underreporting <- reportDataFinal; rm(reportDataFinal) +#save(underreporting, file="data/underreporting.rda") +usethis::use_data(underreporting, overwrite = TRUE) + + + + + +# Travel Restrictions Data ------------------------------------------------ + + +# TSA travel reductions +# Source: https://www.tsa.gov/coronavirus/passenger-throughput +tsa <- readr::read_csv("data/tsa_throughput.csv") %>% + mutate(date = lubridate::as_date(as.Date(date, "%m/%d/%Y")), + p_travel = round(tsa_2020 / tsa_2019, 3)) %>% + arrange(date) +ggplot2::ggplot(tsa, aes(date, p_travel)) + geom_line() + + +# Scrape this table from web +#--- TO DO ------ + + + + + + + +hubei_shutdown <- lubridate::as_date(c("2020-01-24", "2020-09-01")) +data("pop_data", package = "covidImportation") +# this requires the pop_data to have all of the correct source locations + +## make travel_restrictions data +travel_restrictions <- + + # Reduce travel from all Chinese sources to 10% + tibble(loc=unique((pop_data %>% filter(country=="CHN"))$source), + min=hubei_shutdown[1], + max=hubei_shutdown[2], + p_travel=.1) %>% filter(loc!="Hubei") %>% + + # Reduce travel from Hubei to 0 + bind_rows(tibble(loc="Hubei", + min=hubei_shutdown[1], + max=hubei_shutdown[2], + p_travel=0)) %>% + + # Reduce travel from all US sources based on TSA numbers + bind_rows( expand_grid(loc=unique((pop_data %>% filter(country=="USA"))$source), + min=tsa$date) %>% + left_join( + tibble(min=tsa$date, + max=tsa$date, + p_travel=tsa$p_travel), by="min")) %>% + + # Reduce travel from all US sources to 10% + bind_rows(tibble(loc=unique((pop_data %>% filter(country=="USA"))$source), + min=lubridate::as_date(max(tsa$date)+1), + max=lubridate::as_date("2020-09-01"), + p_travel=tsa$p_travel[nrow(tsa)])) %>% + + # # Reduce travel from all US sources to 60% + # bind_rows(data.frame(loc=unique((pop_data %>% filter(country=="USA"))$source), + # min="2020-03-02", + # max="2020-03-08", + # p_travel=.6)) %>% + # + # # Reduce travel from all US sources to 30% + # bind_rows(data.frame(loc=unique((pop_data %>% filter(country=="USA"))$source), + # min="2020-03-09", + # max="2020-03-16", + # p_travel=.3)) %>% + # + # # Reduce travel from all US sources to 10% + # bind_rows(data.frame(loc=unique((pop_data %>% filter(country=="USA"))$source), + # min="2020-03-17", + # max="2020-06-16", + # p_travel=.1)) %>% + + # Reduce travel from non-China to US to 30% + bind_rows(data.frame(loc=unique((pop_data %>% filter(country!="CHN" & country!="USA"))$source), + min=lubridate::as_date("2020-03-02"), + max=lubridate::as_date("2020-03-08"), + p_travel=.3)) %>% + + # Reduce travel from all other sources to 10% + bind_rows(data.frame(loc=unique((pop_data %>% filter(country!="CHN" & country!="USA"))$source), + min=lubridate::as_date("2020-03-09"), + max=lubridate::as_date("2020-03-16"), + p_travel=.1)) %>% + + # Reduce travel from all US sources to 4% (matching overall us travel) + bind_rows(data.frame(loc=unique((pop_data %>% filter(country!="CHN" & country!="USA"))$source), + min=lubridate::as_date("2020-03-17"), + max=lubridate::as_date("2020-09-01"), + p_travel=.04)) + +usethis::use_data(travel_restrictions, overwrite = TRUE) + + + + +# Airport Attributions - China ------------------------------------------ + +## make airport_attributions data +airport_attribution <- read_csv("data-raw/airport_attribution.csv") %>% + mutate(Province = gsub(" Province", "", Province)) %>% + mutate(Province = gsub(" province", "", Province)) %>% + mutate(Province = gsub(" Special Administrative Region", "", Province)) %>% + mutate(Province = gsub(" Autonomous Region", "", Province)) %>% + mutate(Province = gsub(" Municipality", "", Province)) %>% + mutate(Province = ifelse(grepl("Xinjiang", Province), "Xinjiang", Province)) %>% + mutate(Province = ifelse(grepl("Guangxi", Province), "Guangxi", Province)) %>% + mutate(Province = ifelse(grepl("Ningxia", Province), "Ningxia", Province)) %>% + mutate(Province = ifelse(grepl("Inner Mongolia", Province), "Nei Mongol", Province)) %>% + mutate(Province = ifelse(grepl("Macao", Province), "Macau", Province)) %>% + # Attribute travel according to normalizaed attribution score, + # weighted by population + left_join(read_csv("data-raw/pop_data.csv") %>% dplyr::select(source, pop), + by=c("Province"="source")) %>% + group_by(airport_iata) %>% + mutate(attribution = attribution*pop / sum(attribution*pop)) %>% + ungroup() +#save(airport_attribution, file="data/airport_attribution.rda") +usethis::use_data(airport_attribution, overwrite = TRUE) + + + + +# JHUCSSE Case Data ------------------------------------------------------ + +## Generate combined JHU CSSE data for packages (so users dont have to create the full data) +update_jhucsse_package_data <- function(){ + + # # pull the data from github + # pull_JHUCSSE_github_data(case_data_dir = "data/case_data", repull_all=TRUE) + # # read and merge data + # jhucsse_case_data <- read_JHUCSSE_cases(last_date=Sys.Date(), + # append_wiki=TRUE, + # case_data_dir = "data/case_data", + # print_file_path=FALSE) + # New method + jhucsse_case_data <- update_JHUCSSE_github_data(case_data_dir = "data/case_data", + last_date=Sys.time(), + check_saved_data=FALSE, + save_data=TRUE) + + #save(jhucsse_case_data, file="data/jhucsse_case_data.rda") + usethis::use_data(jhucsse_case_data, overwrite = TRUE) +} +update_jhucsse_package_data() + + + + +# Wikipedia Case Data ----------------------------------------------------- + +wikipedia_cases <- readr::read_csv("data-raw/WikipediaWuhanPre1-20-2020.csv", + col_types=readr::cols(Update = readr::col_datetime("%m/%d/%Y"))) +usethis::use_data(wikipedia_cases, overwrite = TRUE) + + + + + +# OAG Travel Data --------------------------------------------------------- + +##' Get OAG travel data +##' +##' Get subsetted and cleaned OAG data for a specific destination +##' +##' @param destination destination of interest; can be a vector. +##' @param destination_type options: "airport", "city", "state", "country" +##' @param dest_0 default=NULL; change to specify higher level destination (i.e. dest_0="USA") +##' @param dest_0_type default=NULL; must specify if specifying a `dest_0` option. +##' @param dest_aggr_level level to which travel will be aggregated for destination. Includes "airport", "city", "state", "country", "metro" (only available for CA currently) + +make_aggr_oag_travel <- function(){ + # Read full data + # these data are clean in `oag_data_cleaning.R` + data_travel_all <- read_csv(file.path("data_other", "complete_OAG_data.csv"), na=c(""," ", "NA"), + col_types = list( + `Dep Airport Code` = col_character(), + `Dep City Name` = col_character(), + `Dep State Code` = col_character(), + `Dep Country Code` = col_character(), + `Arr Airport Code` = col_character(), + `Arr City Name` = col_character(), + `Arr State Code` = col_character(), + `Arr Country Code` = col_character(), + `Total Est. Pax` = col_double(), + `Time Series` = col_double())) + + + # Re-assign city, state, country from airport codes (cuz OAG sucks and these data have tons of errors) + data(airport_data) + airport_data <- airport_data %>% + filter(type!="closed") %>% + mutate(iso_country = ifelse(iso_country=="XK", "KOS", + countrycode::countrycode(iso_country, + origin = "iso2c", + destination = "iso3c"))) %>% + mutate(state = substr(iso_region, 4,6)) %>% + dplyr::select(-c(type, name, continent, gps_code, local_code, coordinates, elevation_ft, ident, iso_region)) %>% + filter(!is.na(iata_code)) + airport_data <- airport_data %>% distinct() %>% + filter(!duplicated(iata_code)) + + + ## Fix arrival codes + data_travel_all <- left_join(data_travel_all, + airport_data, by = c("Arr Airport Code"="iata_code")) + data_travel_all <- data_travel_all %>% + mutate(`Arr City Name` = ifelse(!is.na(municipality), municipality, `Arr City Name`), + `Arr State Code` = ifelse(!is.na(state), state, `Arr State Code`), + `Arr Country Code`= ifelse(!is.na(iso_country), iso_country, `Arr Country Code`)) %>% + dplyr::select(-c(municipality, state, iso_country)) + + ## Fix Departure codes + data_travel_all <- left_join(data_travel_all, + airport_data, by = c("Dep Airport Code"="iata_code")) + data_travel_all <- data_travel_all %>% + mutate(`Dep City Name` = ifelse(!is.na(municipality), municipality, `Dep City Name`), + `Dep State Code` = ifelse(!is.na(state), state, `Dep State Code`), + `Dep Country Code`= ifelse(!is.na(iso_country), iso_country, `Dep Country Code`)) %>% + dplyr::select(-c(municipality, state, iso_country)) + + + + # data_dups <- data_travel_all %>% group_by(`Arr Airport Code`) %>% + # summarise(unique_cities = length(unique(`Arr City Name`))) + # data_dups <- data_travel_all %>% group_by(`Dep Airport Code`) %>% + # summarise(unique_cities = length(unique(`Dep City Name`))) + # View(data_travel_all %>% filter(`Arr Airport Code`== "AUS")) + + + data('pop_data', package = 'covidImportation') + + # Give Chinese airports the provinces + data(airport_attribution) + + # merge with travel data + dest_data <- left_join(data_travel_all, + airport_attribution, + by=c("Dep Airport Code"="airport_iata")) + rm(data_travel_all) + gc() + # Adjust travel volume based on attribution + dest_data <- dest_data %>% + replace_na(list(attribution=1)) %>% + mutate(`Total Est. Pax` = `Total Est. Pax` * attribution) %>% + dplyr::select(-attribution, pop) + + + # # Get us State codes for departures + # airport_data_us <- airport_data %>% + # dplyr::filter(iso_country=="USA") + # + dest_data <- dest_data %>% + rename(dep_airport = `Dep Airport Code`, + dep_state = `Dep State Code`, + dep_country = `Dep Country Code`, + dep_city = `Dep City Name`, + arr_airport = `Arr Airport Code`, + arr_city = `Arr City Name`, + arr_state = `Arr State Code`, + arr_country = `Arr Country Code`, + travelers = `Total Est. Pax`, + yr_month = `Time Series`, + dep_province = Province) + + + # make aggregate source variable, and get mean across 3 years + dest_data <- dest_data %>% + mutate(dep_loc_aggr = ifelse(dep_country=="CHN", dep_province, ifelse(dep_country=="USA", dep_state, dep_country)), + t_year = substr(yr_month, 1,4), + t_month = as.character(substr(yr_month, 5,6))) # Get year and month variables + + + # aggregation levels for destination + aggr_levels <- factor(c("airport", "city", "metro", "state", "country"), levels=c("airport", "city", "metro", "state", "country"), ordered = TRUE) + loc_vars_aggr <- c("arr_airport", "arr_city","arr_metro", "arr_state", "arr_country")[aggr_levels>="airport"] + loc_vars_aggr <- loc_vars_aggr[loc_vars_aggr %in% colnames(dest_data)] + other_vars_aggr <- c("yr_month", "t_year", "t_month", "dep_loc_aggr", "dep_country") + + dest_data_aggr <- dest_data %>% group_by(.dots = c(other_vars_aggr, loc_vars_aggr)) %>% + summarise(travelers = sum(travelers, na.rm = TRUE)) + rm(dest_data) + gc() + + # Get Monthly means across the 3 year (using geometric means) + other_vars_aggr <- c("t_month", "dep_loc_aggr", "dep_country") + dest_data_aggr <- dest_data_aggr %>% + group_by(.dots = c(other_vars_aggr, loc_vars_aggr)) %>% + summarise(travelers_sd = sd(travelers, na.rm = TRUE), + travelers_mean = exp(mean(log(travelers+1), na.rm = TRUE))-1) + + dest_data_aggr <- dest_data_aggr %>% mutate(travelers_sd = ifelse(is.nan(travelers_sd), travelers_mean/1.96, travelers_sd)) # for those with only 1 value for travel, just use that /2 for the SD + + # Save it + write_csv(dest_data_aggr, paste0("data_other/", "complete_oag_aggr.csv")) + + return(dest_data_aggr) +} + + + + + +# ~ Make USA Data --------------------------------------------------------- + +dest_data_aggr_orig <- make_aggr_oag_travel() +dest_data_aggr <- dest_data_aggr_orig %>% + as.data.frame() %>% + # Increase travel for Chinese New Year + mutate(travelers=ifelse(t_month == "01" & dep_country=="CHN", travelers_mean*1.6, travelers_mean)) %>% + select(-arr_city) %>% + mutate(travelers_sd=round(travelers_sd, 1), travelers_mean=round(travelers_mean, 1)) + +format(object.size(dest_data_aggr), "Mb") +write_csv(dest_data_aggr, paste0("data_other/", "complete_oag_aggr_lite.csv")) +save(dest_data_aggr, file=paste0("data_other/", "complete_oag_aggr_lite.rda")) + + +usa_oag_aggr_travel <- dest_data_aggr %>% filter(arr_country=="USA") +format(object.size(usa_oag_aggr_travel), "Mb") +usethis::use_data(usa_oag_aggr_travel, overwrite = TRUE) +#write_csv(dest_data_aggr_usa, paste0("data_other/", "usa_oag_aggr_lite.csv")) +#save(dest_data_aggr_usa, file=paste0("data_other/", "usa_oag_aggr_lite.rda")) + + + +# ~ Make Territory Data --------------------------------------------------------- + +dest_data_aggr <- readr::read_csv(paste0("data_other/", "complete_oag_aggr_lite.csv")) + +us_terr_oag_aggr_travel <- dest_data_aggr %>% filter(arr_country %in% c("GUM","VIR","PRI","ASM","MNP")) +format(object.size(us_terr_oag_aggr_travel), "Mb") +#usethis::use_data(us_terr_oag_aggr_travel, overwrite = TRUE) +write_csv(us_terr_oag_aggr_travel, paste0("data_other/", "us_terr_oag_aggr_travel.csv")) +#save(dest_data_aggr_usa, file=paste0("data_other/", "usa_oag_aggr_lite.rda")) + + + + + +# USA Counties ------------------------------------------------------------ + +us_counties <- readr::read_csv("data-raw/us_counties.csv") +us_counties <- us_counties %>% rowwise() %>% + mutate(FIPS = as.character(FIPS)) %>% + mutate(FIPS = ifelse(stringr::str_length(FIPS)==4, paste0(0, FIPS), FIPS)) +usethis::use_data(us_counties, overwrite = TRUE) diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/oag_data_cleaning.R b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/oag_data_cleaning.R new file mode 100644 index 000000000..3dd1ef1fe --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/oag_data_cleaning.R @@ -0,0 +1,385 @@ +##' Merge CDC-provided OAG data +##' +##' Shaun Truelove (shauntruelove@jhu.edu) +##' 27 February 2020 +##' + + + + +# OPTIONS ----------------------------------------------------------------- + +# whether to save region data individually +save_regions <- FALSE + +# whether to save full data as one file +save_full <- TRUE + + + + +# SETUP ------------------------------------------------------------------- + +if(!require('tidyverse')) install.packages('tidyverse'); library(tidyverse) +if(!require('countrycode')) install.packages('countrycode'); library(countrycode) + + + +# this is set up to use data in "data/OAG_travel_data" +data_dir <- file.path("data", "OAG_travel_data") +data_files <- list.files(data_dir, pattern = ".zip") + +# get region info +region_info <- read_csv(file.path(data_dir, "OAG Region Codes.csv"), na="") +region_info$iso3 <- countrycode::countrycode(region_info$`Country Code`, origin = "iso2c", destination = "iso3c") +region_info$iso3[region_info$`Country Code`=="AN"] <- "ANT" +region_info <- region_info %>% filter(!is.na(iso3)) +regions_ <- unique(region_info$`Region Code`) +n_region <- length(regions_) + + + + +# READ AND EXTRACT ZIPS --------------------------------------------------- +# we will combine them by region first and see how big those are + + +# Loop through the regions +for (i in 1:n_region){ + + # Get files specific to this region + files_region_ <- data_files[grep(regions_[i], data_files)] + + # if no files, skip + if (length(files_region_)==0) next + + # Loop through files for this region, read them, and merge them + # data_merged_ <- NULL + data_merged_ <- list() + for (f in seq_along(files_region_)){ + data_ <- readr::read_csv(file.path(data_dir, files_region_[f]), na="") + # data_merged_ <- bind_rows(data_merged_, data_) + data_merged_[[f]] <- data_ + } + data_merged_ <- rbindlist(data_merged_) + + # change iso2 to iso3 (the "NA" for Namibia keeps getting translated as not available) + data_merged_$`Dep Country Code` <- countrycode::countrycode(data_merged_$`Dep Country Code`, origin = "iso2c", destination = "iso3c") + data_merged_$`Arr Country Code` <- countrycode::countrycode(data_merged_$`Arr Country Code`, origin = "iso2c", destination = "iso3c") + + + # Save regional data if desired + if (save_regions){ + write_csv(data_merged_, file.path("data", paste0(regions_, "_OAG_data.csv"))) + } + + + # Assign region name to object + assign(paste0("data_",regions_[i]), data_merged_) + # Remove temp data + rm(data_merged_, data_) + + #Check size of the data object + print(paste0("data_",regions_[i], " is ", format(object.size(get(paste0("data_",regions_[i]))), "Mb"))) +} + + + +# They are not too big (biggest is 500Mb), so let's just merge them to save + +data_travel_all <- list() +for (i in 1:n_region){ + if (!exists(paste0("data_",regions_[i]))) next + data_travel_all[[i]] <- get(paste0("data_",regions_[i])) + #data_travel_all <- bind_rows(data_travel_all, get(paste0("data_",regions_[i]))) +} +data_travel_all <- rbindlist(data_travel_all) + +print(paste0("Full data is ", format(object.size(data_travel_all), "Mb"))) + + + + +# Save full data if desired +if (save_full){ + write_csv(data_travel_all, file.path("data", "complete_OAG_data.csv")) +} + + + + + + + + +# GET SUMMARY OF LOCATIONS ------------------------------------------------ + +dest_options <- data_travel_all %>% group_by(`Arr Airport Code`, `Arr City Name`, `Arr State Code`, `Arr Country Code`) %>% + summarise(n_occur = n()) + +write_csv(dest_options, "data/oag_destination_combos.csv") + + +get_dest_options <- function(){ + return(readr::read_csv("data/oag_destination_combos.csv")) +} + + + +# + + + + + + + + + + + + + + +# GET A SENSE OF THE DATA ------------------------------------------------- + +us_airports <- unique((data_travel_all %>% filter(`Dep Country Code`=="USA" & `Arr Country Code`=="USA"))$`Arr Airport Code`) + + + + + + + + + +# +# +# +# data_travel_all <- read_csv(file.path("data", "complete_OAG_data.csv"), na=c(""," ", "NA"), +# col_types = list( +# `Dep Airport Code` = col_character(), +# `Dep City Name` = col_character(), +# `Dep State Code` = col_character(), +# `Dep Country Code` = col_character(), +# `Arr Airport Code` = col_character(), +# `Arr City Name` = col_character(), +# `Arr State Code` = col_character(), +# `Arr Country Code` = col_character(), +# `Total Est. Pax` = col_double(), +# `Time Series` = col_double())) +# +# cali_data <- data_travel_all %>% filter(`Arr State Code`=="CA") +# write_csv(cali_data, "data/cali_oag_20172019.csv") +# +# +# +# # SAVE INBOUND TO CALIFORNIA ---------------------------------------------- +# +# cali_data <- read_csv("data/cali_oag_20172019.csv", na=c(""," ","NA"), +# col_types = list( +# `Dep Airport Code` = col_character(), +# `Dep City Name` = col_character(), +# `Dep State Code` = col_character(), +# `Dep Country Code` = col_character(), +# `Arr Airport Code` = col_character(), +# `Arr City Name` = col_character(), +# `Arr State Code` = col_character(), +# `Arr Country Code` = col_character(), +# `Total Est. Pax` = col_double(), +# `Time Series` = col_double())) +# +# +# # Give Chinese airports the provinces +# airport_attribution <- read_csv(file ='data/airport_attribution.csv') +# +# cali_data <- left_join(cali_data, +# airport_attribution %>% mutate(Province = gsub(" Province", "", Province)) %>% +# select(-attribution), +# by=c("Dep Airport Code"="airport_iata")) +# +# +# # Get us State codes for departures +# airport_data <- read_csv("data/airport-codes.csv") +# airport_data <- airport_data %>% mutate(iso_country = ifelse(iso_country=="XK", "KOS", +# countrycode::countrycode(iso_country, origin = "iso2c", destination = "iso3c"))) +# +# airport_data_us <- airport_data %>% filter(iso_country=="USA") +# +# cali_data <- left_join(cali_data, +# airport_data_us %>% mutate(state = substr(iso_region, 4,5)) %>% +# select(state, iata_code), +# by=c("Dep Airport Code"="iata_code")) +# cali_data <- cali_data %>% mutate(`Dep State Code`=ifelse(is.na(`Dep State Code`) & !is.na(state), state, `Dep State Code`)) +# +# +# +# # Aggregate to province (China) or state (US) or country (all others) for source +# cali_data <- cali_data %>% rename(dep_airport = `Dep Airport Code`, +# dep_state = `Dep State Code`, +# dep_country = `Dep Country Code`, +# dep_city = `Dep City Name`, +# arr_airport = `Arr Airport Code`, +# arr_city = `Arr City Name`, +# arr_state = `Arr State Code`, +# arr_country = `Arr Country Code`, +# arr_city = `Arr City Name`, +# travelers = `Total Est. Pax`, +# yr_month = `Time Series`, +# dep_province = Province) +# # Get aggr location +# cali_data_aggr <- cali_data %>% +# mutate(dep_loc_aggr = ifelse(dep_country=="CHN", dep_province, ifelse(dep_country=="USA", dep_state, dep_country))) +# cali_data_aggr <- cali_data_aggr %>% group_by(dep_loc_aggr, dep_country, arr_city, arr_state, arr_country, yr_month) %>% +# summarise(travelers = sum(travelers, na.rm=TRUE)) +# +# # Get Monthly means across the 3 year (will do geometric means) +# cali_data_aggr <- cali_data_aggr %>% +# mutate(t_year = substr(yr_month, 1,4), t_month = as.character(substr(yr_month, 5,6))) +# cali_data_aggr <- cali_data_aggr %>% +# group_by(dep_loc_aggr, dep_country, arr_city, arr_state, arr_country, t_month) %>% +# summarise(travelers_sd = sd(travelers), +# travelers_mean = exp(mean(log(travelers+1)))-1) +# +# cali_data_aggr <- cali_data_aggr %>% mutate(travelers_sd = ifelse(is.nan(travelers_sd), travelers_mean/1.96, travelers_sd)) # for those with only 1 value for travel, just use that /2 for the SD +# +# +# +# # Save it +# write_csv(cali_data_aggr, "data/cali_oag_20172019_aggr.csv") +# +# +# +# +# +# +# +# # SHENZHEN INBOUND -------------------------------------------------------- +# +# +# data_travel_all <- read_csv(file.path("data", "complete_OAG_data.csv"), na=c(""," ", "NA"), +# col_types = list( +# `Dep Airport Code` = col_character(), +# `Dep City Name` = col_character(), +# `Dep State Code` = col_character(), +# `Dep Country Code` = col_character(), +# `Arr Airport Code` = col_character(), +# `Arr City Name` = col_character(), +# `Arr State Code` = col_character(), +# `Arr Country Code` = col_character(), +# `Total Est. Pax` = col_double(), +# `Time Series` = col_double())) +# +# +# # check all locations +# # china_data <- data_travel_all %>% filter(`Arr Country Code`=="CHN") +# # Guangzhou +# +# +# shenzhen_data <- data_travel_all %>% filter(`Arr Airport Code`=="SZX") +# write_csv(shenzhen_data, "data/shenzhen_oag_20172019.csv") +# +# +# +# # SAVE INBOUND TO shenzhenFORNIA ---------------------------------------------- +# +# shenzhen_data <- read_csv("data/shenzhen_oag_20172019.csv", na=c(""," ","NA"), +# col_types = list( +# `Dep Airport Code` = col_character(), +# `Dep City Name` = col_character(), +# `Dep State Code` = col_character(), +# `Dep Country Code` = col_character(), +# `Arr Airport Code` = col_character(), +# `Arr City Name` = col_character(), +# `Arr State Code` = col_character(), +# `Arr Country Code` = col_character(), +# `Total Est. Pax` = col_double(), +# `Time Series` = col_double())) +# +# +# # Give Chinese airports the provinces +# airport_attribution <- read_csv(file ='data/airport_attribution.csv') +# +# shenzhen_data <- left_join(shenzhen_data, +# airport_attribution %>% mutate(Province = gsub(" Province", "", Province)) %>% +# select(-attribution), +# by=c("Dep Airport Code"="airport_iata")) +# +# +# # Get us State codes for departures +# airport_data <- read_csv("data/airport-codes.csv") +# airport_data <- airport_data %>% mutate(iso_country = ifelse(iso_country=="XK", "KOS", +# countrycode::countrycode(iso_country, origin = "iso2c", destination = "iso3c"))) +# +# airport_data_us <- airport_data %>% filter(iso_country=="USA") +# +# shenzhen_data <- left_join(shenzhen_data, +# airport_data_us %>% mutate(state = substr(iso_region, 4,5)) %>% +# select(state, iata_code), +# by=c("Dep Airport Code"="iata_code")) +# shenzhen_data <- shenzhen_data %>% mutate(`Dep State Code`=ifelse(is.na(`Dep State Code`) & !is.na(state), state, `Dep State Code`)) +# +# +# +# # Aggregate SOURCE/Departure Location to province (China) or state (US) or country (all others) for source +# shenzhen_data <- shenzhen_data %>% rename(dep_airport = `Dep Airport Code`, +# dep_state = `Dep State Code`, +# dep_country = `Dep Country Code`, +# dep_city = `Dep City Name`, +# arr_airport = `Arr Airport Code`, +# arr_city = `Arr City Name`, +# arr_state = `Arr State Code`, +# arr_country = `Arr Country Code`, +# arr_city = `Arr City Name`, +# travelers = `Total Est. Pax`, +# yr_month = `Time Series`, +# dep_province = Province) +# +# # Get Aggr Departure location +# shenzhen_data_aggr <- shenzhen_data %>% +# mutate(dep_loc_aggr = ifelse(dep_country=="CHN", dep_province, ifelse(dep_country=="USA", dep_state, dep_country))) +# shenzhen_data_aggr <- shenzhen_data_aggr %>% group_by(dep_loc_aggr, dep_country, arr_city, arr_state, arr_country, yr_month) %>% +# summarise(travelers = sum(travelers, na.rm=TRUE)) +# +# +# +# # Get Monthly means across the 3 year (will do geometric means) +# shenzhen_data_aggr <- shenzhen_data_aggr %>% +# mutate(t_year = substr(yr_month, 1,4), t_month = as.character(substr(yr_month, 5,6))) +# shenzhen_data_aggr <- shenzhen_data_aggr %>% +# group_by(dep_loc_aggr, dep_country, arr_city, arr_state, arr_country, t_month) %>% +# summarise(travelers_sd = sd(travelers), +# travelers_mean = exp(mean(log(travelers+1)))-1) +# +# shenzhen_data_aggr <- shenzhen_data_aggr %>% mutate(travelers_sd = ifelse(is.nan(travelers_sd), travelers_mean/1.96, travelers_sd)) # for those with only 1 value for travel, just use that /2 for the SD +# +# +# +# # Save it +# write_csv(shenzhen_data_aggr, "data/shenzhen_oag_20172019_aggr.csv") +# +# +# +# +# + + + + + +# CHECKS ------------------------------------------------------------------ + +# View(cali_data_aggr %>% filter(is.na(dep_loc_aggr))) +# View(cali_data %>% filter(is.na(dep_state) & dep_country=="USA")) +# tmp <- cali_data_aggr %>% filter(is.na(dep_loc_aggr)) +# +# +# View(cali_data %>% filter(is.na(Province) & dep_country=="CHN")) +# View(cali_data %>% filter(is.na(Province) & dep_country=="CHN")) +# + + + + + + diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/plot_importation_estimates.R b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/plot_importation_estimates.R new file mode 100644 index 000000000..4635fe802 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/plot_importation_estimates.R @@ -0,0 +1,568 @@ +##' Plot the estimated and reported number of importations over time +##' +##' Author: Shaun Truelove +##' email: shauntruelove@jhu.edu +##' Updated: 31 Jan 2020 + + +# SETUP ------------------------------------------------------------------- + +if (!exists("version") | is.list(version)){ version <- "1" } +if (!exists("batch") | is.list(batch)){ batch <- "1" } +if (!exists("project_name")){ project_name <- "california_import" } + +options(scipen=999) + +if(!require('tidyverse')) install.packages('tidyverse'); library(tidyverse) +if(!require('RColorBrewer')) install.packages('RColorBrewer'); library(RColorBrewer) +if(!require('grid')) install.packages('grid'); library(grid) +if(!require('gridExtra')) install.packages('gridExtra'); library(gridExtra) + + +# LOAD SUMMARIZED SIMULATION RESULTS --------------------------------------------------------------- + +# Destination by time +import_results_desttime <- readr::read_csv(file.path("results",project_name, sprintf("import_results_desttime_v%s.csv", version))) +import_results_desttime$t <- lubridate::as_date(import_results_desttime$t) +t_values <- sort(unique(import_results_desttime$t)) +import_results_desttime <- import_results_desttime %>% + mutate(t = factor(as.character(t))) %>% + mutate(t_num = as.integer(t)) + +# Source by time, single destination +import_results_sourcetime <- readr::read_csv(file.path("results",project_name, sprintf("import_results_sourcetime_v%s.csv", version))) +import_results_sourcetime$t <- lubridate::as_date(import_results_sourcetime$t) +t_values <- sort(unique(import_results_sourcetime$t)) +import_results_sourcetime <- import_results_sourcetime %>% + mutate(t = factor(as.character(t))) %>% + mutate(t_num = as.integer(t)) + +# Destination by time, Cumulative +import_results_desttime_cum <- readr::read_csv(file.path("results",project_name, sprintf("import_results_desttime_cumulative_v%s.csv", version))) +import_results_desttime_cum$t <- lubridate::as_date(import_results_desttime_cum$t) +t_values <- sort(unique(import_results_desttime_cum$t)) +import_results_desttime_cum <- import_results_desttime_cum %>% + mutate(t = factor(as.character(t))) %>% + mutate(t_num = as.integer(t)) + + +# Overall Destination by time +import_results_desttime_overall <- readr::read_csv(file.path("results",project_name, sprintf("import_results_desttime_overall_v%s.csv", version))) +import_results_desttime_overall$t <- lubridate::as_date(import_results_desttime_overall$t) +t_values <- sort(unique(import_results_desttime_overall$t)) +import_results_desttime_overall <- import_results_desttime_overall %>% + mutate(t = factor(as.character(t))) %>% + mutate(t_num = as.integer(t)) + +# Overall Destination by time, Cumulative +import_results_desttime_overall_cum <- readr::read_csv(file.path("results",project_name, sprintf("import_results_desttime_overall_cumulative_v%s.csv", version))) +import_results_desttime_overall_cum$t <- lubridate::as_date(import_results_desttime_overall_cum$t) +t_values <- sort(unique(import_results_desttime_overall_cum$t)) +import_results_desttime_overall_cum <- import_results_desttime_overall_cum %>% + mutate(t = factor(as.character(t))) %>% + mutate(t_num = as.integer(t)) + + + +# t_limits <- lubridate::as_date(c("2020-01-01","2020-01-27")) +if (!exists("t_limits")){ t_limits <- range(t_values) } + + + + + +# FUNCTIONS --------------------------------------------------------------- + +plot_imports <- function(data=import_results_desttime, region_ = "All", t_limits=lubridate::as_date(c("2020-01-01","2020-01-27")), + y.size = 9, x.size = 9, + leg.text.size = 12, leg.title.size = 14, + rep_col = "indianred2", est_col = "blue3", est_ribbon_col = "blue3", est_ribbon_alpha=0.25, + time_int = 5, # time interval for x-axis + plot_legend=TRUE, x_axis=TRUE){ + # Subset by region if wanted + if (region_!="All"){ + data <- data %>% filter(region==region_) + } + # Limit the time of the plots + if (!is.na(t_limits[1])){ + data <- data %>% mutate(t = lubridate::as_date(t)) %>% + filter(t >= lubridate::as_date(t_limits[1]) & lubridate::as_date(t) <= lubridate::as_date(t_limits[2])) %>% + mutate(t_num = as.integer(as.factor(t))) + } + t_values <- as.character(sort(data$t)) + + p <- ggplot(data=data, aes(x=t_num, y=import_mean)) + + #geom_hline(yintercept=0)+ + geom_line(aes(color='Estimated', linetype="Estimated"), size=1.2) + + geom_ribbon(aes(ymin=import_ll, ymax=import_ul), alpha=est_ribbon_alpha, fill=est_ribbon_col) + + scale_x_continuous(breaks=seq(1,length(t_values),time_int), + labels=t_values[seq(1,length(t_values),time_int)]) + + ylab("Imported nCoV cases (n)") + + #scale_colour_manual(values=c(Reported=rep_col, Estimated=est_col), guide="none") + + #scale_linetype_manual(values=c("solid","11"), guide=guide_legend(title=element_blank())) + + scale_colour_manual(values=c(Estimated=est_col), guide="none") + + scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) + + theme(axis.line = element_line(colour = "black"), + panel.grid.major = element_blank(), panel.grid.minor = element_blank(), + panel.border = element_blank(), panel.background=element_blank(), + axis.text.y = element_text(size=y.size), + axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)), + axis.title.x = element_blank(), + legend.title=element_text(size=leg.title.size), + legend.text=element_text(size=leg.text.size), # legend text size + legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20), + legend.key.size=unit(15, "pt"), # Change key size in the legend + legend.key = element_blank(), + legend.position=c(.075, .80), legend.background = element_blank(), legend.box.background = element_blank(), + plot.title = element_text(size=leg.title.size, face="bold", vjust=-10, hjust = 0.025), + plot.margin = unit(c(-.75,.25,0,0.25), "cm")) + + if (region_ != "All"){ + p <- p + ggtitle(region_) + } + if (plot_legend==FALSE){ + p <- p + theme(legend.position = "none") + } + if (x_axis==FALSE){ + p <- p + theme(axis.text.x=element_blank(), #axis.line.x=element_blank(), + axis.ticks.x=element_blank(), axis.title.x=element_blank()) + } + return(p) +} + + +plot_imports_barchart <- function(data=import_results_desttime, region_ = "All", t_limits=lubridate::as_date(c("2020-01-01","2020-01-27")), + y.size = 9, x.size = 9, + leg.text.size = 12, leg.title.size = 14, + rep_col = "indianred2", est_col = "blue3", + time_int = 5, # time interval for x-axis + plot_legend=TRUE, x_axis=TRUE){ + # Subset by region if wanted + if (region_!="All"){ + data <- data %>% filter(region==region_) + } + # Limit the time of the plots + if (!is.na(t_limits[1])){ + data <- data %>% mutate(t = lubridate::as_date(t)) %>% + filter(t >= lubridate::as_date(t_limits[1]) & lubridate::as_date(t) <= lubridate::as_date(t_limits[2])) %>% + mutate(t_num = as.integer(as.factor(t))) + } + t_values <- as.character(sort(data$t)) + + p <- ggplot(data=data, aes(x=t_num, y=import_mean, fill='Estimated')) + + geom_bar(stat="identity", color="black") + + geom_errorbar(aes(ymin=import_ll, ymax=import_ul), width=.4) + + ylab("Imported nCoV cases (n)") + + scale_x_continuous(breaks=seq(1,length(t_values),time_int), + labels=t_values[seq(1,length(t_values),time_int)]) + + scale_colour_manual(values=c(Estimated=est_col), guide="none") + + scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) + + #scale_y_continuous(expand = c(0,0)) + + theme(axis.line = element_line(colour = "black"), + panel.grid.major = element_blank(), panel.grid.minor = element_blank(), + panel.border = element_blank(), panel.background=element_blank(), + axis.text.y = element_text(size=y.size), + axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)), + axis.title.x = element_blank(), + legend.title=element_text(size=leg.title.size), + legend.text=element_text(size=leg.text.size), # legend text size + legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20), + legend.key.size=unit(15, "pt"), # Change key size in the legend + legend.key = element_blank(), + legend.position=c(.075, .80), legend.background = element_blank(), legend.box.background = element_blank(), + plot.title = element_text(size=leg.title.size, face="bold", vjust=-10, hjust = 0.025), + plot.margin = unit(c(-.75,.25,0.25,0.25), "cm")) + + guides(fill=guide_legend(title = element_blank())) + + if (region_ != "All"){ + p <- p + ggtitle(region_) + } + if (plot_legend==FALSE){ + p <- p + theme(legend.position = "none") + } + if (x_axis==FALSE){ + p <- p + theme(axis.text.x=element_blank(), #axis.line.x=element_blank(), + axis.ticks.x=element_blank(), axis.title.x=element_blank()) + } + return(p) +} + + +# Barchart plot of importations stacked by source +plot_imports_stackedsource <- function(data=import_results_sourcetime, t_limits=lubridate::as_date(c("2020-01-01","2020-01-27")), + y.size = 9, x.size = 9, + leg.text.size = 8, leg.title.size = 10, + est_col = "blue3", ncol_legend=1, + time_int = 5){ # time interval for x-axis + + # Limit the time of the plots + if (!is.na(t_limits[1])){ + data <- data %>% mutate(t = lubridate::as_date(t)) %>% + filter(t >= lubridate::as_date(t_limits[1]) & lubridate::as_date(t) <= lubridate::as_date(t_limits[2])) %>% + mutate(t_num = as.integer(as.factor(t))) + } + t_values <- as.character(unique(sort(data$t))) + + p <- ggplot(data=data, aes(x=t_num, y=import_mean, fill=source)) + + geom_bar(position="stack", stat="identity", color="black") + + ylab("Imported nCoV cases (n)") + + scale_x_continuous(breaks=seq(1,length(t_values),time_int), + labels=t_values[seq(1,length(t_values),time_int)]) + + scale_colour_manual(values=c(Estimated=est_col), guide="none") + + scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) + + #scale_y_continuous(expand = c(0,0)) + + theme(axis.line = element_line(colour = "black"), + panel.grid.major = element_blank(), panel.grid.minor = element_blank(), + panel.border = element_blank(), panel.background=element_blank(), + axis.text.y = element_text(size=y.size), + axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)), + axis.title.x = element_blank(), + legend.title=element_text(size=leg.title.size), + legend.text=element_text(size=leg.text.size), # legend text size + legend.margin=margin(0,0,0,0), legend.box.margin=margin(0,10,-20,-20), + legend.key.size=unit(8, "pt"), + legend.key = element_blank(), + legend.background = element_blank(), legend.box.background = element_blank(), + plot.title = element_text(size=leg.title.size, face="bold", hjust = 0.025), + plot.margin = unit(c(0.5,.25,0.25,0.25), "cm")) + + guides(fill=guide_legend(title = element_blank(), ncol=ncol_legend)) + return(p) +} + + + + + + + +# Barchart plot of importations stacked by source +plot_imports_facetsource <- function(data=import_results_sourcetime, t_limits=lubridate::as_date(c("2020-01-01","2020-01-27")), + y.size = 9, x.size = 9, + leg.text.size = 8, leg.title.size = 10, + rep_col = "indianred2", est_col = "blue3", ncol_legend=1, ncol_facet=1, + time_int = 5, scales="free_y"){ # time interval for x-axis + + # Limit the time of the plots + if (!is.na(t_limits[1])){ + data <- data %>% mutate(t = lubridate::as_date(t)) %>% + filter(t >= lubridate::as_date(t_limits[1]) & lubridate::as_date(t) <= lubridate::as_date(t_limits[2])) %>% + mutate(t_num = as.integer(as.factor(t))) + } + t_values <- as.character(unique(sort(data$t))) + + p <- ggplot(data=data, aes(x=t_num, y=import_mean, fill=source)) + + geom_bar(stat="identity", color="black") + + ylab("Imported nCoV cases (n)") + + scale_x_continuous(breaks=seq(1,length(t_values),time_int), + labels=t_values[seq(1,length(t_values),time_int)]) + + scale_colour_manual(values=c(Estimated=est_col), guide="none") + + scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) + + #scale_y_continuous(expand = c(0,0)) + + theme(axis.line = element_line(colour = "black"), + panel.grid.major = element_blank(), panel.grid.minor = element_blank(), + panel.border = element_blank(), panel.background=element_blank(), + axis.text.y = element_text(size=y.size), + axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)), + axis.title.x = element_blank(), + legend.title=element_text(size=leg.title.size), + legend.text=element_text(size=leg.text.size), # legend text size + legend.margin=margin(0,0,0,0), legend.box.margin=margin(0,10,-20,-20), + legend.key.size=unit(8, "pt"), + legend.key = element_blank(), + legend.background = element_blank(), legend.box.background = element_blank(), + plot.title = element_text(size=leg.title.size, face="bold", hjust = 0.025), + plot.margin = unit(c(0.5,.25,0.25,0.25), "cm")) + + guides(fill=guide_legend(title = element_blank(), ncol=ncol_legend)) + + facet_wrap(vars(source), ncol=ncol_facet, scales = scales) + return(p) +} + + + + + + + + + +# Barchart plot of importations stacked by source +plot_imports_stackeddest <- function(data=import_results_desttime, t_limits=lubridate::as_date(c("2020-01-01","2020-01-27")), + y.size = 9, x.size = 9, + leg.text.size = 8, leg.title.size = 10, + est_col = "blue3", + time_int = 5){ # time interval for x-axis + + # Limit the time of the plots + if (!is.na(t_limits[1])){ + data <- data %>% mutate(t = lubridate::as_date(t)) %>% + filter(t >= lubridate::as_date(t_limits[1]) & lubridate::as_date(t) <= lubridate::as_date(t_limits[2])) %>% + mutate(t_num = as.integer(as.factor(t))) + } + t_values <- as.character(unique(sort(data$t))) + + # N columns + n_dest <- length(unique(import_results_desttime$destination)) + n_columns <- ceiling(n_dest / 30) + + p <- ggplot(data=data, aes(x=t_num, y=import_mean, fill=destination)) + + geom_bar(position="stack", stat="identity", color="black", fill=est_col) + + ylab("Imported nCoV cases (n)") + + scale_x_continuous(breaks=seq(1,length(t_values),time_int), + labels=t_values[seq(1,length(t_values),time_int)]) + + # scale_fill_manual(values=c(import_mean=est_col), guide="none") + + scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) + + #scale_y_continuous(expand = c(0,0)) + + theme(axis.line = element_line(colour = "black"), + panel.grid.major = element_blank(), panel.grid.minor = element_blank(), + panel.border = element_blank(), panel.background=element_blank(), + axis.text.y = element_text(size=y.size), + axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)), + axis.title.x = element_blank(), + legend.title=element_text(size=leg.title.size), + legend.text=element_text(size=leg.text.size), # legend text size + legend.margin=margin(0,0,0,0), legend.box.margin=margin(0,10,-20,-20), + legend.key.size=unit(8, "pt"), + legend.key = element_blank(), + legend.background = element_blank(), legend.box.background = element_blank(), + plot.title = element_text(size=leg.title.size, face="bold", hjust = 0.025), + plot.margin = unit(c(0.5,.25,0.25,0.25), "cm")) + + guides(fill=guide_legend(title = element_blank(), ncol=n_columns)) + return(p) +} + + + + +# For plotting importions from multiple regions +plot_imports_byregion <- function(data=import_results_desttime_byregion, t_limits=lubridate::as_date(c("2020-01-01","2020-01-27")), + y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14, + rep_col = "indianred2", est_col = "blue3", est_ribbon_col = "blue3", est_ribbon_alpha=0.25, + plot_legend=TRUE){ + + # Limit the time of the plots + if (!is.na(t_limits[1])){ + data <- data %>% mutate(t = lubridate::as_date(t)) %>% + filter(t >= lubridate::as_date(t_limits[1]) & lubridate::as_date(t) <= lubridate::as_date(t_limits[2])) %>% + mutate(t_num = as.integer(as.factor(t))) + } + t_values <- as.character(unique(sort(data$t))) + + p <- ggplot(data=data, aes(x=t_num, color=region, fill=region)) + + geom_line(data=data, aes(y=import_mean), size=1.2) + + geom_ribbon(data=data, aes(ymin=import_ll, ymax=import_ul, fill=region), alpha=est_ribbon_alpha) + + geom_line(data=data, aes(y=rep_import, color="Reported"), size=1.2) + + ylab("Imported nCoV cases (n)") + + #scale_colour_manual(name="Imported cases", values=c(Reported=rep_col, Estimated=est_col)) + + scale_color_manual(values=c("grey50", brewer.pal(3,"Dark2"), "red"), guide=guide_legend(title="Imported cases")) + + scale_x_continuous(breaks=seq(1,length(t_values),time_int), + labels=t_values[seq(1,length(t_values),time_int)]) + + theme(axis.line = element_line(colour = "black"), + panel.grid.major = element_blank(), panel.grid.minor = element_blank(), + panel.border = element_blank(), panel.background=element_blank(), + axis.text.y = element_text(size=y.size), axis.text.x = element_text(size=x.size, angle = 90, hjust = 1), + axis.title.x = element_blank(), + legend.title=element_text(size=leg.title.size), + legend.text=element_text(size=leg.text.size), # legend text size + legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20), + legend.key.size=unit(15, "pt"), # Change key size in the legend + legend.key = element_blank(), + legend.position=c(.1, .90), legend.background = element_blank(), legend.box.background = element_blank(), + plot.margin = unit(c(.5,1,.25,.25), "cm")) + + p + facet_grid(region ~ .) + + + return(p) +} + + + + +plot_cum_imports <- function(data=import_results_desttime_cum, region_ = "All", t_limits=lubridate::as_date(c("2020-01-01","2020-01-27")), + y.size = 9, x.size = 9, + leg.text.size = 12, leg.title.size = 14, + rep_col = "indianred2", est_col = "blue3", est_ribbon_col = "blue3", est_ribbon_alpha=0.25, + time_int = 5, # time interval for x-axis + plot_legend=TRUE, x_axis=TRUE){ + + # Subset by region if wanted + if (region_!="All"){ + data <- data %>% filter(region==region_) + } + # Limit the time of the plots + if (!is.na(t_limits[1])){ + data <- data %>% mutate(t = lubridate::as_date(t)) %>% + filter(t >= lubridate::as_date(t_limits[1]) & lubridate::as_date(t) <= lubridate::as_date(t_limits[2])) %>% + mutate(t_num = as.integer(as.factor(t))) + } + t_values <- as.character(sort(data$t)) + + p <- ggplot(data=data, aes(x=t_num, y=cum_import_mean)) + + geom_line(aes(color='Estimated', linetype="Estimated", group=1), size=1.2) + + geom_ribbon(aes(ymin=cum_import_ll, ymax=cum_import_ul, group=1), alpha=est_ribbon_alpha, fill=est_ribbon_col) + + scale_x_continuous(breaks=seq(1,length(t_values),time_int), + labels=t_values[seq(1,length(t_values),time_int)]) + + ylab("Imported nCoV cases (n)") + + #scale_colour_manual(values=c(Reported=rep_col, Estimated=est_col), guide="none") + + #scale_linetype_manual(values=c("solid","11"), guide=guide_legend(title=element_blank())) + + scale_colour_manual(values=c(Estimated=est_col), guide="none") + + scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) + + #scale_y_continuous(expand = c(0,0)) + + theme(axis.line = element_line(colour = "black"), + panel.grid.major = element_blank(), panel.grid.minor = element_blank(), + panel.border = element_blank(), panel.background=element_blank(), + axis.text.y = element_text(size=y.size), + axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)), + axis.title.x = element_blank(), + legend.title=element_text(size=leg.title.size), + legend.text=element_text(size=leg.text.size), # legend text size + legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20), + legend.key.size=unit(15, "pt"), # Change key size in the legend + legend.key = element_blank(), + legend.position=c(.075, .80), legend.background = element_blank(), legend.box.background = element_blank(), + plot.title = element_text(size=leg.title.size, face="bold", vjust=-10, hjust = 0.025), + plot.margin = unit(c(-.75,.25,0,0.25), "cm")) + + if (region_ != "All"){ + p <- p + ggtitle(region_) + } + if (plot_legend==FALSE){ + p <- p + theme(legend.position = "none") + } + if (x_axis==FALSE){ + p <- p + theme(axis.text.x=element_blank(), #axis.line.x=element_blank(), + axis.ticks.x=element_blank(), axis.title.x=element_blank()) + } + return(p) +} + + + + + + + + +# PLOT SPECIFICS + +# y.size = x.size = 9 +# leg.text.size = 12 +# leg.title.size = 14 +# +# rep_col <- "indianred2" +# est_col <- "blue3" +# est_ribbon_col <- "blue3" +# est_ribbon_alpha <- 0.2 + + +# PLOT TOTAL IMPORTATIONS ------------------------------------------------- +# +# p_total <- plot_imports(data=import_results_desttime_overall, region_ = "All", t_limits=t_limits, +# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14, +# rep_col = "indianred2", +# est_col = "blue3", +# est_ribbon_col = "blue3", +# est_ribbon_alpha=0.25, +# plot_legend=TRUE) +# +# p_cum <- plot_cum_imports(data=import_results_desttime_overall_cum, region_ = "All", t_limits=t_limits, +# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14, +# rep_col = "indianred2", +# est_col = "blue3", +# est_ribbon_col = "blue3", +# est_ribbon_alpha=0.25, +# plot_legend=TRUE) +# #plot(p_cum) +# +# #gridExtra::grid.arrange(p_total, p_cum, nrow=2) +# +# +# +# # p_total_barchart <- plot_imports_barchart(data=import_results_desttime, region_ = "All", t_limits=t_limits, +# # y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14, +# # rep_col = "indianred2", +# # est_col = "blue3", +# # plot_legend=TRUE) +# # +# # gridExtra::grid.arrange(p_total, p_total_barchart, nrow=2) +# +# +# +# p_stackedsource_barchart <- plot_imports_stackedsource(data=import_results_sourcetime, t_limits=t_limits, +# y.size = 8, x.size = 8, leg.text.size = 6, leg.title.size = 8, +# rep_col = "indianred2", +# est_col = "blue3") +# #plot(p_stacked_barchart) +# +# +# p_stackeddest_barchart <- plot_imports_stackeddest(data=import_results_desttime, t_limits=t_limits, +# y.size = 8, x.size = 8, leg.text.size = 6, leg.title.size = 8, +# rep_col = "indianred2", +# est_col = "blue3") +# + + + + + + +# # PLOT ESTIMATED VS REPORTED ---------------------------------------------- +# +# # Reported from CDC +# shen_cases <- readr::read_csv("data/shenzhen_data/shenzhen_case_counts.csv") +# shen_cases <- shen_cases %>% mutate(cum_cases = cumsum(count)) +# +# # From Linelists +# ll_data <- readr::read_csv("data/linelist_current.csv") +# shen_rows <- apply(ll_data, 1, FUN=function(x) sum(grepl("shenzhen", x, ignore.case = TRUE)))>0 +# ll_data_shenzhen <- ll_data[shen_rows, ] +# shen_data_aggr <- ll_data_shenzhen %>% count(date_confirmation) +# rm(ll_data, ll_data_shenzhen, shen_rows) +# +# shen_counts <- full_join(shen_cases %>% rename(count_CDC = count), +# shen_data_aggr %>% rename(count_ll = n, date=date_confirmation), +# by=c("date"="date")) +# shen_counts[is.na(shen_counts)] <- 0 +# +# # Merge with estimates +# shen_counts_all <- full_join(shen_counts, +# import_results_desttime %>% select(date=t, import_mean, import_ll, import_ul) %>% +# mutate(date = lubridate::as_date(date)), by=c("date")) +# shen_counts_all <- full_join(shen_counts_all, +# import_results_desttime_cum %>% select(date=t, cum_import_mean, cum_import_ll, cum_import_ul) %>% +# mutate(date = lubridate::as_date(date)), by=c("date")) +# +# +# +# p_all <- ggplot(shen_counts_all %>% mutate(label1 = "CDC counts", label2 = "Linelist counts", label3="Estimated Imports"), +# aes(x=date, y=count_CDC)) + +# geom_bar(stat="identity", aes(fill=label1)) + +# geom_point(aes(x=date,y=count_ll, shape=label2, color=label2), size=2) + +# geom_point(aes(x=date,y=import_mean, shape=label3, color=label3), size=2) + +# scale_color_manual(values=c("maroon","green")) + +# scale_fill_manual(values=c("navy")) + +# ylab("Reported Cases") + ggtitle("Shenzhen Reported nCoV Cases") + +# theme_classic() + +# theme(#legend.background = element_rect(color="grey"), +# legend.position = c(0.1, 1), +# legend.justification = c(0, 1), +# legend.title = element_blank()) +# #plot(p_all) +# +# # Plot cumulative cases in Shenzhen +# # Get cumulative case counts in each +# shen_counts_cum <- shen_counts_all %>% arrange(date) %>% mutate(cum_CDC = cumsum(count_CDC), cum_ll = cumsum(count_ll)) +# p_cum <- ggplot(shen_counts_cum %>% mutate(label1 = "CDC cumulative", label2 = "Linelist cumulative", label3="Estimated Imports"), +# aes(x=date, y=cum_CDC)) + +# geom_bar(stat="identity", aes(fill=label1)) + +# geom_point(aes(x=date,y=cum_ll, shape=label2, color=label2), size=2) + +# geom_point(aes(x=date,y=cum_import_mean, shape=label3, color=label3), size=2) + +# scale_color_manual(values=c("maroon","green")) + +# scale_fill_manual(values=c("navy")) + +# ylab("Cumulative Cases") + ggtitle("Shenzhen Cumulative nCoV Cases") + +# theme_classic() + +# theme(#legend.background = element_rect(color="grey"), +# legend.position = c(0.05, 1), +# legend.justification = c(0, 1), +# legend.title = element_blank()) +# \ No newline at end of file diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/plot_importation_estimates_detection.R b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/plot_importation_estimates_detection.R new file mode 100644 index 000000000..f85530564 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/plot_importation_estimates_detection.R @@ -0,0 +1,459 @@ +##' Plot the estimated and reported number of importations over time +##' +##' Author: Shaun Truelove +##' email: shauntruelove@jhu.edu +##' Updated: 31 Jan 2020 + + +# SETUP ------------------------------------------------------------------- + +if (!exists("version")){ version <- "1" } +if (!exists("batch")){ batch <- "1" } +if (!exists("project_name")){ project_name <- "california_import" } +import_sim_file <- file.path("output",project_name, sprintf("covid_importation_sim_%s_batch_detect_v%s.RData", batch, version)) + +options(scipen=999) + +if(!require('tidyverse')) install.packages('tidyverse'); library(tidyverse) +if(!require('RColorBrewer')) install.packages('RColorBrewer'); library(RColorBrewer) +if(!require('grid')) install.packages('grid'); library(grid) +if(!require('gridExtra')) install.packages('gridExtra'); library(gridExtra) + + +# LOAD SUMMARIZED SIMULATION RESULTS --------------------------------------------------------------- + +# Destination by time +import_results_desttime_detect <- read_csv(file.path("results",project_name, sprintf("import_results_desttime_detect_v%s.csv", version))) +import_results_desttime_detect$t <- as.Date(import_results_desttime_detect$t) +t_values <- sort(unique(import_results_desttime_detect$t)) +import_results_desttime_detect <- import_results_desttime_detect %>% + mutate(t = factor(as.character(t))) %>% + mutate(t_num = as.integer(t)) + +# Source by time, single destination +import_results_sourcetime_detect <- read_csv(file.path("results",project_name, sprintf("import_results_sourcetime_detect_v%s.csv", version))) +import_results_sourcetime_detect$t <- as.Date(import_results_sourcetime_detect$t) +t_values <- sort(unique(import_results_sourcetime_detect$t)) +import_results_sourcetime_detect <- import_results_sourcetime_detect %>% + mutate(t = factor(as.character(t))) %>% + mutate(t_num = as.integer(t)) +# +# # Destination by time, Cumulative +# import_results_desttime_cum <- read_csv(file.path("results",project_name, sprintf("import_results_desttime_cumulative_detect_v%s.csv", version))) +# import_results_desttime_cum$t <- as.Date(import_results_desttime_cum$t) +# t_values <- sort(unique(import_results_desttime_cum$t)) +# import_results_desttime_cum <- import_results_desttime_cum %>% +# mutate(t = factor(as.character(t))) %>% +# mutate(t_num = as.integer(t)) + + +# t_limits <- as.Date(c("2020-01-01","2020-01-27")) +if (!exists("t_limits")){ t_limits <- range(t_values) } + + +# +# # FUNCTIONS --------------------------------------------------------------- +# +# plot_imports <- function(data=import_results_desttime, region_ = "All", t_limits=as.Date(c("2020-01-01","2020-01-27")), +# y.size = 9, x.size = 9, +# leg.text.size = 12, leg.title.size = 14, +# rep_col = "indianred2", est_col = "blue3", est_ribbon_col = "blue3", est_ribbon_alpha=0.25, +# time_int = 5, # time interval for x-axis +# plot_legend=TRUE, x_axis=TRUE){ +# # Subset by region if wanted +# if (!is.na(t_limits[1])){ +# data <- data %>% mutate(t = as.Date(t)) %>% +# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>% +# mutate(t_num = as.integer(as.factor(t))) +# } +# # Limit the time of the plots +# if (!is.na(t_limits[1])){ +# data <- data %>% rowwise %>% filter(as.Date(t) >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) +# } +# t_values <- as.character(sort(data$t)) +# +# p <- ggplot(data=data, aes(x=t_num, y=import_mean)) + +# #geom_hline(yintercept=0)+ +# geom_line(aes(color='Detected', linetype="Detected"), size=1.2) + +# geom_ribbon(aes(ymin=import_ll, ymax=import_ul), alpha=est_ribbon_alpha, fill=est_ribbon_col) + +# scale_x_continuous(breaks=seq(1,length(t_values),time_int), +# labels=t_values[seq(1,length(t_values),time_int)]) + +# ylab("Detected imported nCoV cases (n)") + +# #scale_colour_manual(values=c(Reported=rep_col, Estimated=est_col), guide="none") + +# #scale_linetype_manual(values=c("solid","11"), guide=guide_legend(title=element_blank())) + +# scale_colour_manual(values=c(Detected=est_col), guide="none") + +# scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) + +# #scale_y_continuous(expand = c(0,0)) + +# theme(axis.line = element_line(colour = "black"), +# panel.grid.major = element_blank(), panel.grid.minor = element_blank(), +# panel.border = element_blank(), panel.background=element_blank(), +# axis.text.y = element_text(size=y.size), +# axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)), +# axis.title.x = element_blank(), +# legend.title=element_text(size=leg.title.size), +# legend.text=element_text(size=leg.text.size), # legend text size +# legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20), +# legend.key.size=unit(15, "pt"), # Change key size in the legend +# legend.key = element_blank(), +# legend.position=c(.075, .80), legend.background = element_blank(), legend.box.background = element_blank(), +# plot.title = element_text(size=leg.title.size, face="bold", vjust=-10, hjust = 0.025), +# plot.margin = unit(c(-.75,.25,0,0.25), "cm")) +# +# if (region_ != "All"){ +# p <- p + ggtitle(region_) +# } +# if (plot_legend==FALSE){ +# p <- p + theme(legend.position = "none") +# } +# if (x_axis==FALSE){ +# p <- p + theme(axis.text.x=element_blank(), #axis.line.x=element_blank(), +# axis.ticks.x=element_blank(), axis.title.x=element_blank()) +# } +# return(p) +# } +# +# +# plot_imports_barchart <- function(data=import_results_desttime, region_ = "All", t_limits=as.Date(c("2020-01-01","2020-01-27")), +# y.size = 9, x.size = 9, +# leg.text.size = 12, leg.title.size = 14, +# rep_col = "indianred2", est_col = "blue3", +# time_int = 5, # time interval for x-axis +# plot_legend=TRUE, x_axis=TRUE){ +# # Subset by region if wanted +# if (!is.na(t_limits[1])){ +# data <- data %>% mutate(t = as.Date(t)) %>% +# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>% +# mutate(t_num = as.integer(as.factor(t))) +# } +# # Limit the time of the plots +# if (!is.na(t_limits[1])){ +# data <- data %>% rowwise %>% filter(as.Date(t) >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) +# } +# t_values <- as.character(sort(data$t)) +# +# p <- ggplot(data=data, aes(x=t_num, y=import_mean, fill='Detected')) + +# geom_bar(stat="identity", color="black") + +# geom_errorbar(aes(ymin=import_ll, ymax=import_ul), width=.4) + +# ylab("Detected imported nCoV cases (n)") + +# scale_x_continuous(breaks=seq(1,length(t_values),time_int), +# labels=t_values[seq(1,length(t_values),time_int)]) + +# scale_colour_manual(values=c(Detected=est_col), guide="none") + +# scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) + +# #scale_y_continuous(expand = c(0,0)) + +# theme(axis.line = element_line(colour = "black"), +# panel.grid.major = element_blank(), panel.grid.minor = element_blank(), +# panel.border = element_blank(), panel.background=element_blank(), +# axis.text.y = element_text(size=y.size), +# axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)), +# axis.title.x = element_blank(), +# legend.title=element_text(size=leg.title.size), +# legend.text=element_text(size=leg.text.size), # legend text size +# legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20), +# legend.key.size=unit(15, "pt"), # Change key size in the legend +# legend.key = element_blank(), +# legend.position=c(.075, .80), legend.background = element_blank(), legend.box.background = element_blank(), +# plot.title = element_text(size=leg.title.size, face="bold", vjust=-10, hjust = 0.025), +# plot.margin = unit(c(-.75,.25,0.25,0.25), "cm")) + +# guides(fill=guide_legend(title = element_blank())) +# +# if (region_ != "All"){ +# p <- p + ggtitle(region_) +# } +# if (plot_legend==FALSE){ +# p <- p + theme(legend.position = "none") +# } +# if (x_axis==FALSE){ +# p <- p + theme(axis.text.x=element_blank(), #axis.line.x=element_blank(), +# axis.ticks.x=element_blank(), axis.title.x=element_blank()) +# } +# return(p) +# } +# +# +# # Barchart plot of importations stacked by source +# plot_imports_stackedsource <- function(data=import_results_sourcetime, t_limits=as.Date(c("2020-01-01","2020-01-27")), +# y.size = 9, x.size = 9, +# leg.text.size = 8, leg.title.size = 10, +# rep_col = "indianred2", est_col = "blue3", +# time_int = 5){ # time interval for x-axis +# +# # Limit the time of the plots +# if (!is.na(t_limits[1])){ +# data <- data %>% mutate(t = as.Date(t)) %>% +# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>% +# mutate(t_num = as.integer(as.factor(t))) +# } +# t_values <- as.character(unique(sort(data$t))) +# +# p <- ggplot(data=data, aes(x=t_num, y=import_mean, fill=source)) + +# geom_bar(position="stack", stat="identity", color="black") + +# ylab("Detected imported nCoV cases (n)") + +# scale_x_continuous(breaks=seq(1,length(t_values),time_int), +# labels=t_values[seq(1,length(t_values),time_int)]) + +# scale_colour_manual(values=c(Detected=est_col), guide="none") + +# scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) + +# #scale_y_continuous(expand = c(0,0)) + +# theme(axis.line = element_line(colour = "black"), +# panel.grid.major = element_blank(), panel.grid.minor = element_blank(), +# panel.border = element_blank(), panel.background=element_blank(), +# axis.text.y = element_text(size=y.size), +# axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)), +# axis.title.x = element_blank(), +# legend.title=element_text(size=leg.title.size), +# legend.text=element_text(size=leg.text.size), # legend text size +# legend.margin=margin(0,0,0,0), legend.box.margin=margin(0,10,-20,-20), +# legend.key.size=unit(8, "pt"), +# legend.key = element_blank(), +# legend.background = element_blank(), legend.box.background = element_blank(), +# plot.title = element_text(size=leg.title.size, face="bold", hjust = 0.025), +# plot.margin = unit(c(0.5,.25,0.25,0.25), "cm")) + +# guides(fill=guide_legend(title = element_blank(), ncol=1)) +# return(p) +# } +# +# +# +# +# +# +# # For plotting importions from multiple regions +# plot_imports_byregion <- function(data=import_results_desttime_byregion, t_limits=as.Date(c("2020-01-01","2020-01-27")), +# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14, +# rep_col = "indianred2", est_col = "blue3", est_ribbon_col = "blue3", est_ribbon_alpha=0.25, +# plot_legend=TRUE){ +# +# # Limit the time of the plots +# if (!is.na(t_limits[1])){ +# data <- data %>% mutate(t = as.Date(t)) %>% +# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>% +# mutate(t_num = as.integer(as.factor(t))) +# } +# +# p <- ggplot(data=data, aes(x=t_num, color=region, fill=region)) + +# geom_line(data=data, aes(y=import_mean), size=1.2) + +# geom_ribbon(data=data, aes(ymin=import_ll, ymax=import_ul, fill=region), alpha=est_ribbon_alpha) + +# #geom_line(data=data, aes(y=rep_import, color="Reported"), size=1.2) + +# ylab("Detected imported nCoV cases (n)") + +# #scale_colour_manual(name="Imported cases", values=c(Reported=rep_col, Estimated=est_col)) + +# scale_color_manual(values=c("grey50", brewer.pal(3,"Dark2"), "red"), guide=guide_legend(title="Detected imported cases")) + +# +# theme(axis.line = element_line(colour = "black"), +# panel.grid.major = element_blank(), panel.grid.minor = element_blank(), +# panel.border = element_blank(), panel.background=element_blank(), +# axis.text.y = element_text(size=y.size), axis.text.x = element_text(size=x.size, angle = 90, hjust = 1), +# axis.title.x = element_blank(), +# legend.title=element_text(size=leg.title.size), +# legend.text=element_text(size=leg.text.size), # legend text size +# legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20), +# legend.key.size=unit(15, "pt"), # Change key size in the legend +# legend.key = element_blank(), +# legend.position=c(.1, .90), legend.background = element_blank(), legend.box.background = element_blank(), +# plot.margin = unit(c(.5,1,.25,.25), "cm")) +# +# p + facet_grid(region ~ .) +# +# +# return(p) +# } +# +# +# +# +# plot_cum_imports <- function(data=import_results_desttime_cum, region_ = "All", t_limits=as.Date(c("2020-01-01","2020-01-27")), +# y.size = 9, x.size = 9, +# leg.text.size = 12, leg.title.size = 14, +# rep_col = "indianred2", est_col = "blue3", est_ribbon_col = "blue3", est_ribbon_alpha=0.25, +# time_int = 5, # time interval for x-axis +# plot_legend=TRUE, x_axis=TRUE){ +# # Subset by region if wanted +# if (region_!="All"){ +# data <- data %>% filter(region==region_) +# } +# # Limit the time of the plots +# if (!is.na(t_limits[1])){ +# data <- data %>% mutate(t = as.Date(t)) %>% +# filter(t >= as.Date(t_limits[1]) & as.Date(t) <= as.Date(t_limits[2])) %>% +# mutate(t_num = as.integer(as.factor(t))) +# } +# t_values <- as.character(sort(data$t)) +# +# p <- ggplot(data=data, aes(x=t_num, y=cum_import_mean)) + +# geom_line(data=data, aes(color='Detected', linetype="Detected"), size=1.2) + +# geom_ribbon(data=data, aes(ymin=cum_import_ll, ymax=cum_import_ul), alpha=est_ribbon_alpha, fill=est_ribbon_col) + +# scale_x_continuous(breaks=seq(1,length(t_values),time_int), +# labels=t_values[seq(1,length(t_values),time_int)]) + +# ylab("Detected imported nCoV cases (n)") + +# #scale_colour_manual(values=c(Reported=rep_col, Estimated=est_col), guide="none") + +# #scale_linetype_manual(values=c("solid","11"), guide=guide_legend(title=element_blank())) + +# scale_colour_manual(values=c(Detected=est_col), guide="none") + +# scale_linetype_manual(values=c("solid"), guide=guide_legend(title=element_blank())) + +# #scale_y_continuous(expand = c(0,0)) + +# theme(axis.line = element_line(colour = "black"), +# panel.grid.major = element_blank(), panel.grid.minor = element_blank(), +# panel.border = element_blank(), panel.background=element_blank(), +# axis.text.y = element_text(size=y.size), +# axis.text.x = element_text(size=x.size, angle = 90, hjust = 1, vjust=.5, margin=margin(t=5)), +# axis.title.x = element_blank(), +# legend.title=element_text(size=leg.title.size), +# legend.text=element_text(size=leg.text.size), # legend text size +# legend.margin=margin(0,0,0,0), legend.box.margin=margin(-20,-20,-20,-20), +# legend.key.size=unit(15, "pt"), # Change key size in the legend +# legend.key = element_blank(), +# legend.position=c(.075, .80), legend.background = element_blank(), legend.box.background = element_blank(), +# plot.title = element_text(size=leg.title.size, face="bold", vjust=-10, hjust = 0.025), +# plot.margin = unit(c(-.75,.25,0,0.25), "cm")) +# +# if (region_ != "All"){ +# p <- p + ggtitle(region_) +# } +# if (plot_legend==FALSE){ +# p <- p + theme(legend.position = "none") +# } +# if (x_axis==FALSE){ +# p <- p + theme(axis.text.x=element_blank(), #axis.line.x=element_blank(), +# axis.ticks.x=element_blank(), axis.title.x=element_blank()) +# } +# return(p) +# } +# +# + + + + + + +# # PLOT SPECIFICS +# +# y.size = x.size = 9 +# leg.text.size = 12 +# leg.title.size = 14 +# +# rep_col <- "indianred2" +# est_col <- "blue3" +# est_ribbon_col <- "blue3" +# est_ribbon_alpha <- 0.2 + +# +# # PLOT TOTAL IMPORTATIONS ------------------------------------------------- +# +# p_total <- plot_imports(data=import_results_desttime, region_ = "All", t_limits=t_limits, +# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14, +# rep_col = "indianred2", +# est_col = "blue3", +# est_ribbon_col = "blue3", +# est_ribbon_alpha=0.25, +# plot_legend=TRUE) +# #plot(p_total) +# +# +# p_total_barchart <- plot_imports_barchart(data=import_results_desttime, region_ = "All", t_limits=t_limits, +# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14, +# rep_col = "indianred2", +# est_col = "blue3", +# plot_legend=TRUE) +# #plot(p_total_barchart) +# +# +# +# p_cum <- plot_cum_imports(data=import_results_desttime_cum, region_ = "All", t_limits=t_limits, +# y.size = 9, x.size = 9, leg.text.size = 12, leg.title.size = 14, +# rep_col = "indianred2", +# est_col = "blue3", +# est_ribbon_col = "blue3", +# est_ribbon_alpha=0.25, +# plot_legend=TRUE) +# +# # Plot 2 plots together +# #gridExtra::grid.arrange(p_total, p_cum, nrow=2) +# +# +# +# p_stacked_barchart <- plot_imports_stackedsource(data=import_results_sourcetime, t_limits=t_limits, +# y.size = 8, x.size = 8, leg.text.size = 6, leg.title.size = 8, +# rep_col = "indianred2", +# est_col = "blue3") +# # plot(p_stacked_barchart) +# +# p_stackeddest_barchart <- plot_imports_stackeddest(data=import_results_desttime, t_limits=t_limits, +# y.size = 8, x.size = 8, leg.text.size = 6, leg.title.size = 8, +# rep_col = "indianred2", +# est_col = "blue3") +# +# +# + + + + +# +# +# # PLOT ESTIMATED VS REPORTED ---------------------------------------------- +# +# # Reported from CDC +# shen_cases <- read_csv("data/shenzhen_data/shenzhen_case_counts.csv") +# shen_cases <- shen_cases %>% mutate(cum_cases = cumsum(count)) +# # From Linelists +# ll_data <- read_csv("data/linelist_current.csv") +# shen_rows <- apply(ll_data, 1, FUN=function(x) sum(grepl("shenzhen", x, ignore.case = TRUE)))>0 +# ll_data_shenzhen <- ll_data[shen_rows, ] +# shen_data_aggr <- ll_data_shenzhen %>% count(date_confirmation) +# rm(ll_data, ll_data_shenzhen, shen_rows) +# +# shen_counts <- full_join(shen_cases %>% rename(count_CDC = count), +# shen_data_aggr %>% rename(count_ll = n, date=date_confirmation), +# by=c("date"="date")) +# shen_counts[is.na(shen_counts)] <- 0 +# +# # Merge with estimates +# shen_counts_all <- full_join(shen_counts, +# import_results_desttime %>% select(date=t, import_mean, import_ll, import_ul) %>% mutate(date = as.Date(date)), by=c("date")) +# shen_counts_all <- full_join(shen_counts_all, +# import_results_desttime_cum %>% select(date=t, cum_import_mean, cum_import_ll, cum_import_ul) %>% mutate(date = as.Date(date)), by=c("date")) +# +# +# # Limit the time of the plots +# if (!is.na(t_limits[1])){ +# shen_counts_all <- shen_counts_all %>% rowwise %>% filter(as.Date(date) >= as.Date(t_limits[1]) & as.Date(date) <= as.Date(t_limits[2])) %>% as.data.frame() +# } +# +# +# p_incid_shen_inclest <- ggplot(shen_counts_all %>% mutate(label1 = "CDC counts", label2 = "Linelist counts", label3="Est. detected imports"), +# aes(x=date, y=count_CDC)) + +# geom_bar(stat="identity", aes(fill=label1)) + +# geom_point(aes(x=date,y=count_ll, shape=label2, color=label2), size=2) + +# geom_point(aes(x=date,y=import_mean, shape=label3, color=label3), size=2) + +# scale_color_manual(values=c("maroon","green")) + +# scale_fill_manual(values=c("navy")) + +# ylab("Reported Cases") + ggtitle("Shenzhen Reported nCoV Cases") + +# theme_classic() + +# theme(#legend.background = element_rect(color="grey"), +# legend.position = c(0.05, 1), +# legend.justification = c(0, 1), +# legend.title = element_blank()) +# #plot(p_incid_shen_inclest) +# +# +# +# # Plot cumulative cases in Shenzhen +# # Get cumulative case counts in each +# shen_counts_cum <- shen_counts_all %>% arrange(as.character(date)) %>% mutate(cum_CDC = cumsum(count_CDC), cum_ll = cumsum(count_ll)) +# +# +# p_cum_shen_inclest <- ggplot(shen_counts_cum %>% mutate(label1 = "CDC cumulative", label2 = "Linelist cumulative", label3="Est. detected imports"), +# aes(x=date, y=cum_CDC)) + +# geom_bar(stat="identity", aes(fill=label1)) + +# geom_point(aes(x=date,y=cum_ll, shape=label2, color=label2), size=2) + +# geom_point(aes(x=date,y=cum_import_mean, shape=label3, color=label3), size=2) + +# scale_color_manual(values=c("maroon","green")) + +# scale_fill_manual(values=c("navy")) + +# ylab("Cumulative Cases") + ggtitle("Shenzhen Cumulative nCoV Cases") + +# coord_cartesian() + +# theme_classic() + +# theme(#legend.background = element_rect(color="grey"), +# legend.position = c(0.05, 1), +# legend.justification = c(0, 1), +# legend.title = element_blank()) +# #plot(p_cum_shen_inclest) +# +# diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/setup_pop_data.R b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/setup_pop_data.R new file mode 100644 index 000000000..fd30c8a97 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/setup_pop_data.R @@ -0,0 +1,126 @@ + +# SETUP POPULATION DATA - FROM WORLDPOP + +if(!require('tidyverse')) install.packages('tidyverse'); library(tidyverse) + + +# CHINA PROVINCE DATA ----------------------------------------------------- + +make_all_pop_data <- function(){ + + + china_pop_data <- read_csv("data-raw/China_popsize_census_2010.csv") + china_pop_data <- china_pop_data %>% rename(loc = province, population=pop) + china_pop_data <- china_pop_data %>% mutate(country = "China", country_code="CHN") %>% rename(pop = population) + write_csv(china_pop_data, "data-raw/china_province_pop_data.csv") + + + # COUNTRY DATA + + country_pop_url <- "https://pkgstore.datahub.io/JohnSnowLabs/population-figures-by-country/population-figures-by-country-csv_csv/data/630580e802a621887384f99527b68f59/population-figures-by-country-csv_csv.csv" + country_pop_data <- readr::read_csv(country_pop_url) + + country_pop_data <- country_pop_data %>% gather(key="year", value="pop", -Country, -Country_Code) %>% + mutate(year = as.integer(substr(year, 6,9))) + + #take only the most recent year + country_pop_data <- country_pop_data %>% rename(country = Country, country_code=Country_Code) %>% + filter(!is.na(year) & !is.na(pop)) %>% + group_by(country, country_code) %>% + filter(year == max(year)) %>% ungroup() + + + + # US STATE DATA + # - source: https://www.census.gov/data/tables/time-series/demo/popest/2010s-state-total.html + us_state_pop <- readr::read_csv("data-raw/us_state_pop.csv") %>% rename(state_name=state) + us_state_pop <- full_join(us_state_pop, + data.frame(state=state.abb, state_name=state.name)) %>% + mutate(state = as.character(state)) + us_state_pop$state[grepl("District", us_state_pop$state_name, ignore.case = TRUE)] <- "DC" + us_state_pop$state[grepl("Puerto", us_state_pop$state_name, ignore.case = TRUE)] <- "PR" + us_state_pop <- us_state_pop %>% rename(pop = population) + + + + # MERGE + + colnames(country_pop_data) + colnames(china_pop_data) + colnames(us_state_pop) + + # ~ Country and China Province + pop_data <- full_join(country_pop_data %>% rename(country_name=country, country=country_code) %>% mutate(location = country) %>% select(-year), + china_pop_data %>% rename(country_name=country, country=country_code), + by=c("location"="loc", "pop"="pop", "country"="country", "country_name")) %>% mutate(pop = as.integer(pop)) + + # ~ US State + colnames(pop_data) + pop_data <- full_join(pop_data, + us_state_pop %>% + mutate(country_name="United States of America", country="USA") %>% + rename(location = state)) + + # fix some randoms + other_pops <- read_csv("data-raw/other_locations_pop.csv") + pop_data <- bind_rows(pop_data, other_pops) + pop_data <- pop_data %>% rename(source = location) + + + write_csv(pop_data, "data/pop_data.csv") + +} + + + +# Function to get population data wanted +##' +##' Return the population of the country or Chinese province of interest. +##' +##' @param loc The location or locations of which population is needed. This can be a vector. +##' +##' @return a named vector of populations of locations +##' +get_population <- function(loc = "Singapore"){ + pop_data <- readr::read_csv("data/pop_data.csv", col_types = cols()) + + match_ <- match(loc, pop_data$location) + + pops <- as.integer(pop_data$population[match_]) + names(pops) <- loc + + return(pops) +} + +## EXAMPLE: +# get_population(c("Aruba", "India", "Germany")) + + + + + +# Loading World Pop data +# {load("../Data/WorldPop_longform_1960.to.2017.RData") +# WorldPop <- WorldPop %>% mutate(Country.Code = countrycode(Country, origin = "country.name", destination = "iso3c")) %>% +# filter(!is.na(Country.Code)) +# +# # if (!any(WorldPop$Year == 2016)) WorldPop <- WorldPop %>% union(filter(WorldPop, Year == 2015) %>% mutate(Year = 2016)) # Assuming 2015 population for 2016 +# # Extrapolating for pop of 2017 +# for (this.country in unique(WorldPop$Country)) { +# # print(this.country) +# +# Fit <- lm(Population ~ Year, data = filter(WorldPop, Country == this.country, Year >= 2008)) +# +# Correlate.vars <- data.frame(Country = this.country, +# Country.Code = countrycode(this.country, origin = "country.name", destination = "iso3c"), +# Year = 2018:2019) +# +# Preds <- predict(Fit, newdata = Correlate.vars) +# +# New.Rows <- Correlate.vars %>% mutate(Population = round(Preds)) +# +# WorldPop <- WorldPop %>% bind_rows(New.Rows) +# } +# Years_pop <- sort(unique(WorldPop$Year)) +# Countries_pop <- str_replace_all(WorldPop$Country, " ", ".") %>% unique +# Country.Codes_pop <- WorldPop$Country.Code %>% unique} diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/testing_import.R b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/testing_import.R new file mode 100644 index 000000000..75030ca13 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/testing_import.R @@ -0,0 +1,214 @@ +library(covidImportation) +#debugonce(setup_and_run_importations) +t1 <- Sys.time() +WC_import <- setup_and_run_importations(dest="AZ",# c("CA","OR","WA","NV","AZ"), + dest_type=c("state"), #,"city","airport", "country"), + dest_country="USA", + dest_aggr_level=c("airport"), #, "city", "state", "country", "metro"), + project_name="WestCoast_import", + first_date = ISOdate(2019,12,1), + last_date = Sys.time(), + update_case_data=TRUE, + case_data_dir = "data/case_data", + check_saved_data=TRUE, + save_case_data=TRUE, + get_travel=TRUE, + n_sim=100, + cores=5, + n_top_dests=25, + get_detection_time=FALSE, + travel_dispersion=3, + allow_travel_variance=FALSE, + print_progress=TRUE, + param_list=list(incub_mean_log=log(5.89), + incub_sd_log=log(1.74), + inf_period_nohosp_mean=15, + inf_period_nohosp_sd=5, + inf_period_hosp_shape=0.75, + inf_period_hosp_scale=5.367, + p_report_source=c(0.05, 0.25), + shift_incid_days=-10, + delta=1)) +print(paste0('Simulation required ', round(as.list(proc.time() - t1)$elapsed/60, 3), ' minutes')) + +save(WC_import, "output/WC_import_100sims.rda") + +(size_ <- format(object.size(WC_import), "Mb")) + +nb_pars <- calc_nb_import_pars(WC_import$importation_sims$importation_sim, cores=6) + +importation_sim <- UT_import$importation_sims$importation_sim + + + + + + + + + + + + + + + +dest=c("CA","OR","WA","NV") +dest_type=c("state") #,"city","airport", "country"), +dest_country="USA" +dest_aggr_level=c("airport") #, "city", "state", "country", "metro"), +project_name="WestCoast_import" +version="global" +batch="1st" +first_date = ISOdate(2019,12,1) +last_date = Sys.time() +update_case_data=TRUE +case_data_dir = "data/case_data" +check_saved_data=TRUE +save_case_data=TRUE +get_travel=TRUE +end_date=Sys.Date() +n_sim=10 +cores=4 +get_detection_time=FALSE +travel_dispersion=3 +allow_travel_variance=FALSE +print_progress=TRUE +get_nb_params = TRUE +param_list=list(incub_mean_log=log(5.89), + incub_sd_log=log(1.74), + inf_period_nohosp_mean=15, + inf_period_nohosp_sd=5, + inf_period_hosp_shape=0.75, + inf_period_hosp_scale=5.367, + p_report_source=c(0.05, 0.25), + shift_incid_days=-10, + delta=1) + + + + + + +test1 <- run_daily_import_model(input_data, + travel_data_monthly, + travel_data_daily, + travel_dispersion=3, + travel_restrictions=NULL, + allow_travel_variance=FALSE, + tr_inf_redux=0, + get_detection_time=FALSE, + time_inftotravel, + time_inftodetect, + project_name=NULL, batch=NULL, version=NULL, + output_dir = file.path("output", paste0(paste(dest, collapse="+"),"_", as.Date(Sys.Date()))), + param_list=list(incub_mean_log=log(5.89), + incub_sd_log=log(1.74), + inf_period_nohosp_mean=15, + inf_period_nohosp_sd=5, + inf_period_hosp_shape=0.75, + inf_period_hosp_scale=5.367)) + + + + + + + + + + + + + + + + + + +# testing +library(covidImportation) + +incid_data <- get_incidence_data(first_date = ISOdate(2019,12,1), + last_date = Sys.time(), + update_case_data=TRUE, + case_data_dir = "data/case_data", + check_saved_data=TRUE, + save_data=TRUE) + + + +covidImportation:::update_JHUCSSE_github_data(last_date = Sys.time(), + case_data_dir = "data/case_data", + check_saved_data=TRUE, + save_data=TRUE) + + + + + + + + + + + + + + + + + + + + + +# TEST NEW VERSION -------------------------------------------------------- + + +library(covidImportation) + +# First run the setup + +dest <- "UT" +dest=c("CA","OR","WA","NV","AZ") +setup_res <- covidImportation::setup_importations(dest=dest, + dest_type=c("state"), #,"city","airport", "country"), + dest_country="USA", + dest_aggr_level=c("airport"), #, "city", "state", "country", "metro"), + first_date = ISOdate(2019,12,1), + last_date = Sys.time(), + update_case_data=TRUE, + case_data_dir = "data/case_data", + output_dir = file.path("output", paste0(paste(dest, collapse="+"),"_", as.Date(Sys.Date()))), + check_saved_data=TRUE, + save_case_data=TRUE, + get_travel=TRUE, + n_top_dests=Inf, + travel_dispersion=3, + param_list=list(incub_mean_log=log(5.89), + incub_sd_log=log(1.74), + inf_period_nohosp_mean=15, + inf_period_nohosp_sd=5, + inf_period_hosp_shape=0.75, + inf_period_hosp_scale=5.367, + p_report_source=c(0.05, 0.25), + shift_incid_days=-10, + delta=1)) + + +sim_res <- covidImportation::run_importations( + n_sim=10, + cores=5, + get_detection_time=FALSE, + travel_dispersion=3, + allow_travel_variance=FALSE, + print_progress=TRUE, + output_dir = file.path("output", paste0(paste(dest, collapse="+"),"_", as.Date(Sys.Date()))), + param_list=list(incub_mean_log=log(5.89), + incub_sd_log=log(1.74), + inf_period_nohosp_mean=15, + inf_period_nohosp_sd=5, + inf_period_hosp_shape=0.75, + inf_period_hosp_scale=5.367, + p_report_source=c(0.05, 0.25))) diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/testing_import_fullUSA.R b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/testing_import_fullUSA.R new file mode 100644 index 000000000..e838e958a --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/covidImportation/testing_import_fullUSA.R @@ -0,0 +1,52 @@ + + +# TEST NEW VERSION -------------------------------------------------------- + + +library(covidImportation) + +# First run the setup + +dest <- "UT" +dest=c("CA","OR","WA","NV","AZ") +dest <- state.abb +setup_res <- covidImportation::setup_importations(dest=dest, + dest_type=c("state"), #,"city","airport", "country"), + dest_country="USA", + dest_aggr_level=c("airport"), #, "city", "state", "country", "metro"), + first_date = ISOdate(2019,12,1), + last_date = ISOdate(2020,3,15), + update_case_data=TRUE, + case_data_dir = "data/case_data", + output_dir = file.path("output", paste0("fullUSA","_", as.Date(Sys.Date()))), + check_saved_data=TRUE, + save_case_data=TRUE, + get_travel=TRUE, + n_top_dests=Inf, + travel_dispersion=3, + param_list=list(incub_mean_log=log(5.89), + incub_sd_log=log(1.74), + inf_period_nohosp_mean=15, + inf_period_nohosp_sd=5, + inf_period_hosp_mean_log=1.23, + inf_period_hosp_sd_log=0.79, + p_report_source=c(0.05, 0.25), + shift_incid_days=-10, + delta=1)) + + +sim_res <- covidImportation::run_importations( + n_sim=2, + cores=2, + get_detection_time=FALSE, + travel_dispersion=3, + allow_travel_variance=FALSE, + print_progress=TRUE, + output_dir = file.path("output", paste0("fullUSA","_", as.Date(Sys.Date()))), + param_list=list(incub_mean_log=log(5.89), + incub_sd_log=log(1.74), + inf_period_nohosp_mean=15, + inf_period_nohosp_sd=5, + inf_period_hosp_mean_log=1.23, + inf_period_hosp_sd_log=0.79, + p_report_source=c(0.05, 0.25))) diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/DESCRIPTION b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/DESCRIPTION new file mode 100644 index 000000000..b182c3d25 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/DESCRIPTION @@ -0,0 +1,35 @@ +Package: globaltoolboxlite +Title: Identify Location Names and Link with Other Data, lite version +Version: 0.0.0.9000 +Authors@R: c( person("Shaun", "Truelove", email = + "shauntruelove@jhu.edu", role = c("aut")), person("Joshua", + "Kaminsky", email = "jkaminsky@jhu.edu", role = c("aut", "cre"))) +Description: Allows users to standardize location names. +Depends: R (>= 3.4) +Imports: countrycode, dplyr, stringdist, stringr, glue, lubridate, + tibble, tidyr, reshape2, stats, rlang +Suggests: readxl, testthat, covr, httr +License: GPL (>=2) +Encoding: UTF-8 +LazyData: true +RoxygenNote: 7.1.0 +Collate: 'string_manipulation.R' 'get_country.R' 'get_region.R' + 'get_who_disease_incidence.R' +RemoteType: github +RemoteHost: api.github.com +RemoteRepo: globaltoolboxlite +RemoteUsername: HopkinsIDD +RemoteRef: master +RemoteSha: bdc856e7aec629d2960b2b72618d9e0b49a5898e +GithubRepo: globaltoolboxlite +GithubUsername: HopkinsIDD +GithubRef: master +GithubSHA1: bdc856e7aec629d2960b2b72618d9e0b49a5898e +NeedsCompilation: no +Packaged: 2020-04-26 15:42:40 UTC; root +Author: Shaun Truelove [aut], Joshua Kaminsky [aut, cre] +Maintainer: Joshua Kaminsky +Built: R 3.6.3; ; 2020-04-26 15:42:41 UTC; unix +InstallAgent: packrat 0.5.0 +InstallSource: github +Hash: 471f116c0a354436b3e1c6cfb3ce5bc2 diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/Meta/Rd.rds b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/Meta/Rd.rds new file mode 100644 index 000000000..ec6c9c3c8 Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/Meta/Rd.rds differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/Meta/data.rds b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/Meta/data.rds new file mode 100644 index 000000000..7a579a7a6 Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/Meta/data.rds differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/Meta/features.rds b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/Meta/features.rds new file mode 100644 index 000000000..772f787fd Binary files /dev/null and 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b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/Meta/nsInfo.rds differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/Meta/package.rds b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/Meta/package.rds new file mode 100644 index 000000000..eecf41b89 Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/Meta/package.rds differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/NAMESPACE b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/NAMESPACE new file mode 100644 index 000000000..e1313022e --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/NAMESPACE @@ -0,0 +1,20 @@ +# Default NAMESPACE created by R +# Remove the previous line if you edit this file + +# Export all names +exportPattern(".") + +# Import all packages listed as Imports or Depends +import( + countrycode, + dplyr, + stringdist, + stringr, + glue, + lubridate, + tibble, + tidyr, + reshape2, + stats, + rlang +) diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/R/globaltoolboxlite b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/R/globaltoolboxlite new file mode 100644 index 000000000..3b65e3cbb --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/R/globaltoolboxlite @@ -0,0 +1,27 @@ +# File share/R/nspackloader.R +# Part of the R package, http://www.R-project.org +# +# Copyright (C) 1995-2012 The R Core Team +# +# This program is free software; you can redistribute it and/or modify +# it under the terms of the GNU General Public License as published by +# the Free Software Foundation; either version 2 of the License, or +# (at your option) any later version. +# +# This program is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +# GNU General Public License for more details. +# +# A copy of the GNU General Public License is available at +# http://www.r-project.org/Licenses/ + +local({ + info <- loadingNamespaceInfo() + pkg <- info$pkgname + ns <- .getNamespace(as.name(pkg)) + if (is.null(ns)) + stop("cannot find namespace environment for ", pkg, domain = NA); + dbbase <- file.path(info$libname, pkg, "R", pkg) + lazyLoad(dbbase, ns, filter = function(n) n != ".__NAMESPACE__.") +}) diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/R/globaltoolboxlite.rdb b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/R/globaltoolboxlite.rdb new file mode 100644 index 000000000..d4f24e736 Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/R/globaltoolboxlite.rdb differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/R/globaltoolboxlite.rdx b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/R/globaltoolboxlite.rdx new file mode 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/dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/data/Rdata.rdx differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/all_countries.csv b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/all_countries.csv new file mode 100644 index 000000000..4ba89008a --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/all_countries.csv @@ -0,0 +1,247 @@ +ABW +AFG +AGO +AIA +ALA +ALB +AND +ANT +ARE +ARG +ARM +ASM +ATA +ATF +ATG +AUS +AUT +AZE +BDI +BEL +BEN +BFA +BGD +BGR +BHR +BHS +BIH +BLM +BLR +BLZ +BMU +BOL +BRA +BRB +BRN +BTN +BVT +BWA +CAF +CAN +CCK +CHE +CHL +CHN +CIV +CMR +COD +COG +COK +COL +COM +CPV +CRI +CUB +CXR +CYM +CYP +CZE +DEU +DJI +DMA +DNK +DOM +DZA +ECU +EGY +ERI +ESH +ESP +EST +ETH +FIN +FJI +FLK +FRA +FRO +FSM +GAB +GBR +GEO +GGY +GHA +GIB +GIN +GLP +GMB +GNB +GNQ +GRC +GRD +GRL +GTM +GUF +GUM +GUY +HKG +HMD +HND +HRV +HTI +HUN +IDN +IMN +IND +IOT +IRL +IRN +IRQ +ISL +ISR +ITA +JAM +JEY +JOR +JPN +KAZ +KEN +KGZ +KHM +KIR +KNA +KOR +KWT +LAO +LBN +LBR +LBY +LCA +LIE +LKA +LSO +LTU +LUX +LVA +MAC +MAF +MAR +MCO +MDA +MDG +MDV +MEX +MHL +MKD +MLI +MLT +MMR +MNE +MNG +MNP +MOZ +MRT +MSR +MTQ +MUS +MWI +MYS +MYT +NAM +NCL +NER +NFK +NGA +NIC +NIU +NLD +NOR +NPL +NRU +NZL +OMN +PAK +PAN +PCN +PER +PHL +PLW +PNG +POL +PRI +PRK +PRT +PRY +PSE +PYF +QAT +REU +ROU +RUS +RWA +SAU +SDN +SEN +SGP +SGS +SHN +SJM +SLB +SLE +SLV +SMR +SOM +SPM +SRB +SSD +STP +SUR +SVK +SVN +SWE +SWZ +SYC +SYR +TCA +TCD +TGO +THA +TJK +TKL +TKM +TLS +TON +TTO +TUN +TUR +TUV +TWN +TZA +UGA +UKR +UMI +URY +USA +UZB +VAT +VCT +VEN +VGB +VIR +VNM +VUT +WLF +WSM +YEM +ZAF +ZMB +ZWE diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/alt_country_names.csv b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/alt_country_names.csv new file mode 100644 index 000000000..35cf23edb --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/alt_country_names.csv @@ -0,0 +1,282 @@ +"ID","ISO3","name1","name2","name3","name4","name5","name6","name7","name8" +1,"afg","Afghanistan","Islamic State of Afghanistan","","","","","",NA +2,"ala","Aland Islands","","","","","","",NA +3,"alb","Albania","Republic of Albania","","","","","",NA +4,"dza","Algeria","People's Democratic Republic of Algeria","","","","","",NA +5,"asm","American Samoa","Territory of American Samoa","","","","","",NA +6,"and","Andorra","Principality of Andorra","","","","","",NA +7,"ago","Angola","Republic of Angola","","","","","",NA +8,"aia","Anguilla","","","","","","",NA +9,"ata","Antarctica","","","","","","",NA +10,"atg","Antigua and Barbuda","","","","","","",NA +11,"arg","Argentina","Argentine Republic","","","","","",NA +12,"arm","Armenia","Republic of Armenia","","","","","",NA +13,"abw","Aruba","","","","","","",NA +277,"","Ascension Island","","","","","","",NA +253,"","Ashmore and Cartier Islands","Territory of Ashmore and Cartier Islands","","","","","",NA +14,"aus","Australia","Commonwealth of Australia","","","","","",NA +15,"aut","Austria","Republic of Austria","","","","","",NA +16,"aze","Azerbaijan","Republic of Azerbaijan","","","","","",NA +17,"bhs","Bahamas","Bahamas, The","Commonwealth of the Bahamas","The Bahamas","","","",NA +18,"bhr","Bahrain","State of Bahrain","","","","","",NA +254,"","Baker Island","","","","","","",NA +19,"bgd","Bangladesh","People's Republic of Bangladesh","","","","","",NA +20,"brb","Barbados","","","","","","",NA +255,"","Bassas da India","","","","","","",NA +21,"blr","Belarus","Republic of Belarus","","","","","",NA +22,"bel","Belgium","Kingdom of Belgium","","","","","",NA +23,"blz","Belize","","","","","","",NA +24,"ben","Benin","Republic of Benin","","","","","",NA +25,"bmu","Bermuda","","","","","","",NA +26,"btn","Bhutan","Kingdom of Bhutan","","","","","",NA +27,"bol","Bolivia, Plurinational State of","Bolivia (Plurinational State of)","Bolivia","Republic of Bolivia","","","",NA +28,"bes","Bonaire, Saint Eustatius and Saba","","","","","","",NA +278,"","Bonaire, Sint Eustatius and Saba","","","","","","",NA +29,"bih","Bosnia and Herzegovina","Bosnia-Herzegovina","Bosnia Herzegovena","","","","",NA +30,"bwa","Botswana","Republic of Botswana","","","","","",NA +31,"","Bouvet Island","","","","","","",NA +32,"bra","Brazil","Federative Republic of Brazil","","","","","",NA +33,"iot","British Indian Ocean Territory","","","","","","",NA +34,"brn","Brunei Darussalam","Brunei","Negara Brunei Darussalam","","","","",NA +35,"bgr","Bulgaria","","","","","","",NA +36,"bfa","Burkina Faso","","","","","","",NA +37,"bdi","Burundi","Republic of Burundi","","","","","",NA +38,"khm","Cambodia","Kingdom of Cambodia","","","","","",NA +39,"cmr","Cameroon","Republic of Cameroon","","","","","",NA +40,"can","Canada","","","","","","",NA +41,"cpv","Cape Verde","Republic of Cape Verde","","","","","",NA +42,"cym","Cayman Islands","","","","","","",NA +43,"caf","Central African Republic","Central African Rep.","","","","","",NA +44,"tcd","Chad","Republic of Chad","","","","","",NA +250,"","Channel Islands","","","","","","",NA +45,"chl","Chile","Republic of Chile","","","","","",NA +46,"chn","China","People's Republic of China","PRC","","","","",NA +47,"","Christmas Island","Territory of Christmas Island","","","","","",NA +256,"clp","Clipperton Island","","","","","","",NA +48,"","Cocos (Keeling) Islands","Territory of Cocos (Keeling) Islands","Keeling Islands","Cocos Islands","","","",NA +49,"col","Colombia","Republic of Colombia","","","","","",NA +50,"com","Comoros","Federal Islamic Republic of the Comoros","","","","","",NA +51,"cog","Congo","Congo (Brazzaville)","Republic of the Congo","Congo, Republic of the","The Republic of the Congo","Congo, Rep.","Republic of Congo","Congo, Republic of" +52,"cod","Congo, The Democratic Republic of the","Democratic Republic of the Congo","Congo (Kinshasa)","Congo, Democratic Republic of the","The Democratic Republic of the Congo","Congo, Dem. Rep.","Democratic Republic of Congo","Congo, Democratic Republic of" +53,"cok","Cook Islands","","","","","","",NA +257,"","Coral Sea Islands","Coral Sea Islands Territory","","","","","",NA +54,"cri","Costa Rica","Republic of Costa Rica","","","","","",NA +55,"civ","Cote d'Ivoire","Republic of Cote D'Ivoire","Ivory Coast","Cote d Ivoire","","","",NA +56,"hrv","Croatia","Republic of Croatia","","","","","",NA +57,"cub","Cuba","Republic of Cuba","","","","","",NA +58,"cuw","Curacao","","","","","","",NA +59,"cyp","Cyprus","Republic of Cyprus","","","","","",NA +60,"cze","Czech Republic","","","","","","",NA +61,"dnk","Denmark","Kingdom of Denmark","","","","","",NA +62,"dji","Djibouti","Republic of Djibouti","","","","","",NA +63,"dma","Dominica","Commonwealth of Dominica","","","","","",NA +64,"dom","Dominican Republic","","","","","","",NA +65,"ecu","Ecuador","Republic of Ecuador","","","","","",NA +66,"egy","Egypt","Arab Republic of Egypt","Egypt, Arab Rep.","","","","",NA +67,"slv","El Salvador","Republic of El Salvador","","","","","",NA +68,"gnq","Equatorial Guinea","Republic of Equatorial Guinea","","","","","",NA +69,"eri","Eritrea","State of Eritrea","","","","","",NA +70,"est","Estonia","Republic of Estonia","","","","","",NA +71,"eth","Ethiopia","Federal Democratic Republic of Ethiopia","","","","","",NA +258,"","Europa Island","","","","","","",NA +279,"","European Union","","","","","","",NA +72,"flk","Falkland Islands (Malvinas)","Falkland Islands (Islas Malvinas)","","","","","",NA +73,"fro","Faroe Islands","Faeroe Islands","","","","","",NA +74,"fji","Fiji","Republic of the Fiji Islands","","","","","",NA +75,"fin","Finland","Republic of Finland","","","","","",NA +76,"fra","France","French Republic","France (metropolitan)","","","","",NA +77,"guf","French Guiana","Department of Guiana","French Guyana","","","","",NA +78,"pyf","French Polynesia","Territory of French Polynesia","","","","","",NA +79,"atf","French Southern Territories","French Southern and Antarctic Lands","Territory of the French Southern and Antarctic Lands","","","","",NA +80,"gab","Gabon","Gabonese Republic","","","","","",NA +81,"gmb","Gambia","Gambia, The","Republic of the Gambia","The Gambia","","","",NA +259,"gaza","Gaza Strip","Gaza","","","","","",NA +82,"geo","Georgia","","","","","","",NA +83,"deu","Germany","Federal Republic of Germany","","","","","",NA +84,"gha","Ghana","Republic of Ghana","","","","","",NA +85,"gib","Gibraltar","","","","","","",NA +260,"","Glorioso Islands","","","","","","",NA +86,"grc","Greece","Hellenic Republic","","","","","",NA +87,"grl","Greenland","","","","","","",NA +88,"grd","Grenada","","","","","","",NA +89,"glp","Guadeloupe","Department of Guadeloupe","France, Guadeloupe","","","","",NA +90,"gum","Guam","Territory of Guam","","","","","",NA +91,"gtm","Guatemala","Republic of Guatemala","","","","","",NA +92,"ggy","Guernsey","Bailiwick of Guernsey","","","","","",NA +93,"gin","Guinea","Republic of Guinea","","","","","",NA +94,"gnb","Guinea-Bissau","Republic of Guinea-Bissau","Guinea Bissau","","","","",NA +95,"guy","Guyana","Co-operative Republic of Guyana","","","","","",NA +96,"hti","Haiti","Republic of Haiti","","","","","",NA +97,"","Heard Island and Mcdonald Islands","Territory of Heard Island and McDonald Islands","","","","","",NA +98,"vat","Holy See (Vatican City State)","Holy See","Vatican City","State of the Vatican City","Holy See (Vatican City)","","",NA +99,"hnd","Honduras","Republic of Honduras","","","","","",NA +100,"hkg","Hong Kong","China, Hong Kong Special Administrative Region","Hong Kong S.A.R.","Hong Kong Special Administrative Region","Hong Kong Special Administrative Region of China","Hong Kong SAR, China","",NA +261,"","Howland Island","","","","","","",NA +101,"hun","Hungary","Republic of Hungary","","","","","",NA +102,"isl","Iceland","Republic of Iceland","","","","","",NA +103,"ind","India","Republic of India","","","","","",NA +104,"idn","Indonesia","Republic of Indonesia","","","","","",NA +105,"irn","Iran, Islamic Republic of","Iran (Islamic Republic of)","Iran","Islamic Republic of Iran","Iran, Islamic Rep.","","",NA +106,"irq","Iraq","Republic of Iraq","","","","","",NA +107,"irl","Ireland","","","","","","",NA +108,"imn","Isle of Man","","","","","","",NA +109,"isr","Israel","State of Israel","","","","","",NA +110,"ita","Italy","Italian Republic","","","","","",NA +111,"jam","Jamaica","","","","","","",NA +262,"","Jan Mayen","","","","","","",NA +112,"jpn","Japan","","","","","","",NA +263,"","Jarvis Island","","","","","","",NA +113,"jey","Jersey","Bailiwick of Jersey","","","","","",NA +264,"","Johnston Atoll","","","","","","",NA +114,"jor","Jordan","Hashemite Kingdom of Jordan","","","","","",NA +265,"","Juan De Nova Island","","","","","","",NA +115,"kaz","Kazakhstan","Republic of Kazakhstan","Kazakstan","","","","",NA +116,"ken","Kenya","Republic of Kenya","","","","","",NA +266,"","Kingman Reef","","","","","","",NA +117,"kir","Kiribati","Republic of Kiribati","","","","","",NA +118,"prk","Korea, Democratic People's Republic of","Democratic People's Republic of Korea","Korea, North","North Korea","Korea, Dem. Rep.","Korea, Democratic Republic of","",NA +119,"kor","Korea, Republic of","Republic of Korea","Korea, South","South Korea","Korea","Korea, Rep.","",NA +282,"kos","Kosovo","","","","","","",NA +120,"kwt","Kuwait","State of Kuwait","","","","","",NA +121,"kgz","Kyrgyzstan","Kyrgyz Republic","","","","","",NA +122,"lao","Lao People's Democratic Republic","Laos","Lao PDR","","","","",NA +123,"lva","Latvia","Republic of Latvia","","","","","",NA +124,"lbn","Lebanon","Lebanese Republic","","","","","",NA +125,"lso","Lesotho","Republic of Lesotho","","","","","",NA +126,"lbr","Liberia","Republic of Liberia","","","","","",NA +127,"lby","Libya","Great Socialist People's Libyan Arab Jamahiriya","","","","","",NA +128,"lie","Liechtenstein","Principality of Liechtenstein","","","","","",NA +129,"ltu","Lithuania","Republic of Lithuania","","","","","",NA +130,"lux","Luxembourg","Grand Duchy of Luxembourg","","","","","",NA +131,"mac","Macao","China, Macao Special Administrative Region","Macau S.A.R","Macau Special Administrative Region","Macau S.A.R.","Macau","Macao Special Administrative Region of China","Macao SAR, China " +132,"mkd","Macedonia, The Former Yugoslav Republic of","The former Yugoslav Republic of Macedonia","Macedonia","Republic of Macedonia","Macedonia, Former Yugoslav Republic of","Macedonia, FYR","FYR Macedonia",NA +133,"mdg","Madagascar","Republic of Madagascar","","","","","",NA +134,"mwi","Malawi","Republic of Malawi","","","","","",NA +135,"mys","Malaysia","","","","","","",NA +136,"mdv","Maldives","Republic of Maldives","","","","","",NA +137,"mli","Mali","Republic of Mali","","","","","",NA +138,"mlt","Malta","Republic of Malta","","","","","",NA +139,"mhl","Marshall Islands","Republic of the Marshall Islands","","","","","",NA +140,"mtq","Martinique","Department of Martinique","France, Martinique","","","","",NA +141,"mrt","Mauritania","Islamic Republic of Mauritania","","","","","",NA +142,"mus","Mauritius","Republic of Mauritius","","","","","",NA +143,"myt","Mayotte","Territorial Collectivity of Mayotte","","","","","",NA +144,"mex","Mexico","United Mexican States","","","","","",NA +145,"fsm","Micronesia, Federated States of","Micronesia (Federated States of)","Federated States of Micronesia","Micronesia, Fed. States","Micronesia, Fed. Sts. ","","",NA +267,"","Midway Islands","","","","","","",NA +146,"mda","Moldova, Republic of","Republic of Moldova","Moldova","","","","",NA +147,"mco","Monaco","Principality of Monaco","","","","","",NA +148,"mng","Mongolia","","","","","","",NA +149,"mne","Montenegro","","","","","","",NA +150,"msr","Montserrat","","","","","","",NA +151,"mar","Morocco","Kingdom of Morocco","","","","","",NA +152,"moz","Mozambique","Republic of Mozambique","","","","","",NA +153,"mmr","Myanmar","Burma","Union of Burma","","","","",NA +154,"nam","Namibia","Republic of Namibia","","","","","",NA +155,"nru","Nauru","Republic of Nauru","","","","","",NA +268,"","Navassa Island","","","","","","",NA +156,"npl","Nepal","Kingdom of Nepal","","","","","",NA +157,"nld","Netherlands","Kingdom of the Netherlands","The Netherlands","","","","",NA +269,"","Netherlands Antilles","","","","","","",NA +158,"ncl","New Caledonia","Territory of New Caledonia and Dependencies","","","","","",NA +159,"nzl","New Zealand","","","","","","",NA +160,"nic","Nicaragua","Republic of Nicaragua","","","","","",NA +161,"ner","Niger","Republic of Niger","","","","","",NA +162,"nga","Nigeria","Federal Republic of Nigeria","","","","","",NA +163,"niu","Niue","","","","","","",NA +164,"nfk","Norfolk Island","Territory of Norfolk Island","","","","","",NA +165,"mnp","Northern Mariana Islands","Commonwealth of the Northern Mariana Islands","","","","","",NA +166,"nor","Norway","Kingdom of Norway","","","","","",NA +167,"omn","Oman","Sultanate of Oman","","","","","",NA +168,"pak","Pakistan","Islamic Republic of Pakistan","","","","","",NA +169,"plw","Palau","Republic of Palau","","","","","",NA +270,"","Palmyra Atoll","","","","","","",NA +171,"pan","Panama","Republic of Panama","","","","","",NA +172,"png","Papua New Guinea","Independent State of Papua New Guinea","","","","","",NA +271,"","Paracel Islands","","","","","","",NA +173,"pry","Paraguay","Republic of Paraguay","","","","","",NA +174,"per","Peru","Republic of Peru","","","","","",NA +175,"phl","Philippines","Republic of the Philippines","","","","","",NA +176,"pcn","Pitcairn","Pitcairn Islands","Pitcairn, Henderson, Ducie and Oeno Islands","Pitcairn Island","","","",NA +177,"pol","Poland","Republic of Poland","","","","","",NA +178,"prt","Portugal","Portuguese Republic","","","","","",NA +281,"","Portuguese Timor","","","","","","",NA +179,"pri","Puerto Rico","Commonwealth of Puerto Rico","","","","","",NA +180,"qat","Qatar","State of Qatar","","","","","",NA +181,"reu","Reunion","Department of Reunion","","","","","",NA +182,"rou","Romania","","","","","","",NA +183,"rus","Russian Federation","Russia","","","","","",NA +184,"rwa","Rwanda","Rwandese Republic","","","","","",NA +185,"blm","Saint Barthelemy","Saint-Barthelemy","","","","","",NA +186,"shn","Saint Helena, Ascension and Tristan da Cunha","Saint Helena","St. Helena","","","","",NA +187,"kna","Saint Kitts and Nevis","Federation of Saint Kitts and Nevis","St. Kitts-Nevis","St. Kitts and Nevis","St. Kitts & Nevis","Saint Kitts & Nevis","",NA +188,"lca","Saint Lucia","St. Lucia","","","","","",NA +189,"maf","Saint Martin (French part)","Saint-Martin (French part)","Saint-Martin","Saint Martin","St. Martin (French part) ","","",NA +190,"spm","Saint Pierre and Miquelon","Territorial Collectivity of Saint Pierre and Miquelon","","","","","",NA +191,"vct","Saint Vincent and the Grenadines","St.Vincent & Grenadines","St. Vincent and the Grenadines","","","","",NA +192,"wsm","Samoa","Independent State of Samoa","","","","","",NA +193,"smr","San Marino","Republic of San Marino","","","","","",NA +194,"stp","Sao Tome and Principe","Democratic Republic of Sao Tome and Principe","Sao Tome & Principe","","","","",NA +251,"","Sark","","","","","","",NA +195,"sau","Saudi Arabia","Kingdom of Saudi Arabia","","","","","",NA +196,"sen","Senegal","Republic of Senegal","","","","","",NA +197,"srb","Serbia","","","","","","",NA +252,"","Serbia and Montenegro","","","","","","",NA +198,"syc","Seychelles","Republic of Seychelles","","","","","",NA +199,"sle","Sierra Leone","Republic of Sierra Leone","","","","","",NA +200,"sgp","Singapore","Republic of Singapore","","","","","",NA +201,"sxm","Sint Maarten (Dutch part)","","","","","","",NA +202,"svk","Slovakia","Slovak Republic","","","","","",NA +203,"svn","Slovenia","Republic of Slovenia","","","","","",NA +204,"slb","Solomon Islands","","","","","","",NA +205,"som","Somalia","","","","","","",NA +206,"zaf","South Africa","Republic of South Africa","South African Republic","","","","",NA +207,"","South Georgia and the South Sandwich Islands","South Georgia and the Islands","","","","","",NA +208,"ssd","South Sudan","","","","","","",NA +280,"","Soviet Union","","","","","","",NA +209,"esp","Spain","Kingdom of Spain","","","","","",NA +272,"","Spratly Islands","","","","","","",NA +210,"lka","Sri Lanka","Democratic Socialist Republic of Sri Lanka","","","","","",NA +211,"sdn","Sudan","Republic of the Sudan","","","","","",NA +212,"sur","Suriname","Republic of Suriname","","","","","",NA +273,"","Svalbard","","","","","","",NA +213,"sjm","Svalbard and Jan Mayen","Svalbard and Jan Mayen Islands","","","","","",NA +214,"swz","Swaziland","Kingdom of Swaziland","","","","","",NA +215,"swe","Sweden","Kingdom of Sweden","","","","","",NA +216,"che","Switzerland","Swiss Confederation","","","","","",NA +217,"syr","Syrian Arab Republic","Syria","Golan Heights (Israeli-occupied)","","","","",NA +218,"twn","Taiwan, Province of China","Taiwan","Chinese Taipei","Republic of China","ROC","","",NA +219,"tjk","Tajikistan","Republic of Tajikistan","","","","","",NA +220,"tza","Tanzania, United Republic of","United Republic of Tanzania","Tanzania","","","","",NA +221,"tha","Thailand","Kingdom of Thailand","","","","","",NA +222,"tls","Timor-Leste","East Timor","","","","","",NA +223,"tgo","Togo","Togolese Republic","","","","","",NA +224,"tkl","Tokelau","","","","","","",NA +225,"ton","Tonga","Kingdom of Tonga","","","","","",NA +226,"tto","Trinidad and Tobago","Republic of Trinidad and Tobago","","","","","",NA +274,"","Tromelin Island","","","","","","",NA +227,"tun","Tunisia","Republic of Tunisia","","","","","",NA +228,"tur","Turkey","Republic of Turkey","","","","","",NA +229,"tkm","Turkmenistan","","","","","","",NA +230,"tca","Turks and Caicos Islands","","","","","","",NA +231,"tuv","Tuvalu","","","","","","",NA +232,"uga","Uganda","","","","","","",NA +233,"ukr","Ukraine","","","","","","",NA +234,"are","United Arab Emirates","","","","","","",NA +235,"gbr","United Kingdom","United Kingdom of Great Britain and Northern Ireland","Great Britain","UK","","","",NA +236,"usa","United States","United States of America","US","USA","U.S.A.","U.S.","",NA +237,"umi","United States Minor Outlying Islands","","","","","","",NA +238,"ury","Uruguay","Oriental Republic of Uruguay","","","","","",NA +239,"uzb","Uzbekistan","Republic of Uzbekistan","","","","","",NA +240,"vut","Vanuatu","Republic of Vanuatu","","","","","",NA +241,"ven","Venezuela, Bolivarian Republic of","Venezuela (Bolivarian Republic of)","Venezuela","Bolivarian Republic of Venezuela","Venezuela, RB","","",NA +242,"vnm","Viet Nam","Vietnam","Socialist Republic of Vietnam","","","","",NA +243,"vgb","Virgin Islands, British","British Virgin Islands","Virgin Islands (UK)","","","","",NA +244,"vir","Virgin Islands, U.S.","United States Virgin Islands","Virgin Islands","Virgin Islands of the United States","Virgin Islands (US)","Virgin Islands (U.S.)","",NA +275,"","Wake Atoll","","","","","","",NA +245,"wlf","Wallis and Futuna","Wallis and Futuna Islands","Territory of the Wallis and Futuna Islands","","","","",NA +276,"pse","Palestine", "West Bank","West Bank and Gaza","Palestinian Territory, Occupied","Occupied Palestinian Territory","","",NA +246,"esh","Western Sahara","","","","","","",NA +247,"yem","Yemen","Republic of Yemen","Yemen, Rep.","","","","",NA +248,"zmb","Zambia","Republic of Zambia","","","","","",NA +249,"zwe","Zimbabwe","Republic of Zimbabwe","","","","","",NA diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/country_aliases.csv b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/country_aliases.csv new file mode 100644 index 000000000..3acfe87d8 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/country_aliases.csv @@ -0,0 +1,305 @@ +country_code,potential_name +AFG,Afghanistan +ALA,Aland Islands +ALA,Åland Islands +ALB,Albania +DZA,Algeria +ASM,American Samoa +AND,Andorra +AGO,Angola +AIA,Anguilla +ATA,Antarctica +ATA,French Southern and Antarctic Lands +ATG,Antigua and Barbuda +ARG,Argentina +ARM,Armenia +ABW,Aruba +AUS,Australia +AUT,Austria +AZE,Azerbaijan +BHS,Bahamas +BHR,Bahrain +BGD,Bangladesh +BRB,Barbados +BLR,Belarus +BEL,Belgium +BLZ,Belize +BEN,Benin +BMU,Bermuda +BTN,Bhutan +BOL,Bolivia +BOL,Bolivia (Plurinational State of) +BIH,Bosnia and Herzegovina +BWA,Botswana +BVT,Bouvet Island +BRA,Brazil +VGB,British Virgin Islands +IOT,British Indian Ocean Territory +BRN,Brunei Darussalam +BGR,Bulgaria +BFA,Burkina Faso +BDI,Burundi +KHM,Cambodia +CMR,Cameroon +CMR,Cameroun +CMR,CAM +CAN,Canada +CPV,Cape Verde +CPV,Cabo Verde +CYM,Cayman Islands +CAF,Central African Republic +TCD,Chad +CHL,Chile +CHN,China +HKG,"Hong Kong, SAR China" +HKG,Hong Kong +MAC,"Macao, SAR China" +MAC,Macao +MAC,Macau +CXR,Christmas Island +CCK,Cocos (Keeling) Islands +COL,Colombia +COM,Comoros +COG,Congo (Brazzaville) +COD,"Congo, (Kinshasa)" +COD,DRC +COD,Democratic Republic of the Congo +COD,Democratic Republic of Congo +COK,Cook Islands +CRI,Costa Rica +CIV,Cote d'Ivoire +CIV,C?_te d'Ivoire +CIV,C\314\253te d'Ivoire +CIV,C_te d'Ivoire +CIV,Cte d'Ivoire +CIV,C\u00f4te d'Ivoire +CIV,Ivory Coast +HRV,Croatia +CUB,Cuba +CYP,Cyprus +CZE,Czech Republic +CZE,Czechia +DNK,Denmark +DJI,Djibouti +DMA,Dominica +DOM,Dominican Republic +DOM,Dom. Rep. +ECU,Ecuador +EGY,Egypt +SLV,El Salvador +GNQ,Equatorial Guinea +ERI,Eritrea +EST,Estonia +ETH,Ethiopia +FLK,Falkland Islands (Malvinas) +FRO,Faroe Islands +FJI,Fiji +FIN,Finland +FRA,France +GUF,French Guiana +PYF,French Polynesia +ATF,French Southern Territories +GAB,Gabon +GMB,Gambia +GEO,Georgia +DEU,Germany +GHA,Ghana +GIB,Gibraltar +GRC,Greece +GRL,Greenland +GRD,Grenada +GLP,Guadeloupe +GUM,Guam +GTM,Guatemala +GGY,Guernsey +GIN,Guinea +GNB,Guinea-Bissau +GNB,Guinea Bissau +GUY,Guyana +HTI,Haiti +HMD,Heard and Mcdonald Islands +HMD,Heard Island and McDonald Islands +VAT,Holy See (Vatican City State) +VAT,Holy See (Vatican City) +HND,Honduras +HUN,Hungary +ISL,Iceland +IND,India +IDN,Indonesia +IRN,"Iran, Islamic Republic of" +IRN,Iran (Islamic Republic of) +IRQ,Iraq +IRL,Ireland +IMN,Isle of Man +ISR,Israel +ITA,Italy +JAM,Jamaica +JPN,Japan +JEY,Jersey +JOR,Jordan +KAZ,Kazakhstan +KEN,Kenya +KIR,Kiribati +PRK,Korea (North) +PRK,Democratic People's Republic of Korea +PRK,"Korea, Democratic People's Republic of" +KOR,Korea (South) +KOR,Republic of Korea +KOR,"Korea, Republic of" +KWT,Kuwait +KGZ,Kyrgyzstan +LAO,Lao PDR +LAO,Lao People's Democratic Republic +LVA,Latvia +LBN,Lebanon +LSO,Lesotho +LBR,Liberia +LBY,Libya +LBY,Libyan Arab Jamahiriya +LIE,Liechtenstein +LTU,Lithuania +LUX,Luxembourg +MKD,"Macedonia, Republic of" +MKD,The former Yugoslav Republic of Macedonia +MDG,Madagascar +MWI,Malawi +MYS,Malaysia +MDV,Maldives +MLI,Mali +MLT,Malta +MHL,Marshall Islands +MTQ,Martinique +MRT,Mauritania +MUS,Mauritius +MYT,Mayotte +MEX,Mexico +FSM,"Micronesia, Federated States of" +FSM,Micronesia (Federated States of) +MDA,Moldova +MDA,Republic of Moldova +MCO,Monaco +MNG,Mongolia +MNE,Montenegro +MSR,Montserrat +MAR,Morocco +MOZ,Mozambique +MMR,Myanmar +MMR,Burma +NAM,Namibia +NRU,Nauru +NPL,Nepal +NLD,Netherlands +ANT,Netherlands Antilles +NCL,New Caledonia +NZL,New Zealand +NIC,Nicaragua +NER,Niger +NGA,Nigeria +NIU,Niue +NFK,Norfolk Island +MNP,Northern Mariana Islands +NOR,Norway +OMN,Oman +PAK,Pakistan +PLW,Palau +PSE,Palestinian Territory +PSE,Palestine +PAN,Panama +PNG,Papua New Guinea +PRY,Paraguay +PER,Peru +PHL,Philippines +PCN,Pitcairn +PCN,Pitcairn Islands +POL,Poland +PRT,Portugal +PRI,Puerto Rico +QAT,Qatar +REU,R͂??union +REU,Reunion +ROU,Romania +RUS,Russian Federation +RUS,Russia +RWA,Rwanda +BLM,Saint-Barth͂??lemy +BLM,Saint Barthelemy +SHN,Saint Helena +KNA,Saint Kitts and Nevis +LCA,Saint Lucia +MAF,Saint-Martin (French part) +MAF,Saint Martin +SPM,Saint Pierre and Miquelon +VCT,Saint Vincent and Grenadines +VCT,Saint Vincent and the Grenadines +WSM,Samoa +SMR,San Marino +STP,Sao Tome and Principe +SAU,Saudi Arabia +SEN,Senegal +SRB,Serbia +SYC,Seychelles +SLE,Sierra Leone +SGP,Singapore +SVK,Slovakia +SVN,Slovenia +SLB,Solomon Islands +SOM,Somalia +ZAF,South Africa +SGS,South Georgia and the South Sandwich Islands +SGS,South Georgia South Sandwich Islands +SSD,South Sudan +ESP,Spain +LKA,Sri Lanka +SDN,Sudan +SUR,Suriname +SJM,Svalbard and Jan Mayen Islands +SJM,Svalbard +SWZ,Swaziland +SWE,Sweden +CHE,Switzerland +SYR,Syrian Arab Republic (Syria) +SYR,Syrian Arab Republic +SYR,Syria +TWN,"Taiwan, Republic of China" +TWN,Taiwan +TJK,Tajikistan +TZA,"Tanzania, United Republic of" +TZA,Tanzania +TZA,United Republic of Tanzania +THA,Thailand +TLS,Timor-Leste +TGO,Togo +TKL,Tokelau +TON,Tonga +TTO,Trinidad and Tobago +TUN,Tunisia +TUR,Turkey +TKM,Turkmenistan +TCA,Turks and Caicos Islands +TUV,Tuvalu +UGA,Uganda +UKR,Ukraine +ARE,United Arab Emirates +GBR,United Kingdom +GBR,United Kingdom of Great Britain and Northern Ireland +USA,United States of America +USA,United States +UMI,US Minor Outlying Islands +UMI,United States Minor Outlying Islands +URY,Uruguay +UZB,Uzbekistan +VUT,Vanuatu +VEN,Venezuela (Bolivarian Republic) +VEN,Venezuela (Bolivarian Republic of) +VEN,Venezuela +VNM,Viet Nam +VIR,"Virgin Islands, US" +VIR,US Virgin Islands +VIR,United States Virgin Islands +WLF,Wallis and Futuna Islands +ESH,Western Sahara +YEM,Yemen +ZMB,Zambia +ZWE,Zimbabwe +COG,Congo +COG,Republic of Congo diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/country_worldpop_regions.csv b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/country_worldpop_regions.csv new file mode 100644 index 000000000..bedfb64dd --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/country_worldpop_regions.csv @@ -0,0 +1,128 @@ +"region","country","country_code","region_code" +"Africa","Algeria","DZA","AFR" +"Africa","Angola","AGO","AFR" +"Africa","Benin","BEN","AFR" +"Africa","Botswana","BWA","AFR" +"Africa","Burkina Faso","BFA","AFR" +"Africa","Burundi","BDI","AFR" +"Africa","Cameroon","CMR","AFR" +"Africa","Central African Republic","CAF","AFR" +"Africa","Chad","TCD","AFR" +"Africa","Congo","COG","AFR" +"Africa","Côte d'Ivoire","CIV","AFR" +"Africa","Democratic Republic of the Congo","COD","AFR" +"Africa","Djibouti","DJI","AFR" +"Africa","Egypt","EGY","AFR" +"Africa","Equatorial Guinea","GNQ","AFR" +"Africa","Eritrea","ERI","AFR" +"Africa","Ethiopia","ETH","AFR" +"Africa","Gabon","GAB","AFR" +"Africa","Gambia","GMB","AFR" +"Africa","Ghana","GHA","AFR" +"Africa","Guinea","GIN","AFR" +"Africa","Guinea-Bissau","GNB","AFR" +"Africa","Kenya","KEN","AFR" +"Africa","Lesotho","LSO","AFR" +"Africa","Liberia","LBR","AFR" +"Africa","Libya","LBY","AFR" +"Africa","Madagascar","MDG","AFR" +"Africa","Malawi","MWI","AFR" +"Africa","Mali","MLI","AFR" +"Africa","Mauritania","MRT","AFR" +"Africa","Morocco","MAR","AFR" +"Africa","Mozambique","MOZ","AFR" +"Africa","Namibia","NAM","AFR" +"Africa","Niger","NER","AFR" +"Africa","Nigeria","NGA","AFR" +"Africa","Rwanda","RWA","AFR" +"Africa","Senegal","SEN","AFR" +"Africa","Sierra Leone","SLE","AFR" +"Africa","Somalia","SOM","AFR" +"Africa","South Africa","ZAF","AFR" +"Africa","South Sudan","SSD","AFR" +"Africa","Sudan","SDN","AFR" +"Africa","Swaziland","SWZ","AFR" +"Africa","Togo","TGO","AFR" +"Africa","Tunisia","TUN","AFR" +"Africa","Uganda","UGA","AFR" +"Africa","United Republic of Tanzania","TZA","AFR" +"Africa","Western Sahara","ESH","AFR" +"Africa","Zambia","ZMB","AFR" +"Africa","Zimbabwe","ZWE","AFR" +"Latin America and the Caribbean","Antigua and Barbuda","ATG","LAC" +"Latin America and the Caribbean","Argentina","ARG","LAC" +"Latin America and the Caribbean","Belize","BLZ","LAC" +"Latin America and the Caribbean","Bolivia (Plurinational State of)","BOL","LAC" +"Latin America and the Caribbean","Brazil","BRA","LAC" +"Latin America and the Caribbean","Chile","CHL","LAC" +"Latin America and the Caribbean","Colombia","COL","LAC" +"Latin America and the Caribbean","Costa Rica","CRI","LAC" +"Latin America and the Caribbean","Cuba","CUB","LAC" +"Latin America and the Caribbean","Dominican Republic","DOM","LAC" +"Latin America and the Caribbean","Ecuador","ECU","LAC" +"Latin America and the Caribbean","El Salvador","SLV","LAC" +"Latin America and the Caribbean","French Guiana","GUF","LAC" +"Latin America and the Caribbean","Guatemala","GTM","LAC" +"Latin America and the Caribbean","Guyana","GUY","LAC" +"Latin America and the Caribbean","Haiti","HTI","LAC" +"Latin America and the Caribbean","Honduras","HND","LAC" +"Latin America and the Caribbean","Jamaica","JAM","LAC" +"Latin America and the Caribbean","Mexico","MEX","LAC" +"Latin America and the Caribbean","Nicaragua","NIC","LAC" +"Latin America and the Caribbean","Panama","PAN","LAC" +"Latin America and the Caribbean","Paraguay","PRY","LAC" +"Latin America and the Caribbean","Peru","PER","LAC" +"Latin America and the Caribbean","Puerto Rico","PRI","LAC" +"Latin America and the Caribbean","Suriname","SUR","LAC" +"Latin America and the Caribbean","Trinidad and Tobago","TTO","LAC" +"Latin America and the Caribbean","Uruguay","URY","LAC" +"Latin America and the Caribbean","Venezuela (Bolivarian Republic of)","VEN","LAC" +"Asia","Afghanistan","AFG","ASI" +"Asia","Armenia","ARM","ASI" +"Asia","Azerbaijan","AZE","ASI" +"Asia","Bangladesh","BGD","ASI" +"Asia","Bhutan","BTN","ASI" +"Asia","Brunei Darussalam","BRN","ASI" +"Asia","Cambodia","KHM","ASI" +"Asia","China","CHN","ASI" +"Asia","Democratic People's Republic of Korea","PRK","ASI" +"Asia","Georgia","GEO","ASI" +"Asia","India","IND","ASI" +"Asia","Indonesia","IDN","ASI" +"Asia","Iraq","IRQ","ASI" +"Asia","Japan","JPN","ASI" +"Asia","Kazakhstan","KAZ","ASI" +"Asia","Kyrgyzstan","KGZ","ASI" +"Asia","Lao People's Democratic Republic","LAO","ASI" +"Asia","Malaysia","MYS","ASI" +"Asia","Maldives","MDV","ASI" +"Asia","Mongolia","MNG","ASI" +"Asia","Myanmar","MMR","ASI" +"Asia","Nepal","NPL","ASI" +"Asia","Oman","OMN","ASI" +"Asia","Pakistan","PAK","ASI" +"Asia","Philippines","PHL","ASI" +"Asia","Republic of Korea","KOR","ASI" +"Asia","Saudi Arabia","SAU","ASI" +"Asia","Singapore","SGP","ASI" +"Asia","Sri Lanka","LKA","ASI" +"Asia","State of Palestine","PSE","ASI" +"Asia","Syrian Arab Republic","SYR","ASI" +"Asia","Taiwan","TWN","ASI" +"Asia","Tajikistan","TJK","ASI" +"Asia","Thailand","THA","ASI" +"Asia","Timor-Leste","TLS","ASI" +"Asia","Uzbekistan","UZB","ASI" +"Asia","Viet Nam","VNM","ASI" +"Asia","Yemen","YEM","ASI" +"Europe","Ukraine","UKR","EUR" +"Oceania","Fiji","FJI","OCE" +"Oceania","Kiribati","KIR","OCE" +"Oceania","Marshall Islands","MHL","OCE" +"Oceania","Micronesia (Federated States of)","FSM","OCE" +"Oceania","Palau","PLW","OCE" +"Oceania","Papua New Guinea","PNG","OCE" +"Oceania","Samoa","WSM","OCE" +"Oceania","Solomon Islands","SLB","OCE" +"Oceania","Tonga","TON","OCE" +"Oceania","Vanuatu","VUT","OCE" diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/iso31662_codes.csv b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/iso31662_codes.csv new file mode 100644 index 000000000..c749b5cbc --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/extdata/iso31662_codes.csv @@ -0,0 +1,4800 @@ +"ISO3","ISO2","Code","Name","Type","Parent","ISO_level" +"AND","AD","AD-02","Canillo","Parish","Andorra",2 +"AND","AD","AD-03","Encamp","Parish","Andorra",2 +"AND","AD","AD-04","La Massana","Parish","Andorra",2 +"AND","AD","AD-05","Ordino","Parish","Andorra",2 +"AND","AD","AD-06","Sant Julià de Lòria","Parish","Andorra",2 +"AND","AD","AD-07","Andorra la Vella","Parish","Andorra",2 +"AND","AD","AD-08","Escaldes-Engordany","Parish","Andorra",2 +"ARE","AE","AE-AJ","Ajman","Emirate","United Arab Emirates",2 +"ARE","AE","AE-AZ","Abu Dhabi","Emirate","United Arab Emirates",2 +"ARE","AE","AE-DU","Dubai","Emirate","United Arab Emirates",2 +"ARE","AE","AE-FU","Al Fujayrah","Emirate","United Arab Emirates",2 +"ARE","AE","AE-RK","Ra’s al Khaymah","Emirate","United Arab Emirates",2 +"ARE","AE","AE-SH","Ash Shāriqah","Emirate","United Arab Emirates",2 +"ARE","AE","AE-UQ","Umm al Qaywayn","Emirate","United Arab Emirates",2 +"AFG","AF","AF-BAL","Balkh","Province","Afghanistan",2 +"AFG","AF","AF-BAM","Bāmyān","Province","Afghanistan",2 +"AFG","AF","AF-BDG","Bādghīs","Province","Afghanistan",2 +"AFG","AF","AF-BDS","Badakhshān","Province","Afghanistan",2 +"AFG","AF","AF-BGL","Baghlān","Province","Afghanistan",2 +"AFG","AF","AF-DAY","Dāykundī","Province","Afghanistan",2 +"AFG","AF","AF-FRA","Farāh","Province","Afghanistan",2 +"AFG","AF","AF-FYB","Fāryāb","Province","Afghanistan",2 +"AFG","AF","AF-GHA","Ghaznī","Province","Afghanistan",2 +"AFG","AF","AF-GHO","Ghōr","Province","Afghanistan",2 +"AFG","AF","AF-HEL","Helmand","Province","Afghanistan",2 +"AFG","AF","AF-HER","Herāt","Province","Afghanistan",2 +"AFG","AF","AF-JOW","Jowzjān","Province","Afghanistan",2 +"AFG","AF","AF-KAB","Kābul","Province","Afghanistan",2 +"AFG","AF","AF-KAN","Kandahār","Province","Afghanistan",2 +"AFG","AF","AF-KAP","Kāpīsā","Province","Afghanistan",2 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+"BEL","BE","BE-WNA","Namur","Province","Belgium",2 +"BFA","BF","BF-01","Boucle du Mouhoun","Region","Burkina Faso",2 +"BFA","BF","BF-02","Cascades","Region","Burkina Faso",2 +"BFA","BF","BF-03","Centre","Region","Burkina Faso",2 +"BFA","BF","BF-04","Centre-Est","Region","Burkina Faso",2 +"BFA","BF","BF-05","Centre-Nord","Region","Burkina Faso",2 +"BFA","BF","BF-06","Centre-Ouest","Region","Burkina Faso",2 +"BFA","BF","BF-07","Centre-Sud","Region","Burkina Faso",2 +"BFA","BF","BF-08","Est","Region","Burkina Faso",2 +"BFA","BF","BF-09","Hauts-Bassins","Region","Burkina Faso",2 +"BFA","BF","BF-10","Nord","Region","Burkina Faso",2 +"BFA","BF","BF-11","Plateau-Central","Region","Burkina Faso",2 +"BFA","BF","BF-12","Sahel","Region","Burkina Faso",2 +"BFA","BF","BF-13","Sud-Ouest","Region","Burkina Faso",2 +"BFA","BF","BF-BAL","Balé","Province","Burkina Faso",2 +"BFA","BF","BF-BAM","Bam","Province","Burkina Faso",2 +"BFA","BF","BF-BAN","Banwa","Province","Burkina Faso",2 +"BFA","BF","BF-BAZ","Bazèga","Province","Burkina Faso",2 +"BFA","BF","BF-BGR","Bougouriba","Province","Burkina Faso",2 +"BFA","BF","BF-BLG","Boulgou","Province","Burkina Faso",2 +"BFA","BF","BF-BLK","Boulkiemdé","Province","Burkina Faso",2 +"BFA","BF","BF-COM","Comoé","Province","Burkina Faso",2 +"BFA","BF","BF-GAN","Ganzourgou","Province","Burkina Faso",2 +"BFA","BF","BF-GNA","Gnagna","Province","Burkina Faso",2 +"BFA","BF","BF-GOU","Gourma","Province","Burkina Faso",2 +"BFA","BF","BF-HOU","Houet","Province","Burkina Faso",2 +"BFA","BF","BF-IOB","Ioba","Province","Burkina Faso",2 +"BFA","BF","BF-KAD","Kadiogo","Province","Burkina Faso",2 +"BFA","BF","BF-KEN","Kénédougou","Province","Burkina Faso",2 +"BFA","BF","BF-KMD","Komondjari","Province","Burkina Faso",2 +"BFA","BF","BF-KMP","Kompienga","Province","Burkina Faso",2 +"BFA","BF","BF-KOP","Koulpélogo","Province","Burkina Faso",2 +"BFA","BF","BF-KOS","Kossi","Province","Burkina Faso",2 +"BFA","BF","BF-KOT","Kouritenga","Province","Burkina Faso",2 +"BFA","BF","BF-KOW","Kourwéogo","Province","Burkina Faso",2 +"BFA","BF","BF-LER","Léraba","Province","Burkina Faso",2 +"BFA","BF","BF-LOR","Loroum","Province","Burkina Faso",2 +"BFA","BF","BF-MOU","Mouhoun","Province","Burkina Faso",2 +"BFA","BF","BF-NAM","Namentenga","Province","Burkina Faso",2 +"BFA","BF","BF-NAO","Naouri","Province","Burkina Faso",2 +"BFA","BF","BF-NAY","Nayala","Province","Burkina Faso",2 +"BFA","BF","BF-NOU","Noumbiel","Province","Burkina Faso",2 +"BFA","BF","BF-OUB","Oubritenga","Province","Burkina Faso",2 +"BFA","BF","BF-OUD","Oudalan","Province","Burkina Faso",2 +"BFA","BF","BF-PAS","Passoré","Province","Burkina Faso",2 +"BFA","BF","BF-PON","Poni","Province","Burkina Faso",2 +"BFA","BF","BF-SEN","Séno","Province","Burkina Faso",2 +"BFA","BF","BF-SIS","Sissili","Province","Burkina Faso",2 +"BFA","BF","BF-SMT","Sanmatenga","Province","Burkina Faso",2 +"BFA","BF","BF-SNG","Sanguié","Province","Burkina Faso",2 +"BFA","BF","BF-SOM","Soum","Province","Burkina Faso",2 +"BFA","BF","BF-SOR","Sourou","Province","Burkina Faso",2 +"BFA","BF","BF-TAP","Tapoa","Province","Burkina Faso",2 +"BFA","BF","BF-TUI","Tui","Province","Burkina Faso",2 +"BFA","BF","BF-YAG","Yagha","Province","Burkina Faso",2 +"BFA","BF","BF-YAT","Yatenga","Province","Burkina Faso",2 +"BFA","BF","BF-ZIR","Ziro","Province","Burkina Faso",2 +"BFA","BF","BF-ZON","Zondoma","Province","Burkina Faso",2 +"BFA","BF","BF-ZOU","Zoundwéogo","Province","Burkina Faso",2 +"BGR","BG","BG-01","Blagoevgrad","Region","Bulgaria",2 +"BGR","BG","BG-02","Burgas","Region","Bulgaria",2 +"BGR","BG","BG-03","Varna","Region","Bulgaria",2 +"BGR","BG","BG-04","Veliko Tarnovo","Region","Bulgaria",2 +"BGR","BG","BG-05","Vidin","Region","Bulgaria",2 +"BGR","BG","BG-06","Vratsa","Region","Bulgaria",2 +"BGR","BG","BG-07","Gabrovo","Region","Bulgaria",2 +"BGR","BG","BG-08","Dobrich","Region","Bulgaria",2 +"BGR","BG","BG-09","Kardzhali","Region","Bulgaria",2 +"BGR","BG","BG-10","Kyustendil","Region","Bulgaria",2 +"BGR","BG","BG-11","Lovech","Region","Bulgaria",2 +"BGR","BG","BG-12","Montana","Region","Bulgaria",2 +"BGR","BG","BG-13","Pazardzhik","Region","Bulgaria",2 +"BGR","BG","BG-14","Pernik","Region","Bulgaria",2 +"BGR","BG","BG-15","Pleven","Region","Bulgaria",2 +"BGR","BG","BG-16","Plovdiv","Region","Bulgaria",2 +"BGR","BG","BG-17","Razgrad","Region","Bulgaria",2 +"BGR","BG","BG-18","Ruse","Region","Bulgaria",2 +"BGR","BG","BG-19","Silistra","Region","Bulgaria",2 +"BGR","BG","BG-20","Sliven","Region","Bulgaria",2 +"BGR","BG","BG-21","Smolyan","Region","Bulgaria",2 +"BGR","BG","BG-22","Sofia-Grad","Region","Bulgaria",2 +"BGR","BG","BG-23","Sofia","Region","Bulgaria",2 +"BGR","BG","BG-24","Stara Zagora","Region","Bulgaria",2 +"BGR","BG","BG-25","Targovishte","Region","Bulgaria",2 +"BGR","BG","BG-26","Haskovo","Region","Bulgaria",2 +"BGR","BG","BG-27","Shumen","Region","Bulgaria",2 +"BGR","BG","BG-28","Yambol","Region","Bulgaria",2 +"BHR","BH","BH-13","Al Manāmah (Al ‘Āşimah)","Governorate","Bahrain",2 +"BHR","BH","BH-14","Al Janūbīyah","Governorate","Bahrain",2 +"BHR","BH","BH-15","Al Muḩarraq","Governorate","Bahrain",2 +"BHR","BH","BH-16","Al Wusţá","Governorate","Bahrain",2 +"BHR","BH","BH-17","Ash Shamālīyah","Governorate","Bahrain",2 +"BDI","BI","BI-BB","Bubanza","Province","Burundi",2 +"BDI","BI","BI-BL","Bujumbura Rural","Province","Burundi",2 +"BDI","BI","BI-BM","Bujumbura Mairie","Province","Burundi",2 +"BDI","BI","BI-BR","Bururi","Province","Burundi",2 +"BDI","BI","BI-CA","Cankuzo","Province","Burundi",2 +"BDI","BI","BI-CI","Cibitoke","Province","Burundi",2 +"BDI","BI","BI-GI","Gitega","Province","Burundi",2 +"BDI","BI","BI-KI","Kirundo","Province","Burundi",2 +"BDI","BI","BI-KR","Karuzi","Province","Burundi",2 +"BDI","BI","BI-KY","Kayanza","Province","Burundi",2 +"BDI","BI","BI-MA","Makamba","Province","Burundi",2 +"BDI","BI","BI-MU","Muramvya","Province","Burundi",2 +"BDI","BI","BI-MW","Mwaro","Province","Burundi",2 +"BDI","BI","BI-NG","Ngozi","Province","Burundi",2 +"BDI","BI","BI-RT","Rutana","Province","Burundi",2 +"BDI","BI","BI-RY","Ruyigi","Province","Burundi",2 +"BEN","BJ","BJ-AK","Atakora","Department","Benin",2 +"BEN","BJ","BJ-AL","Alibori","Department","Benin",2 +"BEN","BJ","BJ-AQ","Atlantique","Department","Benin",2 +"BEN","BJ","BJ-BO","Borgou","Department","Benin",2 +"BEN","BJ","BJ-CO","Collines","Department","Benin",2 +"BEN","BJ","BJ-DO","Donga","Department","Benin",2 +"BEN","BJ","BJ-KO","Kouffo","Department","Benin",2 +"BEN","BJ","BJ-LI","Littoral","Department","Benin",2 +"BEN","BJ","BJ-MO","Mono","Department","Benin",2 +"BEN","BJ","BJ-OU","Ouémé","Department","Benin",2 +"BEN","BJ","BJ-PL","Plateau","Department","Benin",2 +"BEN","BJ","BJ-ZO","Zou","Department","Benin",2 +"BRN","BN","BN-BE","Belait","District","Brunei Darussalam",2 +"BRN","BN","BN-BM","Brunei-Muara","District","Brunei Darussalam",2 +"BRN","BN","BN-TE","Temburong","District","Brunei Darussalam",2 +"BRN","BN","BN-TU","Tutong","District","Brunei Darussalam",2 +"BOL","BO","BO-B","El Beni","Department","Bolivia",2 +"BOL","BO","BO-C","Cochabamba","Department","Bolivia",2 +"BOL","BO","BO-H","Chuquisaca","Department","Bolivia",2 +"BOL","BO","BO-L","La Paz","Department","Bolivia",2 +"BOL","BO","BO-N","Pando","Department","Bolivia",2 +"BOL","BO","BO-O","Oruro","Department","Bolivia",2 +"BOL","BO","BO-P","Potosí","Department","Bolivia",2 +"BOL","BO","BO-S","Santa Cruz","Department","Bolivia",2 +"BOL","BO","BO-T","Tarija","Department","Bolivia",2 +"BES","BQ","BQ-BO","Bonaire","Special municipality","Bonaire, Sint Eustatius and Saba",2 +"BES","BQ","BQ-SA","Saba","Special municipality","Bonaire, Sint Eustatius and Saba",2 +"BES","BQ","BQ-SE","Sint Eustatius","Special municipality","Bonaire, Sint Eustatius and Saba",2 +"BRA","BR","BR-AC","Acre","State","Brazil",2 +"BRA","BR","BR-AL","Alagoas","State","Brazil",2 +"BRA","BR","BR-AM","Amazonas","State","Brazil",2 +"BRA","BR","BR-AP","Amapá","State","Brazil",2 +"BRA","BR","BR-BA","Bahia","State","Brazil",2 +"BRA","BR","BR-CE","Ceará","State","Brazil",2 +"BRA","BR","BR-DF","Distrito Federal","Federal District","Brazil",2 +"BRA","BR","BR-ES","Espírito Santo","State","Brazil",2 +"BRA","BR","BR-FN","Fernando de Noronha","State","Brazil",2 +"BRA","BR","BR-GO","Goiás","State","Brazil",2 +"BRA","BR","BR-MA","Maranhão","State","Brazil",2 +"BRA","BR","BR-MG","Minas Gerais","State","Brazil",2 +"BRA","BR","BR-MS","Mato Grosso do Sul","State","Brazil",2 +"BRA","BR","BR-MT","Mato Grosso","State","Brazil",2 +"BRA","BR","BR-PA","Pará","State","Brazil",2 +"BRA","BR","BR-PB","Paraíba","State","Brazil",2 +"BRA","BR","BR-PE","Pernambuco","State","Brazil",2 +"BRA","BR","BR-PI","Piauí","State","Brazil",2 +"BRA","BR","BR-PR","Paraná","State","Brazil",2 +"BRA","BR","BR-RJ","Rio de Janeiro","State","Brazil",2 +"BRA","BR","BR-RN","Rio Grande do Norte","State","Brazil",2 +"BRA","BR","BR-RO","Rondônia","State","Brazil",2 +"BRA","BR","BR-RR","Roraima","State","Brazil",2 +"BRA","BR","BR-RS","Rio Grande do Sul","State","Brazil",2 +"BRA","BR","BR-SC","Santa Catarina","State","Brazil",2 +"BRA","BR","BR-SE","Sergipe","State","Brazil",2 +"BRA","BR","BR-SP","São Paulo","State","Brazil",2 +"BRA","BR","BR-TO","Tocantins","State","Brazil",2 +"BHS","BS","BS-AK","Acklins","District","Bahamas",2 +"BHS","BS","BS-BI","Bimini","District","Bahamas",2 +"BHS","BS","BS-BP","Black Point","District","Bahamas",2 +"BHS","BS","BS-BY","Berry Islands","District","Bahamas",2 +"BHS","BS","BS-CE","Central Eleuthera","District","Bahamas",2 +"BHS","BS","BS-CI","Cat Island","District","Bahamas",2 +"BHS","BS","BS-CK","Crooked Island and Long Cay","District","Bahamas",2 +"BHS","BS","BS-CO","Central Abaco","District","Bahamas",2 +"BHS","BS","BS-CS","Central Andros","District","Bahamas",2 +"BHS","BS","BS-EG","East Grand Bahama","District","Bahamas",2 +"BHS","BS","BS-EX","Exuma","District","Bahamas",2 +"BHS","BS","BS-FP","City of Freeport","District","Bahamas",2 +"BHS","BS","BS-GC","Grand Cay","District","Bahamas",2 +"BHS","BS","BS-HI","Harbour Island","District","Bahamas",2 +"BHS","BS","BS-HT","Hope Town","District","Bahamas",2 +"BHS","BS","BS-IN","Inagua","District","Bahamas",2 +"BHS","BS","BS-LI","Long Island","District","Bahamas",2 +"BHS","BS","BS-MC","Mangrove Cay","District","Bahamas",2 +"BHS","BS","BS-MG","Mayaguana","District","Bahamas",2 +"BHS","BS","BS-MI","Moore's Island","District","Bahamas",2 +"BHS","BS","BS-NE","North Eleuthera","District","Bahamas",2 +"BHS","BS","BS-NO","North Abaco","District","Bahamas",2 +"BHS","BS","BS-NS","North Andros","District","Bahamas",2 +"BHS","BS","BS-RC","Rum Cay","District","Bahamas",2 +"BHS","BS","BS-RI","Ragged Island","District","Bahamas",2 +"BHS","BS","BS-SA","South Andros","District","Bahamas",2 +"BHS","BS","BS-SE","South Eleuthera","District","Bahamas",2 +"BHS","BS","BS-SO","South Abaco","District","Bahamas",2 +"BHS","BS","BS-SS","San Salvador","District","Bahamas",2 +"BHS","BS","BS-SW","Spanish Wells","District","Bahamas",2 +"BHS","BS","BS-WG","West Grand Bahama","District","Bahamas",2 +"BTN","BT","BT-11","Paro","District","Bhutan",2 +"BTN","BT","BT-12","Chhukha","District","Bhutan",2 +"BTN","BT","BT-13","Ha","District","Bhutan",2 +"BTN","BT","BT-14","Samtee","District","Bhutan",2 +"BTN","BT","BT-15","Thimphu","District","Bhutan",2 +"BTN","BT","BT-21","Tsirang","District","Bhutan",2 +"BTN","BT","BT-22","Dagana","District","Bhutan",2 +"BTN","BT","BT-23","Punakha","District","Bhutan",2 +"BTN","BT","BT-24","Wangdue Phodrang","District","Bhutan",2 +"BTN","BT","BT-31","Sarpang","District","Bhutan",2 +"BTN","BT","BT-32","Trongsa","District","Bhutan",2 +"BTN","BT","BT-33","Bumthang","District","Bhutan",2 +"BTN","BT","BT-34","Zhemgang","District","Bhutan",2 +"BTN","BT","BT-41","Trashigang","District","Bhutan",2 +"BTN","BT","BT-42","Monggar","District","Bhutan",2 +"BTN","BT","BT-43","Pemagatshel","District","Bhutan",2 +"BTN","BT","BT-44","Lhuentse","District","Bhutan",2 +"BTN","BT","BT-45","Samdrup Jongkha","District","Bhutan",2 +"BTN","BT","BT-GA","Gasa","District","Bhutan",2 +"BTN","BT","BT-TY","Trashi Yangtse","District","Bhutan",2 +"BWA","BW","BW-CE","Central","District","Botswana",2 +"BWA","BW","BW-GH","Ghanzi","District","Botswana",2 +"BWA","BW","BW-KG","Kgalagadi","District","Botswana",2 +"BWA","BW","BW-KL","Kgatleng","District","Botswana",2 +"BWA","BW","BW-KW","Kweneng","District","Botswana",2 +"BWA","BW","BW-NE","North-East","District","Botswana",2 +"BWA","BW","BW-NW","North-West","District","Botswana",2 +"BWA","BW","BW-SE","South-East","District","Botswana",2 +"BWA","BW","BW-SO","Southern","District","Botswana",2 +"BLR","BY","BY-BR","Brèsckaja voblasc'","Oblast","Belarus",2 +"BLR","BY","BY-HM","Horad Minsk","City","Belarus",2 +"BLR","BY","BY-HO","Homel'skaja voblasc'","Oblast","Belarus",2 +"BLR","BY","BY-HR","Hrodzenskaja voblasc'","Oblast","Belarus",2 +"BLR","BY","BY-MA","Mahilëuskaja voblasc'","Oblast","Belarus",2 +"BLR","BY","BY-MI","Minskaja voblasc'","Oblast","Belarus",2 +"BLR","BY","BY-VI","Vicebskaja voblasc'","Oblast","Belarus",2 +"BLZ","BZ","BZ-BZ","Belize","District","Belize",2 +"BLZ","BZ","BZ-CY","Cayo","District","Belize",2 +"BLZ","BZ","BZ-CZL","Corozal","District","Belize",2 +"BLZ","BZ","BZ-OW","Orange Walk","District","Belize",2 +"BLZ","BZ","BZ-SC","Stann Creek","District","Belize",2 +"BLZ","BZ","BZ-TOL","Toledo","District","Belize",2 +"CAN","CA","CA-AB","Alberta","Province","Canada",2 +"CAN","CA","CA-BC","British Columbia","Province","Canada",2 +"CAN","CA","CA-MB","Manitoba","Province","Canada",2 +"CAN","CA","CA-NB","New Brunswick","Province","Canada",2 +"CAN","CA","CA-NL","Newfoundland and Labrador","Province","Canada",2 +"CAN","CA","CA-NS","Nova Scotia","Province","Canada",2 +"CAN","CA","CA-NT","Northwest Territories","Territory","Canada",2 +"CAN","CA","CA-NU","Nunavut","Territory","Canada",2 +"CAN","CA","CA-ON","Ontario","Province","Canada",2 +"CAN","CA","CA-PE","Prince Edward Island","Province","Canada",2 +"CAN","CA","CA-QC","Quebec","Province","Canada",2 +"CAN","CA","CA-SK","Saskatchewan","Province","Canada",2 +"CAN","CA","CA-YT","Yukon Territory","Territory","Canada",2 +"COD","CD","CD-BC","Bas-Congo","Province","Congo, The Democratic Republic of the",2 +"COD","CD","CD-BN","Bandundu","Province","Congo, The Democratic Republic of the",2 +"COD","CD","CD-EQ","Équateur","Province","Congo, The Democratic Republic of the",2 +"COD","CD","CD-KA","Katanga","Province","Congo, The Democratic Republic of the",2 +"COD","CD","CD-KE","Kasai-Oriental","Province","Congo, The Democratic Republic of the",2 +"COD","CD","CD-KN","Kinshasa","City","Congo, The Democratic Republic of the",2 +"COD","CD","CD-KW","Kasai-Occidental","Province","Congo, The Democratic Republic of the",2 +"COD","CD","CD-MA","Maniema","Province","Congo, The Democratic Republic of the",2 +"COD","CD","CD-NK","Nord-Kivu","Province","Congo, The Democratic Republic of the",2 +"COD","CD","CD-OR","Orientale","Province","Congo, The Democratic Republic of the",2 +"COD","CD","CD-SK","Sud-Kivu","Province","Congo, The Democratic Republic of the",2 +"CAF","CF","CF-AC","Ouham","Prefecture","Central African Republic",2 +"CAF","CF","CF-BB","Bamingui-Bangoran","Prefecture","Central African Republic",2 +"CAF","CF","CF-BGF","Bangui","Commune","Central African Republic",2 +"CAF","CF","CF-BK","Basse-Kotto","Prefecture","Central African Republic",2 +"CAF","CF","CF-HK","Haute-Kotto","Prefecture","Central African Republic",2 +"CAF","CF","CF-HM","Haut-Mbomou","Prefecture","Central African Republic",2 +"CAF","CF","CF-HS","Haute-Sangha / Mambéré-Kadéï","Prefecture","Central African Republic",2 +"CAF","CF","CF-KB","Gribingui","Economic Prefecture","Central African Republic",2 +"CAF","CF","CF-KG","Kémo-Gribingui","Prefecture","Central African Republic",2 +"CAF","CF","CF-LB","Lobaye","Prefecture","Central African Republic",2 +"CAF","CF","CF-MB","Mbomou","Prefecture","Central African Republic",2 +"CAF","CF","CF-MP","Ombella-M'poko","Prefecture","Central African Republic",2 +"CAF","CF","CF-NM","Nana-Mambéré","Prefecture","Central African Republic",2 +"CAF","CF","CF-OP","Ouham-Pendé","Prefecture","Central African Republic",2 +"CAF","CF","CF-SE","Sangha","Economic Prefecture","Central African Republic",2 +"CAF","CF","CF-UK","Ouaka","Prefecture","Central African Republic",2 +"CAF","CF","CF-VK","Vakaga","Prefecture","Central African Republic",2 +"COG","CG","CG-11","Bouenza","Region","Congo",2 +"COG","CG","CG-12","Pool","Region","Congo",2 +"COG","CG","CG-13","Sangha","Region","Congo",2 +"COG","CG","CG-14","Plateaux","Region","Congo",2 +"COG","CG","CG-15","Cuvette-Ouest","Region","Congo",2 +"COG","CG","CG-2","Lékoumou","Region","Congo",2 +"COG","CG","CG-5","Kouilou","Region","Congo",2 +"COG","CG","CG-7","Likouala","Region","Congo",2 +"COG","CG","CG-8","Cuvette","Region","Congo",2 +"COG","CG","CG-9","Niari","Region","Congo",2 +"COG","CG","CG-BZV","Brazzaville","Capital District","Congo",2 +"CHE","CH","CH-AG","Aargau","Canton","Switzerland",2 +"CHE","CH","CH-AI","Appenzell Innerrhoden","Canton","Switzerland",2 +"CHE","CH","CH-AR","Appenzell Ausserrhoden","Canton","Switzerland",2 +"CHE","CH","CH-BE","Bern","Canton","Switzerland",2 +"CHE","CH","CH-BL","Basel-Landschaft","Canton","Switzerland",2 +"CHE","CH","CH-BS","Basel-Stadt","Canton","Switzerland",2 +"CHE","CH","CH-FR","Fribourg","Canton","Switzerland",2 +"CHE","CH","CH-GE","Genève","Canton","Switzerland",2 +"CHE","CH","CH-GL","Glarus","Canton","Switzerland",2 +"CHE","CH","CH-GR","Graubünden","Canton","Switzerland",2 +"CHE","CH","CH-JU","Jura","Canton","Switzerland",2 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(Région des)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-04","Vallée du Bandama (Région de la)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-05","Moyen-Comoé (Région du)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-06","18 Montagnes (Région des)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-07","Lacs (Région des)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-08","Zanzan (Région du)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-09","Bas-Sassandra (Région du)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-10","Denguélé (Région du)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-11","Nzi-Comoé (Région)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-12","Marahoué (Région de la)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-13","Sud-Comoé (Région du)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-14","Worodouqou (Région du)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-15","Sud-Bandama (Région du)","Region","Côte d'Ivoire",2 +"CIV","CI","CI-16","Agnébi (Région de l')","Region","Côte d'Ivoire",2 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Rica",2 +"CUB","CU","CU-01","Pinar del Rio","Province","Cuba",2 +"CUB","CU","CU-02","La Habana","Province","Cuba",2 +"CUB","CU","CU-03","Ciudad de La Habana","Province","Cuba",2 +"CUB","CU","CU-04","Matanzas","Province","Cuba",2 +"CUB","CU","CU-05","Villa Clara","Province","Cuba",2 +"CUB","CU","CU-06","Cienfuegos","Province","Cuba",2 +"CUB","CU","CU-07","Sancti Spíritus","Province","Cuba",2 +"CUB","CU","CU-08","Ciego de Ávila","Province","Cuba",2 +"CUB","CU","CU-09","Camagüey","Province","Cuba",2 +"CUB","CU","CU-10","Las Tunas","Province","Cuba",2 +"CUB","CU","CU-11","Holguín","Province","Cuba",2 +"CUB","CU","CU-12","Granma","Province","Cuba",2 +"CUB","CU","CU-13","Santiago de Cuba","Province","Cuba",2 +"CUB","CU","CU-14","Guantánamo","Province","Cuba",2 +"CUB","CU","CU-99","Isla de la Juventud","Special municipality","Cuba",2 +"CPV","CV","CV-B","Ilhas de Barlavento","Geographical region","Cabo Verde",2 +"CPV","CV","CV-BR","Brava","Municipality","Cabo Verde",2 +"CPV","CV","CV-BV","Boa Vista","Municipality","Cabo Verde",2 +"CPV","CV","CV-CA","Santa Catarina","Municipality","Cabo Verde",2 +"CPV","CV","CV-CF","Santa Catarina de Fogo","Municipality","Cabo Verde",2 +"CPV","CV","CV-CR","Santa Cruz","Municipality","Cabo Verde",2 +"CPV","CV","CV-MA","Maio","Municipality","Cabo Verde",2 +"CPV","CV","CV-MO","Mosteiros","Municipality","Cabo Verde",2 +"CPV","CV","CV-PA","Paul","Municipality","Cabo Verde",2 +"CPV","CV","CV-PN","Porto Novo","Municipality","Cabo Verde",2 +"CPV","CV","CV-PR","Praia","Municipality","Cabo Verde",2 +"CPV","CV","CV-RB","Ribeira Brava","Municipality","Cabo Verde",2 +"CPV","CV","CV-RG","Ribeira Grande","Municipality","Cabo Verde",2 +"CPV","CV","CV-RS","Ribeira Grande de Santiago","Municipality","Cabo Verde",2 +"CPV","CV","CV-S","Ilhas de Sotavento","Geographical region","Cabo Verde",2 +"CPV","CV","CV-SD","São Domingos","Municipality","Cabo Verde",2 +"CPV","CV","CV-SF","São Filipe","Municipality","Cabo Verde",2 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3","district","Czechia",2 +"CZE","CZ","CZ-104","Praha 4","district","Czechia",2 +"CZE","CZ","CZ-105","Praha 5","district","Czechia",2 +"CZE","CZ","CZ-106","Praha 6","district","Czechia",2 +"CZE","CZ","CZ-107","Praha 7","district","Czechia",2 +"CZE","CZ","CZ-108","Praha 8","district","Czechia",2 +"CZE","CZ","CZ-109","Praha 9","district","Czechia",2 +"CZE","CZ","CZ-110","Praha 10","district","Czechia",2 +"CZE","CZ","CZ-111","Praha 11","district","Czechia",2 +"CZE","CZ","CZ-112","Praha 12","district","Czechia",2 +"CZE","CZ","CZ-113","Praha 13","district","Czechia",2 +"CZE","CZ","CZ-114","Praha 14","district","Czechia",2 +"CZE","CZ","CZ-115","Praha 15","district","Czechia",2 +"CZE","CZ","CZ-116","Praha 16","district","Czechia",2 +"CZE","CZ","CZ-117","Praha 17","district","Czechia",2 +"CZE","CZ","CZ-118","Praha 18","district","Czechia",2 +"CZE","CZ","CZ-119","Praha 19","district","Czechia",2 +"CZE","CZ","CZ-120","Praha 20","district","Czechia",2 +"CZE","CZ","CZ-121","Praha 21","district","Czechia",2 +"CZE","CZ","CZ-122","Praha 22","district","Czechia",2 +"CZE","CZ","CZ-20","Středočeský kraj","region","Czechia",2 +"CZE","CZ","CZ-201","Benešov","district","Czechia",2 +"CZE","CZ","CZ-202","Beroun","district","Czechia",2 +"CZE","CZ","CZ-203","Kladno","district","Czechia",2 +"CZE","CZ","CZ-204","Kolín","district","Czechia",2 +"CZE","CZ","CZ-205","Kutná Hora","district","Czechia",2 +"CZE","CZ","CZ-206","Mělník","district","Czechia",2 +"CZE","CZ","CZ-207","Mladá Boleslav","district","Czechia",2 +"CZE","CZ","CZ-208","Nymburk","district","Czechia",2 +"CZE","CZ","CZ-209","Praha-východ","district","Czechia",2 +"CZE","CZ","CZ-20A","Praha-západ","district","Czechia",2 +"CZE","CZ","CZ-20B","Příbram","district","Czechia",2 +"CZE","CZ","CZ-20C","Rakovník","district","Czechia",2 +"CZE","CZ","CZ-31","Jihočeský kraj","region","Czechia",2 +"CZE","CZ","CZ-311","České Budějovice","district","Czechia",2 +"CZE","CZ","CZ-312","Český Krumlov","district","Czechia",2 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kraj","region","Czechia",2 +"CZE","CZ","CZ-421","Děčín","district","Czechia",2 +"CZE","CZ","CZ-422","Chomutov","district","Czechia",2 +"CZE","CZ","CZ-423","Litoměřice","district","Czechia",2 +"CZE","CZ","CZ-424","Louny","district","Czechia",2 +"CZE","CZ","CZ-425","Most","district","Czechia",2 +"CZE","CZ","CZ-426","Teplice","district","Czechia",2 +"CZE","CZ","CZ-427","Ústí nad Labem","district","Czechia",2 +"CZE","CZ","CZ-51","Liberecký kraj","region","Czechia",2 +"CZE","CZ","CZ-511","Česká Lípa","district","Czechia",2 +"CZE","CZ","CZ-512","Jablonec nad Nisou","district","Czechia",2 +"CZE","CZ","CZ-513","Liberec","district","Czechia",2 +"CZE","CZ","CZ-514","Semily","district","Czechia",2 +"CZE","CZ","CZ-52","Královéhradecký kraj","region","Czechia",2 +"CZE","CZ","CZ-521","Hradec Králové","district","Czechia",2 +"CZE","CZ","CZ-522","Jičín","district","Czechia",2 +"CZE","CZ","CZ-523","Náchod","district","Czechia",2 +"CZE","CZ","CZ-524","Rychnov nad Kněžnou","district","Czechia",2 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+"CZE","CZ","CZ-645","Hodonín","district","Czechia",2 +"CZE","CZ","CZ-646","Vyškov","district","Czechia",2 +"CZE","CZ","CZ-647","Znojmo","district","Czechia",2 +"CZE","CZ","CZ-71","Olomoucký kraj","region","Czechia",2 +"CZE","CZ","CZ-711","Jeseník","district","Czechia",2 +"CZE","CZ","CZ-712","Olomouc","district","Czechia",2 +"CZE","CZ","CZ-713","Prostějov","district","Czechia",2 +"CZE","CZ","CZ-714","Přerov","district","Czechia",2 +"CZE","CZ","CZ-715","Šumperk","district","Czechia",2 +"CZE","CZ","CZ-72","Zlínský kraj","region","Czechia",2 +"CZE","CZ","CZ-721","Kroměříž","district","Czechia",2 +"CZE","CZ","CZ-722","Uherské Hradiště","district","Czechia",2 +"CZE","CZ","CZ-723","Vsetín","district","Czechia",2 +"CZE","CZ","CZ-724","Zlín","district","Czechia",2 +"CZE","CZ","CZ-80","Moravskoslezský kraj","region","Czechia",2 +"CZE","CZ","CZ-801","Bruntál","district","Czechia",2 +"CZE","CZ","CZ-802","Frýdek Místek","district","Czechia",2 +"CZE","CZ","CZ-803","Karviná","district","Czechia",2 +"CZE","CZ","CZ-804","Nový Jičín","district","Czechia",2 +"CZE","CZ","CZ-805","Opava","district","Czechia",2 +"CZE","CZ","CZ-806","Ostrava-město","district","Czechia",2 +"DEU","DE","DE-BB","Brandenburg","State","Germany",2 +"DEU","DE","DE-BE","Berlin","State","Germany",2 +"DEU","DE","DE-BW","Baden-Württemberg","State","Germany",2 +"DEU","DE","DE-BY","Bayern","State","Germany",2 +"DEU","DE","DE-HB","Bremen","State","Germany",2 +"DEU","DE","DE-HE","Hessen","State","Germany",2 +"DEU","DE","DE-HH","Hamburg","State","Germany",2 +"DEU","DE","DE-MV","Mecklenburg-Vorpommern","State","Germany",2 +"DEU","DE","DE-NI","Niedersachsen","State","Germany",2 +"DEU","DE","DE-NW","Nordrhein-Westfalen","State","Germany",2 +"DEU","DE","DE-RP","Rheinland-Pfalz","State","Germany",2 +"DEU","DE","DE-SH","Schleswig-Holstein","State","Germany",2 +"DEU","DE","DE-SL","Saarland","State","Germany",2 +"DEU","DE","DE-SN","Sachsen","State","Germany",2 +"DEU","DE","DE-ST","Sachsen-Anhalt","State","Germany",2 +"DEU","DE","DE-TH","Thüringen","State","Germany",2 +"DJI","DJ","DJ-AR","Arta","Region","Djibouti",2 +"DJI","DJ","DJ-AS","Ali Sabieh","Region","Djibouti",2 +"DJI","DJ","DJ-DI","Dikhil","Region","Djibouti",2 +"DJI","DJ","DJ-DJ","Djibouti","City","Djibouti",2 +"DJI","DJ","DJ-OB","Obock","Region","Djibouti",2 +"DJI","DJ","DJ-TA","Tadjourah","Region","Djibouti",2 +"DNK","DK","DK-81","Nordjylland","Region","Denmark",2 +"DNK","DK","DK-82","Midtjylland","Region","Denmark",2 +"DNK","DK","DK-83","Syddanmark","Region","Denmark",2 +"DNK","DK","DK-84","Hovedstaden","Region","Denmark",2 +"DNK","DK","DK-85","Sjælland","Region","Denmark",2 +"DMA","DM","DM-01","Saint Peter","Parish","Dominica",2 +"DMA","DM","DM-02","Saint Andrew","Parish","Dominica",2 +"DMA","DM","DM-03","Saint David","Parish","Dominica",2 +"DMA","DM","DM-04","Saint George","Parish","Dominica",2 +"DMA","DM","DM-05","Saint John","Parish","Dominica",2 +"DMA","DM","DM-06","Saint Joseph","Parish","Dominica",2 +"DMA","DM","DM-07","Saint Luke","Parish","Dominica",2 +"DMA","DM","DM-08","Saint Mark","Parish","Dominica",2 +"DMA","DM","DM-09","Saint Patrick","Parish","Dominica",2 +"DMA","DM","DM-10","Saint Paul","Parish","Dominica",2 +"DOM","DO","DO-01","Distrito Nacional (Santo Domingo)","District","Dominican Republic",2 +"DOM","DO","DO-02","Azua","Province","Dominican Republic",2 +"DOM","DO","DO-03","Bahoruco","Province","Dominican Republic",2 +"DOM","DO","DO-04","Barahona","Province","Dominican Republic",2 +"DOM","DO","DO-05","Dajabón","Province","Dominican Republic",2 +"DOM","DO","DO-06","Duarte","Province","Dominican Republic",2 +"DOM","DO","DO-07","La Estrelleta [Elías Piña]","Province","Dominican Republic",2 +"DOM","DO","DO-08","El Seybo [El Seibo]","Province","Dominican Republic",2 +"DOM","DO","DO-09","Espaillat","Province","Dominican Republic",2 +"DOM","DO","DO-10","Independencia","Province","Dominican Republic",2 +"DOM","DO","DO-11","La Altagracia","Province","Dominican Republic",2 +"DOM","DO","DO-12","La Romana","Province","Dominican Republic",2 +"DOM","DO","DO-13","La Vega","Province","Dominican Republic",2 +"DOM","DO","DO-14","María Trinidad Sánchez","Province","Dominican Republic",2 +"DOM","DO","DO-15","Monte Cristi","Province","Dominican Republic",2 +"DOM","DO","DO-16","Pedernales","Province","Dominican Republic",2 +"DOM","DO","DO-17","Peravia","Province","Dominican Republic",2 +"DOM","DO","DO-18","Puerto Plata","Province","Dominican Republic",2 +"DOM","DO","DO-19","Salcedo","Province","Dominican Republic",2 +"DOM","DO","DO-20","Samaná","Province","Dominican Republic",2 +"DOM","DO","DO-21","San Cristóbal","Province","Dominican Republic",2 +"DOM","DO","DO-22","San Juan","Province","Dominican Republic",2 +"DOM","DO","DO-23","San Pedro de Macorís","Province","Dominican Republic",2 +"DOM","DO","DO-24","Sánchez Ramírez","Province","Dominican Republic",2 +"DOM","DO","DO-25","Santiago","Province","Dominican Republic",2 +"DOM","DO","DO-26","Santiago Rodríguez","Province","Dominican Republic",2 +"DOM","DO","DO-27","Valverde","Province","Dominican Republic",2 +"DOM","DO","DO-28","Monseñor Nouel","Province","Dominican Republic",2 +"DOM","DO","DO-29","Monte Plata","Province","Dominican Republic",2 +"DOM","DO","DO-30","Hato Mayor","Province","Dominican Republic",2 +"DZA","DZ","DZ-01","Adrar","Province","Algeria",2 +"DZA","DZ","DZ-02","Chlef","Province","Algeria",2 +"DZA","DZ","DZ-03","Laghouat","Province","Algeria",2 +"DZA","DZ","DZ-04","Oum el Bouaghi","Province","Algeria",2 +"DZA","DZ","DZ-05","Batna","Province","Algeria",2 +"DZA","DZ","DZ-06","Béjaïa","Province","Algeria",2 +"DZA","DZ","DZ-07","Biskra","Province","Algeria",2 +"DZA","DZ","DZ-08","Béchar","Province","Algeria",2 +"DZA","DZ","DZ-09","Blida","Province","Algeria",2 +"DZA","DZ","DZ-10","Bouira","Province","Algeria",2 +"DZA","DZ","DZ-11","Tamanghasset","Province","Algeria",2 +"DZA","DZ","DZ-12","Tébessa","Province","Algeria",2 +"DZA","DZ","DZ-13","Tlemcen","Province","Algeria",2 +"DZA","DZ","DZ-14","Tiaret","Province","Algeria",2 +"DZA","DZ","DZ-15","Tizi Ouzou","Province","Algeria",2 +"DZA","DZ","DZ-16","Alger","Province","Algeria",2 +"DZA","DZ","DZ-17","Djelfa","Province","Algeria",2 +"DZA","DZ","DZ-18","Jijel","Province","Algeria",2 +"DZA","DZ","DZ-19","Sétif","Province","Algeria",2 +"DZA","DZ","DZ-20","Saïda","Province","Algeria",2 +"DZA","DZ","DZ-21","Skikda","Province","Algeria",2 +"DZA","DZ","DZ-22","Sidi Bel Abbès","Province","Algeria",2 +"DZA","DZ","DZ-23","Annaba","Province","Algeria",2 +"DZA","DZ","DZ-24","Guelma","Province","Algeria",2 +"DZA","DZ","DZ-25","Constantine","Province","Algeria",2 +"DZA","DZ","DZ-26","Médéa","Province","Algeria",2 +"DZA","DZ","DZ-27","Mostaganem","Province","Algeria",2 +"DZA","DZ","DZ-28","Msila","Province","Algeria",2 +"DZA","DZ","DZ-29","Mascara","Province","Algeria",2 +"DZA","DZ","DZ-30","Ouargla","Province","Algeria",2 +"DZA","DZ","DZ-31","Oran","Province","Algeria",2 +"DZA","DZ","DZ-32","El Bayadh","Province","Algeria",2 +"DZA","DZ","DZ-33","Illizi","Province","Algeria",2 +"DZA","DZ","DZ-34","Bordj Bou Arréridj","Province","Algeria",2 +"DZA","DZ","DZ-35","Boumerdès","Province","Algeria",2 +"DZA","DZ","DZ-36","El Tarf","Province","Algeria",2 +"DZA","DZ","DZ-37","Tindouf","Province","Algeria",2 +"DZA","DZ","DZ-38","Tissemsilt","Province","Algeria",2 +"DZA","DZ","DZ-39","El Oued","Province","Algeria",2 +"DZA","DZ","DZ-40","Khenchela","Province","Algeria",2 +"DZA","DZ","DZ-41","Souk Ahras","Province","Algeria",2 +"DZA","DZ","DZ-42","Tipaza","Province","Algeria",2 +"DZA","DZ","DZ-43","Mila","Province","Algeria",2 +"DZA","DZ","DZ-44","Aïn Defla","Province","Algeria",2 +"DZA","DZ","DZ-45","Naama","Province","Algeria",2 +"DZA","DZ","DZ-46","Aïn Témouchent","Province","Algeria",2 +"DZA","DZ","DZ-47","Ghardaïa","Province","Algeria",2 +"DZA","DZ","DZ-48","Relizane","Province","Algeria",2 +"ECU","EC","EC-A","Azuay","Province","Ecuador",2 +"ECU","EC","EC-B","Bolívar","Province","Ecuador",2 +"ECU","EC","EC-C","Carchi","Province","Ecuador",2 +"ECU","EC","EC-D","Orellana","Province","Ecuador",2 +"ECU","EC","EC-E","Esmeraldas","Province","Ecuador",2 +"ECU","EC","EC-F","Cañar","Province","Ecuador",2 +"ECU","EC","EC-G","Guayas","Province","Ecuador",2 +"ECU","EC","EC-H","Chimborazo","Province","Ecuador",2 +"ECU","EC","EC-I","Imbabura","Province","Ecuador",2 +"ECU","EC","EC-L","Loja","Province","Ecuador",2 +"ECU","EC","EC-M","Manabí","Province","Ecuador",2 +"ECU","EC","EC-N","Napo","Province","Ecuador",2 +"ECU","EC","EC-O","El Oro","Province","Ecuador",2 +"ECU","EC","EC-P","Pichincha","Province","Ecuador",2 +"ECU","EC","EC-R","Los Ríos","Province","Ecuador",2 +"ECU","EC","EC-S","Morona-Santiago","Province","Ecuador",2 +"ECU","EC","EC-SD","Santo Domingo de los Tsáchilas","Province","Ecuador",2 +"ECU","EC","EC-SE","Santa Elena","Province","Ecuador",2 +"ECU","EC","EC-T","Tungurahua","Province","Ecuador",2 +"ECU","EC","EC-U","Sucumbíos","Province","Ecuador",2 +"ECU","EC","EC-W","Galápagos","Province","Ecuador",2 +"ECU","EC","EC-X","Cotopaxi","Province","Ecuador",2 +"ECU","EC","EC-Y","Pastaza","Province","Ecuador",2 +"ECU","EC","EC-Z","Zamora-Chinchipe","Province","Ecuador",2 +"EST","EE","EE-37","Harjumaa","County","Estonia",2 +"EST","EE","EE-39","Hiiumaa","County","Estonia",2 +"EST","EE","EE-44","Ida-Virumaa","County","Estonia",2 +"EST","EE","EE-49","Jõgevamaa","County","Estonia",2 +"EST","EE","EE-51","Järvamaa","County","Estonia",2 +"EST","EE","EE-57","Läänemaa","County","Estonia",2 +"EST","EE","EE-59","Lääne-Virumaa","County","Estonia",2 +"EST","EE","EE-65","Põlvamaa","County","Estonia",2 +"EST","EE","EE-67","Pärnumaa","County","Estonia",2 +"EST","EE","EE-70","Raplamaa","County","Estonia",2 +"EST","EE","EE-74","Saaremaa","County","Estonia",2 +"EST","EE","EE-78","Tartumaa","County","Estonia",2 +"EST","EE","EE-82","Valgamaa","County","Estonia",2 +"EST","EE","EE-84","Viljandimaa","County","Estonia",2 +"EST","EE","EE-86","Võrumaa","County","Estonia",2 +"EGY","EG","EG-ALX","Al Iskandarīyah","Governorate","Egypt",2 +"EGY","EG","EG-ASN","Aswān","Governorate","Egypt",2 +"EGY","EG","EG-AST","Asyūt","Governorate","Egypt",2 +"EGY","EG","EG-BA","Al Bahr al Ahmar","Governorate","Egypt",2 +"EGY","EG","EG-BH","Al Buhayrah","Governorate","Egypt",2 +"EGY","EG","EG-BNS","Banī Suwayf","Governorate","Egypt",2 +"EGY","EG","EG-C","Al Qāhirah","Governorate","Egypt",2 +"EGY","EG","EG-DK","Ad Daqahlīyah","Governorate","Egypt",2 +"EGY","EG","EG-DT","Dumyāt","Governorate","Egypt",2 +"EGY","EG","EG-FYM","Al Fayyūm","Governorate","Egypt",2 +"EGY","EG","EG-GH","Al Gharbīyah","Governorate","Egypt",2 +"EGY","EG","EG-GZ","Al Jīzah","Governorate","Egypt",2 +"EGY","EG","EG-HU","Ḩulwān","Governorate","Egypt",2 +"EGY","EG","EG-IS","Al Ismā`īlīyah","Governorate","Egypt",2 +"EGY","EG","EG-JS","Janūb Sīnā'","Governorate","Egypt",2 +"EGY","EG","EG-KB","Al Qalyūbīyah","Governorate","Egypt",2 +"EGY","EG","EG-KFS","Kafr ash Shaykh","Governorate","Egypt",2 +"EGY","EG","EG-KN","Qinā","Governorate","Egypt",2 +"EGY","EG","EG-MN","Al Minyā","Governorate","Egypt",2 +"EGY","EG","EG-MNF","Al Minūfīyah","Governorate","Egypt",2 +"EGY","EG","EG-MT","Matrūh","Governorate","Egypt",2 +"EGY","EG","EG-PTS","Būr Sa`īd","Governorate","Egypt",2 +"EGY","EG","EG-SHG","Sūhāj","Governorate","Egypt",2 +"EGY","EG","EG-SHR","Ash Sharqīyah","Governorate","Egypt",2 +"EGY","EG","EG-SIN","Shamal Sīnā'","Governorate","Egypt",2 +"EGY","EG","EG-SU","As Sādis min Uktūbar","Governorate","Egypt",2 +"EGY","EG","EG-SUZ","As Suways","Governorate","Egypt",2 +"EGY","EG","EG-WAD","Al Wādī al Jadīd","Governorate","Egypt",2 +"ERI","ER","ER-AN","Ansabā","Province","Eritrea",2 +"ERI","ER","ER-DK","Janūbī al Baḩrī al Aḩmar","Province","Eritrea",2 +"ERI","ER","ER-DU","Al Janūbī","Province","Eritrea",2 +"ERI","ER","ER-GB","Qāsh-Barkah","Province","Eritrea",2 +"ERI","ER","ER-MA","Al Awsaţ","Province","Eritrea",2 +"ERI","ER","ER-SK","Shimālī al Baḩrī al Aḩmar","Province","Eritrea",2 +"ESP","ES","ES-A","Alicante","Province","Spain",2 +"ESP","ES","ES-AB","Albacete","Province","Spain",2 +"ESP","ES","ES-AL","Almería","Province","Spain",2 +"ESP","ES","ES-AN","Andalucía","Autonomous community","Spain",2 +"ESP","ES","ES-AR","Aragón","Autonomous community","Spain",2 +"ESP","ES","ES-AS","Asturias, Principado de","Autonomous community","Spain",2 +"ESP","ES","ES-AV","Ávila","Province","Spain",2 +"ESP","ES","ES-B","Barcelona","Province","Spain",2 +"ESP","ES","ES-BA","Badajoz","Province","Spain",2 +"ESP","ES","ES-BI","Bizkaia","Province","Spain",2 +"ESP","ES","ES-BU","Burgos","Province","Spain",2 +"ESP","ES","ES-C","A Coruña","Province","Spain",2 +"ESP","ES","ES-CA","Cádiz","Province","Spain",2 +"ESP","ES","ES-CB","Cantabria","Autonomous community","Spain",2 +"ESP","ES","ES-CC","Cáceres","Province","Spain",2 +"ESP","ES","ES-CE","Ceuta","Autonomous city","Spain",2 +"ESP","ES","ES-CL","Castilla y León","Autonomous community","Spain",2 +"ESP","ES","ES-CM","Castilla-La Mancha","Autonomous community","Spain",2 +"ESP","ES","ES-CN","Canarias","Autonomous community","Spain",2 +"ESP","ES","ES-CO","Córdoba","Province","Spain",2 +"ESP","ES","ES-CR","Ciudad Real","Province","Spain",2 +"ESP","ES","ES-CS","Castellón","Province","Spain",2 +"ESP","ES","ES-CT","Catalunya","Autonomous community","Spain",2 +"ESP","ES","ES-CU","Cuenca","Province","Spain",2 +"ESP","ES","ES-EX","Extremadura","Autonomous community","Spain",2 +"ESP","ES","ES-GA","Galicia","Autonomous community","Spain",2 +"ESP","ES","ES-GC","Las Palmas","Province","Spain",2 +"ESP","ES","ES-GI","Girona","Province","Spain",2 +"ESP","ES","ES-GR","Granada","Province","Spain",2 +"ESP","ES","ES-GU","Guadalajara","Province","Spain",2 +"ESP","ES","ES-H","Huelva","Province","Spain",2 +"ESP","ES","ES-HU","Huesca","Province","Spain",2 +"ESP","ES","ES-IB","Illes Balears","Autonomous community","Spain",2 +"ESP","ES","ES-J","Jaén","Province","Spain",2 +"ESP","ES","ES-L","Lleida","Province","Spain",2 +"ESP","ES","ES-LE","León","Province","Spain",2 +"ESP","ES","ES-LO","La Rioja","Province","Spain",2 +"ESP","ES","ES-LU","Lugo","Province","Spain",2 +"ESP","ES","ES-M","Madrid","Province","Spain",2 +"ESP","ES","ES-MA","Málaga","Province","Spain",2 +"ESP","ES","ES-MC","Murcia, Región de","Autonomous community","Spain",2 +"ESP","ES","ES-MD","Madrid, Comunidad de","Autonomous community","Spain",2 +"ESP","ES","ES-ML","Melilla","Autonomous city","Spain",2 +"ESP","ES","ES-MU","Murcia","Province","Spain",2 +"ESP","ES","ES-NA","Navarra / Nafarroa","Province","Spain",2 +"ESP","ES","ES-NC","Navarra, Comunidad Foral de / Nafarroako Foru Komunitatea","Autonomous community","Spain",2 +"ESP","ES","ES-O","Asturias","Province","Spain",2 +"ESP","ES","ES-OR","Ourense","Province","Spain",2 +"ESP","ES","ES-P","Palencia","Province","Spain",2 +"ESP","ES","ES-PM","Balears","Province","Spain",2 +"ESP","ES","ES-PO","Pontevedra","Province","Spain",2 +"ESP","ES","ES-PV","País Vasco / Euskal Herria","Autonomous community","Spain",2 +"ESP","ES","ES-RI","La Rioja","Autonomous community","Spain",2 +"ESP","ES","ES-S","Cantabria","Province","Spain",2 +"ESP","ES","ES-SA","Salamanca","Province","Spain",2 +"ESP","ES","ES-SE","Sevilla","Province","Spain",2 +"ESP","ES","ES-SG","Segovia","Province","Spain",2 +"ESP","ES","ES-SO","Soria","Province","Spain",2 +"ESP","ES","ES-SS","Gipuzkoa","Province","Spain",2 +"ESP","ES","ES-T","Tarragona","Province","Spain",2 +"ESP","ES","ES-TE","Teruel","Province","Spain",2 +"ESP","ES","ES-TF","Santa Cruz de Tenerife","Province","Spain",2 +"ESP","ES","ES-TO","Toledo","Province","Spain",2 +"ESP","ES","ES-V","Valencia / València","Province","Spain",2 +"ESP","ES","ES-VA","Valladolid","Province","Spain",2 +"ESP","ES","ES-VC","Valenciana, Comunidad / Valenciana, Comunitat","Autonomous community","Spain",2 +"ESP","ES","ES-VI","Álava","Province","Spain",2 +"ESP","ES","ES-Z","Zaragoza","Province","Spain",2 +"ESP","ES","ES-ZA","Zamora","Province","Spain",2 +"ETH","ET","ET-AA","Ādīs Ābeba","Administration","Ethiopia",2 +"ETH","ET","ET-AF","Āfar","State","Ethiopia",2 +"ETH","ET","ET-AM","Āmara","State","Ethiopia",2 +"ETH","ET","ET-BE","Bīnshangul Gumuz","State","Ethiopia",2 +"ETH","ET","ET-DD","Dirē Dawa","Administration","Ethiopia",2 +"ETH","ET","ET-GA","Gambēla Hizboch","State","Ethiopia",2 +"ETH","ET","ET-HA","Hārerī Hizb","State","Ethiopia",2 +"ETH","ET","ET-OR","Oromīya","State","Ethiopia",2 +"ETH","ET","ET-SN","YeDebub Bihēroch Bihēreseboch na Hizboch","State","Ethiopia",2 +"ETH","ET","ET-SO","Sumalē","State","Ethiopia",2 +"ETH","ET","ET-TI","Tigray","State","Ethiopia",2 +"FIN","FI","FI-01","Ahvenanmaan maakunta","Region","Finland",2 +"FIN","FI","FI-02","Etelä-Karjala","Region","Finland",2 +"FIN","FI","FI-03","Etelä-Pohjanmaa","Region","Finland",2 +"FIN","FI","FI-04","Etelä-Savo","Region","Finland",2 +"FIN","FI","FI-05","Kainuu","Region","Finland",2 +"FIN","FI","FI-06","Kanta-Häme","Region","Finland",2 +"FIN","FI","FI-07","Keski-Pohjanmaa","Region","Finland",2 +"FIN","FI","FI-08","Keski-Suomi","Region","Finland",2 +"FIN","FI","FI-09","Kymenlaakso","Region","Finland",2 +"FIN","FI","FI-10","Lappi","Region","Finland",2 +"FIN","FI","FI-11","Pirkanmaa","Region","Finland",2 +"FIN","FI","FI-12","Pohjanmaa","Region","Finland",2 +"FIN","FI","FI-13","Pohjois-Karjala","Region","Finland",2 +"FIN","FI","FI-14","Pohjois-Pohjanmaa","Region","Finland",2 +"FIN","FI","FI-15","Pohjois-Savo","Region","Finland",2 +"FIN","FI","FI-16","Päijät-Häme","Region","Finland",2 +"FIN","FI","FI-17","Satakunta","Region","Finland",2 +"FIN","FI","FI-18","Uusimaa","Region","Finland",2 +"FIN","FI","FI-19","Varsinais-Suomi","Region","Finland",2 +"FJI","FJ","FJ-C","Central","Division","Fiji",2 +"FJI","FJ","FJ-E","Eastern","Division","Fiji",2 +"FJI","FJ","FJ-N","Northern","Division","Fiji",2 +"FJI","FJ","FJ-R","Rotuma","Dependency","Fiji",2 +"FJI","FJ","FJ-W","Western","Division","Fiji",2 +"FSM","FM","FM-KSA","Kosrae","State","Micronesia, Federated States of",2 +"FSM","FM","FM-PNI","Pohnpei","State","Micronesia, Federated States of",2 +"FSM","FM","FM-TRK","Chuuk","State","Micronesia, Federated States of",2 +"FSM","FM","FM-YAP","Yap","State","Micronesia, Federated States of",2 +"FRA","FR","FR-01","Ain","Metropolitan department","France",2 +"FRA","FR","FR-02","Aisne","Metropolitan department","France",2 +"FRA","FR","FR-03","Allier","Metropolitan department","France",2 +"FRA","FR","FR-04","Alpes-de-Haute-Provence","Metropolitan department","France",2 +"FRA","FR","FR-05","Hautes-Alpes","Metropolitan department","France",2 +"FRA","FR","FR-06","Alpes-Maritimes","Metropolitan department","France",2 +"FRA","FR","FR-07","Ardèche","Metropolitan department","France",2 +"FRA","FR","FR-08","Ardennes","Metropolitan department","France",2 +"FRA","FR","FR-09","Ariège","Metropolitan department","France",2 +"FRA","FR","FR-10","Aube","Metropolitan department","France",2 +"FRA","FR","FR-11","Aude","Metropolitan department","France",2 +"FRA","FR","FR-12","Aveyron","Metropolitan department","France",2 +"FRA","FR","FR-13","Bouches-du-Rhône","Metropolitan department","France",2 +"FRA","FR","FR-14","Calvados","Metropolitan department","France",2 +"FRA","FR","FR-15","Cantal","Metropolitan department","France",2 +"FRA","FR","FR-16","Charente","Metropolitan department","France",2 +"FRA","FR","FR-17","Charente-Maritime","Metropolitan department","France",2 +"FRA","FR","FR-18","Cher","Metropolitan department","France",2 +"FRA","FR","FR-19","Corrèze","Metropolitan department","France",2 +"FRA","FR","FR-21","Côte-d'Or","Metropolitan department","France",2 +"FRA","FR","FR-22","Côtes-d'Armor","Metropolitan department","France",2 +"FRA","FR","FR-23","Creuse","Metropolitan department","France",2 +"FRA","FR","FR-24","Dordogne","Metropolitan department","France",2 +"FRA","FR","FR-25","Doubs","Metropolitan department","France",2 +"FRA","FR","FR-26","Drôme","Metropolitan department","France",2 +"FRA","FR","FR-27","Eure","Metropolitan department","France",2 +"FRA","FR","FR-28","Eure-et-Loir","Metropolitan department","France",2 +"FRA","FR","FR-29","Finistère","Metropolitan department","France",2 +"FRA","FR","FR-2A","Corse-du-Sud","Metropolitan department","France",2 +"FRA","FR","FR-2B","Haute-Corse","Metropolitan department","France",2 +"FRA","FR","FR-30","Gard","Metropolitan department","France",2 +"FRA","FR","FR-31","Haute-Garonne","Metropolitan department","France",2 +"FRA","FR","FR-32","Gers","Metropolitan department","France",2 +"FRA","FR","FR-33","Gironde","Metropolitan department","France",2 +"FRA","FR","FR-34","Hérault","Metropolitan department","France",2 +"FRA","FR","FR-35","Ille-et-Vilaine","Metropolitan department","France",2 +"FRA","FR","FR-36","Indre","Metropolitan department","France",2 +"FRA","FR","FR-37","Indre-et-Loire","Metropolitan department","France",2 +"FRA","FR","FR-38","Isère","Metropolitan department","France",2 +"FRA","FR","FR-39","Jura","Metropolitan department","France",2 +"FRA","FR","FR-40","Landes","Metropolitan department","France",2 +"FRA","FR","FR-41","Loir-et-Cher","Metropolitan department","France",2 +"FRA","FR","FR-42","Loire","Metropolitan department","France",2 +"FRA","FR","FR-43","Haute-Loire","Metropolitan department","France",2 +"FRA","FR","FR-44","Loire-Atlantique","Metropolitan department","France",2 +"FRA","FR","FR-45","Loiret","Metropolitan department","France",2 +"FRA","FR","FR-46","Lot","Metropolitan department","France",2 +"FRA","FR","FR-47","Lot-et-Garonne","Metropolitan department","France",2 +"FRA","FR","FR-48","Lozère","Metropolitan department","France",2 +"FRA","FR","FR-49","Maine-et-Loire","Metropolitan department","France",2 +"FRA","FR","FR-50","Manche","Metropolitan department","France",2 +"FRA","FR","FR-51","Marne","Metropolitan department","France",2 +"FRA","FR","FR-52","Haute-Marne","Metropolitan department","France",2 +"FRA","FR","FR-53","Mayenne","Metropolitan department","France",2 +"FRA","FR","FR-54","Meurthe-et-Moselle","Metropolitan department","France",2 +"FRA","FR","FR-55","Meuse","Metropolitan department","France",2 +"FRA","FR","FR-56","Morbihan","Metropolitan department","France",2 +"FRA","FR","FR-57","Moselle","Metropolitan department","France",2 +"FRA","FR","FR-58","Nièvre","Metropolitan department","France",2 +"FRA","FR","FR-59","Nord","Metropolitan department","France",2 +"FRA","FR","FR-60","Oise","Metropolitan department","France",2 +"FRA","FR","FR-61","Orne","Metropolitan department","France",2 +"FRA","FR","FR-62","Pas-de-Calais","Metropolitan department","France",2 +"FRA","FR","FR-63","Puy-de-Dôme","Metropolitan department","France",2 +"FRA","FR","FR-64","Pyrénées-Atlantiques","Metropolitan department","France",2 +"FRA","FR","FR-65","Hautes-Pyrénées","Metropolitan department","France",2 +"FRA","FR","FR-66","Pyrénées-Orientales","Metropolitan department","France",2 +"FRA","FR","FR-67","Bas-Rhin","Metropolitan department","France",2 +"FRA","FR","FR-68","Haut-Rhin","Metropolitan department","France",2 +"FRA","FR","FR-69","Rhône","Metropolitan department","France",2 +"FRA","FR","FR-70","Haute-Saône","Metropolitan department","France",2 +"FRA","FR","FR-71","Saône-et-Loire","Metropolitan department","France",2 +"FRA","FR","FR-72","Sarthe","Metropolitan department","France",2 +"FRA","FR","FR-73","Savoie","Metropolitan department","France",2 +"FRA","FR","FR-74","Haute-Savoie","Metropolitan department","France",2 +"FRA","FR","FR-75","Paris","Metropolitan department","France",2 +"FRA","FR","FR-76","Seine-Maritime","Metropolitan department","France",2 +"FRA","FR","FR-77","Seine-et-Marne","Metropolitan department","France",2 +"FRA","FR","FR-78","Yvelines","Metropolitan department","France",2 +"FRA","FR","FR-79","Deux-Sèvres","Metropolitan department","France",2 +"FRA","FR","FR-80","Somme","Metropolitan department","France",2 +"FRA","FR","FR-81","Tarn","Metropolitan department","France",2 +"FRA","FR","FR-82","Tarn-et-Garonne","Metropolitan department","France",2 +"FRA","FR","FR-83","Var","Metropolitan department","France",2 +"FRA","FR","FR-84","Vaucluse","Metropolitan department","France",2 +"FRA","FR","FR-85","Vendée","Metropolitan department","France",2 +"FRA","FR","FR-86","Vienne","Metropolitan department","France",2 +"FRA","FR","FR-87","Haute-Vienne","Metropolitan department","France",2 +"FRA","FR","FR-88","Vosges","Metropolitan department","France",2 +"FRA","FR","FR-89","Yonne","Metropolitan department","France",2 +"FRA","FR","FR-90","Territoire de Belfort","Metropolitan department","France",2 +"FRA","FR","FR-91","Essonne","Metropolitan department","France",2 +"FRA","FR","FR-92","Hauts-de-Seine","Metropolitan department","France",2 +"FRA","FR","FR-93","Seine-Saint-Denis","Metropolitan department","France",2 +"FRA","FR","FR-94","Val-de-Marne","Metropolitan department","France",2 +"FRA","FR","FR-95","Val-d'Oise","Metropolitan department","France",2 +"FRA","FR","FR-ARA","Auvergne-Rhône-Alpes","Metropolitan region","France",2 +"FRA","FR","FR-BFC","Bourgogne-Franche-Comté","Metropolitan region","France",2 +"FRA","FR","FR-BL","Saint-Barthélemy","Overseas territorial collectivity","France",2 +"FRA","FR","FR-BRE","Bretagne","Metropolitan region","France",2 +"FRA","FR","FR-COR","Corse","Metropolitan region","France",2 +"FRA","FR","FR-CP","Clipperton","Dependency","France",2 +"FRA","FR","FR-CVL","Centre-Val de Loire","Metropolitan region","France",2 +"FRA","FR","FR-GES","Grand-Est","Metropolitan region","France",2 +"FRA","FR","FR-GF","Guyane (française)","Overseas territorial collectivity","France",2 +"FRA","FR","FR-GP","Guadeloupe","Overseas department","France",2 +"FRA","FR","FR-GUA","Guadeloupe","Overseas region","France",2 +"FRA","FR","FR-HDF","Hauts-de-France","Metropolitan region","France",2 +"FRA","FR","FR-IDF","Île-de-France","Metropolitan region","France",2 +"FRA","FR","FR-LRE","La Réunion","Overseas region","France",2 +"FRA","FR","FR-MAY","Mayotte","Overseas region","France",2 +"FRA","FR","FR-MF","Saint-Martin","Overseas territorial collectivity","France",2 +"FRA","FR","FR-MQ","Martinique","Overseas territorial collectivity","France",2 +"FRA","FR","FR-NAQ","Nouvelle-Aquitaine","Metropolitan region","France",2 +"FRA","FR","FR-NC","Nouvelle-Calédonie","Overseas territorial collectivity","France",2 +"FRA","FR","FR-NOR","Normandie","Metropolitan region","France",2 +"FRA","FR","FR-OCC","Occitanie","Metropolitan region","France",2 +"FRA","FR","FR-PAC","Provence-Alpes-Côte-d’Azur","Metropolitan region","France",2 +"FRA","FR","FR-PDL","Pays-de-la-Loire","Metropolitan region","France",2 +"FRA","FR","FR-PF","Polynésie française","Overseas territorial collectivity","France",2 +"FRA","FR","FR-PM","Saint-Pierre-et-Miquelon","Overseas territorial collectivity","France",2 +"FRA","FR","FR-RE","La Réunion","Overseas department","France",2 +"FRA","FR","FR-TF","Terres australes françaises","Overseas territorial collectivity","France",2 +"FRA","FR","FR-WF","Wallis-et-Futuna","Overseas territorial collectivity","France",2 +"FRA","FR","FR-YT","Mayotte","Overseas department","France",2 +"GAB","GA","GA-1","Estuaire","Province","Gabon",2 +"GAB","GA","GA-2","Haut-Ogooué","Province","Gabon",2 +"GAB","GA","GA-3","Moyen-Ogooué","Province","Gabon",2 +"GAB","GA","GA-4","Ngounié","Province","Gabon",2 +"GAB","GA","GA-5","Nyanga","Province","Gabon",2 +"GAB","GA","GA-6","Ogooué-Ivindo","Province","Gabon",2 +"GAB","GA","GA-7","Ogooué-Lolo","Province","Gabon",2 +"GAB","GA","GA-8","Ogooué-Maritime","Province","Gabon",2 +"GAB","GA","GA-9","Woleu-Ntem","Province","Gabon",2 +"GBR","GB","GB-ABC","Armagh, Banbridge and Craigavon","District","United Kingdom",2 +"GBR","GB","GB-ABD","Aberdeenshire","Council area","United Kingdom",2 +"GBR","GB","GB-ABE","Aberdeen City","Council area","United Kingdom",2 +"GBR","GB","GB-AGB","Argyll and Bute","Council area","United Kingdom",2 +"GBR","GB","GB-AGY","Isle of Anglesey; Sir Ynys Môn","Unitary authority","United Kingdom",2 +"GBR","GB","GB-AND","Ards and North Down","District","United Kingdom",2 +"GBR","GB","GB-ANN","Antrim and Newtownabbey","District","United Kingdom",2 +"GBR","GB","GB-ANS","Angus","Council area","United Kingdom",2 +"GBR","GB","GB-BAS","Bath and North East Somerset","Unitary authority","United Kingdom",2 +"GBR","GB","GB-BBD","Blackburn with Darwen","Unitary authority","United Kingdom",2 +"GBR","GB","GB-BDF","Bedford","Unitary authority","United Kingdom",2 +"GBR","GB","GB-BDG","Barking and Dagenham","London borough","United Kingdom",2 +"GBR","GB","GB-BEN","Brent","London borough","United Kingdom",2 +"GBR","GB","GB-BEX","Bexley","London borough","United Kingdom",2 +"GBR","GB","GB-BFS","Belfast","District","United Kingdom",2 +"GBR","GB","GB-BGE","Bridgend; Pen-y-bont ar Ogwr","Unitary authority","United Kingdom",2 +"GBR","GB","GB-BGW","Blaenau Gwent","Unitary authority","United Kingdom",2 +"GBR","GB","GB-BIR","Birmingham","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-BKM","Buckinghamshire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-BMH","Bournemouth","Unitary authority","United Kingdom",2 +"GBR","GB","GB-BNE","Barnet","London borough","United Kingdom",2 +"GBR","GB","GB-BNH","Brighton and Hove","Unitary authority","United Kingdom",2 +"GBR","GB","GB-BNS","Barnsley","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-BOL","Bolton","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-BPL","Blackpool","Unitary authority","United Kingdom",2 +"GBR","GB","GB-BRC","Bracknell Forest","Unitary authority","United Kingdom",2 +"GBR","GB","GB-BRD","Bradford","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-BRY","Bromley","London borough","United Kingdom",2 +"GBR","GB","GB-BST","Bristol, City of","Unitary authority","United Kingdom",2 +"GBR","GB","GB-BUR","Bury","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-CAM","Cambridgeshire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-CAY","Caerphilly; Caerffili","Unitary authority","United Kingdom",2 +"GBR","GB","GB-CBF","Central Bedfordshire","Unitary authority","United Kingdom",2 +"GBR","GB","GB-CCG","Causeway Coast and Glens","District","United Kingdom",2 +"GBR","GB","GB-CGN","Ceredigion; Sir Ceredigion","Unitary authority","United Kingdom",2 +"GBR","GB","GB-CHE","Cheshire East","Unitary authority","United Kingdom",2 +"GBR","GB","GB-CHW","Cheshire West and Chester","Unitary authority","United Kingdom",2 +"GBR","GB","GB-CLD","Calderdale","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-CLK","Clackmannanshire","Council area","United Kingdom",2 +"GBR","GB","GB-CMA","Cumbria","Two-tier county","United Kingdom",2 +"GBR","GB","GB-CMD","Camden","London borough","United Kingdom",2 +"GBR","GB","GB-CMN","Carmarthenshire; Sir Gaerfyrddin","Unitary authority","United Kingdom",2 +"GBR","GB","GB-CON","Cornwall","Unitary authority","United Kingdom",2 +"GBR","GB","GB-COV","Coventry","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-CRF","Cardiff; Caerdydd","Unitary authority","United Kingdom",2 +"GBR","GB","GB-CRY","Croydon","London borough","United Kingdom",2 +"GBR","GB","GB-CWY","Conwy","Unitary authority","United Kingdom",2 +"GBR","GB","GB-DAL","Darlington","Unitary authority","United Kingdom",2 +"GBR","GB","GB-DBY","Derbyshire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-DEN","Denbighshire; Sir Ddinbych","Unitary authority","United Kingdom",2 +"GBR","GB","GB-DER","Derby","Unitary authority","United Kingdom",2 +"GBR","GB","GB-DEV","Devon","Two-tier county","United Kingdom",2 +"GBR","GB","GB-DGY","Dumfries and Galloway","Council area","United Kingdom",2 +"GBR","GB","GB-DNC","Doncaster","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-DND","Dundee City","Council area","United Kingdom",2 +"GBR","GB","GB-DOR","Dorset","Two-tier county","United Kingdom",2 +"GBR","GB","GB-DRS","Derry and Strabane","District","United Kingdom",2 +"GBR","GB","GB-DUD","Dudley","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-DUR","Durham County","Unitary authority","United Kingdom",2 +"GBR","GB","GB-EAL","Ealing","London borough","United Kingdom",2 +"GBR","GB","GB-EAW","England and Wales","Nation","United Kingdom",2 +"GBR","GB","GB-EAY","East Ayrshire","Council area","United Kingdom",2 +"GBR","GB","GB-EDH","Edinburgh, City of","Council area","United Kingdom",2 +"GBR","GB","GB-EDU","East Dunbartonshire","Council area","United Kingdom",2 +"GBR","GB","GB-ELN","East Lothian","Council area","United Kingdom",2 +"GBR","GB","GB-ELS","Eilean Siar","Council area","United Kingdom",2 +"GBR","GB","GB-ENF","Enfield","London borough","United Kingdom",2 +"GBR","GB","GB-ENG","England","Country","United Kingdom",2 +"GBR","GB","GB-ERW","East Renfrewshire","Council area","United Kingdom",2 +"GBR","GB","GB-ERY","East Riding of Yorkshire","Unitary authority","United Kingdom",2 +"GBR","GB","GB-ESS","Essex","Two-tier county","United Kingdom",2 +"GBR","GB","GB-ESX","East Sussex","Two-tier county","United Kingdom",2 +"GBR","GB","GB-FAL","Falkirk","Council area","United Kingdom",2 +"GBR","GB","GB-FIF","Fife","Council area","United Kingdom",2 +"GBR","GB","GB-FLN","Flintshire; Sir y Fflint","Unitary authority","United Kingdom",2 +"GBR","GB","GB-FMO","Fermanagh and Omagh","District","United Kingdom",2 +"GBR","GB","GB-GAT","Gateshead","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-GBN","Great Britain","Nation","United Kingdom",2 +"GBR","GB","GB-GLG","Glasgow City","Council area","United Kingdom",2 +"GBR","GB","GB-GLS","Gloucestershire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-GRE","Greenwich","London borough","United Kingdom",2 +"GBR","GB","GB-GWN","Gwynedd","Unitary authority","United Kingdom",2 +"GBR","GB","GB-HAL","Halton","Unitary authority","United Kingdom",2 +"GBR","GB","GB-HAM","Hampshire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-HAV","Havering","London borough","United Kingdom",2 +"GBR","GB","GB-HCK","Hackney","London borough","United Kingdom",2 +"GBR","GB","GB-HEF","Herefordshire","Unitary authority","United Kingdom",2 +"GBR","GB","GB-HIL","Hillingdon","London borough","United Kingdom",2 +"GBR","GB","GB-HLD","Highland","Council area","United Kingdom",2 +"GBR","GB","GB-HMF","Hammersmith and Fulham","London borough","United Kingdom",2 +"GBR","GB","GB-HNS","Hounslow","London borough","United Kingdom",2 +"GBR","GB","GB-HPL","Hartlepool","Unitary authority","United Kingdom",2 +"GBR","GB","GB-HRT","Hertfordshire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-HRW","Harrow","London borough","United Kingdom",2 +"GBR","GB","GB-HRY","Haringey","London borough","United Kingdom",2 +"GBR","GB","GB-IOS","Isles of Scilly","Unitary authority","United Kingdom",2 +"GBR","GB","GB-IOW","Isle of Wight","Unitary authority","United Kingdom",2 +"GBR","GB","GB-ISL","Islington","London borough","United Kingdom",2 +"GBR","GB","GB-IVC","Inverclyde","Council area","United Kingdom",2 +"GBR","GB","GB-KEC","Kensington and Chelsea","London borough","United Kingdom",2 +"GBR","GB","GB-KEN","Kent","Two-tier county","United Kingdom",2 +"GBR","GB","GB-KHL","Kingston upon Hull","Unitary authority","United Kingdom",2 +"GBR","GB","GB-KIR","Kirklees","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-KTT","Kingston upon Thames","London borough","United Kingdom",2 +"GBR","GB","GB-KWL","Knowsley","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-LAN","Lancashire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-LBC","Lisburn and Castlereagh","District","United Kingdom",2 +"GBR","GB","GB-LBH","Lambeth","London borough","United Kingdom",2 +"GBR","GB","GB-LCE","Leicester","Unitary authority","United Kingdom",2 +"GBR","GB","GB-LDS","Leeds","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-LEC","Leicestershire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-LEW","Lewisham","London borough","United Kingdom",2 +"GBR","GB","GB-LIN","Lincolnshire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-LIV","Liverpool","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-LND","London, City of","City corporation","United Kingdom",2 +"GBR","GB","GB-LUT","Luton","Unitary authority","United Kingdom",2 +"GBR","GB","GB-MAN","Manchester","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-MDB","Middlesbrough","Unitary authority","United Kingdom",2 +"GBR","GB","GB-MDW","Medway","Unitary authority","United Kingdom",2 +"GBR","GB","GB-MEA","Mid and East Antrim","District","United Kingdom",2 +"GBR","GB","GB-MIK","Milton Keynes","Unitary authority","United Kingdom",2 +"GBR","GB","GB-MLN","Midlothian","Council area","United Kingdom",2 +"GBR","GB","GB-MON","Monmouthshire; Sir Fynwy","Unitary authority","United Kingdom",2 +"GBR","GB","GB-MRT","Merton","London borough","United Kingdom",2 +"GBR","GB","GB-MRY","Moray","Council area","United Kingdom",2 +"GBR","GB","GB-MTY","Merthyr Tydfil; Merthyr Tudful","Unitary authority","United Kingdom",2 +"GBR","GB","GB-MUL","Mid Ulster","District","United Kingdom",2 +"GBR","GB","GB-NAY","North Ayrshire","Council area","United Kingdom",2 +"GBR","GB","GB-NBL","Northumberland","Unitary authority","United Kingdom",2 +"GBR","GB","GB-NEL","North East Lincolnshire","Unitary authority","United Kingdom",2 +"GBR","GB","GB-NET","Newcastle upon Tyne","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-NFK","Norfolk","Two-tier county","United Kingdom",2 +"GBR","GB","GB-NGM","Nottingham","Unitary authority","United Kingdom",2 +"GBR","GB","GB-NIR","Northern Ireland","Province","United Kingdom",2 +"GBR","GB","GB-NLK","North Lanarkshire","Council area","United Kingdom",2 +"GBR","GB","GB-NLN","North Lincolnshire","Unitary authority","United Kingdom",2 +"GBR","GB","GB-NMD","Newry, Mourne and Down","District","United Kingdom",2 +"GBR","GB","GB-NSM","North Somerset","Unitary authority","United Kingdom",2 +"GBR","GB","GB-NTH","Northamptonshire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-NTL","Neath Port Talbot; Castell-nedd Port Talbot","Unitary authority","United Kingdom",2 +"GBR","GB","GB-NTT","Nottinghamshire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-NTY","North Tyneside","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-NWM","Newham","London borough","United Kingdom",2 +"GBR","GB","GB-NWP","Newport; Casnewydd","Unitary authority","United Kingdom",2 +"GBR","GB","GB-NYK","North Yorkshire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-OLD","Oldham","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-ORK","Orkney Islands","Council area","United Kingdom",2 +"GBR","GB","GB-OXF","Oxfordshire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-PEM","Pembrokeshire; Sir Benfro","Unitary authority","United Kingdom",2 +"GBR","GB","GB-PKN","Perth and Kinross","Council area","United Kingdom",2 +"GBR","GB","GB-PLY","Plymouth","Unitary authority","United Kingdom",2 +"GBR","GB","GB-POL","Poole","Unitary authority","United Kingdom",2 +"GBR","GB","GB-POR","Portsmouth","Unitary authority","United Kingdom",2 +"GBR","GB","GB-POW","Powys","Unitary authority","United Kingdom",2 +"GBR","GB","GB-PTE","Peterborough","Unitary authority","United Kingdom",2 +"GBR","GB","GB-RCC","Redcar and Cleveland","Unitary authority","United Kingdom",2 +"GBR","GB","GB-RCH","Rochdale","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-RCT","Rhondda, Cynon, Taff; Rhondda, Cynon, Taf","Unitary authority","United Kingdom",2 +"GBR","GB","GB-RDB","Redbridge","London borough","United Kingdom",2 +"GBR","GB","GB-RDG","Reading","Unitary authority","United Kingdom",2 +"GBR","GB","GB-RFW","Renfrewshire","Council area","United Kingdom",2 +"GBR","GB","GB-RIC","Richmond upon Thames","London borough","United Kingdom",2 +"GBR","GB","GB-ROT","Rotherham","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-RUT","Rutland","Unitary authority","United Kingdom",2 +"GBR","GB","GB-SAW","Sandwell","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-SAY","South Ayrshire","Council area","United Kingdom",2 +"GBR","GB","GB-SCB","Scottish Borders, The","Council area","United Kingdom",2 +"GBR","GB","GB-SCT","Scotland","Country","United Kingdom",2 +"GBR","GB","GB-SFK","Suffolk","Two-tier county","United Kingdom",2 +"GBR","GB","GB-SFT","Sefton","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-SGC","South Gloucestershire","Unitary authority","United Kingdom",2 +"GBR","GB","GB-SHF","Sheffield","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-SHN","St. Helens","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-SHR","Shropshire","Unitary authority","United Kingdom",2 +"GBR","GB","GB-SKP","Stockport","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-SLF","Salford","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-SLG","Slough","Unitary authority","United Kingdom",2 +"GBR","GB","GB-SLK","South Lanarkshire","Council area","United Kingdom",2 +"GBR","GB","GB-SND","Sunderland","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-SOL","Solihull","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-SOM","Somerset","Two-tier county","United Kingdom",2 +"GBR","GB","GB-SOS","Southend-on-Sea","Unitary authority","United Kingdom",2 +"GBR","GB","GB-SRY","Surrey","Two-tier county","United Kingdom",2 +"GBR","GB","GB-STE","Stoke-on-Trent","Unitary authority","United Kingdom",2 +"GBR","GB","GB-STG","Stirling","Council area","United Kingdom",2 +"GBR","GB","GB-STH","Southampton","Unitary authority","United Kingdom",2 +"GBR","GB","GB-STN","Sutton","London borough","United Kingdom",2 +"GBR","GB","GB-STS","Staffordshire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-STT","Stockton-on-Tees","Unitary authority","United Kingdom",2 +"GBR","GB","GB-STY","South Tyneside","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-SWA","Swansea; Abertawe","Unitary authority","United Kingdom",2 +"GBR","GB","GB-SWD","Swindon","Unitary authority","United Kingdom",2 +"GBR","GB","GB-SWK","Southwark","London borough","United Kingdom",2 +"GBR","GB","GB-TAM","Tameside","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-TFW","Telford and Wrekin","Unitary authority","United Kingdom",2 +"GBR","GB","GB-THR","Thurrock","Unitary authority","United Kingdom",2 +"GBR","GB","GB-TOB","Torbay","Unitary authority","United Kingdom",2 +"GBR","GB","GB-TOF","Torfaen; Tor-faen","Unitary authority","United Kingdom",2 +"GBR","GB","GB-TRF","Trafford","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-TWH","Tower Hamlets","London borough","United Kingdom",2 +"GBR","GB","GB-UKM","United Kingdom","Nation","United Kingdom",2 +"GBR","GB","GB-VGL","Vale of Glamorgan, The; Bro Morgannwg","Unitary authority","United Kingdom",2 +"GBR","GB","GB-WAR","Warwickshire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-WBK","West Berkshire","Unitary authority","United Kingdom",2 +"GBR","GB","GB-WDU","West Dunbartonshire","Council area","United Kingdom",2 +"GBR","GB","GB-WFT","Waltham Forest","London borough","United Kingdom",2 +"GBR","GB","GB-WGN","Wigan","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-WIL","Wiltshire","Unitary authority","United Kingdom",2 +"GBR","GB","GB-WKF","Wakefield","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-WLL","Walsall","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-WLN","West Lothian","Council area","United Kingdom",2 +"GBR","GB","GB-WLS","Wales; Cymru","Country","United Kingdom",2 +"GBR","GB","GB-WLV","Wolverhampton","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-WND","Wandsworth","London borough","United Kingdom",2 +"GBR","GB","GB-WNM","Windsor and Maidenhead","Unitary authority","United Kingdom",2 +"GBR","GB","GB-WOK","Wokingham","Unitary authority","United Kingdom",2 +"GBR","GB","GB-WOR","Worcestershire","Two-tier county","United Kingdom",2 +"GBR","GB","GB-WRL","Wirral","Metropolitan district","United Kingdom",2 +"GBR","GB","GB-WRT","Warrington","Unitary authority","United Kingdom",2 +"GBR","GB","GB-WRX","Wrexham; Wrecsam","Unitary authority","United Kingdom",2 +"GBR","GB","GB-WSM","Westminster","London borough","United Kingdom",2 +"GBR","GB","GB-WSX","West Sussex","Two-tier county","United Kingdom",2 +"GBR","GB","GB-YOR","York","Unitary authority","United Kingdom",2 +"GBR","GB","GB-ZET","Shetland Islands","Council area","United Kingdom",2 +"GRD","GD","GD-01","Saint Andrew","Parish","Grenada",2 +"GRD","GD","GD-02","Saint David","Parish","Grenada",2 +"GRD","GD","GD-03","Saint George","Parish","Grenada",2 +"GRD","GD","GD-04","Saint John","Parish","Grenada",2 +"GRD","GD","GD-05","Saint Mark","Parish","Grenada",2 +"GRD","GD","GD-06","Saint Patrick","Parish","Grenada",2 +"GRD","GD","GD-10","Southern Grenadine Islands","Dependency","Grenada",2 +"GEO","GE","GE-AB","Abkhazia","Autonomous republic","Georgia",2 +"GEO","GE","GE-AJ","Ajaria","Autonomous republic","Georgia",2 +"GEO","GE","GE-GU","Guria","Region","Georgia",2 +"GEO","GE","GE-IM","Imeret’i","Region","Georgia",2 +"GEO","GE","GE-KA","Kakhet’i","Region","Georgia",2 +"GEO","GE","GE-KK","K’vemo K’art’li","Region","Georgia",2 +"GEO","GE","GE-MM","Mts’khet’a-Mt’ianet’i","Region","Georgia",2 +"GEO","GE","GE-RL","Racha-Lech’khumi-K’vemo Svanet’i","Region","Georgia",2 +"GEO","GE","GE-SJ","Samts’khe-Javakhet’i","Region","Georgia",2 +"GEO","GE","GE-SK","Shida K’art’li","Region","Georgia",2 +"GEO","GE","GE-SZ","Samegrelo-Zemo Svanet’i","Region","Georgia",2 +"GEO","GE","GE-TB","T’bilisi","City","Georgia",2 +"GHA","GH","GH-AA","Greater Accra","Region","Ghana",2 +"GHA","GH","GH-AH","Ashanti","Region","Ghana",2 +"GHA","GH","GH-BA","Brong-Ahafo","Region","Ghana",2 +"GHA","GH","GH-CP","Central","Region","Ghana",2 +"GHA","GH","GH-EP","Eastern","Region","Ghana",2 +"GHA","GH","GH-NP","Northern","Region","Ghana",2 +"GHA","GH","GH-TV","Volta","Region","Ghana",2 +"GHA","GH","GH-UE","Upper East","Region","Ghana",2 +"GHA","GH","GH-UW","Upper West","Region","Ghana",2 +"GHA","GH","GH-WP","Western","Region","Ghana",2 +"GRL","GL","GL-KU","Kommune Kujalleq","Municipality","Greenland",2 +"GRL","GL","GL-QA","Qaasuitsup Kommunia","Municipality","Greenland",2 +"GRL","GL","GL-QE","Qeqqata Kommunia","Municipality","Greenland",2 +"GRL","GL","GL-SM","Kommuneqarfik Sermersooq","Municipality","Greenland",2 +"GMB","GM","GM-B","Banjul","City","Gambia",2 +"GMB","GM","GM-L","Lower River","Division","Gambia",2 +"GMB","GM","GM-M","Central River","Division","Gambia",2 +"GMB","GM","GM-N","North Bank","Division","Gambia",2 +"GMB","GM","GM-U","Upper River","Division","Gambia",2 +"GMB","GM","GM-W","Western","Division","Gambia",2 +"GIN","GN","GN-B","Boké","Governorate","Guinea",2 +"GIN","GN","GN-BE","Beyla","Prefecture","Guinea",2 +"GIN","GN","GN-BF","Boffa","Prefecture","Guinea",2 +"GIN","GN","GN-BK","Boké","Prefecture","Guinea",2 +"GIN","GN","GN-C","Conakry","Special zone","Guinea",2 +"GIN","GN","GN-CO","Coyah","Prefecture","Guinea",2 +"GIN","GN","GN-D","Kindia","Governorate","Guinea",2 +"GIN","GN","GN-DB","Dabola","Prefecture","Guinea",2 +"GIN","GN","GN-DI","Dinguiraye","Prefecture","Guinea",2 +"GIN","GN","GN-DL","Dalaba","Prefecture","Guinea",2 +"GIN","GN","GN-DU","Dubréka","Prefecture","Guinea",2 +"GIN","GN","GN-F","Faranah","Governorate","Guinea",2 +"GIN","GN","GN-FA","Faranah","Prefecture","Guinea",2 +"GIN","GN","GN-FO","Forécariah","Prefecture","Guinea",2 +"GIN","GN","GN-FR","Fria","Prefecture","Guinea",2 +"GIN","GN","GN-GA","Gaoual","Prefecture","Guinea",2 +"GIN","GN","GN-GU","Guékédou","Prefecture","Guinea",2 +"GIN","GN","GN-K","Kankan","Governorate","Guinea",2 +"GIN","GN","GN-KA","Kankan","Prefecture","Guinea",2 +"GIN","GN","GN-KB","Koubia","Prefecture","Guinea",2 +"GIN","GN","GN-KD","Kindia","Prefecture","Guinea",2 +"GIN","GN","GN-KE","Kérouané","Prefecture","Guinea",2 +"GIN","GN","GN-KN","Koundara","Prefecture","Guinea",2 +"GIN","GN","GN-KO","Kouroussa","Prefecture","Guinea",2 +"GIN","GN","GN-KS","Kissidougou","Prefecture","Guinea",2 +"GIN","GN","GN-L","Labé","Governorate","Guinea",2 +"GIN","GN","GN-LA","Labé","Prefecture","Guinea",2 +"GIN","GN","GN-LE","Lélouma","Prefecture","Guinea",2 +"GIN","GN","GN-LO","Lola","Prefecture","Guinea",2 +"GIN","GN","GN-M","Mamou","Governorate","Guinea",2 +"GIN","GN","GN-MC","Macenta","Prefecture","Guinea",2 +"GIN","GN","GN-MD","Mandiana","Prefecture","Guinea",2 +"GIN","GN","GN-ML","Mali","Prefecture","Guinea",2 +"GIN","GN","GN-MM","Mamou","Prefecture","Guinea",2 +"GIN","GN","GN-N","Nzérékoré","Governorate","Guinea",2 +"GIN","GN","GN-NZ","Nzérékoré","Prefecture","Guinea",2 +"GIN","GN","GN-PI","Pita","Prefecture","Guinea",2 +"GIN","GN","GN-SI","Siguiri","Prefecture","Guinea",2 +"GIN","GN","GN-TE","Télimélé","Prefecture","Guinea",2 +"GIN","GN","GN-TO","Tougué","Prefecture","Guinea",2 +"GIN","GN","GN-YO","Yomou","Prefecture","Guinea",2 +"GNQ","GQ","GQ-AN","Annobón","Province","Equatorial Guinea",2 +"GNQ","GQ","GQ-BN","Bioko Norte","Province","Equatorial Guinea",2 +"GNQ","GQ","GQ-BS","Bioko Sur","Province","Equatorial Guinea",2 +"GNQ","GQ","GQ-C","Región Continental","Region","Equatorial Guinea",2 +"GNQ","GQ","GQ-CS","Centro Sur","Province","Equatorial Guinea",2 +"GNQ","GQ","GQ-I","Región Insular","Region","Equatorial Guinea",2 +"GNQ","GQ","GQ-KN","Kié-Ntem","Province","Equatorial Guinea",2 +"GNQ","GQ","GQ-LI","Litoral","Province","Equatorial Guinea",2 +"GNQ","GQ","GQ-WN","Wele-Nzas","Province","Equatorial Guinea",2 +"GRC","GR","GR-01","Aitolia kai Akarnania","Department","Greece",2 +"GRC","GR","GR-03","Voiotia","Department","Greece",2 +"GRC","GR","GR-04","Evvoias","Department","Greece",2 +"GRC","GR","GR-05","Evrytania","Department","Greece",2 +"GRC","GR","GR-06","Fthiotida","Department","Greece",2 +"GRC","GR","GR-07","Fokida","Department","Greece",2 +"GRC","GR","GR-11","Argolida","Department","Greece",2 +"GRC","GR","GR-12","Arkadia","Department","Greece",2 +"GRC","GR","GR-13","Achaïa","Department","Greece",2 +"GRC","GR","GR-14","Ileia","Department","Greece",2 +"GRC","GR","GR-15","Korinthia","Department","Greece",2 +"GRC","GR","GR-16","Lakonia","Department","Greece",2 +"GRC","GR","GR-17","Messinia","Department","Greece",2 +"GRC","GR","GR-21","Zakynthos","Department","Greece",2 +"GRC","GR","GR-22","Kerkyra","Department","Greece",2 +"GRC","GR","GR-23","Kefallonia","Department","Greece",2 +"GRC","GR","GR-24","Lefkada","Department","Greece",2 +"GRC","GR","GR-31","Arta","Department","Greece",2 +"GRC","GR","GR-32","Thesprotia","Department","Greece",2 +"GRC","GR","GR-33","Ioannina","Department","Greece",2 +"GRC","GR","GR-34","Preveza","Department","Greece",2 +"GRC","GR","GR-41","Karditsa","Department","Greece",2 +"GRC","GR","GR-42","Larisa","Department","Greece",2 +"GRC","GR","GR-43","Magnisia","Department","Greece",2 +"GRC","GR","GR-44","Trikala","Department","Greece",2 +"GRC","GR","GR-51","Grevena","Department","Greece",2 +"GRC","GR","GR-52","Drama","Department","Greece",2 +"GRC","GR","GR-53","Imathia","Department","Greece",2 +"GRC","GR","GR-54","Thessaloniki","Department","Greece",2 +"GRC","GR","GR-55","Kavala","Department","Greece",2 +"GRC","GR","GR-56","Kastoria","Department","Greece",2 +"GRC","GR","GR-57","Kilkis","Department","Greece",2 +"GRC","GR","GR-58","Kozani","Department","Greece",2 +"GRC","GR","GR-59","Pella","Department","Greece",2 +"GRC","GR","GR-61","Pieria","Department","Greece",2 +"GRC","GR","GR-62","Serres","Department","Greece",2 +"GRC","GR","GR-63","Florina","Department","Greece",2 +"GRC","GR","GR-64","Chalkidiki","Department","Greece",2 +"GRC","GR","GR-69","Agio Oros","Self-governed part","Greece",2 +"GRC","GR","GR-71","Evros","Department","Greece",2 +"GRC","GR","GR-72","Xanthi","Department","Greece",2 +"GRC","GR","GR-73","Rodopi","Department","Greece",2 +"GRC","GR","GR-81","Dodekanisos","Department","Greece",2 +"GRC","GR","GR-82","Kyklades","Department","Greece",2 +"GRC","GR","GR-83","Lesvos","Department","Greece",2 +"GRC","GR","GR-84","Samos","Department","Greece",2 +"GRC","GR","GR-85","Chios","Department","Greece",2 +"GRC","GR","GR-91","Irakleio","Department","Greece",2 +"GRC","GR","GR-92","Lasithi","Department","Greece",2 +"GRC","GR","GR-93","Rethymno","Department","Greece",2 +"GRC","GR","GR-94","Chania","Department","Greece",2 +"GRC","GR","GR-A","Anatoliki Makedonia kai Thraki","Administrative region","Greece",2 +"GRC","GR","GR-A1","Attiki","Department","Greece",2 +"GRC","GR","GR-B","Kentriki Makedonia","Administrative region","Greece",2 +"GRC","GR","GR-C","Dytiki Makedonia","Administrative region","Greece",2 +"GRC","GR","GR-D","Ipeiros","Administrative region","Greece",2 +"GRC","GR","GR-E","Thessalia","Administrative region","Greece",2 +"GRC","GR","GR-F","Ionia Nisia","Administrative region","Greece",2 +"GRC","GR","GR-G","Dytiki Ellada","Administrative region","Greece",2 +"GRC","GR","GR-H","Sterea Ellada","Administrative region","Greece",2 +"GRC","GR","GR-I","Attiki","Administrative region","Greece",2 +"GRC","GR","GR-J","Peloponnisos","Administrative region","Greece",2 +"GRC","GR","GR-K","Voreio Aigaio","Administrative region","Greece",2 +"GRC","GR","GR-L","Notio Aigaio","Administrative region","Greece",2 +"GRC","GR","GR-M","Kriti","Administrative region","Greece",2 +"GTM","GT","GT-AV","Alta Verapaz","Department","Guatemala",2 +"GTM","GT","GT-BV","Baja Verapaz","Department","Guatemala",2 +"GTM","GT","GT-CM","Chimaltenango","Department","Guatemala",2 +"GTM","GT","GT-CQ","Chiquimula","Department","Guatemala",2 +"GTM","GT","GT-ES","Escuintla","Department","Guatemala",2 +"GTM","GT","GT-GU","Guatemala","Department","Guatemala",2 +"GTM","GT","GT-HU","Huehuetenango","Department","Guatemala",2 +"GTM","GT","GT-IZ","Izabal","Department","Guatemala",2 +"GTM","GT","GT-JA","Jalapa","Department","Guatemala",2 +"GTM","GT","GT-JU","Jutiapa","Department","Guatemala",2 +"GTM","GT","GT-PE","Petén","Department","Guatemala",2 +"GTM","GT","GT-PR","El Progreso","Department","Guatemala",2 +"GTM","GT","GT-QC","Quiché","Department","Guatemala",2 +"GTM","GT","GT-QZ","Quetzaltenango","Department","Guatemala",2 +"GTM","GT","GT-RE","Retalhuleu","Department","Guatemala",2 +"GTM","GT","GT-SA","Sacatepéquez","Department","Guatemala",2 +"GTM","GT","GT-SM","San Marcos","Department","Guatemala",2 +"GTM","GT","GT-SO","Sololá","Department","Guatemala",2 +"GTM","GT","GT-SR","Santa Rosa","Department","Guatemala",2 +"GTM","GT","GT-SU","Suchitepéquez","Department","Guatemala",2 +"GTM","GT","GT-TO","Totonicapán","Department","Guatemala",2 +"GTM","GT","GT-ZA","Zacapa","Department","Guatemala",2 +"GNB","GW","GW-BA","Bafatá","Region","Guinea-Bissau",2 +"GNB","GW","GW-BL","Bolama","Region","Guinea-Bissau",2 +"GNB","GW","GW-BM","Biombo","Region","Guinea-Bissau",2 +"GNB","GW","GW-BS","Bissau","Autonomous sector","Guinea-Bissau",2 +"GNB","GW","GW-CA","Cacheu","Region","Guinea-Bissau",2 +"GNB","GW","GW-GA","Gabú","Region","Guinea-Bissau",2 +"GNB","GW","GW-L","Leste","Province","Guinea-Bissau",2 +"GNB","GW","GW-N","Norte","Province","Guinea-Bissau",2 +"GNB","GW","GW-OI","Oio","Region","Guinea-Bissau",2 +"GNB","GW","GW-QU","Quinara","Region","Guinea-Bissau",2 +"GNB","GW","GW-S","Sul","Province","Guinea-Bissau",2 +"GNB","GW","GW-TO","Tombali","Region","Guinea-Bissau",2 +"GUY","GY","GY-BA","Barima-Waini","Region","Guyana",2 +"GUY","GY","GY-CU","Cuyuni-Mazaruni","Region","Guyana",2 +"GUY","GY","GY-DE","Demerara-Mahaica","Region","Guyana",2 +"GUY","GY","GY-EB","East Berbice-Corentyne","Region","Guyana",2 +"GUY","GY","GY-ES","Essequibo Islands-West Demerara","Region","Guyana",2 +"GUY","GY","GY-MA","Mahaica-Berbice","Region","Guyana",2 +"GUY","GY","GY-PM","Pomeroon-Supenaam","Region","Guyana",2 +"GUY","GY","GY-PT","Potaro-Siparuni","Region","Guyana",2 +"GUY","GY","GY-UD","Upper Demerara-Berbice","Region","Guyana",2 +"GUY","GY","GY-UT","Upper Takutu-Upper Essequibo","Region","Guyana",2 +"HND","HN","HN-AT","Atlántida","Department","Honduras",2 +"HND","HN","HN-CH","Choluteca","Department","Honduras",2 +"HND","HN","HN-CL","Colón","Department","Honduras",2 +"HND","HN","HN-CM","Comayagua","Department","Honduras",2 +"HND","HN","HN-CP","Copán","Department","Honduras",2 +"HND","HN","HN-CR","Cortés","Department","Honduras",2 +"HND","HN","HN-EP","El Paraíso","Department","Honduras",2 +"HND","HN","HN-FM","Francisco Morazán","Department","Honduras",2 +"HND","HN","HN-GD","Gracias a Dios","Department","Honduras",2 +"HND","HN","HN-IB","Islas de la Bahía","Department","Honduras",2 +"HND","HN","HN-IN","Intibucá","Department","Honduras",2 +"HND","HN","HN-LE","Lempira","Department","Honduras",2 +"HND","HN","HN-LP","La Paz","Department","Honduras",2 +"HND","HN","HN-OC","Ocotepeque","Department","Honduras",2 +"HND","HN","HN-OL","Olancho","Department","Honduras",2 +"HND","HN","HN-SB","Santa Bárbara","Department","Honduras",2 +"HND","HN","HN-VA","Valle","Department","Honduras",2 +"HND","HN","HN-YO","Yoro","Department","Honduras",2 +"HRV","HR","HR-01","Zagrebačka županija","County","Croatia",2 +"HRV","HR","HR-02","Krapinsko-zagorska županija","County","Croatia",2 +"HRV","HR","HR-03","Sisačko-moslavačka županija","County","Croatia",2 +"HRV","HR","HR-04","Karlovačka županija","County","Croatia",2 +"HRV","HR","HR-05","Varaždinska županija","County","Croatia",2 +"HRV","HR","HR-06","Koprivničko-križevačka županija","County","Croatia",2 +"HRV","HR","HR-07","Bjelovarsko-bilogorska županija","County","Croatia",2 +"HRV","HR","HR-08","Primorsko-goranska županija","County","Croatia",2 +"HRV","HR","HR-09","Ličko-senjska županija","County","Croatia",2 +"HRV","HR","HR-10","Virovitičko-podravska županija","County","Croatia",2 +"HRV","HR","HR-11","Požeško-slavonska županija","County","Croatia",2 +"HRV","HR","HR-12","Brodsko-posavska županija","County","Croatia",2 +"HRV","HR","HR-13","Zadarska županija","County","Croatia",2 +"HRV","HR","HR-14","Osječko-baranjska županija","County","Croatia",2 +"HRV","HR","HR-15","Šibensko-kninska županija","County","Croatia",2 +"HRV","HR","HR-16","Vukovarsko-srijemska županija","County","Croatia",2 +"HRV","HR","HR-17","Splitsko-dalmatinska županija","County","Croatia",2 +"HRV","HR","HR-18","Istarska županija","County","Croatia",2 +"HRV","HR","HR-19","Dubrovačko-neretvanska županija","County","Croatia",2 +"HRV","HR","HR-20","Međimurska županija","County","Croatia",2 +"HRV","HR","HR-21","Grad Zagreb","City","Croatia",2 +"HTI","HT","HT-AR","Artibonite","Department","Haiti",2 +"HTI","HT","HT-CE","Centre","Department","Haiti",2 +"HTI","HT","HT-GA","Grande-Anse","Department","Haiti",2 +"HTI","HT","HT-ND","Nord","Department","Haiti",2 +"HTI","HT","HT-NE","Nord-Est","Department","Haiti",2 +"HTI","HT","HT-NO","Nord-Ouest","Department","Haiti",2 +"HTI","HT","HT-OU","Ouest","Department","Haiti",2 +"HTI","HT","HT-SD","Sud","Department","Haiti",2 +"HTI","HT","HT-SE","Sud-Est","Department","Haiti",2 +"HUN","HU","HU-BA","Baranya","County","Hungary",2 +"HUN","HU","HU-BC","Békéscsaba","City with county rights","Hungary",2 +"HUN","HU","HU-BE","Békés","County","Hungary",2 +"HUN","HU","HU-BK","Bács-Kiskun","County","Hungary",2 +"HUN","HU","HU-BU","Budapest","Capital city","Hungary",2 +"HUN","HU","HU-BZ","Borsod-Abaúj-Zemplén","County","Hungary",2 +"HUN","HU","HU-CS","Csongrád","County","Hungary",2 +"HUN","HU","HU-DE","Debrecen","City with county rights","Hungary",2 +"HUN","HU","HU-DU","Dunaújváros","City with county rights","Hungary",2 +"HUN","HU","HU-EG","Eger","City with county rights","Hungary",2 +"HUN","HU","HU-ER","Érd","City with county rights","Hungary",2 +"HUN","HU","HU-FE","Fejér","County","Hungary",2 +"HUN","HU","HU-GS","Győr-Moson-Sopron","County","Hungary",2 +"HUN","HU","HU-GY","Győr","City with county rights","Hungary",2 +"HUN","HU","HU-HB","Hajdú-Bihar","County","Hungary",2 +"HUN","HU","HU-HE","Heves","County","Hungary",2 +"HUN","HU","HU-HV","Hódmezővásárhely","City with county rights","Hungary",2 +"HUN","HU","HU-JN","Jász-Nagykun-Szolnok","County","Hungary",2 +"HUN","HU","HU-KE","Komárom-Esztergom","County","Hungary",2 +"HUN","HU","HU-KM","Kecskemét","City with county rights","Hungary",2 +"HUN","HU","HU-KV","Kaposvár","City with county rights","Hungary",2 +"HUN","HU","HU-MI","Miskolc","City with county rights","Hungary",2 +"HUN","HU","HU-NK","Nagykanizsa","City with county rights","Hungary",2 +"HUN","HU","HU-NO","Nógrád","County","Hungary",2 +"HUN","HU","HU-NY","Nyíregyháza","City with county rights","Hungary",2 +"HUN","HU","HU-PE","Pest","County","Hungary",2 +"HUN","HU","HU-PS","Pécs","City with county rights","Hungary",2 +"HUN","HU","HU-SD","Szeged","City with county rights","Hungary",2 +"HUN","HU","HU-SF","Székesfehérvár","City with county rights","Hungary",2 +"HUN","HU","HU-SH","Szombathely","City with county rights","Hungary",2 +"HUN","HU","HU-SK","Szolnok","City with county rights","Hungary",2 +"HUN","HU","HU-SN","Sopron","City with county rights","Hungary",2 +"HUN","HU","HU-SO","Somogy","County","Hungary",2 +"HUN","HU","HU-SS","Szekszárd","City with county rights","Hungary",2 +"HUN","HU","HU-ST","Salgótarján","City with county rights","Hungary",2 +"HUN","HU","HU-SZ","Szabolcs-Szatmár-Bereg","County","Hungary",2 +"HUN","HU","HU-TB","Tatabánya","City with county rights","Hungary",2 +"HUN","HU","HU-TO","Tolna","County","Hungary",2 +"HUN","HU","HU-VA","Vas","County","Hungary",2 +"HUN","HU","HU-VE","Veszprém (county)","County","Hungary",2 +"HUN","HU","HU-VM","Veszprém","City with county rights","Hungary",2 +"HUN","HU","HU-ZA","Zala","County","Hungary",2 +"HUN","HU","HU-ZE","Zalaegerszeg","City with county rights","Hungary",2 +"IDN","ID","ID-AC","Aceh","Autonomous Province","Indonesia",2 +"IDN","ID","ID-BA","Bali","Province","Indonesia",2 +"IDN","ID","ID-BB","Bangka Belitung","Province","Indonesia",2 +"IDN","ID","ID-BE","Bengkulu","Province","Indonesia",2 +"IDN","ID","ID-BT","Banten","Province","Indonesia",2 +"IDN","ID","ID-GO","Gorontalo","Province","Indonesia",2 +"IDN","ID","ID-IJ","Papua","Geographical unit","Indonesia",2 +"IDN","ID","ID-JA","Jambi","Province","Indonesia",2 +"IDN","ID","ID-JB","Jawa Barat","Province","Indonesia",2 +"IDN","ID","ID-JI","Jawa Timur","Province","Indonesia",2 +"IDN","ID","ID-JK","Jakarta Raya","Special District","Indonesia",2 +"IDN","ID","ID-JT","Jawa Tengah","Province","Indonesia",2 +"IDN","ID","ID-JW","Jawa","Geographical unit","Indonesia",2 +"IDN","ID","ID-KA","Kalimantan","Geographical unit","Indonesia",2 +"IDN","ID","ID-KB","Kalimantan Barat","Province","Indonesia",2 +"IDN","ID","ID-KI","Kalimantan Timur","Province","Indonesia",2 +"IDN","ID","ID-KR","Kepulauan Riau","Province","Indonesia",2 +"IDN","ID","ID-KS","Kalimantan Selatan","Province","Indonesia",2 +"IDN","ID","ID-KT","Kalimantan Tengah","Province","Indonesia",2 +"IDN","ID","ID-LA","Lampung","Province","Indonesia",2 +"IDN","ID","ID-MA","Maluku","Province","Indonesia",2 +"IDN","ID","ID-ML","Maluku","Geographical unit","Indonesia",2 +"IDN","ID","ID-MU","Maluku Utara","Province","Indonesia",2 +"IDN","ID","ID-NB","Nusa Tenggara Barat","Province","Indonesia",2 +"IDN","ID","ID-NT","Nusa Tenggara Timur","Province","Indonesia",2 +"IDN","ID","ID-NU","Nusa Tenggara","Geographical unit","Indonesia",2 +"IDN","ID","ID-PA","Papua","Province","Indonesia",2 +"IDN","ID","ID-PB","Papua Barat","Province","Indonesia",2 +"IDN","ID","ID-RI","Riau","Province","Indonesia",2 +"IDN","ID","ID-SA","Sulawesi Utara","Province","Indonesia",2 +"IDN","ID","ID-SB","Sumatra Barat","Province","Indonesia",2 +"IDN","ID","ID-SG","Sulawesi Tenggara","Province","Indonesia",2 +"IDN","ID","ID-SL","Sulawesi","Geographical unit","Indonesia",2 +"IDN","ID","ID-SM","Sumatera","Geographical unit","Indonesia",2 +"IDN","ID","ID-SN","Sulawesi Selatan","Province","Indonesia",2 +"IDN","ID","ID-SR","Sulawesi Barat","Province","Indonesia",2 +"IDN","ID","ID-SS","Sumatra Selatan","Province","Indonesia",2 +"IDN","ID","ID-ST","Sulawesi Tengah","Province","Indonesia",2 +"IDN","ID","ID-SU","Sumatera Utara","Province","Indonesia",2 +"IDN","ID","ID-YO","Yogyakarta","Special Region","Indonesia",2 +"IRL","IE","IE-C","Connacht","Province","Ireland",2 +"IRL","IE","IE-CE","Clare","County","Ireland",2 +"IRL","IE","IE-CN","Cavan","County","Ireland",2 +"IRL","IE","IE-CO","Cork","County","Ireland",2 +"IRL","IE","IE-CW","Carlow","County","Ireland",2 +"IRL","IE","IE-D","Dublin","County","Ireland",2 +"IRL","IE","IE-DL","Donegal","County","Ireland",2 +"IRL","IE","IE-G","Galway","County","Ireland",2 +"IRL","IE","IE-KE","Kildare","County","Ireland",2 +"IRL","IE","IE-KK","Kilkenny","County","Ireland",2 +"IRL","IE","IE-KY","Kerry","County","Ireland",2 +"IRL","IE","IE-L","Leinster","Province","Ireland",2 +"IRL","IE","IE-LD","Longford","County","Ireland",2 +"IRL","IE","IE-LH","Louth","County","Ireland",2 +"IRL","IE","IE-LK","Limerick","County","Ireland",2 +"IRL","IE","IE-LM","Leitrim","County","Ireland",2 +"IRL","IE","IE-LS","Laois","County","Ireland",2 +"IRL","IE","IE-M","Munster","Province","Ireland",2 +"IRL","IE","IE-MH","Meath","County","Ireland",2 +"IRL","IE","IE-MN","Monaghan","County","Ireland",2 +"IRL","IE","IE-MO","Mayo","County","Ireland",2 +"IRL","IE","IE-OY","Offaly","County","Ireland",2 +"IRL","IE","IE-RN","Roscommon","County","Ireland",2 +"IRL","IE","IE-SO","Sligo","County","Ireland",2 +"IRL","IE","IE-TA","Tipperary","County","Ireland",2 +"IRL","IE","IE-U","Ulster","Province","Ireland",2 +"IRL","IE","IE-WD","Waterford","County","Ireland",2 +"IRL","IE","IE-WH","Westmeath","County","Ireland",2 +"IRL","IE","IE-WW","Wicklow","County","Ireland",2 +"IRL","IE","IE-WX","Wexford","County","Ireland",2 +"ISR","IL","IL-D","HaDarom","District","Israel",2 +"ISR","IL","IL-HA","Hefa","District","Israel",2 +"ISR","IL","IL-JM","Yerushalayim Al Quds","District","Israel",2 +"ISR","IL","IL-M","HaMerkaz","District","Israel",2 +"ISR","IL","IL-TA","Tel-Aviv","District","Israel",2 +"ISR","IL","IL-Z","HaZafon","District","Israel",2 +"IND","IN","IN-AN","Andaman and Nicobar Islands","Union territory","India",2 +"IND","IN","IN-AP","Andhra Pradesh","State","India",2 +"IND","IN","IN-AR","Arunachal Pradesh","State","India",2 +"IND","IN","IN-AS","Assam","State","India",2 +"IND","IN","IN-BR","Bihar","State","India",2 +"IND","IN","IN-CH","Chandigarh","Union territory","India",2 +"IND","IN","IN-CT","Chhattisgarh","State","India",2 +"IND","IN","IN-DD","Damen and Diu","Union territory","India",2 +"IND","IN","IN-DL","Delhi","Union territory","India",2 +"IND","IN","IN-DN","Dadra and Nagar Haveli","Union territory","India",2 +"IND","IN","IN-GA","Goa","State","India",2 +"IND","IN","IN-GJ","Gujarat","State","India",2 +"IND","IN","IN-HP","Himachal Pradesh","State","India",2 +"IND","IN","IN-HR","Haryana","State","India",2 +"IND","IN","IN-JH","Jharkhand","State","India",2 +"IND","IN","IN-JK","Jammu and Kashmir","State","India",2 +"IND","IN","IN-KA","Karnataka","State","India",2 +"IND","IN","IN-KL","Kerala","State","India",2 +"IND","IN","IN-LD","Lakshadweep","Union territory","India",2 +"IND","IN","IN-MH","Maharashtra","State","India",2 +"IND","IN","IN-ML","Meghalaya","State","India",2 +"IND","IN","IN-MN","Manipur","State","India",2 +"IND","IN","IN-MP","Madhya Pradesh","State","India",2 +"IND","IN","IN-MZ","Mizoram","State","India",2 +"IND","IN","IN-NL","Nagaland","State","India",2 +"IND","IN","IN-OR","Orissa","State","India",2 +"IND","IN","IN-PB","Punjab","State","India",2 +"IND","IN","IN-PY","Puducherry","Union territory","India",2 +"IND","IN","IN-RJ","Rajasthan","State","India",2 +"IND","IN","IN-SK","Sikkim","State","India",2 +"IND","IN","IN-TN","Tamil Nadu","State","India",2 +"IND","IN","IN-TR","Tripura","State","India",2 +"IND","IN","IN-UP","Uttar Pradesh","State","India",2 +"IND","IN","IN-UT","Uttarakhand","State","India",2 +"IND","IN","IN-WB","West Bengal","State","India",2 +"IRQ","IQ","IQ-AN","Al Anbar","Governorate","Iraq",2 +"IRQ","IQ","IQ-AR","Arbil","Governorate","Iraq",2 +"IRQ","IQ","IQ-BA","Al Basrah","Governorate","Iraq",2 +"IRQ","IQ","IQ-BB","Babil","Governorate","Iraq",2 +"IRQ","IQ","IQ-BG","Baghdad","Governorate","Iraq",2 +"IRQ","IQ","IQ-DA","Dahuk","Governorate","Iraq",2 +"IRQ","IQ","IQ-DI","Diyala","Governorate","Iraq",2 +"IRQ","IQ","IQ-DQ","Dhi Qar","Governorate","Iraq",2 +"IRQ","IQ","IQ-KA","Karbala'","Governorate","Iraq",2 +"IRQ","IQ","IQ-MA","Maysan","Governorate","Iraq",2 +"IRQ","IQ","IQ-MU","Al Muthanna","Governorate","Iraq",2 +"IRQ","IQ","IQ-NA","An Najef","Governorate","Iraq",2 +"IRQ","IQ","IQ-NI","Ninawa","Governorate","Iraq",2 +"IRQ","IQ","IQ-QA","Al Qadisiyah","Governorate","Iraq",2 +"IRQ","IQ","IQ-SD","Salah ad Din","Governorate","Iraq",2 +"IRQ","IQ","IQ-SW","As Sulaymaniyah","Governorate","Iraq",2 +"IRQ","IQ","IQ-TS","At Ta'mim","Governorate","Iraq",2 +"IRQ","IQ","IQ-WA","Wasit","Governorate","Iraq",2 +"IRN","IR","IR-01","Āzarbāyjān-e Sharqī","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-02","Āzarbāyjān-e Gharbī","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-03","Ardabīl","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-04","Eşfahān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-05","Īlām","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-06","Būshehr","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-07","Tehrān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-08","Chahār Mahāll va Bakhtīārī","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-10","Khūzestān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-11","Zanjān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-12","Semnān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-13","Sīstān va Balūchestān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-14","Fārs","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-15","Kermān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-16","Kordestān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-17","Kermānshāh","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-18","Kohgīlūyeh va Būyer Ahmad","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-19","Gīlān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-20","Lorestān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-21","Māzandarān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-22","Markazī","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-23","Hormozgān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-24","Hamadān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-25","Yazd","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-26","Qom","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-27","Golestān","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-28","Qazvīn","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-29","Khorāsān-e Janūbī","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-30","Khorāsān-e Razavī","Province","Iran, Islamic Republic of",2 +"IRN","IR","IR-31","Khorāsān-e Shemālī","Province","Iran, Islamic Republic of",2 +"ISL","IS","IS-0","Reykjavík","City","Iceland",2 +"ISL","IS","IS-1","Höfuðborgarsvæðið","Region","Iceland",2 +"ISL","IS","IS-2","Suðurnes","Region","Iceland",2 +"ISL","IS","IS-3","Vesturland","Region","Iceland",2 +"ISL","IS","IS-4","Vestfirðir","Region","Iceland",2 +"ISL","IS","IS-5","Norðurland vestra","Region","Iceland",2 +"ISL","IS","IS-6","Norðurland eystra","Region","Iceland",2 +"ISL","IS","IS-7","Austurland","Region","Iceland",2 +"ISL","IS","IS-8","Suðurland","Region","Iceland",2 +"ITA","IT","IT-21","Piemonte","Region","Italy",2 +"ITA","IT","IT-23","Valle d'Aosta","Region","Italy",2 +"ITA","IT","IT-25","Lombardia","Region","Italy",2 +"ITA","IT","IT-32","Trentino-Alto Adige","Region","Italy",2 +"ITA","IT","IT-34","Veneto","Region","Italy",2 +"ITA","IT","IT-36","Friuli-Venezia Giulia","Region","Italy",2 +"ITA","IT","IT-42","Liguria","Region","Italy",2 +"ITA","IT","IT-45","Emilia-Romagna","Region","Italy",2 +"ITA","IT","IT-52","Toscana","Region","Italy",2 +"ITA","IT","IT-55","Umbria","Region","Italy",2 +"ITA","IT","IT-57","Marche","Region","Italy",2 +"ITA","IT","IT-62","Lazio","Region","Italy",2 +"ITA","IT","IT-65","Abruzzo","Region","Italy",2 +"ITA","IT","IT-67","Molise","Region","Italy",2 +"ITA","IT","IT-72","Campania","Region","Italy",2 +"ITA","IT","IT-75","Puglia","Region","Italy",2 +"ITA","IT","IT-77","Basilicata","Region","Italy",2 +"ITA","IT","IT-78","Calabria","Region","Italy",2 +"ITA","IT","IT-82","Sicilia","Region","Italy",2 +"ITA","IT","IT-88","Sardegna","Region","Italy",2 +"ITA","IT","IT-AG","Agrigento","Province","Italy",2 +"ITA","IT","IT-AL","Alessandria","Province","Italy",2 +"ITA","IT","IT-AN","Ancona","Province","Italy",2 +"ITA","IT","IT-AO","Aosta","Province","Italy",2 +"ITA","IT","IT-AP","Ascoli Piceno","Province","Italy",2 +"ITA","IT","IT-AQ","L'Aquila","Province","Italy",2 +"ITA","IT","IT-AR","Arezzo","Province","Italy",2 +"ITA","IT","IT-AT","Asti","Province","Italy",2 +"ITA","IT","IT-AV","Avellino","Province","Italy",2 +"ITA","IT","IT-BA","Bari","Province","Italy",2 +"ITA","IT","IT-BG","Bergamo","Province","Italy",2 +"ITA","IT","IT-BI","Biella","Province","Italy",2 +"ITA","IT","IT-BL","Belluno","Province","Italy",2 +"ITA","IT","IT-BN","Benevento","Province","Italy",2 +"ITA","IT","IT-BO","Bologna","Province","Italy",2 +"ITA","IT","IT-BR","Brindisi","Province","Italy",2 +"ITA","IT","IT-BS","Brescia","Province","Italy",2 +"ITA","IT","IT-BT","Barletta-Andria-Trani","Province","Italy",2 +"ITA","IT","IT-BZ","Bolzano","Province","Italy",2 +"ITA","IT","IT-CA","Cagliari","Province","Italy",2 +"ITA","IT","IT-CB","Campobasso","Province","Italy",2 +"ITA","IT","IT-CE","Caserta","Province","Italy",2 +"ITA","IT","IT-CH","Chieti","Province","Italy",2 +"ITA","IT","IT-CI","Carbonia-Iglesias","Province","Italy",2 +"ITA","IT","IT-CL","Caltanissetta","Province","Italy",2 +"ITA","IT","IT-CN","Cuneo","Province","Italy",2 +"ITA","IT","IT-CO","Como","Province","Italy",2 +"ITA","IT","IT-CR","Cremona","Province","Italy",2 +"ITA","IT","IT-CS","Cosenza","Province","Italy",2 +"ITA","IT","IT-CT","Catania","Province","Italy",2 +"ITA","IT","IT-CZ","Catanzaro","Province","Italy",2 +"ITA","IT","IT-EN","Enna","Province","Italy",2 +"ITA","IT","IT-FC","Forlì-Cesena","Province","Italy",2 +"ITA","IT","IT-FE","Ferrara","Province","Italy",2 +"ITA","IT","IT-FG","Foggia","Province","Italy",2 +"ITA","IT","IT-FI","Firenze","Province","Italy",2 +"ITA","IT","IT-FM","Fermo","Province","Italy",2 +"ITA","IT","IT-FR","Frosinone","Province","Italy",2 +"ITA","IT","IT-GE","Genova","Province","Italy",2 +"ITA","IT","IT-GO","Gorizia","Province","Italy",2 +"ITA","IT","IT-GR","Grosseto","Province","Italy",2 +"ITA","IT","IT-IM","Imperia","Province","Italy",2 +"ITA","IT","IT-IS","Isernia","Province","Italy",2 +"ITA","IT","IT-KR","Crotone","Province","Italy",2 +"ITA","IT","IT-LC","Lecco","Province","Italy",2 +"ITA","IT","IT-LE","Lecce","Province","Italy",2 +"ITA","IT","IT-LI","Livorno","Province","Italy",2 +"ITA","IT","IT-LO","Lodi","Province","Italy",2 +"ITA","IT","IT-LT","Latina","Province","Italy",2 +"ITA","IT","IT-LU","Lucca","Province","Italy",2 +"ITA","IT","IT-MB","Monza e Brianza","Province","Italy",2 +"ITA","IT","IT-MC","Macerata","Province","Italy",2 +"ITA","IT","IT-ME","Messina","Province","Italy",2 +"ITA","IT","IT-MI","Milano","Province","Italy",2 +"ITA","IT","IT-MN","Mantova","Province","Italy",2 +"ITA","IT","IT-MO","Modena","Province","Italy",2 +"ITA","IT","IT-MS","Massa-Carrara","Province","Italy",2 +"ITA","IT","IT-MT","Matera","Province","Italy",2 +"ITA","IT","IT-NA","Napoli","Province","Italy",2 +"ITA","IT","IT-NO","Novara","Province","Italy",2 +"ITA","IT","IT-NU","Nuoro","Province","Italy",2 +"ITA","IT","IT-OG","Ogliastra","Province","Italy",2 +"ITA","IT","IT-OR","Oristano","Province","Italy",2 +"ITA","IT","IT-OT","Olbia-Tempio","Province","Italy",2 +"ITA","IT","IT-PA","Palermo","Province","Italy",2 +"ITA","IT","IT-PC","Piacenza","Province","Italy",2 +"ITA","IT","IT-PD","Padova","Province","Italy",2 +"ITA","IT","IT-PE","Pescara","Province","Italy",2 +"ITA","IT","IT-PG","Perugia","Province","Italy",2 +"ITA","IT","IT-PI","Pisa","Province","Italy",2 +"ITA","IT","IT-PN","Pordenone","Province","Italy",2 +"ITA","IT","IT-PO","Prato","Province","Italy",2 +"ITA","IT","IT-PR","Parma","Province","Italy",2 +"ITA","IT","IT-PT","Pistoia","Province","Italy",2 +"ITA","IT","IT-PU","Pesaro e Urbino","Province","Italy",2 +"ITA","IT","IT-PV","Pavia","Province","Italy",2 +"ITA","IT","IT-PZ","Potenza","Province","Italy",2 +"ITA","IT","IT-RA","Ravenna","Province","Italy",2 +"ITA","IT","IT-RC","Reggio Calabria","Province","Italy",2 +"ITA","IT","IT-RE","Reggio Emilia","Province","Italy",2 +"ITA","IT","IT-RG","Ragusa","Province","Italy",2 +"ITA","IT","IT-RI","Rieti","Province","Italy",2 +"ITA","IT","IT-RM","Roma","Province","Italy",2 +"ITA","IT","IT-RN","Rimini","Province","Italy",2 +"ITA","IT","IT-RO","Rovigo","Province","Italy",2 +"ITA","IT","IT-SA","Salerno","Province","Italy",2 +"ITA","IT","IT-SI","Siena","Province","Italy",2 +"ITA","IT","IT-SO","Sondrio","Province","Italy",2 +"ITA","IT","IT-SP","La Spezia","Province","Italy",2 +"ITA","IT","IT-SR","Siracusa","Province","Italy",2 +"ITA","IT","IT-SS","Sassari","Province","Italy",2 +"ITA","IT","IT-SV","Savona","Province","Italy",2 +"ITA","IT","IT-TA","Taranto","Province","Italy",2 +"ITA","IT","IT-TE","Teramo","Province","Italy",2 +"ITA","IT","IT-TN","Trento","Province","Italy",2 +"ITA","IT","IT-TO","Torino","Province","Italy",2 +"ITA","IT","IT-TP","Trapani","Province","Italy",2 +"ITA","IT","IT-TR","Terni","Province","Italy",2 +"ITA","IT","IT-TS","Trieste","Province","Italy",2 +"ITA","IT","IT-TV","Treviso","Province","Italy",2 +"ITA","IT","IT-UD","Udine","Province","Italy",2 +"ITA","IT","IT-VA","Varese","Province","Italy",2 +"ITA","IT","IT-VB","Verbano-Cusio-Ossola","Province","Italy",2 +"ITA","IT","IT-VC","Vercelli","Province","Italy",2 +"ITA","IT","IT-VE","Venezia","Province","Italy",2 +"ITA","IT","IT-VI","Vicenza","Province","Italy",2 +"ITA","IT","IT-VR","Verona","Province","Italy",2 +"ITA","IT","IT-VS","Medio Campidano","Province","Italy",2 +"ITA","IT","IT-VT","Viterbo","Province","Italy",2 +"ITA","IT","IT-VV","Vibo Valentia","Province","Italy",2 +"JAM","JM","JM-01","Kingston","Parish","Jamaica",2 +"JAM","JM","JM-02","Saint Andrew","Parish","Jamaica",2 +"JAM","JM","JM-03","Saint Thomas","Parish","Jamaica",2 +"JAM","JM","JM-04","Portland","Parish","Jamaica",2 +"JAM","JM","JM-05","Saint Mary","Parish","Jamaica",2 +"JAM","JM","JM-06","Saint Ann","Parish","Jamaica",2 +"JAM","JM","JM-07","Trelawny","Parish","Jamaica",2 +"JAM","JM","JM-08","Saint James","Parish","Jamaica",2 +"JAM","JM","JM-09","Hanover","Parish","Jamaica",2 +"JAM","JM","JM-10","Westmoreland","Parish","Jamaica",2 +"JAM","JM","JM-11","Saint Elizabeth","Parish","Jamaica",2 +"JAM","JM","JM-12","Manchester","Parish","Jamaica",2 +"JAM","JM","JM-13","Clarendon","Parish","Jamaica",2 +"JAM","JM","JM-14","Saint Catherine","Parish","Jamaica",2 +"JOR","JO","JO-AJ","‘Ajlūn","Governorate","Jordan",2 +"JOR","JO","JO-AM","‘Ammān (Al ‘Aşimah)","Governorate","Jordan",2 +"JOR","JO","JO-AQ","Al ‘Aqabah","Governorate","Jordan",2 +"JOR","JO","JO-AT","Aţ Ţafīlah","Governorate","Jordan",2 +"JOR","JO","JO-AZ","Az Zarqā'","Governorate","Jordan",2 +"JOR","JO","JO-BA","Al Balqā'","Governorate","Jordan",2 +"JOR","JO","JO-IR","Irbid","Governorate","Jordan",2 +"JOR","JO","JO-JA","Jarash","Governorate","Jordan",2 +"JOR","JO","JO-KA","Al Karak","Governorate","Jordan",2 +"JOR","JO","JO-MA","Al Mafraq","Governorate","Jordan",2 +"JOR","JO","JO-MD","Mādabā","Governorate","Jordan",2 +"JOR","JO","JO-MN","Ma‘ān","Governorate","Jordan",2 +"JPN","JP","JP-01","Hokkaido","Prefecture","Japan",2 +"JPN","JP","JP-02","Aomori","Prefecture","Japan",2 +"JPN","JP","JP-03","Iwate","Prefecture","Japan",2 +"JPN","JP","JP-04","Miyagi","Prefecture","Japan",2 +"JPN","JP","JP-05","Akita","Prefecture","Japan",2 +"JPN","JP","JP-06","Yamagata","Prefecture","Japan",2 +"JPN","JP","JP-07","Fukushima","Prefecture","Japan",2 +"JPN","JP","JP-08","Ibaraki","Prefecture","Japan",2 +"JPN","JP","JP-09","Tochigi","Prefecture","Japan",2 +"JPN","JP","JP-10","Gunma","Prefecture","Japan",2 +"JPN","JP","JP-11","Saitama","Prefecture","Japan",2 +"JPN","JP","JP-12","Chiba","Prefecture","Japan",2 +"JPN","JP","JP-13","Tokyo","Prefecture","Japan",2 +"JPN","JP","JP-14","Kanagawa","Prefecture","Japan",2 +"JPN","JP","JP-15","Niigata","Prefecture","Japan",2 +"JPN","JP","JP-16","Toyama","Prefecture","Japan",2 +"JPN","JP","JP-17","Ishikawa","Prefecture","Japan",2 +"JPN","JP","JP-18","Fukui","Prefecture","Japan",2 +"JPN","JP","JP-19","Yamanashi","Prefecture","Japan",2 +"JPN","JP","JP-20","Nagano","Prefecture","Japan",2 +"JPN","JP","JP-21","Gifu","Prefecture","Japan",2 +"JPN","JP","JP-22","Shizuoka","Prefecture","Japan",2 +"JPN","JP","JP-23","Aichi","Prefecture","Japan",2 +"JPN","JP","JP-24","Mie","Prefecture","Japan",2 +"JPN","JP","JP-25","Shiga","Prefecture","Japan",2 +"JPN","JP","JP-26","Kyoto","Prefecture","Japan",2 +"JPN","JP","JP-27","Osaka","Prefecture","Japan",2 +"JPN","JP","JP-28","Hyogo","Prefecture","Japan",2 +"JPN","JP","JP-29","Nara","Prefecture","Japan",2 +"JPN","JP","JP-30","Wakayama","Prefecture","Japan",2 +"JPN","JP","JP-31","Tottori","Prefecture","Japan",2 +"JPN","JP","JP-32","Shimane","Prefecture","Japan",2 +"JPN","JP","JP-33","Okayama","Prefecture","Japan",2 +"JPN","JP","JP-34","Hiroshima","Prefecture","Japan",2 +"JPN","JP","JP-35","Yamaguchi","Prefecture","Japan",2 +"JPN","JP","JP-36","Tokushima","Prefecture","Japan",2 +"JPN","JP","JP-37","Kagawa","Prefecture","Japan",2 +"JPN","JP","JP-38","Ehime","Prefecture","Japan",2 +"JPN","JP","JP-39","Kochi","Prefecture","Japan",2 +"JPN","JP","JP-40","Fukuoka","Prefecture","Japan",2 +"JPN","JP","JP-41","Saga","Prefecture","Japan",2 +"JPN","JP","JP-42","Nagasaki","Prefecture","Japan",2 +"JPN","JP","JP-43","Kumamoto","Prefecture","Japan",2 +"JPN","JP","JP-44","Oita","Prefecture","Japan",2 +"JPN","JP","JP-45","Miyazaki","Prefecture","Japan",2 +"JPN","JP","JP-46","Kagoshima","Prefecture","Japan",2 +"JPN","JP","JP-47","Okinawa","Prefecture","Japan",2 +"KEN","KE","KE-110","Nairobi Municipality","Province","Kenya",2 +"KEN","KE","KE-200","Central","Province","Kenya",2 +"KEN","KE","KE-300","Coast","Province","Kenya",2 +"KEN","KE","KE-400","Eastern","Province","Kenya",2 +"KEN","KE","KE-500","North-Eastern Kaskazini Mashariki","Province","Kenya",2 +"KEN","KE","KE-700","Rift Valley","Province","Kenya",2 +"KEN","KE","KE-800","Western Magharibi","Province","Kenya",2 +"KGZ","KG","KG-B","Batken","Region","Kyrgyzstan",2 +"KGZ","KG","KG-C","Chü","Region","Kyrgyzstan",2 +"KGZ","KG","KG-GB","Bishkek","City","Kyrgyzstan",2 +"KGZ","KG","KG-J","Jalal-Abad","Region","Kyrgyzstan",2 +"KGZ","KG","KG-N","Naryn","Region","Kyrgyzstan",2 +"KGZ","KG","KG-O","Osh","Region","Kyrgyzstan",2 +"KGZ","KG","KG-T","Talas","Region","Kyrgyzstan",2 +"KGZ","KG","KG-Y","Ysyk-Köl","Region","Kyrgyzstan",2 +"KHM","KH","KH-1","Banteay Mean Chey","Province","Cambodia",2 +"KHM","KH","KH-10","Krachoh","Province","Cambodia",2 +"KHM","KH","KH-11","Mondol Kiri","Province","Cambodia",2 +"KHM","KH","KH-12","Phnom Penh","Autonomous municipality","Cambodia",2 +"KHM","KH","KH-13","Preah Vihear","Province","Cambodia",2 +"KHM","KH","KH-14","Prey Veaeng","Province","Cambodia",2 +"KHM","KH","KH-15","Pousaat","Province","Cambodia",2 +"KHM","KH","KH-16","Rotanak Kiri","Province","Cambodia",2 +"KHM","KH","KH-17","Siem Reab","Province","Cambodia",2 +"KHM","KH","KH-18","Krong Preah Sihanouk","Autonomous municipality","Cambodia",2 +"KHM","KH","KH-19","Stueng Traeng","Province","Cambodia",2 +"KHM","KH","KH-2","Battambang","Province","Cambodia",2 +"KHM","KH","KH-20","Svaay Rieng","Province","Cambodia",2 +"KHM","KH","KH-21","Taakaev","Province","Cambodia",2 +"KHM","KH","KH-22","Otdar Mean Chey","Province","Cambodia",2 +"KHM","KH","KH-23","Krong Kaeb","Autonomous municipality","Cambodia",2 +"KHM","KH","KH-24","Krong Pailin","Autonomous municipality","Cambodia",2 +"KHM","KH","KH-3","Kampong Cham","Province","Cambodia",2 +"KHM","KH","KH-4","Kampong Chhnang","Province","Cambodia",2 +"KHM","KH","KH-5","Kampong Speu","Province","Cambodia",2 +"KHM","KH","KH-6","Kampong Thom","Province","Cambodia",2 +"KHM","KH","KH-7","Kampot","Province","Cambodia",2 +"KHM","KH","KH-8","Kandal","Province","Cambodia",2 +"KHM","KH","KH-9","Kach Kong","Province","Cambodia",2 +"KIR","KI","KI-G","Gilbert Islands","Island group","Kiribati",2 +"KIR","KI","KI-L","Line Islands","Island group","Kiribati",2 +"KIR","KI","KI-P","Phoenix Islands","Island group","Kiribati",2 +"COM","KM","KM-A","Andjouân (Anjwān)","Island","Comoros",2 +"COM","KM","KM-G","Andjazîdja (Anjazījah)","Island","Comoros",2 +"COM","KM","KM-M","Moûhîlî (Mūhīlī)","Island","Comoros",2 +"KNA","KN","KN-01","Christ Church Nichola Town","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-02","Saint Anne Sandy Point","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-03","Saint George Basseterre","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-04","Saint George Gingerland","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-05","Saint James Windward","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-06","Saint John Capisterre","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-07","Saint John Figtree","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-08","Saint Mary Cayon","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-09","Saint Paul Capisterre","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-10","Saint Paul Charlestown","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-11","Saint Peter Basseterre","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-12","Saint Thomas Lowland","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-13","Saint Thomas Middle Island","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-15","Trinity Palmetto Point","Parish","Saint Kitts and Nevis",2 +"KNA","KN","KN-K","Saint Kitts","State","Saint Kitts and Nevis",2 +"KNA","KN","KN-N","Nevis","State","Saint Kitts and Nevis",2 +"PRK","KP","KP-01","P’yŏngyang","Capital city","Korea, Democratic People's Republic of",2 +"PRK","KP","KP-02","P’yŏngan-namdo","Province","Korea, Democratic People's Republic of",2 +"PRK","KP","KP-03","P’yŏngan-bukto","Province","Korea, Democratic People's Republic of",2 +"PRK","KP","KP-04","Chagang-do","Province","Korea, Democratic People's Republic of",2 +"PRK","KP","KP-05","Hwanghae-namdo","Province","Korea, Democratic People's Republic of",2 +"PRK","KP","KP-06","Hwanghae-bukto","Province","Korea, Democratic People's Republic of",2 +"PRK","KP","KP-07","Kangwŏn-do","Province","Korea, Democratic People's Republic of",2 +"PRK","KP","KP-08","Hamgyŏng-namdo","Province","Korea, Democratic People's Republic of",2 +"PRK","KP","KP-09","Hamgyŏng-bukto","Province","Korea, Democratic People's Republic of",2 +"PRK","KP","KP-10","Yanggang-do","Province","Korea, Democratic People's Republic of",2 +"PRK","KP","KP-13","Nasŏn (Najin-Sŏnbong)","Special city","Korea, Democratic People's Republic of",2 +"KOR","KR","KR-11","Seoul Teugbyeolsi","Capital Metropolitan City","Korea, Republic of",2 +"KOR","KR","KR-26","Busan Gwang'yeogsi","Metropolitan cities","Korea, Republic of",2 +"KOR","KR","KR-27","Daegu Gwang'yeogsi","Metropolitan cities","Korea, Republic of",2 +"KOR","KR","KR-28","Incheon Gwang'yeogsi","Metropolitan cities","Korea, Republic of",2 +"KOR","KR","KR-29","Gwangju Gwang'yeogsi","Metropolitan cities","Korea, Republic of",2 +"KOR","KR","KR-30","Daejeon Gwang'yeogsi","Metropolitan cities","Korea, Republic of",2 +"KOR","KR","KR-31","Ulsan Gwang'yeogsi","Metropolitan cities","Korea, Republic of",2 +"KOR","KR","KR-41","Gyeonggido","Province","Korea, Republic of",2 +"KOR","KR","KR-42","Gang'weondo","Province","Korea, Republic of",2 +"KOR","KR","KR-43","Chungcheongbukdo","Province","Korea, Republic of",2 +"KOR","KR","KR-44","Chungcheongnamdo","Province","Korea, Republic of",2 +"KOR","KR","KR-45","Jeonrabukdo","Province","Korea, Republic of",2 +"KOR","KR","KR-46","Jeonranamdo","Province","Korea, Republic of",2 +"KOR","KR","KR-47","Gyeongsangbukdo","Province","Korea, Republic of",2 +"KOR","KR","KR-48","Gyeongsangnamdo","Province","Korea, Republic of",2 +"KOR","KR","KR-49","Jejudo","Province","Korea, Republic of",2 +"KWT","KW","KW-AH","Al Ahmadi","Governorate","Kuwait",2 +"KWT","KW","KW-FA","Al Farwānīyah","Governorate","Kuwait",2 +"KWT","KW","KW-HA","Hawallī","Governorate","Kuwait",2 +"KWT","KW","KW-JA","Al Jahrrā’","Governorate","Kuwait",2 +"KWT","KW","KW-KU","Al Kuwayt (Al ‘Āşimah)","Governorate","Kuwait",2 +"KWT","KW","KW-MU","Mubārak al Kabīr","Governorate","Kuwait",2 +"KAZ","KZ","KZ-AKM","Aqmola oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-AKT","Aqtöbe oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-ALA","Almaty","City","Kazakhstan",2 +"KAZ","KZ","KZ-ALM","Almaty oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-AST","Astana","City","Kazakhstan",2 +"KAZ","KZ","KZ-ATY","Atyraū oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-KAR","Qaraghandy oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-KUS","Qostanay oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-KZY","Qyzylorda oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-MAN","Mangghystaū oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-PAV","Pavlodar oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-SEV","Soltüstik Quzaqstan oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-VOS","Shyghys Qazaqstan oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-YUZ","Ongtüstik Qazaqstan oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-ZAP","Batys Quzaqstan oblysy","Region","Kazakhstan",2 +"KAZ","KZ","KZ-ZHA","Zhambyl oblysy","Region","Kazakhstan",2 +"LAO","LA","LA-AT","Attapu","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-BK","Bokèo","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-BL","Bolikhamxai","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-CH","Champasak","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-HO","Houaphan","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-KH","Khammouan","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-LM","Louang Namtha","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-LP","Louangphabang","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-OU","Oudômxai","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-PH","Phôngsali","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-SL","Salavan","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-SV","Savannakhét","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-VI","Vientiane","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-VT","Vientiane","Prefecture","Lao People's Democratic Republic",2 +"LAO","LA","LA-XA","Xaignabouli","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-XE","Xékong","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-XI","Xiangkhouang","Province","Lao People's Democratic Republic",2 +"LAO","LA","LA-XS","Xaisômboun","Province","Lao People's Democratic Republic",2 +"LBN","LB","LB-AK","Aakkâr","Governorate","Lebanon",2 +"LBN","LB","LB-AS","Liban-Nord","Governorate","Lebanon",2 +"LBN","LB","LB-BA","Beyrouth","Governorate","Lebanon",2 +"LBN","LB","LB-BH","Baalbek-Hermel","Governorate","Lebanon",2 +"LBN","LB","LB-BI","Béqaa","Governorate","Lebanon",2 +"LBN","LB","LB-JA","Liban-Sud","Governorate","Lebanon",2 +"LBN","LB","LB-JL","Mont-Liban","Governorate","Lebanon",2 +"LBN","LB","LB-NA","Nabatîyé","Governorate","Lebanon",2 +"LIE","LI","LI-01","Balzers","Commune","Liechtenstein",2 +"LIE","LI","LI-02","Eschen","Commune","Liechtenstein",2 +"LIE","LI","LI-03","Gamprin","Commune","Liechtenstein",2 +"LIE","LI","LI-04","Mauren","Commune","Liechtenstein",2 +"LIE","LI","LI-05","Planken","Commune","Liechtenstein",2 +"LIE","LI","LI-06","Ruggell","Commune","Liechtenstein",2 +"LIE","LI","LI-07","Schaan","Commune","Liechtenstein",2 +"LIE","LI","LI-08","Schellenberg","Commune","Liechtenstein",2 +"LIE","LI","LI-09","Triesen","Commune","Liechtenstein",2 +"LIE","LI","LI-10","Triesenberg","Commune","Liechtenstein",2 +"LIE","LI","LI-11","Vaduz","Commune","Liechtenstein",2 +"LKA","LK","LK-1","Basnāhira paḷāta","Province","Sri Lanka",2 +"LKA","LK","LK-11","Kŏḷamba","District","Sri Lanka",2 +"LKA","LK","LK-12","Gampaha","District","Sri Lanka",2 +"LKA","LK","LK-13","Kaḷutara","District","Sri Lanka",2 +"LKA","LK","LK-2","Madhyama paḷāta","Province","Sri Lanka",2 +"LKA","LK","LK-21","Mahanuvara","District","Sri Lanka",2 +"LKA","LK","LK-22","Mātale","District","Sri Lanka",2 +"LKA","LK","LK-23","Nuvara Ĕliya","District","Sri Lanka",2 +"LKA","LK","LK-3","Dakuṇu paḷāta","Province","Sri Lanka",2 +"LKA","LK","LK-31","Gālla","District","Sri Lanka",2 +"LKA","LK","LK-32","Mātara","District","Sri Lanka",2 +"LKA","LK","LK-33","Hambantŏṭa","District","Sri Lanka",2 +"LKA","LK","LK-4","Uturu paḷāta","Province","Sri Lanka",2 +"LKA","LK","LK-41","Yāpanaya","District","Sri Lanka",2 +"LKA","LK","LK-42","Kilinŏchchi","District","Sri Lanka",2 +"LKA","LK","LK-43","Mannārama","District","Sri Lanka",2 +"LKA","LK","LK-44","Vavuniyāva","District","Sri Lanka",2 +"LKA","LK","LK-45","Mulativ","District","Sri Lanka",2 +"LKA","LK","LK-5","Næ̆gĕnahira paḷāta","Province","Sri Lanka",2 +"LKA","LK","LK-51","Maḍakalapuva","District","Sri Lanka",2 +"LKA","LK","LK-52","Ampāara","District","Sri Lanka",2 +"LKA","LK","LK-53","Trikuṇāmalaya","District","Sri Lanka",2 +"LKA","LK","LK-6","Vayamba paḷāta","Province","Sri Lanka",2 +"LKA","LK","LK-61","Kuruṇægala","District","Sri Lanka",2 +"LKA","LK","LK-62","Puttalama","District","Sri Lanka",2 +"LKA","LK","LK-7","Uturumæ̆da paḷāta","Province","Sri Lanka",2 +"LKA","LK","LK-71","Anurādhapura","District","Sri Lanka",2 +"LKA","LK","LK-72","Pŏḷŏnnaruva","District","Sri Lanka",2 +"LKA","LK","LK-8","Ūva paḷāta","Province","Sri Lanka",2 +"LKA","LK","LK-81","Badulla","District","Sri Lanka",2 +"LKA","LK","LK-82","Mŏṇarāgala","District","Sri Lanka",2 +"LKA","LK","LK-9","Sabaragamuva paḷāta","Province","Sri Lanka",2 +"LKA","LK","LK-91","Ratnapura","District","Sri Lanka",2 +"LKA","LK","LK-92","Kægalla","District","Sri Lanka",2 +"LBR","LR","LR-BG","Bong","County","Liberia",2 +"LBR","LR","LR-BM","Bomi","County","Liberia",2 +"LBR","LR","LR-CM","Grand Cape Mount","County","Liberia",2 +"LBR","LR","LR-GB","Grand Bassa","County","Liberia",2 +"LBR","LR","LR-GG","Grand Gedeh","County","Liberia",2 +"LBR","LR","LR-GK","Grand Kru","County","Liberia",2 +"LBR","LR","LR-LO","Lofa","County","Liberia",2 +"LBR","LR","LR-MG","Margibi","County","Liberia",2 +"LBR","LR","LR-MO","Montserrado","County","Liberia",2 +"LBR","LR","LR-MY","Maryland","County","Liberia",2 +"LBR","LR","LR-NI","Nimba","County","Liberia",2 +"LBR","LR","LR-RI","Rivercess","County","Liberia",2 +"LBR","LR","LR-SI","Sinoe","County","Liberia",2 +"LSO","LS","LS-A","Maseru","District","Lesotho",2 +"LSO","LS","LS-B","Butha-Buthe","District","Lesotho",2 +"LSO","LS","LS-C","Leribe","District","Lesotho",2 +"LSO","LS","LS-D","Berea","District","Lesotho",2 +"LSO","LS","LS-E","Mafeteng","District","Lesotho",2 +"LSO","LS","LS-F","Mohale's Hoek","District","Lesotho",2 +"LSO","LS","LS-G","Quthing","District","Lesotho",2 +"LSO","LS","LS-H","Qacha's Nek","District","Lesotho",2 +"LSO","LS","LS-J","Mokhotlong","District","Lesotho",2 +"LSO","LS","LS-K","Thaba-Tseka","District","Lesotho",2 +"LTU","LT","LT-AL","Alytaus Apskritis","County","Lithuania",2 +"LTU","LT","LT-KL","Klaipėdos Apskritis","County","Lithuania",2 +"LTU","LT","LT-KU","Kauno Apskritis","County","Lithuania",2 +"LTU","LT","LT-MR","Marijampolės Apskritis","County","Lithuania",2 +"LTU","LT","LT-PN","Panevėžio Apskritis","County","Lithuania",2 +"LTU","LT","LT-SA","Šiaulių Apskritis","County","Lithuania",2 +"LTU","LT","LT-TA","Tauragés Apskritis","County","Lithuania",2 +"LTU","LT","LT-TE","Telšių Apskritis","County","Lithuania",2 +"LTU","LT","LT-UT","Utenos Apskritis","County","Lithuania",2 +"LTU","LT","LT-VL","Vilniaus Apskritis","County","Lithuania",2 +"LUX","LU","LU-D","Diekirch","District","Luxembourg",2 +"LUX","LU","LU-G","Grevenmacher","District","Luxembourg",2 +"LUX","LU","LU-L","Luxembourg","District","Luxembourg",2 +"LVA","LV","LV-001","Aglonas novads","Municipality","Latvia",2 +"LVA","LV","LV-002","Aizkraukles novads","Municipality","Latvia",2 +"LVA","LV","LV-003","Aizputes novads","Municipality","Latvia",2 +"LVA","LV","LV-004","Aknīstes novads","Municipality","Latvia",2 +"LVA","LV","LV-005","Alojas novads","Municipality","Latvia",2 +"LVA","LV","LV-006","Alsungas novads","Municipality","Latvia",2 +"LVA","LV","LV-007","Alūksnes novads","Municipality","Latvia",2 +"LVA","LV","LV-008","Amatas novads","Municipality","Latvia",2 +"LVA","LV","LV-009","Apes novads","Municipality","Latvia",2 +"LVA","LV","LV-010","Auces novads","Municipality","Latvia",2 +"LVA","LV","LV-011","Ādažu novads","Municipality","Latvia",2 +"LVA","LV","LV-012","Babītes novads","Municipality","Latvia",2 +"LVA","LV","LV-013","Baldones novads","Municipality","Latvia",2 +"LVA","LV","LV-014","Baltinavas novads","Municipality","Latvia",2 +"LVA","LV","LV-015","Balvu novads","Municipality","Latvia",2 +"LVA","LV","LV-016","Bauskas novads","Municipality","Latvia",2 +"LVA","LV","LV-017","Beverīnas novads","Municipality","Latvia",2 +"LVA","LV","LV-018","Brocēnu novads","Municipality","Latvia",2 +"LVA","LV","LV-019","Burtnieku novads","Municipality","Latvia",2 +"LVA","LV","LV-020","Carnikavas novads","Municipality","Latvia",2 +"LVA","LV","LV-021","Cesvaines novads","Municipality","Latvia",2 +"LVA","LV","LV-022","Cēsu novads","Municipality","Latvia",2 +"LVA","LV","LV-023","Ciblas novads","Municipality","Latvia",2 +"LVA","LV","LV-024","Dagdas novads","Municipality","Latvia",2 +"LVA","LV","LV-025","Daugavpils novads","Municipality","Latvia",2 +"LVA","LV","LV-026","Dobeles novads","Municipality","Latvia",2 +"LVA","LV","LV-027","Dundagas novads","Municipality","Latvia",2 +"LVA","LV","LV-028","Durbes novads","Municipality","Latvia",2 +"LVA","LV","LV-029","Engures novads","Municipality","Latvia",2 +"LVA","LV","LV-030","Ērgļu novads","Municipality","Latvia",2 +"LVA","LV","LV-031","Garkalnes novads","Municipality","Latvia",2 +"LVA","LV","LV-032","Grobiņas novads","Municipality","Latvia",2 +"LVA","LV","LV-033","Gulbenes novads","Municipality","Latvia",2 +"LVA","LV","LV-034","Iecavas novads","Municipality","Latvia",2 +"LVA","LV","LV-035","Ikšķiles novads","Municipality","Latvia",2 +"LVA","LV","LV-036","Ilūkstes novads","Municipality","Latvia",2 +"LVA","LV","LV-037","Inčukalna novads","Municipality","Latvia",2 +"LVA","LV","LV-038","Jaunjelgavas novads","Municipality","Latvia",2 +"LVA","LV","LV-039","Jaunpiebalgas novads","Municipality","Latvia",2 +"LVA","LV","LV-040","Jaunpils novads","Municipality","Latvia",2 +"LVA","LV","LV-041","Jelgavas novads","Municipality","Latvia",2 +"LVA","LV","LV-042","Jēkabpils novads","Municipality","Latvia",2 +"LVA","LV","LV-043","Kandavas novads","Municipality","Latvia",2 +"LVA","LV","LV-044","Kārsavas novads","Municipality","Latvia",2 +"LVA","LV","LV-045","Kocēnu novads","Municipality","Latvia",2 +"LVA","LV","LV-046","Kokneses novads","Municipality","Latvia",2 +"LVA","LV","LV-047","Krāslavas novads","Municipality","Latvia",2 +"LVA","LV","LV-048","Krimuldas novads","Municipality","Latvia",2 +"LVA","LV","LV-049","Krustpils novads","Municipality","Latvia",2 +"LVA","LV","LV-050","Kuldīgas novads","Municipality","Latvia",2 +"LVA","LV","LV-051","Ķeguma novads","Municipality","Latvia",2 +"LVA","LV","LV-052","Ķekavas novads","Municipality","Latvia",2 +"LVA","LV","LV-053","Lielvārdes novads","Municipality","Latvia",2 +"LVA","LV","LV-054","Limbažu novads","Municipality","Latvia",2 +"LVA","LV","LV-055","Līgatnes novads","Municipality","Latvia",2 +"LVA","LV","LV-056","Līvānu novads","Municipality","Latvia",2 +"LVA","LV","LV-057","Lubānas novads","Municipality","Latvia",2 +"LVA","LV","LV-058","Ludzas novads","Municipality","Latvia",2 +"LVA","LV","LV-059","Madonas novads","Municipality","Latvia",2 +"LVA","LV","LV-060","Mazsalacas novads","Municipality","Latvia",2 +"LVA","LV","LV-061","Mālpils novads","Municipality","Latvia",2 +"LVA","LV","LV-062","Mārupes novads","Municipality","Latvia",2 +"LVA","LV","LV-063","Mērsraga novads","Municipality","Latvia",2 +"LVA","LV","LV-064","Naukšēnu novads","Municipality","Latvia",2 +"LVA","LV","LV-065","Neretas novads","Municipality","Latvia",2 +"LVA","LV","LV-066","Nīcas novads","Municipality","Latvia",2 +"LVA","LV","LV-067","Ogres novads","Municipality","Latvia",2 +"LVA","LV","LV-068","Olaines novads","Municipality","Latvia",2 +"LVA","LV","LV-069","Ozolnieku novads","Municipality","Latvia",2 +"LVA","LV","LV-070","Pārgaujas novads","Municipality","Latvia",2 +"LVA","LV","LV-071","Pāvilostas novads","Municipality","Latvia",2 +"LVA","LV","LV-072","Pļaviņu novads","Municipality","Latvia",2 +"LVA","LV","LV-073","Preiļu novads","Municipality","Latvia",2 +"LVA","LV","LV-074","Priekules novads","Municipality","Latvia",2 +"LVA","LV","LV-075","Priekuļu novads","Municipality","Latvia",2 +"LVA","LV","LV-076","Raunas novads","Municipality","Latvia",2 +"LVA","LV","LV-077","Rēzeknes novads","Municipality","Latvia",2 +"LVA","LV","LV-078","Riebiņu novads","Municipality","Latvia",2 +"LVA","LV","LV-079","Rojas novads","Municipality","Latvia",2 +"LVA","LV","LV-080","Ropažu novads","Municipality","Latvia",2 +"LVA","LV","LV-081","Rucavas novads","Municipality","Latvia",2 +"LVA","LV","LV-082","Rugāju novads","Municipality","Latvia",2 +"LVA","LV","LV-083","Rundāles novads","Municipality","Latvia",2 +"LVA","LV","LV-084","Rūjienas novads","Municipality","Latvia",2 +"LVA","LV","LV-085","Salas novads","Municipality","Latvia",2 +"LVA","LV","LV-086","Salacgrīvas novads","Municipality","Latvia",2 +"LVA","LV","LV-087","Salaspils novads","Municipality","Latvia",2 +"LVA","LV","LV-088","Saldus novads","Municipality","Latvia",2 +"LVA","LV","LV-089","Saulkrastu novads","Municipality","Latvia",2 +"LVA","LV","LV-090","Sējas novads","Municipality","Latvia",2 +"LVA","LV","LV-091","Siguldas novads","Municipality","Latvia",2 +"LVA","LV","LV-092","Skrīveru novads","Municipality","Latvia",2 +"LVA","LV","LV-093","Skrundas novads","Municipality","Latvia",2 +"LVA","LV","LV-094","Smiltenes novads","Municipality","Latvia",2 +"LVA","LV","LV-095","Stopiņu novads","Municipality","Latvia",2 +"LVA","LV","LV-096","Strenču novads","Municipality","Latvia",2 +"LVA","LV","LV-097","Talsu novads","Municipality","Latvia",2 +"LVA","LV","LV-098","Tērvetes novads","Municipality","Latvia",2 +"LVA","LV","LV-099","Tukuma novads","Municipality","Latvia",2 +"LVA","LV","LV-100","Vaiņodes novads","Municipality","Latvia",2 +"LVA","LV","LV-101","Valkas novads","Municipality","Latvia",2 +"LVA","LV","LV-102","Varakļānu novads","Municipality","Latvia",2 +"LVA","LV","LV-103","Vārkavas novads","Municipality","Latvia",2 +"LVA","LV","LV-104","Vecpiebalgas novads","Municipality","Latvia",2 +"LVA","LV","LV-105","Vecumnieku novads","Municipality","Latvia",2 +"LVA","LV","LV-106","Ventspils novads","Municipality","Latvia",2 +"LVA","LV","LV-107","Viesītes novads","Municipality","Latvia",2 +"LVA","LV","LV-108","Viļakas novads","Municipality","Latvia",2 +"LVA","LV","LV-109","Viļānu novads","Municipality","Latvia",2 +"LVA","LV","LV-110","Zilupes novads","Municipality","Latvia",2 +"LVA","LV","LV-DGV","Daugavpils","Republican City","Latvia",2 +"LVA","LV","LV-JEL","Jelgava","Republican City","Latvia",2 +"LVA","LV","LV-JKB","Jēkabpils","Republican City","Latvia",2 +"LVA","LV","LV-JUR","Jūrmala","Republican City","Latvia",2 +"LVA","LV","LV-LPX","Liepāja","Republican City","Latvia",2 +"LVA","LV","LV-REZ","Rēzekne","Republican City","Latvia",2 +"LVA","LV","LV-RIX","Rīga","Republican City","Latvia",2 +"LVA","LV","LV-VEN","Ventspils","Republican City","Latvia",2 +"LVA","LV","LV-VMR","Valmiera","Republican City","Latvia",2 +"LBY","LY","LY-BA","Banghāzī","Popularates","Libya",2 +"LBY","LY","LY-BU","Al Buţnān","Popularates","Libya",2 +"LBY","LY","LY-DR","Darnah","Popularates","Libya",2 +"LBY","LY","LY-GT","Ghāt","Popularates","Libya",2 +"LBY","LY","LY-JA","Al Jabal al Akhḑar","Popularates","Libya",2 +"LBY","LY","LY-JB","Jaghbūb","Popularates","Libya",2 +"LBY","LY","LY-JG","Al Jabal al Gharbī","Popularates","Libya",2 +"LBY","LY","LY-JI","Al Jifārah","Popularates","Libya",2 +"LBY","LY","LY-JU","Al Jufrah","Popularates","Libya",2 +"LBY","LY","LY-KF","Al Kufrah","Popularates","Libya",2 +"LBY","LY","LY-MB","Al Marqab","Popularates","Libya",2 +"LBY","LY","LY-MI","Mişrātah","Popularates","Libya",2 +"LBY","LY","LY-MJ","Al Marj","Popularates","Libya",2 +"LBY","LY","LY-MQ","Murzuq","Popularates","Libya",2 +"LBY","LY","LY-NL","Nālūt","Popularates","Libya",2 +"LBY","LY","LY-NQ","An Nuqaţ al Khams","Popularates","Libya",2 +"LBY","LY","LY-SB","Sabhā","Popularates","Libya",2 +"LBY","LY","LY-SR","Surt","Popularates","Libya",2 +"LBY","LY","LY-TB","Ţarābulus","Popularates","Libya",2 +"LBY","LY","LY-WA","Al Wāḩāt","Popularates","Libya",2 +"LBY","LY","LY-WD","Wādī al Ḩayāt","Popularates","Libya",2 +"LBY","LY","LY-WS","Wādī ash Shāţiʾ","Popularates","Libya",2 +"LBY","LY","LY-ZA","Az Zāwiyah","Popularates","Libya",2 +"MAR","MA","MA-01","Tanger-Tétouan","Economic region","Morocco",2 +"MAR","MA","MA-02","Gharb-Chrarda-Beni Hssen","Economic region","Morocco",2 +"MAR","MA","MA-03","Taza-Al Hoceima-Taounate","Economic region","Morocco",2 +"MAR","MA","MA-04","L'Oriental","Economic region","Morocco",2 +"MAR","MA","MA-05","Fès-Boulemane","Economic region","Morocco",2 +"MAR","MA","MA-06","Meknès-Tafilalet","Economic region","Morocco",2 +"MAR","MA","MA-07","Rabat-Salé-Zemmour-Zaer","Economic region","Morocco",2 +"MAR","MA","MA-08","Grand Casablanca","Economic region","Morocco",2 +"MAR","MA","MA-09","Chaouia-Ouardigha","Economic region","Morocco",2 +"MAR","MA","MA-10","Doukhala-Abda","Economic region","Morocco",2 +"MAR","MA","MA-11","Marrakech-Tensift-Al Haouz","Economic region","Morocco",2 +"MAR","MA","MA-12","Tadla-Azilal","Economic region","Morocco",2 +"MAR","MA","MA-13","Sous-Massa-Draa","Economic region","Morocco",2 +"MAR","MA","MA-14","Guelmim-Es Smara","Economic region","Morocco",2 +"MAR","MA","MA-15","Laâyoune-Boujdour-Sakia el Hamra","Economic region","Morocco",2 +"MAR","MA","MA-16","Oued ed Dahab-Lagouira","Economic region","Morocco",2 +"MAR","MA","MA-AGD","Agadir-Ida-Outanane","Prefecture","Morocco",2 +"MAR","MA","MA-AOU","Aousserd","Prefecture","Morocco",2 +"MAR","MA","MA-ASZ","Assa-Zag","Province","Morocco",2 +"MAR","MA","MA-AZI","Azilal","Province","Morocco",2 +"MAR","MA","MA-BEM","Beni Mellal","Province","Morocco",2 +"MAR","MA","MA-BER","Berkane","Province","Morocco",2 +"MAR","MA","MA-BES","Ben Slimane","Province","Morocco",2 +"MAR","MA","MA-BOD","Boujdour (EH)","Province","Morocco",2 +"MAR","MA","MA-BOM","Boulemane","Province","Morocco",2 +"MAR","MA","MA-CAS","Casablanca [Dar el Beïda]","Prefecture","Morocco",2 +"MAR","MA","MA-CHE","Chefchaouen","Province","Morocco",2 +"MAR","MA","MA-CHI","Chichaoua","Province","Morocco",2 +"MAR","MA","MA-CHT","Chtouka-Ait Baha","Province","Morocco",2 +"MAR","MA","MA-ERR","Errachidia","Province","Morocco",2 +"MAR","MA","MA-ESI","Essaouira","Province","Morocco",2 +"MAR","MA","MA-ESM","Es Smara (EH)","Province","Morocco",2 +"MAR","MA","MA-FAH","Fahs-Beni Makada","Prefecture","Morocco",2 +"MAR","MA","MA-FES","Fès-Dar-Dbibegh","Prefecture","Morocco",2 +"MAR","MA","MA-FIG","Figuig","Province","Morocco",2 +"MAR","MA","MA-GUE","Guelmim","Province","Morocco",2 +"MAR","MA","MA-HAJ","El Hajeb","Province","Morocco",2 +"MAR","MA","MA-HAO","Al Haouz","Province","Morocco",2 +"MAR","MA","MA-HOC","Al Hoceïma","Province","Morocco",2 +"MAR","MA","MA-IFR","Ifrane","Province","Morocco",2 +"MAR","MA","MA-INE","Inezgane-Ait Melloul","Prefecture","Morocco",2 +"MAR","MA","MA-JDI","El Jadida","Province","Morocco",2 +"MAR","MA","MA-JRA","Jrada","Province","Morocco",2 +"MAR","MA","MA-KEN","Kénitra","Province","Morocco",2 +"MAR","MA","MA-KES","Kelaat es Sraghna","Province","Morocco",2 +"MAR","MA","MA-KHE","Khemisaet","Province","Morocco",2 +"MAR","MA","MA-KHN","Khenifra","Province","Morocco",2 +"MAR","MA","MA-KHO","Khouribga","Province","Morocco",2 +"MAR","MA","MA-LAA","Laâyoune (EH)","Province","Morocco",2 +"MAR","MA","MA-LAR","Larache","Province","Morocco",2 +"MAR","MA","MA-MED","Médiouna","Province","Morocco",2 +"MAR","MA","MA-MEK","Meknès","Prefecture","Morocco",2 +"MAR","MA","MA-MMD","Marrakech-Medina","Prefecture","Morocco",2 +"MAR","MA","MA-MMN","Marrakech-Menara","Prefecture","Morocco",2 +"MAR","MA","MA-MOH","Mohammadia","Prefecture","Morocco",2 +"MAR","MA","MA-MOU","Moulay Yacoub","Province","Morocco",2 +"MAR","MA","MA-NAD","Nador","Province","Morocco",2 +"MAR","MA","MA-NOU","Nouaceur","Province","Morocco",2 +"MAR","MA","MA-OUA","Ouarzazate","Province","Morocco",2 +"MAR","MA","MA-OUD","Oued ed Dahab (EH)","Province","Morocco",2 +"MAR","MA","MA-OUJ","Oujda-Angad","Prefecture","Morocco",2 +"MAR","MA","MA-RAB","Rabat","Prefecture","Morocco",2 +"MAR","MA","MA-SAF","Safi","Province","Morocco",2 +"MAR","MA","MA-SAL","Salé","Prefecture","Morocco",2 +"MAR","MA","MA-SEF","Sefrou","Province","Morocco",2 +"MAR","MA","MA-SET","Settat","Province","Morocco",2 +"MAR","MA","MA-SIK","Sidl Kacem","Province","Morocco",2 +"MAR","MA","MA-SKH","Skhirate-Témara","Prefecture","Morocco",2 +"MAR","MA","MA-SYB","Sidi Youssef Ben Ali","Prefecture","Morocco",2 +"MAR","MA","MA-TAI","Taourirt","Province","Morocco",2 +"MAR","MA","MA-TAO","Taounate","Province","Morocco",2 +"MAR","MA","MA-TAR","Taroudant","Province","Morocco",2 +"MAR","MA","MA-TAT","Tata","Province","Morocco",2 +"MAR","MA","MA-TAZ","Taza","Province","Morocco",2 +"MAR","MA","MA-TET","Tétouan","Prefecture","Morocco",2 +"MAR","MA","MA-TIZ","Tiznit","Province","Morocco",2 +"MAR","MA","MA-TNG","Tanger-Assilah","Prefecture","Morocco",2 +"MAR","MA","MA-TNT","Tan-Tan","Province","Morocco",2 +"MAR","MA","MA-ZAG","Zagora","Province","Morocco",2 +"MCO","MC","MC-CL","La Colle","Quarter","Monaco",2 +"MCO","MC","MC-CO","La Condamine","Quarter","Monaco",2 +"MCO","MC","MC-FO","Fontvieille","Quarter","Monaco",2 +"MCO","MC","MC-GA","La Gare","Quarter","Monaco",2 +"MCO","MC","MC-JE","Jardin Exotique","Quarter","Monaco",2 +"MCO","MC","MC-LA","Larvotto","Quarter","Monaco",2 +"MCO","MC","MC-MA","Malbousquet","Quarter","Monaco",2 +"MCO","MC","MC-MC","Monte-Carlo","Quarter","Monaco",2 +"MCO","MC","MC-MG","Moneghetti","Quarter","Monaco",2 +"MCO","MC","MC-MO","Monaco-Ville","Quarter","Monaco",2 +"MCO","MC","MC-MU","Moulins","Quarter","Monaco",2 +"MCO","MC","MC-PH","Port-Hercule","Quarter","Monaco",2 +"MCO","MC","MC-SD","Sainte-Dévote","Quarter","Monaco",2 +"MCO","MC","MC-SO","La Source","Quarter","Monaco",2 +"MCO","MC","MC-SP","Spélugues","Quarter","Monaco",2 +"MCO","MC","MC-SR","Saint-Roman","Quarter","Monaco",2 +"MCO","MC","MC-VR","Vallon de la Rousse","Quarter","Monaco",2 +"MDA","MD","MD-AN","Anenii Noi","District","Moldova",2 +"MDA","MD","MD-BA","Bălți","City","Moldova",2 +"MDA","MD","MD-BD","Tighina","City","Moldova",2 +"MDA","MD","MD-BR","Briceni","District","Moldova",2 +"MDA","MD","MD-BS","Basarabeasca","District","Moldova",2 +"MDA","MD","MD-CA","Cahul","District","Moldova",2 +"MDA","MD","MD-CL","Călărași","District","Moldova",2 +"MDA","MD","MD-CM","Cimișlia","District","Moldova",2 +"MDA","MD","MD-CR","Criuleni","District","Moldova",2 +"MDA","MD","MD-CS","Căușeni","District","Moldova",2 +"MDA","MD","MD-CT","Cantemir","District","Moldova",2 +"MDA","MD","MD-CU","Chișinău","City","Moldova",2 +"MDA","MD","MD-DO","Dondușeni","District","Moldova",2 +"MDA","MD","MD-DR","Drochia","District","Moldova",2 +"MDA","MD","MD-DU","Dubăsari","District","Moldova",2 +"MDA","MD","MD-ED","Edineț","District","Moldova",2 +"MDA","MD","MD-FA","Fălești","District","Moldova",2 +"MDA","MD","MD-FL","Florești","District","Moldova",2 +"MDA","MD","MD-GA","Găgăuzia, Unitatea teritorială autonomă","Autonomous territorial unit","Moldova",2 +"MDA","MD","MD-GL","Glodeni","District","Moldova",2 +"MDA","MD","MD-HI","Hîncești","District","Moldova",2 +"MDA","MD","MD-IA","Ialoveni","District","Moldova",2 +"MDA","MD","MD-LE","Leova","District","Moldova",2 +"MDA","MD","MD-NI","Nisporeni","District","Moldova",2 +"MDA","MD","MD-OC","Ocnița","District","Moldova",2 +"MDA","MD","MD-OR","Orhei","District","Moldova",2 +"MDA","MD","MD-RE","Rezina","District","Moldova",2 +"MDA","MD","MD-RI","Rîșcani","District","Moldova",2 +"MDA","MD","MD-SD","Șoldănești","District","Moldova",2 +"MDA","MD","MD-SI","Sîngerei","District","Moldova",2 +"MDA","MD","MD-SN","Stînga Nistrului, unitatea teritorială din","Territorial unit","Moldova",2 +"MDA","MD","MD-SO","Soroca","District","Moldova",2 +"MDA","MD","MD-ST","Strășeni","District","Moldova",2 +"MDA","MD","MD-SV","Ștefan Vodă","District","Moldova",2 +"MDA","MD","MD-TA","Taraclia","District","Moldova",2 +"MDA","MD","MD-TE","Telenești","District","Moldova",2 +"MDA","MD","MD-UN","Ungheni","District","Moldova",2 +"MNE","ME","ME-01","Andrijevica","Municipality","Montenegro",2 +"MNE","ME","ME-02","Bar","Municipality","Montenegro",2 +"MNE","ME","ME-03","Berane","Municipality","Montenegro",2 +"MNE","ME","ME-04","Bijelo Polje","Municipality","Montenegro",2 +"MNE","ME","ME-05","Budva","Municipality","Montenegro",2 +"MNE","ME","ME-06","Cetinje","Municipality","Montenegro",2 +"MNE","ME","ME-07","Danilovgrad","Municipality","Montenegro",2 +"MNE","ME","ME-08","Herceg-Novi","Municipality","Montenegro",2 +"MNE","ME","ME-09","Kolašin","Municipality","Montenegro",2 +"MNE","ME","ME-10","Kotor","Municipality","Montenegro",2 +"MNE","ME","ME-11","Mojkovac","Municipality","Montenegro",2 +"MNE","ME","ME-12","Nikšić","Municipality","Montenegro",2 +"MNE","ME","ME-13","Plav","Municipality","Montenegro",2 +"MNE","ME","ME-14","Pljevlja","Municipality","Montenegro",2 +"MNE","ME","ME-15","Plužine","Municipality","Montenegro",2 +"MNE","ME","ME-16","Podgorica","Municipality","Montenegro",2 +"MNE","ME","ME-17","Rožaje","Municipality","Montenegro",2 +"MNE","ME","ME-18","Šavnik","Municipality","Montenegro",2 +"MNE","ME","ME-19","Tivat","Municipality","Montenegro",2 +"MNE","ME","ME-20","Ulcinj","Municipality","Montenegro",2 +"MNE","ME","ME-21","Žabljak","Municipality","Montenegro",2 +"MDG","MG","MG-A","Toamasina","Autonomous province","Madagascar",2 +"MDG","MG","MG-D","Antsiranana","Autonomous province","Madagascar",2 +"MDG","MG","MG-F","Fianarantsoa","Autonomous province","Madagascar",2 +"MDG","MG","MG-M","Mahajanga","Autonomous province","Madagascar",2 +"MDG","MG","MG-T","Antananarivo","Autonomous province","Madagascar",2 +"MDG","MG","MG-U","Toliara","Autonomous province","Madagascar",2 +"MHL","MH","MH-ALK","Ailuk","Municipality","Marshall Islands",2 +"MHL","MH","MH-ALL","Ailinglaplap","Municipality","Marshall Islands",2 +"MHL","MH","MH-ARN","Arno","Municipality","Marshall Islands",2 +"MHL","MH","MH-AUR","Aur","Municipality","Marshall Islands",2 +"MHL","MH","MH-EBO","Ebon","Municipality","Marshall Islands",2 +"MHL","MH","MH-ENI","Enewetak","Municipality","Marshall Islands",2 +"MHL","MH","MH-JAB","Jabat","Municipality","Marshall Islands",2 +"MHL","MH","MH-JAL","Jaluit","Municipality","Marshall Islands",2 +"MHL","MH","MH-KIL","Kili","Municipality","Marshall Islands",2 +"MHL","MH","MH-KWA","Kwajalein","Municipality","Marshall Islands",2 +"MHL","MH","MH-L","Ralik chain","Chains (of islands)","Marshall Islands",2 +"MHL","MH","MH-LAE","Lae","Municipality","Marshall Islands",2 +"MHL","MH","MH-LIB","Lib","Municipality","Marshall Islands",2 +"MHL","MH","MH-LIK","Likiep","Municipality","Marshall Islands",2 +"MHL","MH","MH-MAJ","Majuro","Municipality","Marshall Islands",2 +"MHL","MH","MH-MAL","Maloelap","Municipality","Marshall Islands",2 +"MHL","MH","MH-MEJ","Mejit","Municipality","Marshall Islands",2 +"MHL","MH","MH-MIL","Mili","Municipality","Marshall Islands",2 +"MHL","MH","MH-NMK","Namdrik","Municipality","Marshall Islands",2 +"MHL","MH","MH-NMU","Namu","Municipality","Marshall Islands",2 +"MHL","MH","MH-RON","Rongelap","Municipality","Marshall Islands",2 +"MHL","MH","MH-T","Ratak chain","Chains (of islands)","Marshall Islands",2 +"MHL","MH","MH-UJA","Ujae","Municipality","Marshall Islands",2 +"MHL","MH","MH-UTI","Utirik","Municipality","Marshall Islands",2 +"MHL","MH","MH-WTJ","Wotje","Municipality","Marshall Islands",2 +"MHL","MH","MH-WTN","Wotho","Municipality","Marshall Islands",2 +"MKD","MK","MK-01","Aerodrom","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-02","Aračinovo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-03","Berovo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-04","Bitola","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-05","Bogdanci","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-06","Bogovinje","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-07","Bosilovo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-08","Brvenica","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-09","Butel","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-10","Valandovo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-11","Vasilevo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-12","Vevčani","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-13","Veles","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-14","Vinica","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-15","Vraneštica","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-16","Vrapčište","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-17","Gazi Baba","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-18","Gevgelija","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-19","Gostivar","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-20","Gradsko","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-21","Debar","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-22","Debarca","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-23","Delčevo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-24","Demir Kapija","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-25","Demir Hisar","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-26","Dojran","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-27","Dolneni","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-28","Drugovo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-29","Gjorče Petrov","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-30","Želino","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-31","Zajas","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-32","Zelenikovo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-33","Zrnovci","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-34","Ilinden","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-35","Jegunovce","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-36","Kavadarci","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-37","Karbinci","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-38","Karpoš","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-39","Kisela Voda","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-40","Kičevo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-41","Konče","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-42","Kočani","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-43","Kratovo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-44","Kriva Palanka","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-45","Krivogaštani","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-46","Kruševo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-47","Kumanovo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-48","Lipkovo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-49","Lozovo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-50","Mavrovo-i-Rostuša","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-51","Makedonska Kamenica","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-52","Makedonski Brod","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-53","Mogila","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-54","Negotino","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-55","Novaci","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-56","Novo Selo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-57","Oslomej","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-58","Ohrid","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-59","Petrovec","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-60","Pehčevo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-61","Plasnica","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-62","Prilep","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-63","Probištip","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-64","Radoviš","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-65","Rankovce","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-66","Resen","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-67","Rosoman","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-68","Saraj","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-69","Sveti Nikole","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-70","Sopište","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-71","Staro Nagoričane","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-72","Struga","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-73","Strumica","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-74","Studeničani","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-75","Tearce","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-76","Tetovo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-77","Centar","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-78","Centar Župa","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-79","Čair","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-80","Čaška","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-81","Češinovo-Obleševo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-82","Čučer Sandevo","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-83","Štip","Municipality","Macedonia, Republic of",2 +"MKD","MK","MK-84","Šuto Orizari","Municipality","Macedonia, Republic of",2 +"MLI","ML","ML-1","Kayes","Region","Mali",2 +"MLI","ML","ML-2","Koulikoro","Region","Mali",2 +"MLI","ML","ML-3","Sikasso","Region","Mali",2 +"MLI","ML","ML-4","Ségou","Region","Mali",2 +"MLI","ML","ML-5","Mopti","Region","Mali",2 +"MLI","ML","ML-6","Tombouctou","Region","Mali",2 +"MLI","ML","ML-7","Gao","Region","Mali",2 +"MLI","ML","ML-8","Kidal","Region","Mali",2 +"MLI","ML","ML-BK0","Bamako","District","Mali",2 +"MMR","MM","MM-01","Sagaing","Division","Myanmar",2 +"MMR","MM","MM-02","Bago","Division","Myanmar",2 +"MMR","MM","MM-03","Magway","Division","Myanmar",2 +"MMR","MM","MM-04","Mandalay","Division","Myanmar",2 +"MMR","MM","MM-05","Tanintharyi","Division","Myanmar",2 +"MMR","MM","MM-06","Yangon","Division","Myanmar",2 +"MMR","MM","MM-07","Ayeyarwady","Division","Myanmar",2 +"MMR","MM","MM-11","Kachin","State","Myanmar",2 +"MMR","MM","MM-12","Kayah","State","Myanmar",2 +"MMR","MM","MM-13","Kayin","State","Myanmar",2 +"MMR","MM","MM-14","Chin","State","Myanmar",2 +"MMR","MM","MM-15","Mon","State","Myanmar",2 +"MMR","MM","MM-16","Rakhine","State","Myanmar",2 +"MMR","MM","MM-17","Shan","State","Myanmar",2 +"MNG","MN","MN-035","Orhon","Municipality","Mongolia",2 +"MNG","MN","MN-037","Darhan uul","Municipality","Mongolia",2 +"MNG","MN","MN-039","Hentiy","Province","Mongolia",2 +"MNG","MN","MN-041","Hövsgöl","Province","Mongolia",2 +"MNG","MN","MN-043","Hovd","Province","Mongolia",2 +"MNG","MN","MN-046","Uvs","Province","Mongolia",2 +"MNG","MN","MN-047","Töv","Province","Mongolia",2 +"MNG","MN","MN-049","Selenge","Province","Mongolia",2 +"MNG","MN","MN-051","Sühbaatar","Province","Mongolia",2 +"MNG","MN","MN-053","Ömnögovi","Province","Mongolia",2 +"MNG","MN","MN-055","Övörhangay","Province","Mongolia",2 +"MNG","MN","MN-057","Dzavhan","Province","Mongolia",2 +"MNG","MN","MN-059","Dundgovi","Province","Mongolia",2 +"MNG","MN","MN-061","Dornod","Province","Mongolia",2 +"MNG","MN","MN-063","Dornogovi","Province","Mongolia",2 +"MNG","MN","MN-064","Govi-Sumber","Municipality","Mongolia",2 +"MNG","MN","MN-065","Govi-Altay","Province","Mongolia",2 +"MNG","MN","MN-067","Bulgan","Province","Mongolia",2 +"MNG","MN","MN-069","Bayanhongor","Province","Mongolia",2 +"MNG","MN","MN-071","Bayan-Ölgiy","Province","Mongolia",2 +"MNG","MN","MN-073","Arhangay","Province","Mongolia",2 +"MNG","MN","MN-1","Ulanbaatar","Municipality","Mongolia",2 +"MRT","MR","MR-01","Hodh ech Chargui","Region","Mauritania",2 +"MRT","MR","MR-02","Hodh el Charbi","Region","Mauritania",2 +"MRT","MR","MR-03","Assaba","Region","Mauritania",2 +"MRT","MR","MR-04","Gorgol","Region","Mauritania",2 +"MRT","MR","MR-05","Brakna","Region","Mauritania",2 +"MRT","MR","MR-06","Trarza","Region","Mauritania",2 +"MRT","MR","MR-07","Adrar","Region","Mauritania",2 +"MRT","MR","MR-08","Dakhlet Nouadhibou","Region","Mauritania",2 +"MRT","MR","MR-09","Tagant","Region","Mauritania",2 +"MRT","MR","MR-10","Guidimaka","Region","Mauritania",2 +"MRT","MR","MR-11","Tiris Zemmour","Region","Mauritania",2 +"MRT","MR","MR-12","Inchiri","Region","Mauritania",2 +"MRT","MR","MR-NKC","Nouakchott","District","Mauritania",2 +"MLT","MT","MT-01","Attard","Local council","Malta",2 +"MLT","MT","MT-02","Balzan","Local council","Malta",2 +"MLT","MT","MT-03","Birgu","Local council","Malta",2 +"MLT","MT","MT-04","Birkirkara","Local council","Malta",2 +"MLT","MT","MT-05","Birżebbuġa","Local council","Malta",2 +"MLT","MT","MT-06","Bormla","Local council","Malta",2 +"MLT","MT","MT-07","Dingli","Local council","Malta",2 +"MLT","MT","MT-08","Fgura","Local council","Malta",2 +"MLT","MT","MT-09","Floriana","Local council","Malta",2 +"MLT","MT","MT-10","Fontana","Local council","Malta",2 +"MLT","MT","MT-11","Gudja","Local council","Malta",2 +"MLT","MT","MT-12","Gżira","Local council","Malta",2 +"MLT","MT","MT-13","Għajnsielem","Local council","Malta",2 +"MLT","MT","MT-14","Għarb","Local council","Malta",2 +"MLT","MT","MT-15","Għargħur","Local council","Malta",2 +"MLT","MT","MT-16","Għasri","Local council","Malta",2 +"MLT","MT","MT-17","Għaxaq","Local council","Malta",2 +"MLT","MT","MT-18","Ħamrun","Local council","Malta",2 +"MLT","MT","MT-19","Iklin","Local council","Malta",2 +"MLT","MT","MT-20","Isla","Local council","Malta",2 +"MLT","MT","MT-21","Kalkara","Local council","Malta",2 +"MLT","MT","MT-22","Kerċem","Local council","Malta",2 +"MLT","MT","MT-23","Kirkop","Local council","Malta",2 +"MLT","MT","MT-24","Lija","Local council","Malta",2 +"MLT","MT","MT-25","Luqa","Local council","Malta",2 +"MLT","MT","MT-26","Marsa","Local council","Malta",2 +"MLT","MT","MT-27","Marsaskala","Local council","Malta",2 +"MLT","MT","MT-28","Marsaxlokk","Local council","Malta",2 +"MLT","MT","MT-29","Mdina","Local council","Malta",2 +"MLT","MT","MT-30","Mellieħa","Local council","Malta",2 +"MLT","MT","MT-31","Mġarr","Local council","Malta",2 +"MLT","MT","MT-32","Mosta","Local council","Malta",2 +"MLT","MT","MT-33","Mqabba","Local council","Malta",2 +"MLT","MT","MT-34","Msida","Local council","Malta",2 +"MLT","MT","MT-35","Mtarfa","Local council","Malta",2 +"MLT","MT","MT-36","Munxar","Local council","Malta",2 +"MLT","MT","MT-37","Nadur","Local council","Malta",2 +"MLT","MT","MT-38","Naxxar","Local council","Malta",2 +"MLT","MT","MT-39","Paola","Local council","Malta",2 +"MLT","MT","MT-40","Pembroke","Local council","Malta",2 +"MLT","MT","MT-41","Pietà","Local council","Malta",2 +"MLT","MT","MT-42","Qala","Local council","Malta",2 +"MLT","MT","MT-43","Qormi","Local council","Malta",2 +"MLT","MT","MT-44","Qrendi","Local council","Malta",2 +"MLT","MT","MT-45","Rabat Għawdex","Local council","Malta",2 +"MLT","MT","MT-46","Rabat Malta","Local council","Malta",2 +"MLT","MT","MT-47","Safi","Local council","Malta",2 +"MLT","MT","MT-48","San Ġiljan","Local council","Malta",2 +"MLT","MT","MT-49","San Ġwann","Local council","Malta",2 +"MLT","MT","MT-50","San Lawrenz","Local council","Malta",2 +"MLT","MT","MT-51","San Pawl il-Baħar","Local council","Malta",2 +"MLT","MT","MT-52","Sannat","Local council","Malta",2 +"MLT","MT","MT-53","Santa Luċija","Local council","Malta",2 +"MLT","MT","MT-54","Santa Venera","Local council","Malta",2 +"MLT","MT","MT-55","Siġġiewi","Local council","Malta",2 +"MLT","MT","MT-56","Sliema","Local council","Malta",2 +"MLT","MT","MT-57","Swieqi","Local council","Malta",2 +"MLT","MT","MT-58","Ta’ Xbiex","Local council","Malta",2 +"MLT","MT","MT-59","Tarxien","Local council","Malta",2 +"MLT","MT","MT-60","Valletta","Local council","Malta",2 +"MLT","MT","MT-61","Xagħra","Local council","Malta",2 +"MLT","MT","MT-62","Xewkija","Local council","Malta",2 +"MLT","MT","MT-63","Xgħajra","Local council","Malta",2 +"MLT","MT","MT-64","Żabbar","Local council","Malta",2 +"MLT","MT","MT-65","Żebbuġ Għawdex","Local council","Malta",2 +"MLT","MT","MT-66","Żebbuġ Malta","Local council","Malta",2 +"MLT","MT","MT-67","Żejtun","Local council","Malta",2 +"MLT","MT","MT-68","Żurrieq","Local council","Malta",2 +"MUS","MU","MU-AG","Agalega Islands","Dependency","Mauritius",2 +"MUS","MU","MU-BL","Black River","District","Mauritius",2 +"MUS","MU","MU-BR","Beau Bassin-Rose Hill","City","Mauritius",2 +"MUS","MU","MU-CC","Cargados Carajos Shoals","Dependency","Mauritius",2 +"MUS","MU","MU-CU","Curepipe","City","Mauritius",2 +"MUS","MU","MU-FL","Flacq","District","Mauritius",2 +"MUS","MU","MU-GP","Grand Port","District","Mauritius",2 +"MUS","MU","MU-MO","Moka","District","Mauritius",2 +"MUS","MU","MU-PA","Pamplemousses","District","Mauritius",2 +"MUS","MU","MU-PL","Port Louis","District","Mauritius",2 +"MUS","MU","MU-PU","Port Louis","City","Mauritius",2 +"MUS","MU","MU-PW","Plaines Wilhems","District","Mauritius",2 +"MUS","MU","MU-QB","Quatre Bornes","City","Mauritius",2 +"MUS","MU","MU-RO","Rodrigues Island","Dependency","Mauritius",2 +"MUS","MU","MU-RP","Rivière du Rempart","District","Mauritius",2 +"MUS","MU","MU-SA","Savanne","District","Mauritius",2 +"MUS","MU","MU-VP","Vacoas-Phoenix","City","Mauritius",2 +"MDV","MV","MV-00","Alifu Dhaalu","Administrative atoll","Maldives",2 +"MDV","MV","MV-01","Seenu","Administrative atoll","Maldives",2 +"MDV","MV","MV-02","Alifu Alifu","Administrative atoll","Maldives",2 +"MDV","MV","MV-03","Lhaviyani","Administrative atoll","Maldives",2 +"MDV","MV","MV-04","Vaavu","Administrative atoll","Maldives",2 +"MDV","MV","MV-05","Laamu","Administrative atoll","Maldives",2 +"MDV","MV","MV-07","Haa Alifu","Administrative atoll","Maldives",2 +"MDV","MV","MV-08","Thaa","Administrative atoll","Maldives",2 +"MDV","MV","MV-12","Meemu","Administrative atoll","Maldives",2 +"MDV","MV","MV-13","Raa","Administrative atoll","Maldives",2 +"MDV","MV","MV-14","Faafu","Administrative atoll","Maldives",2 +"MDV","MV","MV-17","Dhaalu","Administrative atoll","Maldives",2 +"MDV","MV","MV-20","Baa","Administrative atoll","Maldives",2 +"MDV","MV","MV-23","Haa Dhaalu","Administrative atoll","Maldives",2 +"MDV","MV","MV-24","Shaviyani","Administrative atoll","Maldives",2 +"MDV","MV","MV-25","Noonu","Administrative atoll","Maldives",2 +"MDV","MV","MV-26","Kaafu","Administrative atoll","Maldives",2 +"MDV","MV","MV-27","Gaafu Alifu","Administrative atoll","Maldives",2 +"MDV","MV","MV-28","Gaafu Dhaalu","Administrative atoll","Maldives",2 +"MDV","MV","MV-29","Gnaviyani","Administrative atoll","Maldives",2 +"MDV","MV","MV-CE","Central","Province","Maldives",2 +"MDV","MV","MV-MLE","Male","City","Maldives",2 +"MDV","MV","MV-NC","North Central","Province","Maldives",2 +"MDV","MV","MV-NO","North","Province","Maldives",2 +"MDV","MV","MV-SC","South Central","Province","Maldives",2 +"MDV","MV","MV-SU","South","Province","Maldives",2 +"MDV","MV","MV-UN","Upper North","Province","Maldives",2 +"MDV","MV","MV-US","Upper South","Province","Maldives",2 +"MWI","MW","MW-BA","Balaka","District","Malawi",2 +"MWI","MW","MW-BL","Blantyre","District","Malawi",2 +"MWI","MW","MW-C","Central Region","Region","Malawi",2 +"MWI","MW","MW-CK","Chikwawa","District","Malawi",2 +"MWI","MW","MW-CR","Chiradzulu","District","Malawi",2 +"MWI","MW","MW-CT","Chitipa","District","Malawi",2 +"MWI","MW","MW-DE","Dedza","District","Malawi",2 +"MWI","MW","MW-DO","Dowa","District","Malawi",2 +"MWI","MW","MW-KR","Karonga","District","Malawi",2 +"MWI","MW","MW-KS","Kasungu","District","Malawi",2 +"MWI","MW","MW-LI","Lilongwe","District","Malawi",2 +"MWI","MW","MW-LK","Likoma","District","Malawi",2 +"MWI","MW","MW-MC","Mchinji","District","Malawi",2 +"MWI","MW","MW-MG","Mangochi","District","Malawi",2 +"MWI","MW","MW-MH","Machinga","District","Malawi",2 +"MWI","MW","MW-MU","Mulanje","District","Malawi",2 +"MWI","MW","MW-MW","Mwanza","District","Malawi",2 +"MWI","MW","MW-MZ","Mzimba","District","Malawi",2 +"MWI","MW","MW-N","Northern Region","Region","Malawi",2 +"MWI","MW","MW-NB","Nkhata Bay","District","Malawi",2 +"MWI","MW","MW-NE","Neno","District","Malawi",2 +"MWI","MW","MW-NI","Ntchisi","District","Malawi",2 +"MWI","MW","MW-NK","Nkhotakota","District","Malawi",2 +"MWI","MW","MW-NS","Nsanje","District","Malawi",2 +"MWI","MW","MW-NU","Ntcheu","District","Malawi",2 +"MWI","MW","MW-PH","Phalombe","District","Malawi",2 +"MWI","MW","MW-RU","Rumphi","District","Malawi",2 +"MWI","MW","MW-S","Southern Region","Region","Malawi",2 +"MWI","MW","MW-SA","Salima","District","Malawi",2 +"MWI","MW","MW-TH","Thyolo","District","Malawi",2 +"MWI","MW","MW-ZO","Zomba","District","Malawi",2 +"MEX","MX","MX-AGU","Aguascalientes","State","Mexico",2 +"MEX","MX","MX-BCN","Baja California","State","Mexico",2 +"MEX","MX","MX-BCS","Baja California Sur","State","Mexico",2 +"MEX","MX","MX-CAM","Campeche","State","Mexico",2 +"MEX","MX","MX-CHH","Chihuahua","State","Mexico",2 +"MEX","MX","MX-CHP","Chiapas","State","Mexico",2 +"MEX","MX","MX-COA","Coahuila","State","Mexico",2 +"MEX","MX","MX-COL","Colima","State","Mexico",2 +"MEX","MX","MX-DIF","Distrito Federal","Federal district","Mexico",2 +"MEX","MX","MX-DUR","Durango","State","Mexico",2 +"MEX","MX","MX-GRO","Guerrero","State","Mexico",2 +"MEX","MX","MX-GUA","Guanajuato","State","Mexico",2 +"MEX","MX","MX-HID","Hidalgo","State","Mexico",2 +"MEX","MX","MX-JAL","Jalisco","State","Mexico",2 +"MEX","MX","MX-MEX","México","State","Mexico",2 +"MEX","MX","MX-MIC","Michoacán","State","Mexico",2 +"MEX","MX","MX-MOR","Morelos","State","Mexico",2 +"MEX","MX","MX-NAY","Nayarit","State","Mexico",2 +"MEX","MX","MX-NLE","Nuevo León","State","Mexico",2 +"MEX","MX","MX-OAX","Oaxaca","State","Mexico",2 +"MEX","MX","MX-PUE","Puebla","State","Mexico",2 +"MEX","MX","MX-QUE","Querétaro","State","Mexico",2 +"MEX","MX","MX-ROO","Quintana Roo","State","Mexico",2 +"MEX","MX","MX-SIN","Sinaloa","State","Mexico",2 +"MEX","MX","MX-SLP","San Luis Potosí","State","Mexico",2 +"MEX","MX","MX-SON","Sonora","State","Mexico",2 +"MEX","MX","MX-TAB","Tabasco","State","Mexico",2 +"MEX","MX","MX-TAM","Tamaulipas","State","Mexico",2 +"MEX","MX","MX-TLA","Tlaxcala","State","Mexico",2 +"MEX","MX","MX-VER","Veracruz","State","Mexico",2 +"MEX","MX","MX-YUC","Yucatán","State","Mexico",2 +"MEX","MX","MX-ZAC","Zacatecas","State","Mexico",2 +"MYS","MY","MY-01","Johor","State","Malaysia",2 +"MYS","MY","MY-02","Kedah","State","Malaysia",2 +"MYS","MY","MY-03","Kelantan","State","Malaysia",2 +"MYS","MY","MY-04","Melaka","State","Malaysia",2 +"MYS","MY","MY-05","Negeri Sembilan","State","Malaysia",2 +"MYS","MY","MY-06","Pahang","State","Malaysia",2 +"MYS","MY","MY-07","Pulau Pinang","State","Malaysia",2 +"MYS","MY","MY-08","Perak","State","Malaysia",2 +"MYS","MY","MY-09","Perlis","State","Malaysia",2 +"MYS","MY","MY-10","Selangor","State","Malaysia",2 +"MYS","MY","MY-11","Terengganu","State","Malaysia",2 +"MYS","MY","MY-12","Sabah","State","Malaysia",2 +"MYS","MY","MY-13","Sarawak","State","Malaysia",2 +"MYS","MY","MY-14","Wilayah Persekutuan Kuala Lumpur","Federal Territories","Malaysia",2 +"MYS","MY","MY-15","Wilayah Persekutuan Labuan","Federal Territories","Malaysia",2 +"MYS","MY","MY-16","Wilayah Persekutuan Putrajaya","Federal Territories","Malaysia",2 +"MOZ","MZ","MZ-A","Niassa","Province","Mozambique",2 +"MOZ","MZ","MZ-B","Manica","Province","Mozambique",2 +"MOZ","MZ","MZ-G","Gaza","Province","Mozambique",2 +"MOZ","MZ","MZ-I","Inhambane","Province","Mozambique",2 +"MOZ","MZ","MZ-L","Maputo","Province","Mozambique",2 +"MOZ","MZ","MZ-MPM","Maputo (city)","City","Mozambique",2 +"MOZ","MZ","MZ-N","Numpula","Province","Mozambique",2 +"MOZ","MZ","MZ-P","Cabo Delgado","Province","Mozambique",2 +"MOZ","MZ","MZ-Q","Zambezia","Province","Mozambique",2 +"MOZ","MZ","MZ-S","Sofala","Province","Mozambique",2 +"MOZ","MZ","MZ-T","Tete","Province","Mozambique",2 +"NAM","NA","NA-CA","Caprivi","Region","Namibia",2 +"NAM","NA","NA-ER","Erongo","Region","Namibia",2 +"NAM","NA","NA-HA","Hardap","Region","Namibia",2 +"NAM","NA","NA-KA","Karas","Region","Namibia",2 +"NAM","NA","NA-KH","Khomas","Region","Namibia",2 +"NAM","NA","NA-KU","Kunene","Region","Namibia",2 +"NAM","NA","NA-OD","Otjozondjupa","Region","Namibia",2 +"NAM","NA","NA-OH","Omaheke","Region","Namibia",2 +"NAM","NA","NA-OK","Okavango","Region","Namibia",2 +"NAM","NA","NA-ON","Oshana","Region","Namibia",2 +"NAM","NA","NA-OS","Omusati","Region","Namibia",2 +"NAM","NA","NA-OT","Oshikoto","Region","Namibia",2 +"NAM","NA","NA-OW","Ohangwena","Region","Namibia",2 +"NER","NE","NE-1","Agadez","Department","Niger",2 +"NER","NE","NE-2","Diffa","Department","Niger",2 +"NER","NE","NE-3","Dosso","Department","Niger",2 +"NER","NE","NE-4","Maradi","Department","Niger",2 +"NER","NE","NE-5","Tahoua","Department","Niger",2 +"NER","NE","NE-6","Tillabéri","Department","Niger",2 +"NER","NE","NE-7","Zinder","Department","Niger",2 +"NER","NE","NE-8","Niamey","Capital District","Niger",2 +"NGA","NG","NG-AB","Abia","State","Nigeria",2 +"NGA","NG","NG-AD","Adamawa","State","Nigeria",2 +"NGA","NG","NG-AK","Akwa Ibom","State","Nigeria",2 +"NGA","NG","NG-AN","Anambra","State","Nigeria",2 +"NGA","NG","NG-BA","Bauchi","State","Nigeria",2 +"NGA","NG","NG-BE","Benue","State","Nigeria",2 +"NGA","NG","NG-BO","Borno","State","Nigeria",2 +"NGA","NG","NG-BY","Bayelsa","State","Nigeria",2 +"NGA","NG","NG-CR","Cross River","State","Nigeria",2 +"NGA","NG","NG-DE","Delta","State","Nigeria",2 +"NGA","NG","NG-EB","Ebonyi","State","Nigeria",2 +"NGA","NG","NG-ED","Edo","State","Nigeria",2 +"NGA","NG","NG-EK","Ekiti","State","Nigeria",2 +"NGA","NG","NG-EN","Enugu","State","Nigeria",2 +"NGA","NG","NG-FC","Abuja Capital Territory","Capital Territory","Nigeria",2 +"NGA","NG","NG-GO","Gombe","State","Nigeria",2 +"NGA","NG","NG-IM","Imo","State","Nigeria",2 +"NGA","NG","NG-JI","Jigawa","State","Nigeria",2 +"NGA","NG","NG-KD","Kaduna","State","Nigeria",2 +"NGA","NG","NG-KE","Kebbi","State","Nigeria",2 +"NGA","NG","NG-KN","Kano","State","Nigeria",2 +"NGA","NG","NG-KO","Kogi","State","Nigeria",2 +"NGA","NG","NG-KT","Katsina","State","Nigeria",2 +"NGA","NG","NG-KW","Kwara","State","Nigeria",2 +"NGA","NG","NG-LA","Lagos","State","Nigeria",2 +"NGA","NG","NG-NA","Nassarawa","State","Nigeria",2 +"NGA","NG","NG-NI","Niger","State","Nigeria",2 +"NGA","NG","NG-OG","Ogun","State","Nigeria",2 +"NGA","NG","NG-ON","Ondo","State","Nigeria",2 +"NGA","NG","NG-OS","Osun","State","Nigeria",2 +"NGA","NG","NG-OY","Oyo","State","Nigeria",2 +"NGA","NG","NG-PL","Plateau","State","Nigeria",2 +"NGA","NG","NG-RI","Rivers","State","Nigeria",2 +"NGA","NG","NG-SO","Sokoto","State","Nigeria",2 +"NGA","NG","NG-TA","Taraba","State","Nigeria",2 +"NGA","NG","NG-YO","Yobe","State","Nigeria",2 +"NGA","NG","NG-ZA","Zamfara","State","Nigeria",2 +"NIC","NI","NI-AN","Atlántico Norte","Autonomous Region","Nicaragua",2 +"NIC","NI","NI-AS","Atlántico Sur","Autonomous Region","Nicaragua",2 +"NIC","NI","NI-BO","Boaco","Department","Nicaragua",2 +"NIC","NI","NI-CA","Carazo","Department","Nicaragua",2 +"NIC","NI","NI-CI","Chinandega","Department","Nicaragua",2 +"NIC","NI","NI-CO","Chontales","Department","Nicaragua",2 +"NIC","NI","NI-ES","Estelí","Department","Nicaragua",2 +"NIC","NI","NI-GR","Granada","Department","Nicaragua",2 +"NIC","NI","NI-JI","Jinotega","Department","Nicaragua",2 +"NIC","NI","NI-LE","León","Department","Nicaragua",2 +"NIC","NI","NI-MD","Madriz","Department","Nicaragua",2 +"NIC","NI","NI-MN","Managua","Department","Nicaragua",2 +"NIC","NI","NI-MS","Masaya","Department","Nicaragua",2 +"NIC","NI","NI-MT","Matagalpa","Department","Nicaragua",2 +"NIC","NI","NI-NS","Nueva Segovia","Department","Nicaragua",2 +"NIC","NI","NI-RI","Rivas","Department","Nicaragua",2 +"NIC","NI","NI-SJ","Río San Juan","Department","Nicaragua",2 +"NLD","NL","NL-AW","Aruba","Country","Netherlands",2 +"NLD","NL","NL-BQ1","Bonaire","Special municipality","Netherlands",2 +"NLD","NL","NL-BQ2","Saba","Special municipality","Netherlands",2 +"NLD","NL","NL-BQ3","Sint Eustatius","Special municipality","Netherlands",2 +"NLD","NL","NL-CW","Curaçao","Country","Netherlands",2 +"NLD","NL","NL-DR","Drenthe","Province","Netherlands",2 +"NLD","NL","NL-FL","Flevoland","Province","Netherlands",2 +"NLD","NL","NL-FR","Friesland","Province","Netherlands",2 +"NLD","NL","NL-GE","Gelderland","Province","Netherlands",2 +"NLD","NL","NL-GR","Groningen","Province","Netherlands",2 +"NLD","NL","NL-LI","Limburg","Province","Netherlands",2 +"NLD","NL","NL-NB","Noord-Brabant","Province","Netherlands",2 +"NLD","NL","NL-NH","Noord-Holland","Province","Netherlands",2 +"NLD","NL","NL-OV","Overijssel","Province","Netherlands",2 +"NLD","NL","NL-SX","Sint Maarten","Country","Netherlands",2 +"NLD","NL","NL-UT","Utrecht","Province","Netherlands",2 +"NLD","NL","NL-ZE","Zeeland","Province","Netherlands",2 +"NLD","NL","NL-ZH","Zuid-Holland","Province","Netherlands",2 +"NOR","NO","NO-01","Østfold","County","Norway",2 +"NOR","NO","NO-02","Akershus","County","Norway",2 +"NOR","NO","NO-03","Oslo","County","Norway",2 +"NOR","NO","NO-04","Hedmark","County","Norway",2 +"NOR","NO","NO-05","Oppland","County","Norway",2 +"NOR","NO","NO-06","Buskerud","County","Norway",2 +"NOR","NO","NO-07","Vestfold","County","Norway",2 +"NOR","NO","NO-08","Telemark","County","Norway",2 +"NOR","NO","NO-09","Aust-Agder","County","Norway",2 +"NOR","NO","NO-10","Vest-Agder","County","Norway",2 +"NOR","NO","NO-11","Rogaland","County","Norway",2 +"NOR","NO","NO-12","Hordaland","County","Norway",2 +"NOR","NO","NO-14","Sogn og Fjordane","County","Norway",2 +"NOR","NO","NO-15","Møre og Romsdal","County","Norway",2 +"NOR","NO","NO-16","Sør-Trøndelag","County","Norway",2 +"NOR","NO","NO-17","Nord-Trøndelag","County","Norway",2 +"NOR","NO","NO-18","Nordland","County","Norway",2 +"NOR","NO","NO-19","Troms","County","Norway",2 +"NOR","NO","NO-20","Finnmark","County","Norway",2 +"NOR","NO","NO-21","Svalbard (Arctic Region)","Arctic Region","Norway",2 +"NOR","NO","NO-22","Jan Mayen (Arctic Region)","Arctic Region","Norway",2 +"NPL","NP","NP-1","Madhyamanchal","Development region","Nepal",2 +"NPL","NP","NP-2","Madhya Pashchimanchal","Development region","Nepal",2 +"NPL","NP","NP-3","Pashchimanchal","Development region","Nepal",2 +"NPL","NP","NP-4","Purwanchal","Development region","Nepal",2 +"NPL","NP","NP-5","Sudur Pashchimanchal","Development region","Nepal",2 +"NPL","NP","NP-BA","Bagmati","zone","Nepal",2 +"NPL","NP","NP-BH","Bheri","zone","Nepal",2 +"NPL","NP","NP-DH","Dhawalagiri","zone","Nepal",2 +"NPL","NP","NP-GA","Gandaki","zone","Nepal",2 +"NPL","NP","NP-JA","Janakpur","zone","Nepal",2 +"NPL","NP","NP-KA","Karnali","zone","Nepal",2 +"NPL","NP","NP-KO","Kosi","zone","Nepal",2 +"NPL","NP","NP-LU","Lumbini","zone","Nepal",2 +"NPL","NP","NP-MA","Mahakali","zone","Nepal",2 +"NPL","NP","NP-ME","Mechi","zone","Nepal",2 +"NPL","NP","NP-NA","Narayani","zone","Nepal",2 +"NPL","NP","NP-RA","Rapti","zone","Nepal",2 +"NPL","NP","NP-SA","Sagarmatha","zone","Nepal",2 +"NPL","NP","NP-SE","Seti","zone","Nepal",2 +"NRU","NR","NR-01","Aiwo","District","Nauru",2 +"NRU","NR","NR-02","Anabar","District","Nauru",2 +"NRU","NR","NR-03","Anetan","District","Nauru",2 +"NRU","NR","NR-04","Anibare","District","Nauru",2 +"NRU","NR","NR-05","Baiti","District","Nauru",2 +"NRU","NR","NR-06","Boe","District","Nauru",2 +"NRU","NR","NR-07","Buada","District","Nauru",2 +"NRU","NR","NR-08","Denigomodu","District","Nauru",2 +"NRU","NR","NR-09","Ewa","District","Nauru",2 +"NRU","NR","NR-10","Ijuw","District","Nauru",2 +"NRU","NR","NR-11","Meneng","District","Nauru",2 +"NRU","NR","NR-12","Nibok","District","Nauru",2 +"NRU","NR","NR-13","Uaboe","District","Nauru",2 +"NRU","NR","NR-14","Yaren","District","Nauru",2 +"NZL","NZ","NZ-AUK","Auckland","Regional council","New Zealand",2 +"NZL","NZ","NZ-BOP","Bay of Plenty","Regional council","New Zealand",2 +"NZL","NZ","NZ-CAN","Canterbury","Regional council","New Zealand",2 +"NZL","NZ","NZ-CIT","Chatham Islands Territory","Special island authority","New Zealand",2 +"NZL","NZ","NZ-GIS","Gisborne District","Unitary authority","New Zealand",2 +"NZL","NZ","NZ-HKB","Hawke's Bay","Regional council","New Zealand",2 +"NZL","NZ","NZ-MBH","Marlborough District","Unitary authority","New Zealand",2 +"NZL","NZ","NZ-MWT","Manawatu-Wanganui","Regional council","New Zealand",2 +"NZL","NZ","NZ-N","North Island","Island","New Zealand",2 +"NZL","NZ","NZ-NSN","Nelson City","Unitary authority","New Zealand",2 +"NZL","NZ","NZ-NTL","Northland","Regional council","New Zealand",2 +"NZL","NZ","NZ-OTA","Otago","Regional council","New Zealand",2 +"NZL","NZ","NZ-S","South Island","Island","New Zealand",2 +"NZL","NZ","NZ-STL","Southland","Regional council","New Zealand",2 +"NZL","NZ","NZ-TAS","Tasman District","Unitary authority","New Zealand",2 +"NZL","NZ","NZ-TKI","Taranaki","Regional council","New Zealand",2 +"NZL","NZ","NZ-WGN","Wellington","Regional council","New Zealand",2 +"NZL","NZ","NZ-WKO","Waikato","Regional council","New Zealand",2 +"NZL","NZ","NZ-WTC","West Coast","Regional council","New Zealand",2 +"OMN","OM","OM-BA","Al Bāţinah","Region","Oman",2 +"OMN","OM","OM-BU","Al Buraymī","Governorate","Oman",2 +"OMN","OM","OM-DA","Ad Dākhilīya","Region","Oman",2 +"OMN","OM","OM-MA","Masqaţ","Governorate","Oman",2 +"OMN","OM","OM-MU","Musandam","Governorate","Oman",2 +"OMN","OM","OM-SH","Ash Sharqīyah","Region","Oman",2 +"OMN","OM","OM-WU","Al Wusţá","Region","Oman",2 +"OMN","OM","OM-ZA","Az̧ Z̧āhirah","Region","Oman",2 +"OMN","OM","OM-ZU","Z̧ufār","Governorate","Oman",2 +"PAN","PA","PA-1","Bocas del Toro","Province","Panama",2 +"PAN","PA","PA-2","Coclé","Province","Panama",2 +"PAN","PA","PA-3","Colón","Province","Panama",2 +"PAN","PA","PA-4","Chiriquí","Province","Panama",2 +"PAN","PA","PA-5","Darién","Province","Panama",2 +"PAN","PA","PA-6","Herrera","Province","Panama",2 +"PAN","PA","PA-7","Los Santos","Province","Panama",2 +"PAN","PA","PA-8","Panamá","Province","Panama",2 +"PAN","PA","PA-9","Veraguas","Province","Panama",2 +"PAN","PA","PA-EM","Emberá","Indigenous region","Panama",2 +"PAN","PA","PA-KY","Kuna Yala","Indigenous region","Panama",2 +"PAN","PA","PA-NB","Ngöbe-Buglé","Indigenous region","Panama",2 +"PER","PE","PE-AMA","Amazonas","Region","Peru",2 +"PER","PE","PE-ANC","Ancash","Region","Peru",2 +"PER","PE","PE-APU","Apurímac","Region","Peru",2 +"PER","PE","PE-ARE","Arequipa","Region","Peru",2 +"PER","PE","PE-AYA","Ayacucho","Region","Peru",2 +"PER","PE","PE-CAJ","Cajamarca","Region","Peru",2 +"PER","PE","PE-CAL","El Callao","Constitutional province","Peru",2 +"PER","PE","PE-CUS","Cusco [Cuzco]","Region","Peru",2 +"PER","PE","PE-HUC","Huánuco","Region","Peru",2 +"PER","PE","PE-HUV","Huancavelica","Region","Peru",2 +"PER","PE","PE-ICA","Ica","Region","Peru",2 +"PER","PE","PE-JUN","Junín","Region","Peru",2 +"PER","PE","PE-LAL","La Libertad","Region","Peru",2 +"PER","PE","PE-LAM","Lambayeque","Region","Peru",2 +"PER","PE","PE-LIM","Lima","Region","Peru",2 +"PER","PE","PE-LMA","Municipalidad Metropolitana de Lima","Municipality","Peru",2 +"PER","PE","PE-LOR","Loreto","Region","Peru",2 +"PER","PE","PE-MDD","Madre de Dios","Region","Peru",2 +"PER","PE","PE-MOQ","Moquegua","Region","Peru",2 +"PER","PE","PE-PAS","Pasco","Region","Peru",2 +"PER","PE","PE-PIU","Piura","Region","Peru",2 +"PER","PE","PE-PUN","Puno","Region","Peru",2 +"PER","PE","PE-SAM","San Martín","Region","Peru",2 +"PER","PE","PE-TAC","Tacna","Region","Peru",2 +"PER","PE","PE-TUM","Tumbes","Region","Peru",2 +"PER","PE","PE-UCA","Ucayali","Region","Peru",2 +"PNG","PG","PG-CPK","Chimbu","Province","Papua New Guinea",2 +"PNG","PG","PG-CPM","Central","Province","Papua New Guinea",2 +"PNG","PG","PG-EBR","East New Britain","Province","Papua New Guinea",2 +"PNG","PG","PG-EHG","Eastern Highlands","Province","Papua New Guinea",2 +"PNG","PG","PG-EPW","Enga","Province","Papua New Guinea",2 +"PNG","PG","PG-ESW","East Sepik","Province","Papua New Guinea",2 +"PNG","PG","PG-GPK","Gulf","Province","Papua New Guinea",2 +"PNG","PG","PG-MBA","Milne Bay","Province","Papua New Guinea",2 +"PNG","PG","PG-MPL","Morobe","Province","Papua New Guinea",2 +"PNG","PG","PG-MPM","Madang","Province","Papua New Guinea",2 +"PNG","PG","PG-MRL","Manus","Province","Papua New Guinea",2 +"PNG","PG","PG-NCD","National Capital District (Port Moresby)","District","Papua New Guinea",2 +"PNG","PG","PG-NIK","New Ireland","Province","Papua New Guinea",2 +"PNG","PG","PG-NPP","Northern","Province","Papua New Guinea",2 +"PNG","PG","PG-NSB","Bougainville","Autonomous region","Papua New Guinea",2 +"PNG","PG","PG-SAN","Sandaun","Province","Papua New Guinea",2 +"PNG","PG","PG-SHM","Southern Highlands","Province","Papua New Guinea",2 +"PNG","PG","PG-WBK","West New Britain","Province","Papua New Guinea",2 +"PNG","PG","PG-WHM","Western Highlands","Province","Papua New Guinea",2 +"PNG","PG","PG-WPD","Western","Province","Papua New Guinea",2 +"PHL","PH","PH-00","National Capital Region","Region","Philippines",2 +"PHL","PH","PH-01","Ilocos (Region I)","Region","Philippines",2 +"PHL","PH","PH-02","Cagayan Valley (Region II)","Region","Philippines",2 +"PHL","PH","PH-03","Central Luzon (Region III)","Region","Philippines",2 +"PHL","PH","PH-05","Bicol (Region V)","Region","Philippines",2 +"PHL","PH","PH-06","Western Visayas (Region VI)","Region","Philippines",2 +"PHL","PH","PH-07","Central Visayas (Region VII)","Region","Philippines",2 +"PHL","PH","PH-08","Eastern Visayas (Region VIII)","Region","Philippines",2 +"PHL","PH","PH-09","Zamboanga Peninsula (Region IX)","Region","Philippines",2 +"PHL","PH","PH-10","Northern Mindanao (Region X)","Region","Philippines",2 +"PHL","PH","PH-11","Davao (Region XI)","Region","Philippines",2 +"PHL","PH","PH-12","Soccsksargen (Region XII)","Region","Philippines",2 +"PHL","PH","PH-13","Caraga (Region XIII)","Region","Philippines",2 +"PHL","PH","PH-14","Autonomous Region in Muslim Mindanao (ARMM)","Region","Philippines",2 +"PHL","PH","PH-15","Cordillera Administrative Region (CAR)","Region","Philippines",2 +"PHL","PH","PH-40","CALABARZON (Region IV-A)","Region","Philippines",2 +"PHL","PH","PH-41","MIMAROPA (Region IV-B)","Region","Philippines",2 +"PHL","PH","PH-ABR","Abra","Province","Philippines",2 +"PHL","PH","PH-AGN","Agusan del Norte","Province","Philippines",2 +"PHL","PH","PH-AGS","Agusan del Sur","Province","Philippines",2 +"PHL","PH","PH-AKL","Aklan","Province","Philippines",2 +"PHL","PH","PH-ALB","Albay","Province","Philippines",2 +"PHL","PH","PH-ANT","Antique","Province","Philippines",2 +"PHL","PH","PH-APA","Apayao","Province","Philippines",2 +"PHL","PH","PH-AUR","Aurora","Province","Philippines",2 +"PHL","PH","PH-BAN","Batasn","Province","Philippines",2 +"PHL","PH","PH-BAS","Basilan","Province","Philippines",2 +"PHL","PH","PH-BEN","Benguet","Province","Philippines",2 +"PHL","PH","PH-BIL","Biliran","Province","Philippines",2 +"PHL","PH","PH-BOH","Bohol","Province","Philippines",2 +"PHL","PH","PH-BTG","Batangas","Province","Philippines",2 +"PHL","PH","PH-BTN","Batanes","Province","Philippines",2 +"PHL","PH","PH-BUK","Bukidnon","Province","Philippines",2 +"PHL","PH","PH-BUL","Bulacan","Province","Philippines",2 +"PHL","PH","PH-CAG","Cagayan","Province","Philippines",2 +"PHL","PH","PH-CAM","Camiguin","Province","Philippines",2 +"PHL","PH","PH-CAN","Camarines Norte","Province","Philippines",2 +"PHL","PH","PH-CAP","Capiz","Province","Philippines",2 +"PHL","PH","PH-CAS","Camarines Sur","Province","Philippines",2 +"PHL","PH","PH-CAT","Catanduanes","Province","Philippines",2 +"PHL","PH","PH-CAV","Cavite","Province","Philippines",2 +"PHL","PH","PH-CEB","Cebu","Province","Philippines",2 +"PHL","PH","PH-COM","Compostela Valley","Province","Philippines",2 +"PHL","PH","PH-DAO","Davao Oriental","Province","Philippines",2 +"PHL","PH","PH-DAS","Davao del Sur","Province","Philippines",2 +"PHL","PH","PH-DAV","Davao del Norte","Province","Philippines",2 +"PHL","PH","PH-DIN","Dinagat Islands","Province","Philippines",2 +"PHL","PH","PH-EAS","Eastern Samar","Province","Philippines",2 +"PHL","PH","PH-GUI","Guimaras","Province","Philippines",2 +"PHL","PH","PH-IFU","Ifugao","Province","Philippines",2 +"PHL","PH","PH-ILI","Iloilo","Province","Philippines",2 +"PHL","PH","PH-ILN","Ilocos Norte","Province","Philippines",2 +"PHL","PH","PH-ILS","Ilocos Sur","Province","Philippines",2 +"PHL","PH","PH-ISA","Isabela","Province","Philippines",2 +"PHL","PH","PH-KAL","Kalinga-Apayso","Province","Philippines",2 +"PHL","PH","PH-LAG","Laguna","Province","Philippines",2 +"PHL","PH","PH-LAN","Lanao del Norte","Province","Philippines",2 +"PHL","PH","PH-LAS","Lanao del Sur","Province","Philippines",2 +"PHL","PH","PH-LEY","Leyte","Province","Philippines",2 +"PHL","PH","PH-LUN","La Union","Province","Philippines",2 +"PHL","PH","PH-MAD","Marinduque","Province","Philippines",2 +"PHL","PH","PH-MAG","Maguindanao","Province","Philippines",2 +"PHL","PH","PH-MAS","Masbate","Province","Philippines",2 +"PHL","PH","PH-MDC","Mindoro Occidental","Province","Philippines",2 +"PHL","PH","PH-MDR","Mindoro Oriental","Province","Philippines",2 +"PHL","PH","PH-MOU","Mountain Province","Province","Philippines",2 +"PHL","PH","PH-MSC","Misamis Occidental","Province","Philippines",2 +"PHL","PH","PH-MSR","Misamis Oriental","Province","Philippines",2 +"PHL","PH","PH-NCO","North Cotabato","Province","Philippines",2 +"PHL","PH","PH-NEC","Negros Occidental","Province","Philippines",2 +"PHL","PH","PH-NER","Negros Oriental","Province","Philippines",2 +"PHL","PH","PH-NSA","Northern Samar","Province","Philippines",2 +"PHL","PH","PH-NUE","Nueva Ecija","Province","Philippines",2 +"PHL","PH","PH-NUV","Nueva Vizcaya","Province","Philippines",2 +"PHL","PH","PH-PAM","Pampanga","Province","Philippines",2 +"PHL","PH","PH-PAN","Pangasinan","Province","Philippines",2 +"PHL","PH","PH-PLW","Palawan","Province","Philippines",2 +"PHL","PH","PH-QUE","Quezon","Province","Philippines",2 +"PHL","PH","PH-QUI","Quirino","Province","Philippines",2 +"PHL","PH","PH-RIZ","Rizal","Province","Philippines",2 +"PHL","PH","PH-ROM","Romblon","Province","Philippines",2 +"PHL","PH","PH-SAR","Sarangani","Province","Philippines",2 +"PHL","PH","PH-SCO","South Cotabato","Province","Philippines",2 +"PHL","PH","PH-SIG","Siquijor","Province","Philippines",2 +"PHL","PH","PH-SLE","Southern Leyte","Province","Philippines",2 +"PHL","PH","PH-SLU","Sulu","Province","Philippines",2 +"PHL","PH","PH-SOR","Sorsogon","Province","Philippines",2 +"PHL","PH","PH-SUK","Sultan Kudarat","Province","Philippines",2 +"PHL","PH","PH-SUN","Surigao del Norte","Province","Philippines",2 +"PHL","PH","PH-SUR","Surigao del Sur","Province","Philippines",2 +"PHL","PH","PH-TAR","Tarlac","Province","Philippines",2 +"PHL","PH","PH-TAW","Tawi-Tawi","Province","Philippines",2 +"PHL","PH","PH-WSA","Western Samar","Province","Philippines",2 +"PHL","PH","PH-ZAN","Zamboanga del Norte","Province","Philippines",2 +"PHL","PH","PH-ZAS","Zamboanga del Sur","Province","Philippines",2 +"PHL","PH","PH-ZMB","Zambales","Province","Philippines",2 +"PHL","PH","PH-ZSI","Zamboanga Sibugay","Province","Philippines",2 +"PAK","PK","PK-BA","Balochistan","Province","Pakistan",2 +"PAK","PK","PK-GB","Gilgit-Baltistan","Area","Pakistan",2 +"PAK","PK","PK-IS","Islamabad","Capital territory","Pakistan",2 +"PAK","PK","PK-JK","Azad Kashmir","Area","Pakistan",2 +"PAK","PK","PK-KP","Khyber Pakhtunkhwa","Province","Pakistan",2 +"PAK","PK","PK-PB","Punjab","Province","Pakistan",2 +"PAK","PK","PK-SD","Sindh","Province","Pakistan",2 +"PAK","PK","PK-TA","Federally Administered Tribal Areas","Territory","Pakistan",2 +"POL","PL","PL-DS","Dolnośląskie","Province","Poland",2 +"POL","PL","PL-KP","Kujawsko-pomorskie","Province","Poland",2 +"POL","PL","PL-LB","Lubuskie","Province","Poland",2 +"POL","PL","PL-LD","Łódzkie","Province","Poland",2 +"POL","PL","PL-LU","Lubelskie","Province","Poland",2 +"POL","PL","PL-MA","Małopolskie","Province","Poland",2 +"POL","PL","PL-MZ","Mazowieckie","Province","Poland",2 +"POL","PL","PL-OP","Opolskie","Province","Poland",2 +"POL","PL","PL-PD","Podlaskie","Province","Poland",2 +"POL","PL","PL-PK","Podkarpackie","Province","Poland",2 +"POL","PL","PL-PM","Pomorskie","Province","Poland",2 +"POL","PL","PL-SK","Świętokrzyskie","Province","Poland",2 +"POL","PL","PL-SL","Śląskie","Province","Poland",2 +"POL","PL","PL-WN","Warmińsko-mazurskie","Province","Poland",2 +"POL","PL","PL-WP","Wielkopolskie","Province","Poland",2 +"POL","PL","PL-ZP","Zachodniopomorskie","Province","Poland",2 +"PSE","PS","PS-BTH","Bethlehem","Governorate","Palestine, State of",2 +"PSE","PS","PS-DEB","Deir El Balah","Governorate","Palestine, State of",2 +"PSE","PS","PS-GZA","Gaza","Governorate","Palestine, State of",2 +"PSE","PS","PS-HBN","Hebron","Governorate","Palestine, State of",2 +"PSE","PS","PS-JEM","Jerusalem","Governorate","Palestine, State of",2 +"PSE","PS","PS-JEN","Jenin","Governorate","Palestine, State of",2 +"PSE","PS","PS-JRH","Jericho - Al Aghwar","Governorate","Palestine, State of",2 +"PSE","PS","PS-KYS","Khan Yunis","Governorate","Palestine, State of",2 +"PSE","PS","PS-NBS","Nablus","Governorate","Palestine, State of",2 +"PSE","PS","PS-NGZ","North Gaza","Governorate","Palestine, State of",2 +"PSE","PS","PS-QQA","Qalqilya","Governorate","Palestine, State of",2 +"PSE","PS","PS-RBH","Ramallah","Governorate","Palestine, State of",2 +"PSE","PS","PS-RFH","Rafah","Governorate","Palestine, State of",2 +"PSE","PS","PS-SLT","Salfit","Governorate","Palestine, State of",2 +"PSE","PS","PS-TBS","Tubas","Governorate","Palestine, State of",2 +"PSE","PS","PS-TKM","Tulkarm","Governorate","Palestine, State of",2 +"PRT","PT","PT-01","Aveiro","District","Portugal",2 +"PRT","PT","PT-02","Beja","District","Portugal",2 +"PRT","PT","PT-03","Braga","District","Portugal",2 +"PRT","PT","PT-04","Bragança","District","Portugal",2 +"PRT","PT","PT-05","Castelo Branco","District","Portugal",2 +"PRT","PT","PT-06","Coimbra","District","Portugal",2 +"PRT","PT","PT-07","Évora","District","Portugal",2 +"PRT","PT","PT-08","Faro","District","Portugal",2 +"PRT","PT","PT-09","Guarda","District","Portugal",2 +"PRT","PT","PT-10","Leiria","District","Portugal",2 +"PRT","PT","PT-11","Lisboa","District","Portugal",2 +"PRT","PT","PT-12","Portalegre","District","Portugal",2 +"PRT","PT","PT-13","Porto","District","Portugal",2 +"PRT","PT","PT-14","Santarém","District","Portugal",2 +"PRT","PT","PT-15","Setúbal","District","Portugal",2 +"PRT","PT","PT-16","Viana do Castelo","District","Portugal",2 +"PRT","PT","PT-17","Vila Real","District","Portugal",2 +"PRT","PT","PT-18","Viseu","District","Portugal",2 +"PRT","PT","PT-20","Região Autónoma dos Açores","Autonomous region","Portugal",2 +"PRT","PT","PT-30","Região Autónoma da Madeira","Autonomous region","Portugal",2 +"PLW","PW","PW-002","Aimeliik","State","Palau",2 +"PLW","PW","PW-004","Airai","State","Palau",2 +"PLW","PW","PW-010","Angaur","State","Palau",2 +"PLW","PW","PW-050","Hatobohei","State","Palau",2 +"PLW","PW","PW-100","Kayangel","State","Palau",2 +"PLW","PW","PW-150","Koror","State","Palau",2 +"PLW","PW","PW-212","Melekeok","State","Palau",2 +"PLW","PW","PW-214","Ngaraard","State","Palau",2 +"PLW","PW","PW-218","Ngarchelong","State","Palau",2 +"PLW","PW","PW-222","Ngardmau","State","Palau",2 +"PLW","PW","PW-224","Ngatpang","State","Palau",2 +"PLW","PW","PW-226","Ngchesar","State","Palau",2 +"PLW","PW","PW-227","Ngeremlengui","State","Palau",2 +"PLW","PW","PW-228","Ngiwal","State","Palau",2 +"PLW","PW","PW-350","Peleliu","State","Palau",2 +"PLW","PW","PW-370","Sonsorol","State","Palau",2 +"PRY","PY","PY-1","Concepción","Department","Paraguay",2 +"PRY","PY","PY-10","Alto Paraná","Department","Paraguay",2 +"PRY","PY","PY-11","Central","Department","Paraguay",2 +"PRY","PY","PY-12","Ñeembucú","Department","Paraguay",2 +"PRY","PY","PY-13","Amambay","Department","Paraguay",2 +"PRY","PY","PY-14","Canindeyú","Department","Paraguay",2 +"PRY","PY","PY-15","Presidente Hayes","Department","Paraguay",2 +"PRY","PY","PY-16","Alto Paraguay","Department","Paraguay",2 +"PRY","PY","PY-19","Boquerón","Department","Paraguay",2 +"PRY","PY","PY-2","San Pedro","Department","Paraguay",2 +"PRY","PY","PY-3","Cordillera","Department","Paraguay",2 +"PRY","PY","PY-4","Guairá","Department","Paraguay",2 +"PRY","PY","PY-5","Caaguazú","Department","Paraguay",2 +"PRY","PY","PY-6","Caazapá","Department","Paraguay",2 +"PRY","PY","PY-7","Itapúa","Department","Paraguay",2 +"PRY","PY","PY-8","Misiones","Department","Paraguay",2 +"PRY","PY","PY-9","Paraguarí","Department","Paraguay",2 +"PRY","PY","PY-ASU","Asunción","Capital district","Paraguay",2 +"QAT","QA","QA-DA","Ad Dawhah","Municipality","Qatar",2 +"QAT","QA","QA-KH","Al Khawr wa adh Dhakhīrah","Municipality","Qatar",2 +"QAT","QA","QA-MS","Ash Shamal","Municipality","Qatar",2 +"QAT","QA","QA-RA","Ar Rayyan","Municipality","Qatar",2 +"QAT","QA","QA-US","Umm Salal","Municipality","Qatar",2 +"QAT","QA","QA-WA","Al Wakrah","Municipality","Qatar",2 +"QAT","QA","QA-ZA","Az̧ Z̧a‘āyin","Municipality","Qatar",2 +"ROU","RO","RO-AB","Alba","Department","Romania",2 +"ROU","RO","RO-AG","Argeș","Department","Romania",2 +"ROU","RO","RO-AR","Arad","Department","Romania",2 +"ROU","RO","RO-B","București","Municipality","Romania",2 +"ROU","RO","RO-BC","Bacău","Department","Romania",2 +"ROU","RO","RO-BH","Bihor","Department","Romania",2 +"ROU","RO","RO-BN","Bistrița-Năsăud","Department","Romania",2 +"ROU","RO","RO-BR","Brăila","Department","Romania",2 +"ROU","RO","RO-BT","Botoșani","Department","Romania",2 +"ROU","RO","RO-BV","Brașov","Department","Romania",2 +"ROU","RO","RO-BZ","Buzău","Department","Romania",2 +"ROU","RO","RO-CJ","Cluj","Department","Romania",2 +"ROU","RO","RO-CL","Călărași","Department","Romania",2 +"ROU","RO","RO-CS","Caraș-Severin","Department","Romania",2 +"ROU","RO","RO-CT","Constanța","Department","Romania",2 +"ROU","RO","RO-CV","Covasna","Department","Romania",2 +"ROU","RO","RO-DB","Dâmbovița","Department","Romania",2 +"ROU","RO","RO-DJ","Dolj","Department","Romania",2 +"ROU","RO","RO-GJ","Gorj","Department","Romania",2 +"ROU","RO","RO-GL","Galați","Department","Romania",2 +"ROU","RO","RO-GR","Giurgiu","Department","Romania",2 +"ROU","RO","RO-HD","Hunedoara","Department","Romania",2 +"ROU","RO","RO-HR","Harghita","Department","Romania",2 +"ROU","RO","RO-IF","Ilfov","Department","Romania",2 +"ROU","RO","RO-IL","Ialomița","Department","Romania",2 +"ROU","RO","RO-IS","Iași","Department","Romania",2 +"ROU","RO","RO-MH","Mehedinți","Department","Romania",2 +"ROU","RO","RO-MM","Maramureș","Department","Romania",2 +"ROU","RO","RO-MS","Mureș","Department","Romania",2 +"ROU","RO","RO-NT","Neamț","Department","Romania",2 +"ROU","RO","RO-OT","Olt","Department","Romania",2 +"ROU","RO","RO-PH","Prahova","Department","Romania",2 +"ROU","RO","RO-SB","Sibiu","Department","Romania",2 +"ROU","RO","RO-SJ","Sălaj","Department","Romania",2 +"ROU","RO","RO-SM","Satu Mare","Department","Romania",2 +"ROU","RO","RO-SV","Suceava","Department","Romania",2 +"ROU","RO","RO-TL","Tulcea","Department","Romania",2 +"ROU","RO","RO-TM","Timiș","Department","Romania",2 +"ROU","RO","RO-TR","Teleorman","Department","Romania",2 +"ROU","RO","RO-VL","Vâlcea","Department","Romania",2 +"ROU","RO","RO-VN","Vrancea","Department","Romania",2 +"ROU","RO","RO-VS","Vaslui","Department","Romania",2 +"SRB","RS","RS-00","Beograd","City","Serbia",2 +"SRB","RS","RS-01","Severnobački okrug","District","Serbia",2 +"SRB","RS","RS-02","Srednjebanatski okrug","District","Serbia",2 +"SRB","RS","RS-03","Severnobanatski okrug","District","Serbia",2 +"SRB","RS","RS-04","Južnobanatski okrug","District","Serbia",2 +"SRB","RS","RS-05","Zapadnobački okrug","District","Serbia",2 +"SRB","RS","RS-06","Južnobački okrug","District","Serbia",2 +"SRB","RS","RS-07","Sremski okrug","District","Serbia",2 +"SRB","RS","RS-08","Mačvanski okrug","District","Serbia",2 +"SRB","RS","RS-09","Kolubarski okrug","District","Serbia",2 +"SRB","RS","RS-10","Podunavski okrug","District","Serbia",2 +"SRB","RS","RS-11","Braničevski okrug","District","Serbia",2 +"SRB","RS","RS-12","Šumadijski okrug","District","Serbia",2 +"SRB","RS","RS-13","Pomoravski okrug","District","Serbia",2 +"SRB","RS","RS-14","Borski okrug","District","Serbia",2 +"SRB","RS","RS-15","Zaječarski okrug","District","Serbia",2 +"SRB","RS","RS-16","Zlatiborski okrug","District","Serbia",2 +"SRB","RS","RS-17","Moravički okrug","District","Serbia",2 +"SRB","RS","RS-18","Raški okrug","District","Serbia",2 +"SRB","RS","RS-19","Rasinski okrug","District","Serbia",2 +"SRB","RS","RS-20","Nišavski okrug","District","Serbia",2 +"SRB","RS","RS-21","Toplički okrug","District","Serbia",2 +"SRB","RS","RS-22","Pirotski okrug","District","Serbia",2 +"SRB","RS","RS-23","Jablanički okrug","District","Serbia",2 +"SRB","RS","RS-24","Pčinjski okrug","District","Serbia",2 +"SRB","RS","RS-25","Kosovski okrug","District","Serbia",2 +"SRB","RS","RS-26","Pećki okrug","District","Serbia",2 +"SRB","RS","RS-27","Prizrenski okrug","District","Serbia",2 +"SRB","RS","RS-28","Kosovsko-Mitrovački okrug","District","Serbia",2 +"SRB","RS","RS-29","Kosovsko-Pomoravski okrug","District","Serbia",2 +"SRB","RS","RS-KM","Kosovo-Metohija","Autonomous province","Serbia",2 +"SRB","RS","RS-VO","Vojvodina","Autonomous province","Serbia",2 +"RUS","RU","RU-AD","Adygeya, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-AL","Altay, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-ALT","Altayskiy kray","Administrative Territory","Russian Federation",2 +"RUS","RU","RU-AMU","Amurskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-ARK","Arkhangel'skaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-AST","Astrakhanskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-BA","Bashkortostan, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-BEL","Belgorodskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-BRY","Bryanskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-BU","Buryatiya, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-CE","Chechenskaya Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-CHE","Chelyabinskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-CHU","Chukotskiy avtonomnyy okrug","Autonomous District","Russian Federation",2 +"RUS","RU","RU-CU","Chuvashskaya Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-DA","Dagestan, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-IN","Respublika Ingushetiya","Republic","Russian Federation",2 +"RUS","RU","RU-IRK","Irkutiskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-IVA","Ivanovskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-KAM","Kamchatskiy kray","Administrative Territory","Russian Federation",2 +"RUS","RU","RU-KB","Kabardino-Balkarskaya Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-KC","Karachayevo-Cherkesskaya Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-KDA","Krasnodarskiy kray","Administrative Territory","Russian Federation",2 +"RUS","RU","RU-KEM","Kemerovskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-KGD","Kaliningradskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-KGN","Kurganskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-KHA","Khabarovskiy kray","Administrative Territory","Russian Federation",2 +"RUS","RU","RU-KHM","Khanty-Mansiysky avtonomnyy okrug-Yugra","Autonomous District","Russian Federation",2 +"RUS","RU","RU-KIR","Kirovskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-KK","Khakasiya, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-KL","Kalmykiya, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-KLU","Kaluzhskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-KO","Komi, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-KOS","Kostromskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-KR","Kareliya, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-KRS","Kurskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-KYA","Krasnoyarskiy kray","Administrative Territory","Russian Federation",2 +"RUS","RU","RU-LEN","Leningradskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-LIP","Lipetskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-MAG","Magadanskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-ME","Mariy El, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-MO","Mordoviya, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-MOS","Moskovskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-MOW","Moskva","Autonomous City","Russian Federation",2 +"RUS","RU","RU-MUR","Murmanskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-NEN","Nenetskiy avtonomnyy okrug","Autonomous District","Russian Federation",2 +"RUS","RU","RU-NGR","Novgorodskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-NIZ","Nizhegorodskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-NVS","Novosibirskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-OMS","Omskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-ORE","Orenburgskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-ORL","Orlovskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-PER","Permskiy kray","Administrative Territory","Russian Federation",2 +"RUS","RU","RU-PNZ","Penzenskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-PRI","Primorskiy kray","Administrative Territory","Russian Federation",2 +"RUS","RU","RU-PSK","Pskovskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-ROS","Rostovskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-RYA","Ryazanskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-SA","Sakha, Respublika [Yakutiya]","Republic","Russian Federation",2 +"RUS","RU","RU-SAK","Sakhalinskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-SAM","Samaraskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-SAR","Saratovskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-SE","Severnaya Osetiya-Alaniya, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-SMO","Smolenskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-SPE","Sankt-Peterburg","Autonomous City","Russian Federation",2 +"RUS","RU","RU-STA","Stavropol'skiy kray","Administrative Territory","Russian Federation",2 +"RUS","RU","RU-SVE","Sverdlovskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-TA","Tatarstan, Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-TAM","Tambovskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-TOM","Tomskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-TUL","Tul'skaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-TVE","Tverskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-TY","Tyva, Respublika [Tuva]","Republic","Russian Federation",2 +"RUS","RU","RU-TYU","Tyumenskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-UD","Udmurtskaya Respublika","Republic","Russian Federation",2 +"RUS","RU","RU-ULY","Ul'yanovskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-VGG","Volgogradskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-VLA","Vladimirskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-VLG","Vologodskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-VOR","Voronezhskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-YAN","Yamalo-Nenetskiy avtonomnyy okrug","Autonomous District","Russian Federation",2 +"RUS","RU","RU-YAR","Yaroslavskaya oblast'","Administrative Region","Russian Federation",2 +"RUS","RU","RU-YEV","Yevreyskaya avtonomnaya oblast'","Autonomous Region","Russian Federation",2 +"RUS","RU","RU-ZAB","Zabajkal'skij kraj","Administrative Territory","Russian Federation",2 +"RWA","RW","RW-01","Ville de Kigali","Town council","Rwanda",2 +"RWA","RW","RW-02","Est","Province","Rwanda",2 +"RWA","RW","RW-03","Nord","Province","Rwanda",2 +"RWA","RW","RW-04","Ouest","Province","Rwanda",2 +"RWA","RW","RW-05","Sud","Province","Rwanda",2 +"SAU","SA","SA-01","Ar Riyāḍ","Province","Saudi Arabia",2 +"SAU","SA","SA-02","Makkah","Province","Saudi Arabia",2 +"SAU","SA","SA-03","Al Madīnah","Province","Saudi Arabia",2 +"SAU","SA","SA-04","Ash Sharqīyah","Province","Saudi Arabia",2 +"SAU","SA","SA-05","Al Qaşīm","Province","Saudi Arabia",2 +"SAU","SA","SA-06","Ḥā'il","Province","Saudi Arabia",2 +"SAU","SA","SA-07","Tabūk","Province","Saudi Arabia",2 +"SAU","SA","SA-08","Al Ḥudūd ash Shamāliyah","Province","Saudi Arabia",2 +"SAU","SA","SA-09","Jīzan","Province","Saudi Arabia",2 +"SAU","SA","SA-10","Najrān","Province","Saudi Arabia",2 +"SAU","SA","SA-11","Al Bāhah","Province","Saudi Arabia",2 +"SAU","SA","SA-12","Al Jawf","Province","Saudi Arabia",2 +"SAU","SA","SA-14","`Asīr","Province","Saudi Arabia",2 +"SLB","SB","SB-CE","Central","Province","Solomon Islands",2 +"SLB","SB","SB-CH","Choiseul","Province","Solomon Islands",2 +"SLB","SB","SB-CT","Capital Territory (Honiara)","Capital territory","Solomon Islands",2 +"SLB","SB","SB-GU","Guadalcanal","Province","Solomon Islands",2 +"SLB","SB","SB-IS","Isabel","Province","Solomon Islands",2 +"SLB","SB","SB-MK","Makira","Province","Solomon Islands",2 +"SLB","SB","SB-ML","Malaita","Province","Solomon Islands",2 +"SLB","SB","SB-RB","Rennell and Bellona","Province","Solomon Islands",2 +"SLB","SB","SB-TE","Temotu","Province","Solomon Islands",2 +"SLB","SB","SB-WE","Western","Province","Solomon Islands",2 +"SYC","SC","SC-01","Anse aux Pins","District","Seychelles",2 +"SYC","SC","SC-02","Anse Boileau","District","Seychelles",2 +"SYC","SC","SC-03","Anse Etoile","District","Seychelles",2 +"SYC","SC","SC-04","Anse Louis","District","Seychelles",2 +"SYC","SC","SC-05","Anse Royale","District","Seychelles",2 +"SYC","SC","SC-06","Baie Lazare","District","Seychelles",2 +"SYC","SC","SC-07","Baie Sainte Anne","District","Seychelles",2 +"SYC","SC","SC-08","Beau Vallon","District","Seychelles",2 +"SYC","SC","SC-09","Bel Air","District","Seychelles",2 +"SYC","SC","SC-10","Bel Ombre","District","Seychelles",2 +"SYC","SC","SC-11","Cascade","District","Seychelles",2 +"SYC","SC","SC-12","Glacis","District","Seychelles",2 +"SYC","SC","SC-13","Grand Anse Mahe","District","Seychelles",2 +"SYC","SC","SC-14","Grand Anse Praslin","District","Seychelles",2 +"SYC","SC","SC-15","La Digue","District","Seychelles",2 +"SYC","SC","SC-16","English River","District","Seychelles",2 +"SYC","SC","SC-17","Mont Buxton","District","Seychelles",2 +"SYC","SC","SC-18","Mont Fleuri","District","Seychelles",2 +"SYC","SC","SC-19","Plaisance","District","Seychelles",2 +"SYC","SC","SC-20","Pointe Larue","District","Seychelles",2 +"SYC","SC","SC-21","Port Glaud","District","Seychelles",2 +"SYC","SC","SC-22","Saint Louis","District","Seychelles",2 +"SYC","SC","SC-23","Takamaka","District","Seychelles",2 +"SYC","SC","SC-24","Les Mamelles","District","Seychelles",2 +"SYC","SC","SC-25","Roche Caiman","District","Seychelles",2 +"SDN","SD","SD-DC","Zalingei","state","Sudan",2 +"SDN","SD","SD-DE","Sharq Dārfūr","state","Sudan",2 +"SDN","SD","SD-DN","Shamāl Dārfūr","state","Sudan",2 +"SDN","SD","SD-DS","Janūb Dārfūr","state","Sudan",2 +"SDN","SD","SD-DW","Gharb Dārfūr","state","Sudan",2 +"SDN","SD","SD-GD","Al Qaḑārif","state","Sudan",2 +"SDN","SD","SD-GZ","Al Jazīrah","state","Sudan",2 +"SDN","SD","SD-KA","Kassalā","state","Sudan",2 +"SDN","SD","SD-KH","Al Kharţūm","state","Sudan",2 +"SDN","SD","SD-KN","Shamāl Kurdufān","state","Sudan",2 +"SDN","SD","SD-KS","Janūb Kurdufān","state","Sudan",2 +"SDN","SD","SD-NB","An Nīl al Azraq","state","Sudan",2 +"SDN","SD","SD-NO","Ash Shamālīyah","state","Sudan",2 +"SDN","SD","SD-NR","An Nīl","state","Sudan",2 +"SDN","SD","SD-NW","An Nīl al Abyaḑ","state","Sudan",2 +"SDN","SD","SD-RS","Al Baḩr al Aḩmar","state","Sudan",2 +"SDN","SD","SD-SI","Sinnār","state","Sudan",2 +"SWE","SE","SE-AB","Stockholms län","County","Sweden",2 +"SWE","SE","SE-AC","Västerbottens län","County","Sweden",2 +"SWE","SE","SE-BD","Norrbottens län","County","Sweden",2 +"SWE","SE","SE-C","Uppsala län","County","Sweden",2 +"SWE","SE","SE-D","Södermanlands län","County","Sweden",2 +"SWE","SE","SE-E","Östergötlands län","County","Sweden",2 +"SWE","SE","SE-F","Jönköpings län","County","Sweden",2 +"SWE","SE","SE-G","Kronobergs län","County","Sweden",2 +"SWE","SE","SE-H","Kalmar län","County","Sweden",2 +"SWE","SE","SE-I","Gotlands län","County","Sweden",2 +"SWE","SE","SE-K","Blekinge län","County","Sweden",2 +"SWE","SE","SE-M","Skåne län","County","Sweden",2 +"SWE","SE","SE-N","Hallands län","County","Sweden",2 +"SWE","SE","SE-O","Västra Götalands län","County","Sweden",2 +"SWE","SE","SE-S","Värmlands län","County","Sweden",2 +"SWE","SE","SE-T","Örebro län","County","Sweden",2 +"SWE","SE","SE-U","Västmanlands län","County","Sweden",2 +"SWE","SE","SE-W","Dalarnas län","County","Sweden",2 +"SWE","SE","SE-X","Gävleborgs län","County","Sweden",2 +"SWE","SE","SE-Y","Västernorrlands län","County","Sweden",2 +"SWE","SE","SE-Z","Jämtlands län","County","Sweden",2 +"SGP","SG","SG-01","Central Singapore","district","Singapore",2 +"SGP","SG","SG-02","North East","district","Singapore",2 +"SGP","SG","SG-03","North West","district","Singapore",2 +"SGP","SG","SG-04","South East","district","Singapore",2 +"SGP","SG","SG-05","South West","district","Singapore",2 +"SHN","SH","SH-AC","Ascension","Geographical Entity","Saint Helena, Ascension and Tristan da Cunha",2 +"SHN","SH","SH-HL","Saint Helena","Geographical Entity","Saint Helena, Ascension and Tristan da Cunha",2 +"SHN","SH","SH-TA","Tristan da Cunha","Geographical Entity","Saint Helena, Ascension and Tristan da Cunha",2 +"SVN","SI","SI-001","Ajdovščina","Municipality","Slovenia",2 +"SVN","SI","SI-002","Beltinci","Municipality","Slovenia",2 +"SVN","SI","SI-003","Bled","Municipality","Slovenia",2 +"SVN","SI","SI-004","Bohinj","Municipality","Slovenia",2 +"SVN","SI","SI-005","Borovnica","Municipality","Slovenia",2 +"SVN","SI","SI-006","Bovec","Municipality","Slovenia",2 +"SVN","SI","SI-007","Brda","Municipality","Slovenia",2 +"SVN","SI","SI-008","Brezovica","Municipality","Slovenia",2 +"SVN","SI","SI-009","Brežice","Municipality","Slovenia",2 +"SVN","SI","SI-010","Tišina","Municipality","Slovenia",2 +"SVN","SI","SI-011","Celje","Municipality","Slovenia",2 +"SVN","SI","SI-012","Cerklje na Gorenjskem","Municipality","Slovenia",2 +"SVN","SI","SI-013","Cerknica","Municipality","Slovenia",2 +"SVN","SI","SI-014","Cerkno","Municipality","Slovenia",2 +"SVN","SI","SI-015","Črenšovci","Municipality","Slovenia",2 +"SVN","SI","SI-016","Črna na Koroškem","Municipality","Slovenia",2 +"SVN","SI","SI-017","Črnomelj","Municipality","Slovenia",2 +"SVN","SI","SI-018","Destrnik","Municipality","Slovenia",2 +"SVN","SI","SI-019","Divača","Municipality","Slovenia",2 +"SVN","SI","SI-020","Dobrepolje","Municipality","Slovenia",2 +"SVN","SI","SI-021","Dobrova-Polhov Gradec","Municipality","Slovenia",2 +"SVN","SI","SI-022","Dol pri Ljubljani","Municipality","Slovenia",2 +"SVN","SI","SI-023","Domžale","Municipality","Slovenia",2 +"SVN","SI","SI-024","Dornava","Municipality","Slovenia",2 +"SVN","SI","SI-025","Dravograd","Municipality","Slovenia",2 +"SVN","SI","SI-026","Duplek","Municipality","Slovenia",2 +"SVN","SI","SI-027","Gorenja vas-Poljane","Municipality","Slovenia",2 +"SVN","SI","SI-028","Gorišnica","Municipality","Slovenia",2 +"SVN","SI","SI-029","Gornja Radgona","Municipality","Slovenia",2 +"SVN","SI","SI-030","Gornji Grad","Municipality","Slovenia",2 +"SVN","SI","SI-031","Gornji Petrovci","Municipality","Slovenia",2 +"SVN","SI","SI-032","Grosuplje","Municipality","Slovenia",2 +"SVN","SI","SI-033","Šalovci","Municipality","Slovenia",2 +"SVN","SI","SI-034","Hrastnik","Municipality","Slovenia",2 +"SVN","SI","SI-035","Hrpelje-Kozina","Municipality","Slovenia",2 +"SVN","SI","SI-036","Idrija","Municipality","Slovenia",2 +"SVN","SI","SI-037","Ig","Municipality","Slovenia",2 +"SVN","SI","SI-038","Ilirska Bistrica","Municipality","Slovenia",2 +"SVN","SI","SI-039","Ivančna Gorica","Municipality","Slovenia",2 +"SVN","SI","SI-040","Izola/Isola","Municipality","Slovenia",2 +"SVN","SI","SI-041","Jesenice","Municipality","Slovenia",2 +"SVN","SI","SI-042","Juršinci","Municipality","Slovenia",2 +"SVN","SI","SI-043","Kamnik","Municipality","Slovenia",2 +"SVN","SI","SI-044","Kanal","Municipality","Slovenia",2 +"SVN","SI","SI-045","Kidričevo","Municipality","Slovenia",2 +"SVN","SI","SI-046","Kobarid","Municipality","Slovenia",2 +"SVN","SI","SI-047","Kobilje","Municipality","Slovenia",2 +"SVN","SI","SI-048","Kočevje","Municipality","Slovenia",2 +"SVN","SI","SI-049","Komen","Municipality","Slovenia",2 +"SVN","SI","SI-050","Koper/Capodistria","Municipality","Slovenia",2 +"SVN","SI","SI-051","Kozje","Municipality","Slovenia",2 +"SVN","SI","SI-052","Kranj","Municipality","Slovenia",2 +"SVN","SI","SI-053","Kranjska Gora","Municipality","Slovenia",2 +"SVN","SI","SI-054","Krško","Municipality","Slovenia",2 +"SVN","SI","SI-055","Kungota","Municipality","Slovenia",2 +"SVN","SI","SI-056","Kuzma","Municipality","Slovenia",2 +"SVN","SI","SI-057","Laško","Municipality","Slovenia",2 +"SVN","SI","SI-058","Lenart","Municipality","Slovenia",2 +"SVN","SI","SI-059","Lendava/Lendva","Municipality","Slovenia",2 +"SVN","SI","SI-060","Litija","Municipality","Slovenia",2 +"SVN","SI","SI-061","Ljubljana","Municipality","Slovenia",2 +"SVN","SI","SI-062","Ljubno","Municipality","Slovenia",2 +"SVN","SI","SI-063","Ljutomer","Municipality","Slovenia",2 +"SVN","SI","SI-064","Logatec","Municipality","Slovenia",2 +"SVN","SI","SI-065","Loška dolina","Municipality","Slovenia",2 +"SVN","SI","SI-066","Loški Potok","Municipality","Slovenia",2 +"SVN","SI","SI-067","Luče","Municipality","Slovenia",2 +"SVN","SI","SI-068","Lukovica","Municipality","Slovenia",2 +"SVN","SI","SI-069","Majšperk","Municipality","Slovenia",2 +"SVN","SI","SI-070","Maribor","Municipality","Slovenia",2 +"SVN","SI","SI-071","Medvode","Municipality","Slovenia",2 +"SVN","SI","SI-072","Mengeš","Municipality","Slovenia",2 +"SVN","SI","SI-073","Metlika","Municipality","Slovenia",2 +"SVN","SI","SI-074","Mežica","Municipality","Slovenia",2 +"SVN","SI","SI-075","Miren-Kostanjevica","Municipality","Slovenia",2 +"SVN","SI","SI-076","Mislinja","Municipality","Slovenia",2 +"SVN","SI","SI-077","Moravče","Municipality","Slovenia",2 +"SVN","SI","SI-078","Moravske Toplice","Municipality","Slovenia",2 +"SVN","SI","SI-079","Mozirje","Municipality","Slovenia",2 +"SVN","SI","SI-080","Murska Sobota","Municipality","Slovenia",2 +"SVN","SI","SI-081","Muta","Municipality","Slovenia",2 +"SVN","SI","SI-082","Naklo","Municipality","Slovenia",2 +"SVN","SI","SI-083","Nazarje","Municipality","Slovenia",2 +"SVN","SI","SI-084","Nova Gorica","Municipality","Slovenia",2 +"SVN","SI","SI-085","Novo mesto","Municipality","Slovenia",2 +"SVN","SI","SI-086","Odranci","Municipality","Slovenia",2 +"SVN","SI","SI-087","Ormož","Municipality","Slovenia",2 +"SVN","SI","SI-088","Osilnica","Municipality","Slovenia",2 +"SVN","SI","SI-089","Pesnica","Municipality","Slovenia",2 +"SVN","SI","SI-090","Piran/Pirano","Municipality","Slovenia",2 +"SVN","SI","SI-091","Pivka","Municipality","Slovenia",2 +"SVN","SI","SI-092","Podčetrtek","Municipality","Slovenia",2 +"SVN","SI","SI-093","Podvelka","Municipality","Slovenia",2 +"SVN","SI","SI-094","Postojna","Municipality","Slovenia",2 +"SVN","SI","SI-095","Preddvor","Municipality","Slovenia",2 +"SVN","SI","SI-096","Ptuj","Municipality","Slovenia",2 +"SVN","SI","SI-097","Puconci","Municipality","Slovenia",2 +"SVN","SI","SI-098","Rače-Fram","Municipality","Slovenia",2 +"SVN","SI","SI-099","Radeče","Municipality","Slovenia",2 +"SVN","SI","SI-100","Radenci","Municipality","Slovenia",2 +"SVN","SI","SI-101","Radlje ob Dravi","Municipality","Slovenia",2 +"SVN","SI","SI-102","Radovljica","Municipality","Slovenia",2 +"SVN","SI","SI-103","Ravne na Koroškem","Municipality","Slovenia",2 +"SVN","SI","SI-104","Ribnica","Municipality","Slovenia",2 +"SVN","SI","SI-105","Rogašovci","Municipality","Slovenia",2 +"SVN","SI","SI-106","Rogaška Slatina","Municipality","Slovenia",2 +"SVN","SI","SI-107","Rogatec","Municipality","Slovenia",2 +"SVN","SI","SI-108","Ruše","Municipality","Slovenia",2 +"SVN","SI","SI-109","Semič","Municipality","Slovenia",2 +"SVN","SI","SI-110","Sevnica","Municipality","Slovenia",2 +"SVN","SI","SI-111","Sežana","Municipality","Slovenia",2 +"SVN","SI","SI-112","Slovenj Gradec","Municipality","Slovenia",2 +"SVN","SI","SI-113","Slovenska Bistrica","Municipality","Slovenia",2 +"SVN","SI","SI-114","Slovenske Konjice","Municipality","Slovenia",2 +"SVN","SI","SI-115","Starče","Municipality","Slovenia",2 +"SVN","SI","SI-116","Sveti Jurij","Municipality","Slovenia",2 +"SVN","SI","SI-117","Šenčur","Municipality","Slovenia",2 +"SVN","SI","SI-118","Šentilj","Municipality","Slovenia",2 +"SVN","SI","SI-119","Šentjernej","Municipality","Slovenia",2 +"SVN","SI","SI-120","Šentjur","Municipality","Slovenia",2 +"SVN","SI","SI-121","Škocjan","Municipality","Slovenia",2 +"SVN","SI","SI-122","Škofja Loka","Municipality","Slovenia",2 +"SVN","SI","SI-123","Škofljica","Municipality","Slovenia",2 +"SVN","SI","SI-124","Šmarje pri Jelšah","Municipality","Slovenia",2 +"SVN","SI","SI-125","Šmartno ob Paki","Municipality","Slovenia",2 +"SVN","SI","SI-126","Šoštanj","Municipality","Slovenia",2 +"SVN","SI","SI-127","Štore","Municipality","Slovenia",2 +"SVN","SI","SI-128","Tolmin","Municipality","Slovenia",2 +"SVN","SI","SI-129","Trbovlje","Municipality","Slovenia",2 +"SVN","SI","SI-130","Trebnje","Municipality","Slovenia",2 +"SVN","SI","SI-131","Tržič","Municipality","Slovenia",2 +"SVN","SI","SI-132","Turnišče","Municipality","Slovenia",2 +"SVN","SI","SI-133","Velenje","Municipality","Slovenia",2 +"SVN","SI","SI-134","Velike Lašče","Municipality","Slovenia",2 +"SVN","SI","SI-135","Videm","Municipality","Slovenia",2 +"SVN","SI","SI-136","Vipava","Municipality","Slovenia",2 +"SVN","SI","SI-137","Vitanje","Municipality","Slovenia",2 +"SVN","SI","SI-138","Vodice","Municipality","Slovenia",2 +"SVN","SI","SI-139","Vojnik","Municipality","Slovenia",2 +"SVN","SI","SI-140","Vrhnika","Municipality","Slovenia",2 +"SVN","SI","SI-141","Vuzenica","Municipality","Slovenia",2 +"SVN","SI","SI-142","Zagorje ob Savi","Municipality","Slovenia",2 +"SVN","SI","SI-143","Zavrč","Municipality","Slovenia",2 +"SVN","SI","SI-144","Zreče","Municipality","Slovenia",2 +"SVN","SI","SI-146","Železniki","Municipality","Slovenia",2 +"SVN","SI","SI-147","Žiri","Municipality","Slovenia",2 +"SVN","SI","SI-148","Benedikt","Municipality","Slovenia",2 +"SVN","SI","SI-149","Bistrica ob Sotli","Municipality","Slovenia",2 +"SVN","SI","SI-150","Bloke","Municipality","Slovenia",2 +"SVN","SI","SI-151","Braslovče","Municipality","Slovenia",2 +"SVN","SI","SI-152","Cankova","Municipality","Slovenia",2 +"SVN","SI","SI-153","Cerkvenjak","Municipality","Slovenia",2 +"SVN","SI","SI-154","Dobje","Municipality","Slovenia",2 +"SVN","SI","SI-155","Dobrna","Municipality","Slovenia",2 +"SVN","SI","SI-156","Dobrovnik/Dobronak","Municipality","Slovenia",2 +"SVN","SI","SI-157","Dolenjske Toplice","Municipality","Slovenia",2 +"SVN","SI","SI-158","Grad","Municipality","Slovenia",2 +"SVN","SI","SI-159","Hajdina","Municipality","Slovenia",2 +"SVN","SI","SI-160","Hoče-Slivnica","Municipality","Slovenia",2 +"SVN","SI","SI-161","Hodoš/Hodos","Municipality","Slovenia",2 +"SVN","SI","SI-162","Horjul","Municipality","Slovenia",2 +"SVN","SI","SI-163","Jezersko","Municipality","Slovenia",2 +"SVN","SI","SI-164","Komenda","Municipality","Slovenia",2 +"SVN","SI","SI-165","Kostel","Municipality","Slovenia",2 +"SVN","SI","SI-166","Križevci","Municipality","Slovenia",2 +"SVN","SI","SI-167","Lovrenc na Pohorju","Municipality","Slovenia",2 +"SVN","SI","SI-168","Markovci","Municipality","Slovenia",2 +"SVN","SI","SI-169","Miklavž na Dravskem polju","Municipality","Slovenia",2 +"SVN","SI","SI-170","Mirna Peč","Municipality","Slovenia",2 +"SVN","SI","SI-171","Oplotnica","Municipality","Slovenia",2 +"SVN","SI","SI-172","Podlehnik","Municipality","Slovenia",2 +"SVN","SI","SI-173","Polzela","Municipality","Slovenia",2 +"SVN","SI","SI-174","Prebold","Municipality","Slovenia",2 +"SVN","SI","SI-175","Prevalje","Municipality","Slovenia",2 +"SVN","SI","SI-176","Razkrižje","Municipality","Slovenia",2 +"SVN","SI","SI-177","Ribnica na Pohorju","Municipality","Slovenia",2 +"SVN","SI","SI-178","Selnica ob Dravi","Municipality","Slovenia",2 +"SVN","SI","SI-179","Sodražica","Municipality","Slovenia",2 +"SVN","SI","SI-180","Solčava","Municipality","Slovenia",2 +"SVN","SI","SI-181","Sveta Ana","Municipality","Slovenia",2 +"SVN","SI","SI-182","Sveta Andraž v Slovenskih Goricah","Municipality","Slovenia",2 +"SVN","SI","SI-183","Šempeter-Vrtojba","Municipality","Slovenia",2 +"SVN","SI","SI-184","Tabor","Municipality","Slovenia",2 +"SVN","SI","SI-185","Trnovska vas","Municipality","Slovenia",2 +"SVN","SI","SI-186","Trzin","Municipality","Slovenia",2 +"SVN","SI","SI-187","Velika Polana","Municipality","Slovenia",2 +"SVN","SI","SI-188","Veržej","Municipality","Slovenia",2 +"SVN","SI","SI-189","Vransko","Municipality","Slovenia",2 +"SVN","SI","SI-190","Žalec","Municipality","Slovenia",2 +"SVN","SI","SI-191","Žetale","Municipality","Slovenia",2 +"SVN","SI","SI-192","Žirovnica","Municipality","Slovenia",2 +"SVN","SI","SI-193","Žužemberk","Municipality","Slovenia",2 +"SVN","SI","SI-194","Šmartno pri Litiji","Municipality","Slovenia",2 +"SVN","SI","SI-195","Apače","Municipality","Slovenia",2 +"SVN","SI","SI-196","Cirkulane","Municipality","Slovenia",2 +"SVN","SI","SI-197","Kosanjevica na Krki","Municipality","Slovenia",2 +"SVN","SI","SI-198","Makole","Municipality","Slovenia",2 +"SVN","SI","SI-199","Mokronog-Trebelno","Municipality","Slovenia",2 +"SVN","SI","SI-200","Poljčane","Municipality","Slovenia",2 +"SVN","SI","SI-201","Renče-Vogrsko","Municipality","Slovenia",2 +"SVN","SI","SI-202","Središče ob Dravi","Municipality","Slovenia",2 +"SVN","SI","SI-203","Straža","Municipality","Slovenia",2 +"SVN","SI","SI-204","Sveta Trojica v Slovenskih Goricah","Municipality","Slovenia",2 +"SVN","SI","SI-205","Sveti Tomaž","Municipality","Slovenia",2 +"SVN","SI","SI-206","Šmarjeske Topliče","Municipality","Slovenia",2 +"SVN","SI","SI-207","Gorje","Municipality","Slovenia",2 +"SVN","SI","SI-208","Log-Dragomer","Municipality","Slovenia",2 +"SVN","SI","SI-209","Rečica ob Savinji","Municipality","Slovenia",2 +"SVN","SI","SI-210","Sveti Jurij v Slovenskih Goricah","Municipality","Slovenia",2 +"SVN","SI","SI-211","Šentrupert","Municipality","Slovenia",2 +"SVK","SK","SK-BC","Banskobystrický kraj","Region","Slovakia",2 +"SVK","SK","SK-BL","Bratislavský kraj","Region","Slovakia",2 +"SVK","SK","SK-KI","Košický kraj","Region","Slovakia",2 +"SVK","SK","SK-NI","Nitriansky kraj","Region","Slovakia",2 +"SVK","SK","SK-PV","Prešovský kraj","Region","Slovakia",2 +"SVK","SK","SK-TA","Trnavský kraj","Region","Slovakia",2 +"SVK","SK","SK-TC","Trenčiansky kraj","Region","Slovakia",2 +"SVK","SK","SK-ZI","Žilinský kraj","Region","Slovakia",2 +"SLE","SL","SL-E","Eastern","Province","Sierra Leone",2 +"SLE","SL","SL-N","Northern","Province","Sierra Leone",2 +"SLE","SL","SL-S","Southern (Sierra Leone)","Province","Sierra Leone",2 +"SLE","SL","SL-W","Western Area (Freetown)","Area","Sierra Leone",2 +"SMR","SM","SM-01","Acquaviva","Municipalities","San Marino",2 +"SMR","SM","SM-02","Chiesanuova","Municipalities","San Marino",2 +"SMR","SM","SM-03","Domagnano","Municipalities","San Marino",2 +"SMR","SM","SM-04","Faetano","Municipalities","San Marino",2 +"SMR","SM","SM-05","Fiorentino","Municipalities","San Marino",2 +"SMR","SM","SM-06","Borgo Maggiore","Municipalities","San Marino",2 +"SMR","SM","SM-07","San Marino","Municipalities","San Marino",2 +"SMR","SM","SM-08","Montegiardino","Municipalities","San Marino",2 +"SMR","SM","SM-09","Serravalle","Municipalities","San Marino",2 +"SEN","SN","SN-DB","Diourbel","Region","Senegal",2 +"SEN","SN","SN-DK","Dakar","Region","Senegal",2 +"SEN","SN","SN-FK","Fatick","Region","Senegal",2 +"SEN","SN","SN-KA","Kaffrine","Region","Senegal",2 +"SEN","SN","SN-KD","Kolda","Region","Senegal",2 +"SEN","SN","SN-KE","Kédougou","Region","Senegal",2 +"SEN","SN","SN-KL","Kaolack","Region","Senegal",2 +"SEN","SN","SN-LG","Louga","Region","Senegal",2 +"SEN","SN","SN-MT","Matam","Region","Senegal",2 +"SEN","SN","SN-SE","Sédhiou","Region","Senegal",2 +"SEN","SN","SN-SL","Saint-Louis","Region","Senegal",2 +"SEN","SN","SN-TC","Tambacounda","Region","Senegal",2 +"SEN","SN","SN-TH","Thiès","Region","Senegal",2 +"SEN","SN","SN-ZG","Ziguinchor","Region","Senegal",2 +"SOM","SO","SO-AW","Awdal","Region","Somalia",2 +"SOM","SO","SO-BK","Bakool","Region","Somalia",2 +"SOM","SO","SO-BN","Banaadir","Region","Somalia",2 +"SOM","SO","SO-BR","Bari","Region","Somalia",2 +"SOM","SO","SO-BY","Bay","Region","Somalia",2 +"SOM","SO","SO-GA","Galguduud","Region","Somalia",2 +"SOM","SO","SO-GE","Gedo","Region","Somalia",2 +"SOM","SO","SO-HI","Hiirsan","Region","Somalia",2 +"SOM","SO","SO-JD","Jubbada Dhexe","Region","Somalia",2 +"SOM","SO","SO-JH","Jubbada Hoose","Region","Somalia",2 +"SOM","SO","SO-MU","Mudug","Region","Somalia",2 +"SOM","SO","SO-NU","Nugaal","Region","Somalia",2 +"SOM","SO","SO-SA","Saneag","Region","Somalia",2 +"SOM","SO","SO-SD","Shabeellaha Dhexe","Region","Somalia",2 +"SOM","SO","SO-SH","Shabeellaha Hoose","Region","Somalia",2 +"SOM","SO","SO-SO","Sool","Region","Somalia",2 +"SOM","SO","SO-TO","Togdheer","Region","Somalia",2 +"SOM","SO","SO-WO","Woqooyi Galbeed","Region","Somalia",2 +"SUR","SR","SR-BR","Brokopondo","District","Suriname",2 +"SUR","SR","SR-CM","Commewijne","District","Suriname",2 +"SUR","SR","SR-CR","Coronie","District","Suriname",2 +"SUR","SR","SR-MA","Marowijne","District","Suriname",2 +"SUR","SR","SR-NI","Nickerie","District","Suriname",2 +"SUR","SR","SR-PM","Paramaribo","District","Suriname",2 +"SUR","SR","SR-PR","Para","District","Suriname",2 +"SUR","SR","SR-SA","Saramacca","District","Suriname",2 +"SUR","SR","SR-SI","Sipaliwini","District","Suriname",2 +"SUR","SR","SR-WA","Wanica","District","Suriname",2 +"SSD","SS","SS-BN","Northern Bahr el-Ghazal","state","South Sudan",2 +"SSD","SS","SS-BW","Western Bahr el-Ghazal","state","South Sudan",2 +"SSD","SS","SS-EC","Central Equatoria","state","South Sudan",2 +"SSD","SS","SS-EE8","Eastern Equatoria","state","South Sudan",2 +"SSD","SS","SS-EW","Western Equatoria","state","South Sudan",2 +"SSD","SS","SS-JG","Jonglei","state","South Sudan",2 +"SSD","SS","SS-LK","Lakes","state","South Sudan",2 +"SSD","SS","SS-NU","Upper Nile","state","South Sudan",2 +"SSD","SS","SS-UY","Unity","state","South Sudan",2 +"SSD","SS","SS-WR","Warrap","state","South Sudan",2 +"STP","ST","ST-P","Príncipe","Municipality","Sao Tome and Principe",2 +"STP","ST","ST-S","São Tomé","Municipality","Sao Tome and Principe",2 +"SLV","SV","SV-AH","Ahuachapán","Department","El Salvador",2 +"SLV","SV","SV-CA","Cabañas","Department","El Salvador",2 +"SLV","SV","SV-CH","Chalatenango","Department","El Salvador",2 +"SLV","SV","SV-CU","Cuscatlán","Department","El Salvador",2 +"SLV","SV","SV-LI","La Libertad","Department","El Salvador",2 +"SLV","SV","SV-MO","Morazán","Department","El Salvador",2 +"SLV","SV","SV-PA","La Paz","Department","El Salvador",2 +"SLV","SV","SV-SA","Santa Ana","Department","El Salvador",2 +"SLV","SV","SV-SM","San Miguel","Department","El Salvador",2 +"SLV","SV","SV-SO","Sonsonate","Department","El Salvador",2 +"SLV","SV","SV-SS","San Salvador","Department","El Salvador",2 +"SLV","SV","SV-SV","San Vicente","Department","El Salvador",2 +"SLV","SV","SV-UN","La Unión","Department","El Salvador",2 +"SLV","SV","SV-US","Usulután","Department","El Salvador",2 +"SYR","SY","SY-DI","Dimashq","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-DR","Dar'a","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-DY","Dayr az Zawr","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-HA","Al Hasakah","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-HI","Homs","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-HL","Halab","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-HM","Hamah","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-ID","Idlib","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-LA","Al Ladhiqiyah","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-QU","Al Qunaytirah","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-RA","Ar Raqqah","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-RD","Rif Dimashq","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-SU","As Suwayda'","Governorate","Syrian Arab Republic",2 +"SYR","SY","SY-TA","Tartus","Governorate","Syrian Arab Republic",2 +"SWZ","SZ","SZ-HH","Hhohho","District","Swaziland",2 +"SWZ","SZ","SZ-LU","Lubombo","District","Swaziland",2 +"SWZ","SZ","SZ-MA","Manzini","District","Swaziland",2 +"SWZ","SZ","SZ-SH","Shiselweni","District","Swaziland",2 +"TCD","TD","TD-BA","Al Baṭḩah","Region","Chad",2 +"TCD","TD","TD-BG","Baḩr al Ghazāl","Region","Chad",2 +"TCD","TD","TD-BO","Būrkū","Region","Chad",2 +"TCD","TD","TD-CB","Shārī Bāqirmī","Region","Chad",2 +"TCD","TD","TD-EN","Innīdī","Region","Chad",2 +"TCD","TD","TD-GR","Qīrā","Region","Chad",2 +"TCD","TD","TD-HL","Ḥajjar Lamīs","Region","Chad",2 +"TCD","TD","TD-KA","Kānim","Region","Chad",2 +"TCD","TD","TD-LC","Al Buḩayrah","Region","Chad",2 +"TCD","TD","TD-LO","Lūqūn al Gharbī","Region","Chad",2 +"TCD","TD","TD-LR","Lūqūn ash Sharqī","Region","Chad",2 +"TCD","TD","TD-MA","Māndūl","Region","Chad",2 +"TCD","TD","TD-MC","Shārī al Awsaṭ","Region","Chad",2 +"TCD","TD","TD-ME","Māyū Kībbī ash Sharqī","Region","Chad",2 +"TCD","TD","TD-MO","Māyū Kībbī al Gharbī","Region","Chad",2 +"TCD","TD","TD-ND","Madīnat Injamīnā","Region","Chad",2 +"TCD","TD","TD-OD","Waddāy","Region","Chad",2 +"TCD","TD","TD-SA","Salāmāt","Region","Chad",2 +"TCD","TD","TD-SI","Sīlā","Region","Chad",2 +"TCD","TD","TD-TA","Tānjilī","Region","Chad",2 +"TCD","TD","TD-TI","Tibastī","Region","Chad",2 +"TCD","TD","TD-WF","Wādī Fīrā","Region","Chad",2 +"TGO","TG","TG-C","Région du Centre","Region","Togo",2 +"TGO","TG","TG-K","Région de la Kara","Region","Togo",2 +"TGO","TG","TG-M","Région Maritime","Region","Togo",2 +"TGO","TG","TG-P","Région des Plateaux","Region","Togo",2 +"TGO","TG","TG-S","Région des Savannes","Region","Togo",2 +"THA","TH","TH-10","Krung Thep Maha Nakhon Bangkok","Municipality","Thailand",2 +"THA","TH","TH-11","Samut Prakan","Province","Thailand",2 +"THA","TH","TH-12","Nonthaburi","Province","Thailand",2 +"THA","TH","TH-13","Pathum Thani","Province","Thailand",2 +"THA","TH","TH-14","Phra Nakhon Si Ayutthaya","Province","Thailand",2 +"THA","TH","TH-15","Ang Thong","Province","Thailand",2 +"THA","TH","TH-16","Lop Buri","Province","Thailand",2 +"THA","TH","TH-17","Sing Buri","Province","Thailand",2 +"THA","TH","TH-18","Chai Nat","Province","Thailand",2 +"THA","TH","TH-19","Saraburi","Province","Thailand",2 +"THA","TH","TH-20","Chon Buri","Province","Thailand",2 +"THA","TH","TH-21","Rayong","Province","Thailand",2 +"THA","TH","TH-22","Chanthaburi","Province","Thailand",2 +"THA","TH","TH-23","Trat","Province","Thailand",2 +"THA","TH","TH-24","Chachoengsao","Province","Thailand",2 +"THA","TH","TH-25","Prachin Buri","Province","Thailand",2 +"THA","TH","TH-26","Nakhon Nayok","Province","Thailand",2 +"THA","TH","TH-27","Sa Kaeo","Province","Thailand",2 +"THA","TH","TH-30","Nakhon Ratchasima","Province","Thailand",2 +"THA","TH","TH-31","Buri Ram","Province","Thailand",2 +"THA","TH","TH-32","Surin","Province","Thailand",2 +"THA","TH","TH-33","Si Sa Ket","Province","Thailand",2 +"THA","TH","TH-34","Ubon Ratchathani","Province","Thailand",2 +"THA","TH","TH-35","Yasothon","Province","Thailand",2 +"THA","TH","TH-36","Chaiyaphum","Province","Thailand",2 +"THA","TH","TH-37","Amnat Charoen","Province","Thailand",2 +"THA","TH","TH-39","Nong Bua Lam Phu","Province","Thailand",2 +"THA","TH","TH-40","Khon Kaen","Province","Thailand",2 +"THA","TH","TH-41","Udon Thani","Province","Thailand",2 +"THA","TH","TH-42","Loei","Province","Thailand",2 +"THA","TH","TH-43","Nong Khai","Province","Thailand",2 +"THA","TH","TH-44","Maha Sarakham","Province","Thailand",2 +"THA","TH","TH-45","Roi Et","Province","Thailand",2 +"THA","TH","TH-46","Kalasin","Province","Thailand",2 +"THA","TH","TH-47","Sakon Nakhon","Province","Thailand",2 +"THA","TH","TH-48","Nakhon Phanom","Province","Thailand",2 +"THA","TH","TH-49","Mukdahan","Province","Thailand",2 +"THA","TH","TH-50","Chiang Mai","Province","Thailand",2 +"THA","TH","TH-51","Lamphun","Province","Thailand",2 +"THA","TH","TH-52","Lampang","Province","Thailand",2 +"THA","TH","TH-53","Uttaradit","Province","Thailand",2 +"THA","TH","TH-54","Phrae","Province","Thailand",2 +"THA","TH","TH-55","Nan","Province","Thailand",2 +"THA","TH","TH-56","Phayao","Province","Thailand",2 +"THA","TH","TH-57","Chiang Rai","Province","Thailand",2 +"THA","TH","TH-58","Mae Hong Son","Province","Thailand",2 +"THA","TH","TH-60","Nakhon Sawan","Province","Thailand",2 +"THA","TH","TH-61","Uthai Thani","Province","Thailand",2 +"THA","TH","TH-62","Kamphaeng Phet","Province","Thailand",2 +"THA","TH","TH-63","Tak","Province","Thailand",2 +"THA","TH","TH-64","Sukhothai","Province","Thailand",2 +"THA","TH","TH-65","Phitsanulok","Province","Thailand",2 +"THA","TH","TH-66","Phichit","Province","Thailand",2 +"THA","TH","TH-67","Phetchabun","Province","Thailand",2 +"THA","TH","TH-70","Ratchaburi","Province","Thailand",2 +"THA","TH","TH-71","Kanchanaburi","Province","Thailand",2 +"THA","TH","TH-72","Suphan Buri","Province","Thailand",2 +"THA","TH","TH-73","Nakhon Pathom","Province","Thailand",2 +"THA","TH","TH-74","Samut Sakhon","Province","Thailand",2 +"THA","TH","TH-75","Samut Songkhram","Province","Thailand",2 +"THA","TH","TH-76","Phetchaburi","Province","Thailand",2 +"THA","TH","TH-77","Prachuap Khiri Khan","Province","Thailand",2 +"THA","TH","TH-80","Nakhon Si Thammarat","Province","Thailand",2 +"THA","TH","TH-81","Krabi","Province","Thailand",2 +"THA","TH","TH-82","Phangnga","Province","Thailand",2 +"THA","TH","TH-83","Phuket","Province","Thailand",2 +"THA","TH","TH-84","Surat Thani","Province","Thailand",2 +"THA","TH","TH-85","Ranong","Province","Thailand",2 +"THA","TH","TH-86","Chumphon","Province","Thailand",2 +"THA","TH","TH-90","Songkhla","Province","Thailand",2 +"THA","TH","TH-91","Satun","Province","Thailand",2 +"THA","TH","TH-92","Trang","Province","Thailand",2 +"THA","TH","TH-93","Phatthalung","Province","Thailand",2 +"THA","TH","TH-94","Pattani","Province","Thailand",2 +"THA","TH","TH-95","Yala","Province","Thailand",2 +"THA","TH","TH-96","Narathiwat","Province","Thailand",2 +"THA","TH","TH-S","Phatthaya","Province","Thailand",2 +"TJK","TJ","TJ-GB","Gorno-Badakhshan","Autonomous region","Tajikistan",2 +"TJK","TJ","TJ-KT","Khatlon","Region","Tajikistan",2 +"TJK","TJ","TJ-SU","Sughd","Region","Tajikistan",2 +"TLS","TL","TL-AL","Aileu","District","Timor-Leste",2 +"TLS","TL","TL-AN","Ainaro","District","Timor-Leste",2 +"TLS","TL","TL-BA","Baucau","District","Timor-Leste",2 +"TLS","TL","TL-BO","Bobonaro","District","Timor-Leste",2 +"TLS","TL","TL-CO","Cova Lima","District","Timor-Leste",2 +"TLS","TL","TL-DI","Díli","District","Timor-Leste",2 +"TLS","TL","TL-ER","Ermera","District","Timor-Leste",2 +"TLS","TL","TL-LA","Lautem","District","Timor-Leste",2 +"TLS","TL","TL-LI","Liquiça","District","Timor-Leste",2 +"TLS","TL","TL-MF","Manufahi","District","Timor-Leste",2 +"TLS","TL","TL-MT","Manatuto","District","Timor-Leste",2 +"TLS","TL","TL-OE","Oecussi","District","Timor-Leste",2 +"TLS","TL","TL-VI","Viqueque","District","Timor-Leste",2 +"TKM","TM","TM-A","Ahal","Region","Turkmenistan",2 +"TKM","TM","TM-B","Balkan","Region","Turkmenistan",2 +"TKM","TM","TM-D","Daşoguz","Region","Turkmenistan",2 +"TKM","TM","TM-L","Lebap","Region","Turkmenistan",2 +"TKM","TM","TM-M","Mary","Region","Turkmenistan",2 +"TKM","TM","TM-S","Aşgabat","City","Turkmenistan",2 +"TUN","TN","TN-11","Tunis","Governorate","Tunisia",2 +"TUN","TN","TN-12","Ariana","Governorate","Tunisia",2 +"TUN","TN","TN-13","Ben Arous","Governorate","Tunisia",2 +"TUN","TN","TN-14","La Manouba","Governorate","Tunisia",2 +"TUN","TN","TN-21","Nabeul","Governorate","Tunisia",2 +"TUN","TN","TN-22","Zaghouan","Governorate","Tunisia",2 +"TUN","TN","TN-23","Bizerte","Governorate","Tunisia",2 +"TUN","TN","TN-31","Béja","Governorate","Tunisia",2 +"TUN","TN","TN-32","Jendouba","Governorate","Tunisia",2 +"TUN","TN","TN-33","Le Kef","Governorate","Tunisia",2 +"TUN","TN","TN-34","Siliana","Governorate","Tunisia",2 +"TUN","TN","TN-41","Kairouan","Governorate","Tunisia",2 +"TUN","TN","TN-42","Kasserine","Governorate","Tunisia",2 +"TUN","TN","TN-43","Sidi Bouzid","Governorate","Tunisia",2 +"TUN","TN","TN-51","Sousse","Governorate","Tunisia",2 +"TUN","TN","TN-52","Monastir","Governorate","Tunisia",2 +"TUN","TN","TN-53","Mahdia","Governorate","Tunisia",2 +"TUN","TN","TN-61","Sfax","Governorate","Tunisia",2 +"TUN","TN","TN-71","Gafsa","Governorate","Tunisia",2 +"TUN","TN","TN-72","Tozeur","Governorate","Tunisia",2 +"TUN","TN","TN-73","Kebili","Governorate","Tunisia",2 +"TUN","TN","TN-81","Gabès","Governorate","Tunisia",2 +"TUN","TN","TN-82","Medenine","Governorate","Tunisia",2 +"TUN","TN","TN-83","Tataouine","Governorate","Tunisia",2 +"TON","TO","TO-01","'Eua","Division","Tonga",2 +"TON","TO","TO-02","Ha'apai","Division","Tonga",2 +"TON","TO","TO-03","Niuas","Division","Tonga",2 +"TON","TO","TO-04","Tongatapu","Division","Tonga",2 +"TON","TO","TO-05","Vava'u","Division","Tonga",2 +"TUR","TR","TR-01","Adana","Province","Turkey",2 +"TUR","TR","TR-02","Adıyaman","Province","Turkey",2 +"TUR","TR","TR-03","Afyonkarahisar","Province","Turkey",2 +"TUR","TR","TR-04","Ağrı","Province","Turkey",2 +"TUR","TR","TR-05","Amasya","Province","Turkey",2 +"TUR","TR","TR-06","Ankara","Province","Turkey",2 +"TUR","TR","TR-07","Antalya","Province","Turkey",2 +"TUR","TR","TR-08","Artvin","Province","Turkey",2 +"TUR","TR","TR-09","Aydın","Province","Turkey",2 +"TUR","TR","TR-10","Balıkesir","Province","Turkey",2 +"TUR","TR","TR-11","Bilecik","Province","Turkey",2 +"TUR","TR","TR-12","Bingöl","Province","Turkey",2 +"TUR","TR","TR-13","Bitlis","Province","Turkey",2 +"TUR","TR","TR-14","Bolu","Province","Turkey",2 +"TUR","TR","TR-15","Burdur","Province","Turkey",2 +"TUR","TR","TR-16","Bursa","Province","Turkey",2 +"TUR","TR","TR-17","Çanakkale","Province","Turkey",2 +"TUR","TR","TR-18","Çankırı","Province","Turkey",2 +"TUR","TR","TR-19","Çorum","Province","Turkey",2 +"TUR","TR","TR-20","Denizli","Province","Turkey",2 +"TUR","TR","TR-21","Diyarbakır","Province","Turkey",2 +"TUR","TR","TR-22","Edirne","Province","Turkey",2 +"TUR","TR","TR-23","Elazığ","Province","Turkey",2 +"TUR","TR","TR-24","Erzincan","Province","Turkey",2 +"TUR","TR","TR-25","Erzurum","Province","Turkey",2 +"TUR","TR","TR-26","Eskişehir","Province","Turkey",2 +"TUR","TR","TR-27","Gaziantep","Province","Turkey",2 +"TUR","TR","TR-28","Giresun","Province","Turkey",2 +"TUR","TR","TR-29","Gümüşhane","Province","Turkey",2 +"TUR","TR","TR-30","Hakkâri","Province","Turkey",2 +"TUR","TR","TR-31","Hatay","Province","Turkey",2 +"TUR","TR","TR-32","Isparta","Province","Turkey",2 +"TUR","TR","TR-33","Mersin","Province","Turkey",2 +"TUR","TR","TR-34","İstanbul","Province","Turkey",2 +"TUR","TR","TR-35","İzmir","Province","Turkey",2 +"TUR","TR","TR-36","Kars","Province","Turkey",2 +"TUR","TR","TR-37","Kastamonu","Province","Turkey",2 +"TUR","TR","TR-38","Kayseri","Province","Turkey",2 +"TUR","TR","TR-39","Kırklareli","Province","Turkey",2 +"TUR","TR","TR-40","Kırşehir","Province","Turkey",2 +"TUR","TR","TR-41","Kocaeli","Province","Turkey",2 +"TUR","TR","TR-42","Konya","Province","Turkey",2 +"TUR","TR","TR-43","Kütahya","Province","Turkey",2 +"TUR","TR","TR-44","Malatya","Province","Turkey",2 +"TUR","TR","TR-45","Manisa","Province","Turkey",2 +"TUR","TR","TR-46","Kahramanmaraş","Province","Turkey",2 +"TUR","TR","TR-47","Mardin","Province","Turkey",2 +"TUR","TR","TR-48","Muğla","Province","Turkey",2 +"TUR","TR","TR-49","Muş","Province","Turkey",2 +"TUR","TR","TR-50","Nevşehir","Province","Turkey",2 +"TUR","TR","TR-51","Niğde","Province","Turkey",2 +"TUR","TR","TR-52","Ordu","Province","Turkey",2 +"TUR","TR","TR-53","Rize","Province","Turkey",2 +"TUR","TR","TR-54","Sakarya","Province","Turkey",2 +"TUR","TR","TR-55","Samsun","Province","Turkey",2 +"TUR","TR","TR-56","Siirt","Province","Turkey",2 +"TUR","TR","TR-57","Sinop","Province","Turkey",2 +"TUR","TR","TR-58","Sivas","Province","Turkey",2 +"TUR","TR","TR-59","Tekirdağ","Province","Turkey",2 +"TUR","TR","TR-60","Tokat","Province","Turkey",2 +"TUR","TR","TR-61","Trabzon","Province","Turkey",2 +"TUR","TR","TR-62","Tunceli","Province","Turkey",2 +"TUR","TR","TR-63","Şanlıurfa","Province","Turkey",2 +"TUR","TR","TR-64","Uşak","Province","Turkey",2 +"TUR","TR","TR-65","Van","Province","Turkey",2 +"TUR","TR","TR-66","Yozgat","Province","Turkey",2 +"TUR","TR","TR-67","Zonguldak","Province","Turkey",2 +"TUR","TR","TR-68","Aksaray","Province","Turkey",2 +"TUR","TR","TR-69","Bayburt","Province","Turkey",2 +"TUR","TR","TR-70","Karaman","Province","Turkey",2 +"TUR","TR","TR-71","Kırıkkale","Province","Turkey",2 +"TUR","TR","TR-72","Batman","Province","Turkey",2 +"TUR","TR","TR-73","Şırnak","Province","Turkey",2 +"TUR","TR","TR-74","Bartın","Province","Turkey",2 +"TUR","TR","TR-75","Ardahan","Province","Turkey",2 +"TUR","TR","TR-76","Iğdır","Province","Turkey",2 +"TUR","TR","TR-77","Yalova","Province","Turkey",2 +"TUR","TR","TR-78","Karabük","Province","Turkey",2 +"TUR","TR","TR-79","Kilis","Province","Turkey",2 +"TUR","TR","TR-80","Osmaniye","Province","Turkey",2 +"TUR","TR","TR-81","Düzce","Province","Turkey",2 +"TTO","TT","TT-ARI","Arima","Borough","Trinidad and Tobago",2 +"TTO","TT","TT-CHA","Chaguanas","Borough","Trinidad and Tobago",2 +"TTO","TT","TT-CTT","Couva-Tabaquite-Talparo","Region","Trinidad and Tobago",2 +"TTO","TT","TT-DMN","Diego Martin","Region","Trinidad and Tobago",2 +"TTO","TT","TT-ETO","Eastern Tobago","Region","Trinidad and Tobago",2 +"TTO","TT","TT-PED","Penal-Debe","Region","Trinidad and Tobago",2 +"TTO","TT","TT-POS","Port of Spain","City","Trinidad and Tobago",2 +"TTO","TT","TT-PRT","Princes Town","Region","Trinidad and Tobago",2 +"TTO","TT","TT-PTF","Point Fortin","Borough","Trinidad and Tobago",2 +"TTO","TT","TT-RCM","Rio Claro-Mayaro","Region","Trinidad and Tobago",2 +"TTO","TT","TT-SFO","San Fernando","City","Trinidad and Tobago",2 +"TTO","TT","TT-SGE","Sangre Grande","Region","Trinidad and Tobago",2 +"TTO","TT","TT-SIP","Siparia","Region","Trinidad and Tobago",2 +"TTO","TT","TT-SJL","San Juan-Laventille","Region","Trinidad and Tobago",2 +"TTO","TT","TT-TUP","Tunapuna-Piarco","Region","Trinidad and Tobago",2 +"TTO","TT","TT-WTO","Western Tobago","Region","Trinidad and Tobago",2 +"TUV","TV","TV-FUN","Funafuti","Town council","Tuvalu",2 +"TUV","TV","TV-NIT","Niutao","Island council","Tuvalu",2 +"TUV","TV","TV-NKF","Nukufetau","Island council","Tuvalu",2 +"TUV","TV","TV-NKL","Nukulaelae","Island council","Tuvalu",2 +"TUV","TV","TV-NMA","Nanumea","Island council","Tuvalu",2 +"TUV","TV","TV-NMG","Nanumanga","Island council","Tuvalu",2 +"TUV","TV","TV-NUI","Nui","Island council","Tuvalu",2 +"TUV","TV","TV-VAI","Vaitupu","Island council","Tuvalu",2 +"TWN","TW","TW-CHA","Changhua","District","Taiwan",2 +"TWN","TW","TW-CYI","Chiay City","Municipality","Taiwan",2 +"TWN","TW","TW-CYQ","Chiayi","District","Taiwan",2 +"TWN","TW","TW-HSQ","Hsinchu","District","Taiwan",2 +"TWN","TW","TW-HSZ","Hsinchui City","Municipality","Taiwan",2 +"TWN","TW","TW-HUA","Hualien","District","Taiwan",2 +"TWN","TW","TW-ILA","Ilan","District","Taiwan",2 +"TWN","TW","TW-KEE","Keelung City","Municipality","Taiwan",2 +"TWN","TW","TW-KHH","Kaohsiung City","Special Municipality","Taiwan",2 +"TWN","TW","TW-KHQ","Kaohsiung","District","Taiwan",2 +"TWN","TW","TW-MIA","Miaoli","District","Taiwan",2 +"TWN","TW","TW-NAN","Nantou","District","Taiwan",2 +"TWN","TW","TW-PEN","Penghu","District","Taiwan",2 +"TWN","TW","TW-PIF","Pingtung","District","Taiwan",2 +"TWN","TW","TW-TAO","Taoyuan","District","Taiwan",2 +"TWN","TW","TW-TNN","Tainan City","Municipality","Taiwan",2 +"TWN","TW","TW-TNQ","Tainan","District","Taiwan",2 +"TWN","TW","TW-TPE","Taipei City","Special Municipality","Taiwan",2 +"TWN","TW","TW-TPQ","Taipei","District","Taiwan",2 +"TWN","TW","TW-TTT","Taitung","District","Taiwan",2 +"TWN","TW","TW-TXG","Taichung City","Municipality","Taiwan",2 +"TWN","TW","TW-TXQ","Taichung","District","Taiwan",2 +"TWN","TW","TW-YUN","Yunlin","District","Taiwan",2 +"TZA","TZ","TZ-01","Arusha","Region","Tanzania",2 +"TZA","TZ","TZ-02","Dar-es-Salaam","Region","Tanzania",2 +"TZA","TZ","TZ-03","Dodoma","Region","Tanzania",2 +"TZA","TZ","TZ-04","Iringa","Region","Tanzania",2 +"TZA","TZ","TZ-05","Kagera","Region","Tanzania",2 +"TZA","TZ","TZ-06","Kaskazini Pemba","Region","Tanzania",2 +"TZA","TZ","TZ-07","Kaskazini Unguja","Region","Tanzania",2 +"TZA","TZ","TZ-08","Kigoma","Region","Tanzania",2 +"TZA","TZ","TZ-09","Kilimanjaro","Region","Tanzania",2 +"TZA","TZ","TZ-10","Kusini Pemba","Region","Tanzania",2 +"TZA","TZ","TZ-11","Kusini Unguja","Region","Tanzania",2 +"TZA","TZ","TZ-12","Lindi","Region","Tanzania",2 +"TZA","TZ","TZ-13","Mara","Region","Tanzania",2 +"TZA","TZ","TZ-14","Mbeya","Region","Tanzania",2 +"TZA","TZ","TZ-15","Mjini Magharibi","Region","Tanzania",2 +"TZA","TZ","TZ-16","Morogoro","Region","Tanzania",2 +"TZA","TZ","TZ-17","Mtwara","Region","Tanzania",2 +"TZA","TZ","TZ-18","Mwanza","Region","Tanzania",2 +"TZA","TZ","TZ-19","Pwani","Region","Tanzania",2 +"TZA","TZ","TZ-20","Rukwa","Region","Tanzania",2 +"TZA","TZ","TZ-21","Ruvuma","Region","Tanzania",2 +"TZA","TZ","TZ-22","Shinyanga","Region","Tanzania",2 +"TZA","TZ","TZ-23","Singida","Region","Tanzania",2 +"TZA","TZ","TZ-24","Tabora","Region","Tanzania",2 +"TZA","TZ","TZ-25","Tanga","Region","Tanzania",2 +"TZA","TZ","TZ-26","Manyara","Region","Tanzania",2 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+"UKR","UA","UA-48","Mykolaïvs'ka Oblast'","Province","Ukraine",2 +"UKR","UA","UA-51","Odes'ka Oblast'","Province","Ukraine",2 +"UKR","UA","UA-53","Poltavs'ka Oblast'","Province","Ukraine",2 +"UKR","UA","UA-56","Rivnens'ka Oblast'","Province","Ukraine",2 +"UKR","UA","UA-59","Sums 'ka Oblast'","Province","Ukraine",2 +"UKR","UA","UA-61","Ternopil's'ka Oblast'","Province","Ukraine",2 +"UKR","UA","UA-63","Kharkivs'ka Oblast'","Province","Ukraine",2 +"UKR","UA","UA-65","Khersons'ka Oblast'","Province","Ukraine",2 +"UKR","UA","UA-68","Khmel'nyts'ka Oblast'","Province","Ukraine",2 +"UKR","UA","UA-71","Cherkas'ka Oblast'","Province","Ukraine",2 +"UKR","UA","UA-74","Chernihivs'ka Oblast'","Province","Ukraine",2 +"UKR","UA","UA-77","Chernivets'ka Oblast'","Province","Ukraine",2 +"UGA","UG","UG-101","Kalangala","District","Uganda",2 +"UGA","UG","UG-102","Kampala","District","Uganda",2 +"UGA","UG","UG-103","Kiboga","District","Uganda",2 +"UGA","UG","UG-104","Luwero","District","Uganda",2 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States",2 +"USA","US","US-IA","Iowa","State","United States",2 +"USA","US","US-ID","Idaho","State","United States",2 +"USA","US","US-IL","Illinois","State","United States",2 +"USA","US","US-IN","Indiana","State","United States",2 +"USA","US","US-KS","Kansas","State","United States",2 +"USA","US","US-KY","Kentucky","State","United States",2 +"USA","US","US-LA","Louisiana","State","United States",2 +"USA","US","US-MA","Massachusetts","State","United States",2 +"USA","US","US-MD","Maryland","State","United States",2 +"USA","US","US-ME","Maine","State","United States",2 +"USA","US","US-MI","Michigan","State","United States",2 +"USA","US","US-MN","Minnesota","State","United States",2 +"USA","US","US-MO","Missouri","State","United States",2 +"USA","US","US-MP","Northern Mariana Islands","Outlying area","United States",2 +"USA","US","US-MS","Mississippi","State","United States",2 +"USA","US","US-MT","Montana","State","United States",2 +"USA","US","US-NC","North Carolina","State","United States",2 +"USA","US","US-ND","North Dakota","State","United States",2 +"USA","US","US-NE","Nebraska","State","United States",2 +"USA","US","US-NH","New Hampshire","State","United States",2 +"USA","US","US-NJ","New Jersey","State","United States",2 +"USA","US","US-NM","New Mexico","State","United States",2 +"USA","US","US-NV","Nevada","State","United States",2 +"USA","US","US-NY","New York","State","United States",2 +"USA","US","US-OH","Ohio","State","United States",2 +"USA","US","US-OK","Oklahoma","State","United States",2 +"USA","US","US-OR","Oregon","State","United States",2 +"USA","US","US-PA","Pennsylvania","State","United States",2 +"USA","US","US-PR","Puerto Rico","Outlying area","United States",2 +"USA","US","US-RI","Rhode Island","State","United States",2 +"USA","US","US-SC","South Carolina","State","United States",2 +"USA","US","US-SD","South Dakota","State","United States",2 +"USA","US","US-TN","Tennessee","State","United States",2 +"USA","US","US-TX","Texas","State","United States",2 +"USA","US","US-UM","United States Minor Outlying Islands","Outlying area","United States",2 +"USA","US","US-UT","Utah","State","United States",2 +"USA","US","US-VA","Virginia","State","United States",2 +"USA","US","US-VI","Virgin Islands","Outlying area","United States",2 +"USA","US","US-VT","Vermont","State","United States",2 +"USA","US","US-WA","Washington","State","United States",2 +"USA","US","US-WI","Wisconsin","State","United States",2 +"USA","US","US-WV","West Virginia","State","United States",2 +"USA","US","US-WY","Wyoming","State","United States",2 +"URY","UY","UY-AR","Artigas","Department","Uruguay",2 +"URY","UY","UY-CA","Canelones","Department","Uruguay",2 +"URY","UY","UY-CL","Cerro Largo","Department","Uruguay",2 +"URY","UY","UY-CO","Colonia","Department","Uruguay",2 +"URY","UY","UY-DU","Durazno","Department","Uruguay",2 +"URY","UY","UY-FD","Florida","Department","Uruguay",2 +"URY","UY","UY-FS","Flores","Department","Uruguay",2 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a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/AnIndex b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/AnIndex new file mode 100644 index 000000000..e69de29bb diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/aliases.rds b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/aliases.rds new file mode 100644 index 000000000..b1ab83d07 Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/aliases.rds differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/globaltoolboxlite.rdb b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/globaltoolboxlite.rdb new file mode 100644 index 000000000..e69de29bb diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/globaltoolboxlite.rdx b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/globaltoolboxlite.rdx new file mode 100644 index 000000000..66cf8133a Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/globaltoolboxlite.rdx differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/paths.rds b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/paths.rds new file mode 100644 index 000000000..ce327e040 Binary files /dev/null and b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/help/paths.rds differ diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/html/00Index.html b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/html/00Index.html new file mode 100644 index 000000000..d8b71fcb0 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/html/00Index.html @@ -0,0 +1,23 @@ + + +R: Identify Location Names and Link with Other Data, lite version + + + +

Identify Location Names and Link with Other Data, lite version + +

+
+
+[Up] +[Top] +

Documentation for package ‘globaltoolboxlite’ version 0.0.0.9000

+ + + +

Help Pages

+ + +There are no help pages in this package + diff --git a/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/html/R.css b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/html/R.css new file mode 100644 index 000000000..f10f5ea66 --- /dev/null +++ b/packrat/lib/x86_64-pc-linux-gnu/3.6.3/globaltoolboxlite/html/R.css @@ -0,0 +1,97 @@ +body { + background: white; + color: black; +} + +a:link { + background: white; + color: blue; +} + +a:visited { + background: white; + color: rgb(50%, 0%, 50%); +} + +h1 { + background: white; + color: rgb(55%, 55%, 55%); + font-family: monospace; + font-size: x-large; + text-align: center; +} + +h2 { + background: white; + color: rgb(40%, 40%, 40%); + font-family: monospace; + font-size: large; + text-align: center; +} + +h3 { + background: white; + color: rgb(40%, 40%, 40%); + font-family: monospace; + font-size: large; +} + +h4 { + background: white; + color: rgb(40%, 40%, 40%); + font-family: monospace; + font-style: italic; + font-size: 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+78000,0.49894541692599875,0.010547869855155424,0.08786314574696748,0.41244665090062294,0.029145843921922435,0.013407628097723414,0.021140328174854915,0.1760977108243464,0.8239022891756536,0.33171864806500373,0.460018523863661,1.046595949165634,0.010098041051706573,1.0476749128202962,0.08405206988062329,1.0218270517493733,0.48829110990902336,1.004694662577577,0.02915578159137823,1.0267085437640042,0.013054262827494433 diff --git a/sample_data/param-age-dist.rds b/sample_data/param-age-dist.rds new file mode 100644 index 000000000..ad23f2117 Binary files /dev/null and b/sample_data/param-age-dist.rds differ diff --git a/sample_data/united-states-commutes/census_tracts_island_areas_2010.csv b/sample_data/united-states-commutes/census_tracts_island_areas_2010.csv new file mode 100644 index 000000000..40713b038 --- /dev/null +++ b/sample_data/united-states-commutes/census_tracts_island_areas_2010.csv @@ -0,0 +1,5 @@ +USPS,geoid,population +"AS","60000",55519 +"MP","69000",53883 +"GU","66000",159385 +"VI","78000",106405 \ No newline at end of file diff --git a/scripts/QuantileSummarizeGeoExtent.R b/scripts/QuantileSummarizeGeoExtent.R new file mode 100644 index 000000000..dd2e17a32 --- /dev/null +++ b/scripts/QuantileSummarizeGeoExtent.R @@ -0,0 +1,119 @@ +## First parse the options to the scripts +suppressMessages({ + library(optparse, quietly=TRUE) + library(tidyverse, quietly=TRUE) + library(parallel, quietly=TRUE) +}) + +##List of specified options +option_list <- list( + make_option(c("-c", "--config"), action="store", default=Sys.getenv("CONFIG_PATH"), type='character', help="path to the config file"), + make_option(c("-j", "--jobs"), action="store", default=detectCores(), type='numeric', help="number of cores used"), + make_option(c("-n", "--num_simulations"), action="store", default=-1, type='numeric', help="number of simulations to run, overrides config file value"), + + make_option(c("-d", "--name_filter"), type="character", default="", help="filename filter, usually deaths"), + make_option(c("-o","--outfile"), type="character", default=NULL, help="file to save output"), + make_option("--start_date", type="character", default=NULL, help="earliest date to include"), + make_option("--end_date", type="character", default=NULL, help="latest date to include") +) + +opt_parser <- OptionParser(option_list = option_list, usage="%prog [options] [one or more scenarios]") +arguments <- parse_args(opt_parser, positional_arguments=TRUE) +opts <- arguments$options + +scenarios <- arguments$args + +if(is.null(opts$outfile)) { + stop("outfile must be specified") +} + +config <- covidcommon::load_config(opts$c) +if (length(config) == 0) { + stop("no configuration found -- please set CONFIG_PATH environment variable or use the -c command flag") +} + + +## Register the parallel backend +doParallel::registerDoParallel(opts$j) + + +##Convert times to date objects +if (is.null(opts$start_date)) { + opts$start_date <- as.Date(config$start_date) +} +opts$start_date <- as.Date(opts$start_date) + +if (is.null(opts$end_date)) { + opts$end_date <- config$end_date +} +opts$end_date <- as.Date(opts$end_date) + +##Per file filtering code +post_proc <- function(x, opts) { + + + x%>% + group_by(geoid) %>% + mutate(cum_infections=cumsum(incidI)) %>% + mutate(cum_death=cumsum(incidD)) %>% + ungroup()%>% + filter(time>=opts$start_date & time<=opts$end_date) %>% + group_by(time) %>% + summarize(hosp_curr=sum(hosp_curr), + cum_death=sum(cum_death), + hosp=sum(incidH), + death=sum(incidD), + infections=sum(incidI), + cum_infections=sum(cum_infections)) %>% + ungroup() +} + +##Run over scenarios and death rates as appropriate. Note that +##Final results will average accross whatever is included +res_all <-list() +setup_name <- config$spatial_setup$setup_name +for (i in 1:length(scenarios)) { + scenario_dir = paste0(setup_name,"_",scenarios[i]) + res_all[[i]] <- report.generation::load_hosp_sims_filtered(scenario_dir, + name_filter = opts$name_filter, + num_files = ifelse(opts$num_simulations > 0, opts$num_simulations, config$nsimulations), + post_process = post_proc, + opt=opts)%>% + mutate(scenario=scenarios[i]) + + +} + +##Put in one data frame +res_all<-dplyr::bind_rows(res_all) + +##deregister backend +doParallel::stopImplicitCluster() + + +## Extract quantiles +tmp_col <- function(x, col) { + x%>% + group_by(time) %>% + summarize(x=list(enframe(quantile(!!sym(col), probs=c(0.01, 0.025, + seq(0.05, 0.95, by = 0.05), 0.975, 0.99)), + "quantile",col))) %>% + unnest(x) + +} + + +to_save <- inner_join(tmp_col(res_all,"hosp_curr"), + tmp_col(res_all,"cum_death"))%>% + inner_join(tmp_col(res_all,"death"))%>% + inner_join(tmp_col(res_all,"infections"))%>% + inner_join(tmp_col(res_all,"cum_infections"))%>% + inner_join(tmp_col(res_all,"hosp")) + + +write_csv(to_save, path=opts$outfile) + + + + + diff --git a/scripts/QuantileSummarizeGeoidLevel.R b/scripts/QuantileSummarizeGeoidLevel.R new file mode 100644 index 000000000..3a308ffae --- /dev/null +++ b/scripts/QuantileSummarizeGeoidLevel.R @@ -0,0 +1,103 @@ + +# XXX: this branch was in a transitory state before packrat, so these packages need to be installed to run this script: +# install.packages("tdigest") +# +# TODO: update dependencies + +PROBS = c(0.01, 0.025, seq(0.05, 0.95, by = 0.05), 0.975, 0.99) + +suppressMessages({ + library(optparse, quietly=TRUE) + library(tidyverse, quietly=TRUE) + library(tdigest) + library(scales) + library(parallel) + library(doParallel) + library(data.table) +}) + +option_list <- list( + make_option(c("-c", "--config"), action="store", default=Sys.getenv("CONFIG_PATH"), type='character', help="path to the config file"), + make_option(c("-j", "--jobs"), action="store", default=detectCores(), type='numeric', help="number of cores used"), + make_option(c("-n", "--num_simulations"), action="store", default=-1, type='numeric', help="number of simulations to run, overrides config file value"), + + make_option(c("-d", "--name_filter"), type="character", default="", help="filename filter, usually deaths"), + make_option(c("-o","--outfile"), type="character", default=NULL, help="file to save output"), + make_option("--start_date", type="character", default=NULL, help="earliest date to include"), + make_option("--end_date", type="character", default=NULL, help="latest date to include") +) + +opt_parser <- OptionParser(option_list = option_list, usage="%prog [options] [one or more scenarios]") + +## Paerse the +arguments <- parse_args(opt_parser, positional_arguments=TRUE) +opt <- arguments$options +scenarios <- arguments$args + +if (is.null(opt$outfile)) { + stop("outfile must be specified") +} + +cl = makeCluster(opt$jobs, outfile="") +doParallel::registerDoParallel(cl) + +config <- covidcommon::load_config(opt$c) +if (length(config) == 0) { + stop("no configuration found -- please set CONFIG_PATH environment variable or use the -c command flag") +} + +##Load the geodata file +suppressMessages(geodata <- readr::read_csv(paste0(config$spatial_setup$base_path,"/",config$spatial_setup$geodata))) + + +##Convert times to date objects +if (is.null(opt$start_date)) { + opt$start_date <- as.Date(config$start_date) +} +opt$start_date <- as.Date(opt$start_date) + +if (is.null(opt$end_date)) { + opt$end_date <- config$end_date +} +opt$end_date <- as.Date(opt$end_date) + +post_proc <- function(x, geodata, opt) { + x %>% + group_by(geoid) %>% + mutate(cum_infections=cumsum(incidI)) %>% + mutate(cum_death=cumsum(incidD)) %>% + ungroup() %>% + filter(time >= opt$start_date & time <= opt$end_date) %>% + rename(infections=incidI, death=incidD, hosp=incidH) +} + +setup_name <- config$spatial_setup$setup_name +scenarios <- scenarios %>% lapply(function(x) { paste0(setup_name,"_",x)}) %>% unlist() +res_geoid <- data.table::rbindlist(purrr::pmap(data.frame(scenario=scenarios), function(scenario) { + report.generation::load_hosp_sims_filtered(scenario, + name_filter=opt$name_filter, + num_files=opt$num_simulations, + post_process=post_proc, + geodata=geodata, + opt=opt) +})) + +q <- function(col) { + # if col is empty, tquantile fails; in that case, return what quantile() would (all 0's) + tryCatch(tquantile(tdigest(col), PROBS), error = function(e) { quantile(col, PROBS) }) +} + +res_split <- split(res_geoid, res_geoid$time) +to_save_geo <- foreach(r_split=res_split, .combine=rbind, .packages="data.table", .inorder=FALSE, .multicombine=TRUE, .verbose=TRUE) %dopar% { + stopifnot(is.data.table(r_split)) + r_split[, .(quantile=scales::percent(PROBS), + hosp_curr=q(hosp_curr), + cum_death=q(cum_death), + death=q(death), + infections=q(infections), + cum_infections=q(cum_infections), + hosp=q(hosp)), by=list(time, geoid)] +} +data.table::fwrite(to_save_geo, file=opt$outfile) + +stopCluster(cl) diff --git a/scripts/QuantileSummarizeStateLevel.R b/scripts/QuantileSummarizeStateLevel.R new file mode 100644 index 000000000..25d1efb00 --- /dev/null +++ b/scripts/QuantileSummarizeStateLevel.R @@ -0,0 +1,126 @@ +## First parse the options to the scripts +suppressMessages({ + library(optparse, quietly=TRUE) + library(tidyverse, quietly=TRUE) + library(parallel, quietly=TRUE) +}) + +##List of specified options +option_list <- list( + make_option(c("-c", "--config"), action="store", default=Sys.getenv("CONFIG_PATH"), type='character', help="path to the config file"), + make_option(c("-j", "--jobs"), action="store", default=detectCores(), type='numeric', help="number of cores used"), + make_option(c("-n", "--num_simulations"), action="store", default=-1, type='numeric', help="number of simulations to run, overrides config file value"), + + make_option(c("-d", "--name_filter"), type="character", default="", help="filename filter, usually deaths"), + make_option(c("-o","--outfile"), type="character", default=NULL, help="file to save output"), + make_option("--start_date", type="character", default=NULL, help="earliest date to include"), + make_option("--end_date", type="character", default=NULL, help="latest date to include") +) + +opt_parser <- OptionParser(option_list = option_list, usage="%prog [options] [one or more scenarios]") + +## Paerse the +arguments <- parse_args(opt_parser, positional_arguments=c(1,Inf)) +opt <- arguments$options +scenarios <- arguments$args + +if(is.null(opt$outfile)) { + stop("outfile must be specified") +} + +config <- covidcommon::load_config(opt$c) +if (length(config) == 0) { + stop("no configuration found -- please set CONFIG_PATH environment variable or use the -c command flag") +} + +##Load the geodata file +suppressMessages(geodata <- readr::read_csv(paste0(config$spatial_setup$base_path,"/",config$spatial_setup$geodata))) +geodata <- geodata %>% mutate(geoid=as.character(geoid)) + +## Register the parallel backend +doParallel::registerDoParallel(opt$jobs) + + +##Convert times to date objects +if (is.null(opt$start_date)) { + opt$start_date <- as.Date(config$start_date) +} +opt$start_date <- as.Date(opt$start_date) + +if (is.null(opt$end_date)) { + opt$end_date <- config$end_date +} +opt$end_date <- as.Date(opt$end_date) + + +##Per file filtering code +post_proc <- function(x,geodata,opt) { + + + x%>% + group_by(geoid) %>% + mutate(cum_infections=cumsum(incidI)) %>% + mutate(cum_death=cumsum(incidD)) %>% + ungroup()%>% + filter(time>=opt$start_date& time<=opt$end_date) %>% + inner_join(geodata%>%select(geoid, USPS)) %>% + group_by(USPS, time) %>% + summarize(hosp_curr=sum(hosp_curr), + cum_death=sum(cum_death), + death=sum(incidD), + hosp=sum(incidH), + infections=sum(incidI), + cum_infections=sum(cum_infections)) %>% + ungroup() +} + +##Run over scenarios and death rates as appropriate. Note that +##Final results will average accross whatever is included +res_state <-list() +setup_name <- config$spatial_setup$setup_name +for (i in 1:length(scenarios)) { + scenario_dir = paste0(setup_name,"_",scenarios[i]) + res_state[[i]] <- report.generation::load_hosp_sims_filtered(scenario_dir, + name_filter = opt$name_filter, + ifelse(opt$num_simulations > 0, opt$num_simulations, config$nsimulations), + post_process = post_proc, + geodata=geodata, + opt=opt)%>% + mutate(scenario=scenarios[i]) + + +} + +##Put in one data frame +res_state<-dplyr::bind_rows(res_state) + +##deregister backend +doParallel::stopImplicitCluster() + + +## Extract quantiles +tmp_col <- function(x, col) { + x%>% + group_by(time,USPS) %>% + summarize(x=list(enframe(quantile(!!sym(col), probs=c(0.01, 0.025, + seq(0.05, 0.95, by = 0.05), 0.975, 0.99)), + "quantile",col))) %>% + unnest(x) + +} + + +to_save_st <- inner_join(tmp_col(res_state,"hosp_curr"), + tmp_col(res_state,"cum_death"))%>% + inner_join(tmp_col(res_state,"death"))%>% + inner_join(tmp_col(res_state,"infections"))%>% + inner_join(tmp_col(res_state,"cum_infections"))%>% + inner_join(tmp_col(res_state,"hosp")) + + +write_csv(to_save_st, path=opt$outfile) + + + + + diff --git a/scripts/quantile_summarize_geoid_level.py b/scripts/quantile_summarize_geoid_level.py new file mode 100644 index 000000000..4ff310e67 --- /dev/null +++ b/scripts/quantile_summarize_geoid_level.py @@ -0,0 +1,84 @@ +#!/opt/spark/bin/spark-submit +""" +A faster and distributed version of QuantileSummarizeGeoidLevel.R, which uses Apache Spark as its execution engine + +This script can be executed from the command line in the container by running Apache Spark locally: +% /opt/spark/bin/spark-submit --driver-memory 20g --executor-memory 20g \ + quantile_summarize_geoid_level.py USA_None -c config.yml -o usa_none.csv +""" + +import itertools +import pathlib +import re + +import click +import confuse +import numpy as np +from pyspark.sql import functions as F, SparkSession, SQLContext, Window + +PROBS = np.concatenate([[0.01, 0.025], np.arange(start=0.05, stop=0.95, step=0.05), [0.975, 0.99]]) +METRICS = ["hosp_curr", "cum_death", "death", "infections", "cum_infections", "hosp"] + +spark = (SparkSession.builder.appName("quantile report").getOrCreate()) +sc = spark.sparkContext +sc.setLogLevel("WARN") +sqlContext = SQLContext(sc) + + +@click.command() +@click.option("-c", "--config", "config_file", envvar="CONFIG_PATH", type=click.Path(exists=True), required=True, + help="configuration file for this simulation") +@click.option("-d", "--name_filter", type=str, default=".*", metavar="REGEX", + help="only process files matching this filter") +@click.option("-o", "--output", type=pathlib.Path, required=True, + help="write output to this directory") +@click.option("--start_date", type=click.DateTime(formats=["%Y-%m-%d"]), + default="2020-01-01", show_default=True, + help="earliest date to include") +@click.option("--end_date", type=click.DateTime(formats=["%Y-%m-%d"]), + default="2022-01-01", show_default=True, + help="latest date to include") +@click.argument("scenarios", type=str, nargs=-1, required=True) +def process(config_file, scenarios, output, start_date, end_date, name_filter): + config = confuse.Configuration("COVIDScenarioPipeline") + config.set_file(config_file) + + input_paths = (f"{config['spatial_setup']['setup_name'].get()}_{scenario}" for scenario in scenarios) + paths = itertools.chain(*(pathlib.Path("hospitalization/model_output").glob(p + "/**/*.parquet") + for p in input_paths)) + paths = (str(p) for p in paths if p.is_file()) + paths = filter(lambda p: re.search(name_filter, p), paths) + paths = list(paths) + if not paths: + raise click.BadParameter("no files found in input path") + + df = sqlContext.read.parquet(*paths) + df = df.withColumnRenamed("incidI", "infections") \ + .withColumnRenamed("incidD", "death") \ + .withColumnRenamed("incidH", "hosp") + df = df.filter((df.time > start_date.date()) & (df.time <= end_date.date())) + df = df.withColumn("cum_infections", F.sum(df.infections).over( + Window.partitionBy(df.geoid).orderBy(df.time, df.uid))) + df = df.withColumn("cum_death", F.sum(df.death).over( + Window.partitionBy(df.geoid).orderBy(df.time, df.uid))) + + # construct gnarly spark sql statement to compute quantiles via percentile_approx() + df.registerTempTable("df") + agg_sql = ", ".join(f"percentile_approx({metric}, {prob}, 100) AS {metric}__{str(round(prob, 3)).replace('.', '_')}" + for metric, prob in itertools.product(METRICS, PROBS)) + rollup_df = sqlContext.sql(f"""\ +SELECT geoid, time, {agg_sql} FROM df +GROUP BY geoid, time +""") + + # perform the final transform from column-wise to row-wise on the driver node + result_df = rollup_df.coalesce(1).toPandas() + result_df = result_df.melt(id_vars=["geoid", "time"]) + result_df["variable"], result_df["quantile"] = result_df["variable"].apply(lambda x: x.split("__")).str + result_df["quantile"] = result_df["quantile"].apply(lambda x: float(x.replace("_", "."))) + result_df = result_df.pivot_table(index=["geoid", "time", "quantile"], columns=["variable"], values="value") + + result_df.to_csv(output) + + +process() diff --git a/setup.py b/setup.py new file mode 100644 index 000000000..757141ef5 --- /dev/null +++ b/setup.py @@ -0,0 +1,23 @@ +import setuptools + +from SEIR.steps_source import cc as steps_cc + +with open("requirements.txt") as f: + requirements = f.read().splitlines() + +setuptools.setup( + name="SEIR", + version="0.1", + author="Joshua Kaminsky", + author_email="jkaminsky@jhu.edu", + description="SEIR simulation", + packages=setuptools.find_packages(exclude=["*.test*"]), + ext_modules=[steps_cc.distutils_extension()], + license="LICENSE", + install_requires=requirements, + python_requires='>=3.7', + zip_safe=True, + scripts=[ + "SEIR/simulate.py" + ], +) diff --git a/test/run_tests.py b/test/run_tests.py index 72de03cfc..f50ebaa47 100644 --- a/test/run_tests.py +++ b/test/run_tests.py @@ -21,7 +21,7 @@ def _success(test_dir): # Make Makefile cmd = ["Rscript", "../../R/scripts/make_makefile.R", - "-c", f"config.yml", + "-c", "config.yml", "-p", "../..", "-n", str(multiprocessing.cpu_count()), "-y", sys.executable] @@ -45,6 +45,112 @@ def teardown_function(self): os.chdir("..") + +# Test other scripts ------------------------------------------------------------ + +# Test build_US_setup +def _success_build_US_setup(test_dir): + os.chdir(test_dir) + + # Run Build Script + cmd = ["Rscript", "../../R/scripts/build_US_setup.R", + "-c", "config.yml", + "-p", "../..", + "-w", "FALSE"] + complete = subprocess.run(cmd) + assert complete.returncode == 0, f"build_US_setup.R failed with code {complete.returncode}" + + assert_file("data/mobility.csv") + assert_file("data/geodata.csv") + + +# Test build_nonUS_setup +def _success_build_nonUS_setup(test_dir): + os.chdir(test_dir) + + # Run Build script + cmd = ["Rscript", "../../R/scripts/build_nonUS_setup.R", + "-c", "config.yml", + "-w", "FALSE", + "-n", "population_data.csv", + "-m", "mobility_data.csv"] + complete = subprocess.run(cmd) + assert complete.returncode == 0, f"build_nonUS_setup.R failed with code {complete.returncode}" + + assert_file("data/mobility.csv") + assert_file("data/geodata.csv") + + + +# Test create_seeding_US +def _success_create_seeding_US(test_dir): + os.chdir(test_dir) + + # Run Seeding script + cmd = ["Rscript", "../../R/scripts/create_seeding.R", + "-c", "config.yml", + "-s", "CSSE"] + complete = subprocess.run(cmd) + assert complete.returncode == 0, f"create_seeding.R failed for US setup using JHU CSSE data with code {complete.returncode}" + + assert_file("data/seeding.csv") + + +# Test create_seeding_nonUS +def _success_create_seeding_nonUS(test_dir): + os.chdir(test_dir) + + # Make Makefile + cmd = ["Rscript", "../../R/scripts/create_seeding.R", + "-c", "config.yml", + "-d", "data/case_data/case_data.csv"] + complete = subprocess.run(cmd) + assert complete.returncode == 0, f"create_seeding.R failed for non-US setup with code {complete.returncode}" + + assert_file("data/seeding.csv") + +# Test runs 2x in a row +def _success_x2(test_dir): + os.chdir(test_dir) + subprocess.run(["make", "clean"]) + + # Make Makefile + cmd = ["Rscript", "../../R/scripts/make_makefile.R", + "-c", "config.yml", + "-p", "../..", + "-n", str(multiprocessing.cpu_count()), + "-y", sys.executable] + complete = subprocess.run(cmd) + assert complete.returncode == 0, f"make_makefile.R failed with code {complete.returncode}" + + assert_file("Makefile") + + # Run the Makefile + cmd = ["make"] + complete = subprocess.run(cmd) + assert complete.returncode == 0, f"make failed with code {complete.returncode}" + + assert_dir("model_parameters") + assert_dir("model_output") + assert_dir("hospitalization") + + # Make clean + subprocess.run(["make", "clean"]) + + # Run the Makefile a second time + cmd = ["make"] + complete = subprocess.run(cmd) + assert complete.returncode == 0, f"make failed with code {complete.returncode}" + + assert_dir("model_parameters") + assert_dir("model_output") + assert_dir("hospitalization") + + # Make clean again + subprocess.run(["make", "clean"]) + + + # Test definitions def test_simple(): @@ -53,14 +159,16 @@ def test_simple(): def test_importation(): _success("test_importation") - assert_file("data/filter.txt") + assert_file("data/geodata.csv") + assert_file("data/mobility.txt") assert_dir("data/shp") assert_dir("importation") def test_report(): _success("test_report") - assert_file("data/filter.txt") + assert_file("data/geodata.csv") + assert_file("data/mobility.csv") assert_dir("data/shp") assert_dir("importation") assert_dir("notebooks") @@ -69,3 +177,19 @@ def test_report(): def test_hosp_age_adjust(): _success("test_hosp_age_adjust") + +def test_build_US(): + _success_build_US_setup("test_build_US_setup") + +def test_build_nonUS(): + _success_build_nonUS_setup("test_build_nonUS_setup") + +def test_create_seeding_US(): + _success_create_seeding_US("test_create_seeding_US") + +def test_create_seeding_nonUS(): + _success_create_seeding_nonUS("test_create_seeding_nonUS") + +def test_simple_x2(): + _success_x2("test_simple_x2") + diff --git a/test/test_build_US_setup/config.yml b/test/test_build_US_setup/config.yml new file mode 100644 index 000000000..0b63e8129 --- /dev/null +++ b/test/test_build_US_setup/config.yml @@ -0,0 +1,75 @@ +name: test_build_US_setup +start_date: 2020-01-31 +end_date: 2020-05-31 +nsimulations: 1 +dt: 0.25 + +spatial_setup: + census_year: 2010 + base_path: data + setup_name: test1 + modeled_states: + - MD + geodata: geodata.csv + mobility: mobility.csv + popnodes: pop2010 + nodenames: geoid + include_in_report: targeted + +seeding: + method: PoissonDistributed + lambda_file: data/seeding.csv + +seir: + parameters: + sigma: 1 / 5.2 + gamma: + distribution: uniform + low: 1 / 6 + high: 1 / 2.6 + R0s: + distribution: uniform + low: 2 + high: 3 + +interventions: + scenarios: + - None + - Scenario1 + settings: + None: + template: ReduceR0 + period_start_date: 2020-04-01 + period_end_date: 2020-05-15 + value: + distribution: fixed + value: 0 + Place1: + template: ReduceR0 + period_start_date: 2020-04-01 + period_end_date: 2020-05-15 + value: + distribution: uniform + low: .14 + high: .33 + Scenario1: + template: Stacked + scenarios: + - Place1 + - None + +hospitalization: + paths: + output_path: hospitalization + parameters: + time_hosp: [1.23, 0.79] + time_disch: [log(11.5), log(1.22)] + time_death: [log(11.25), log(1.15)] + time_ICU: [log(8.25), log(2.2)] + time_ICUdur: [log(16), log(2.96)] + time_vent: [log(10.5), log((10.5-8)/1.35)] + p_death: [.0025, .005, .01] + p_death_names: ["low","med","high"] + p_death_rate: 0.1 + p_ICU: 0.32 + p_vent: 0.15 diff --git a/test/test_build_nonUS_setup/config.yml b/test/test_build_nonUS_setup/config.yml new file mode 100644 index 000000000..1ca4a7ffb --- /dev/null +++ b/test/test_build_nonUS_setup/config.yml @@ -0,0 +1,77 @@ +name: test_build_nonUS_setup +start_date: 2020-01-31 +end_date: 2020-05-31 +nsimulations: 1 +dt: 0.25 + +spatial_setup: + census_year: 2020 + base_path: data + setup_name: test1 + us_model: FALSE + modeled_states: + - ZMB + geoid_len: 5 + geodata: geodata.csv + mobility: mobility.csv + popnodes: pop + nodenames: geoid + include_in_report: targeted + +seeding: + method: PoissonDistributed + lambda_file: data/seeding.csv + +seir: + parameters: + sigma: 1 / 5.2 + gamma: + distribution: uniform + low: 1 / 6 + high: 1 / 2.6 + R0s: + distribution: uniform + low: 2 + high: 3 + +interventions: + scenarios: + - None + - Scenario1 + settings: + None: + template: ReduceR0 + period_start_date: 2020-04-01 + period_end_date: 2020-05-15 + value: + distribution: fixed + value: 0 + Place1: + template: ReduceR0 + period_start_date: 2020-04-01 + period_end_date: 2020-05-15 + value: + distribution: uniform + low: .14 + high: .33 + Scenario1: + template: Stacked + scenarios: + - Place1 + - None + +hospitalization: + paths: + output_path: hospitalization + parameters: + time_hosp: [1.23, 0.79] + time_disch: [log(11.5), log(1.22)] + time_death: [log(11.25), log(1.15)] + time_ICU: [log(8.25), log(2.2)] + time_ICUdur: [log(16), log(2.96)] + time_vent: [log(10.5), log((10.5-8)/1.35)] + p_death: [.0025, .005, .01] + p_death_names: ["low","med","high"] + p_death_rate: 0.1 + p_ICU: 0.32 + p_vent: 0.15 diff --git a/test/test_build_nonUS_setup/data/geodata/mobility_data.csv b/test/test_build_nonUS_setup/data/geodata/mobility_data.csv new file mode 100644 index 000000000..ffec6b5a2 --- /dev/null +++ b/test/test_build_nonUS_setup/data/geodata/mobility_data.csv @@ -0,0 +1,17 @@ +origin,destination,FLOW,pop_orig,OGEOID,pop_dest,DGEOID +Chibombo,Chibombo,474886,475009,00006,475009,00006 +Chibombo,Kitwe,3,475009,00006,754441,00044 +Chibombo,Kafue,2,475009,00006,146232,00029 +Chibombo,Lusaka,23,475009,00006,2577305,00059 +Kitwe,Chibombo,0,754441,00044,475009,00006 +Kitwe,Kitwe,754432,754441,00044,754441,00044 +Kitwe,Kafue,0,754441,00044,146232,00029 +Kitwe,Lusaka,0,754441,00044,2577305,00059 +Kafue,Chibombo,248,146232,00029,475009,00006 +Kafue,Kitwe,100,146232,00029,754441,00044 +Kafue,Kafue,136654,146232,00029,146232,00029 +Kafue,Lusaka,3350,146232,00029,2577305,00059 +Lusaka,Chibombo,0,2577305,00059,475009,00006 +Lusaka,Kitwe,0,2577305,00059,754441,00044 +Lusaka,Kafue,0,2577305,00059,146232,00029 +Lusaka,Lusaka,2577305,2577305,00059,2577305,00059 diff --git a/test/test_build_nonUS_setup/data/geodata/population_data.csv b/test/test_build_nonUS_setup/data/geodata/population_data.csv new file mode 100644 index 000000000..8ecd1fe36 --- /dev/null +++ b/test/test_build_nonUS_setup/data/geodata/population_data.csv @@ -0,0 +1,5 @@ +ADMIN0,ADMIN2,GEOID,POP +ZMB,Chibombo,00006,475009 +ZMB,Kafue,00029,146232 +ZMB,Kitwe,00044,754441 +ZMB,Lusaka,00059,2577305 diff --git a/test/test_build_nonUS_setup/data/mobility.csv b/test/test_build_nonUS_setup/data/mobility.csv new file mode 100644 index 000000000..77af06d3b --- /dev/null +++ b/test/test_build_nonUS_setup/data/mobility.csv @@ -0,0 +1,25 @@ +"ori","dest","amount" +"00006","00029",2 +"00006","00044",3 +"00006","00059",23 +"00029","00006",248 +"00029","00044",100 +"00029","00059",3350 +"00044","00006",0 +"00044","00029",0 +"00044","00059",0 +"00059","00006",0 +"00059","00029",0 +"00059","00044",0 +"00029","00006",2 +"00044","00006",3 +"00059","00006",23 +"00006","00029",248 +"00044","00029",100 +"00059","00029",3350 +"00006","00044",0 +"00029","00044",0 +"00059","00044",0 +"00006","00059",0 +"00029","00059",0 +"00044","00059",0 diff --git a/test/test_create_seeding_US/config.yml b/test/test_create_seeding_US/config.yml new file mode 100644 index 000000000..1dd408cae --- /dev/null +++ b/test/test_create_seeding_US/config.yml @@ -0,0 +1,75 @@ +name: test_create_seeding_US +start_date: 2020-01-31 +end_date: 2020-03-31 +nsimulations: 1 +dt: 0.25 + +spatial_setup: + census_year: 2010 + base_path: data + setup_name: test1 + modeled_states: + - MD + geodata: geodata.csv + mobility: mobility.csv + popnodes: pop2010 + nodenames: geoid + include_in_report: targeted + +seeding: + method: PoissonDistributed + lambda_file: data/seeding.csv + +seir: + parameters: + sigma: 1 / 5.2 + gamma: + distribution: uniform + low: 1 / 6 + high: 1 / 2.6 + R0s: + distribution: uniform + low: 2 + high: 3 + +interventions: + scenarios: + - None + - Scenario1 + settings: + None: + template: ReduceR0 + period_start_date: 2020-04-01 + period_end_date: 2020-05-15 + value: + distribution: fixed + value: 0 + Place1: + template: ReduceR0 + period_start_date: 2020-04-01 + period_end_date: 2020-05-15 + value: + distribution: uniform + low: .14 + high: .33 + Scenario1: + template: Stacked + scenarios: + - Place1 + - None + +hospitalization: + paths: + output_path: hospitalization + parameters: + time_hosp: [1.23, 0.79] + time_disch: [log(11.5), log(1.22)] + time_death: [log(11.25), log(1.15)] + time_ICU: [log(8.25), log(2.2)] + time_ICUdur: [log(16), log(2.96)] + time_vent: [log(10.5), log((10.5-8)/1.35)] + p_death: [.0025, .005, .01] + p_death_names: ["low","med","high"] + p_death_rate: 0.1 + p_ICU: 0.32 + p_vent: 0.15 diff --git a/test/test_create_seeding_US/data/geodata.csv b/test/test_create_seeding_US/data/geodata.csv new file mode 100644 index 000000000..c7d03fc61 --- /dev/null +++ b/test/test_create_seeding_US/data/geodata.csv @@ -0,0 +1,25 @@ +"geoid","USPS","pop2010" +"24029","MD",20197 +"24039","MD",26470 +"24023","MD",30097 +"24019","MD",32618 +"24011","MD",33066 +"24041","MD",37782 +"24035","MD",47798 +"24047","MD",51454 +"24001","MD",75087 +"24009","MD",88737 +"24045","MD",98733 +"24015","MD",101108 +"24037","MD",105151 +"24017","MD",146551 +"24043","MD",147430 +"24013","MD",167134 +"24021","MD",233385 +"24025","MD",244826 +"24027","MD",287085 +"24003","MD",537656 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scenarios: + - None + - Scenario1 + settings: + None: + template: ReduceR0 + period_start_date: 2020-04-01 + period_end_date: 2020-05-15 + value: + distribution: fixed + value: 0 + Place1: + template: ReduceR0 + period_start_date: 2020-04-01 + period_end_date: 2020-05-15 + value: + distribution: uniform + low: .14 + high: .33 + Scenario1: + template: Stacked + scenarios: + - Place1 + - None + +hospitalization: + paths: + output_path: hospitalization + parameters: + time_hosp: [1.23, 0.79] + time_disch: [log(11.5), log(1.22)] + time_death: [log(11.25), log(1.15)] + time_ICU: [log(8.25), log(2.2)] + time_ICUdur: [log(16), log(2.96)] + time_vent: [log(10.5), log((10.5-8)/1.35)] + p_death: [.0025, .005, .01] + p_death_names: ["low","med","high"] + p_death_rate: 0.1 + p_ICU: 0.32 + p_vent: 0.15 diff --git a/test/test_create_seeding_nonUS/data/case_data/case_data.csv b/test/test_create_seeding_nonUS/data/case_data/case_data.csv new file mode 100644 index 000000000..ee54e9fba --- /dev/null +++ b/test/test_create_seeding_nonUS/data/case_data/case_data.csv @@ -0,0 +1,11 @@ +date,district,incidI,geoid +2020-03-25,kitwe,3,00044 +2020-03-29,lusaka,2,00059 +2020-03-30,lusaka,1,00059 +2020-03-31,lusaka,1,00059 +2020-04-07,lusaka,1,00059 +2020-04-09,lusaka,1,00059 +2020-04-10,lusaka,8,00059 +2020-04-11,kafue,1,00029 +2020-04-11,lusaka,1,00059 +2020-04-16,kafue,21,00029 diff --git a/test/test_create_seeding_nonUS/data/geodata.csv b/test/test_create_seeding_nonUS/data/geodata.csv new file mode 100644 index 000000000..be052650e --- /dev/null +++ b/test/test_create_seeding_nonUS/data/geodata.csv @@ -0,0 +1,5 @@ +"geoid","admin0","pop" +"00029","ZMB",146232 +"00006","ZMB",475009 +"00044","ZMB",754441 +"00059","ZMB",2577305 diff --git a/test/test_create_seeding_nonUS/data/mobility.csv b/test/test_create_seeding_nonUS/data/mobility.csv new file mode 100644 index 000000000..77af06d3b --- /dev/null +++ b/test/test_create_seeding_nonUS/data/mobility.csv @@ -0,0 +1,25 @@ +"ori","dest","amount" +"00006","00029",2 +"00006","00044",3 +"00006","00059",23 +"00029","00006",248 +"00029","00044",100 +"00029","00059",3350 +"00044","00006",0 +"00044","00029",0 +"00044","00059",0 +"00059","00006",0 +"00059","00029",0 +"00059","00044",0 +"00029","00006",2 +"00044","00006",3 +"00059","00006",23 +"00006","00029",248 +"00044","00029",100 +"00059","00029",3350 +"00006","00044",0 +"00029","00044",0 +"00059","00044",0 +"00006","00059",0 +"00029","00059",0 +"00044","00059",0 diff --git a/test/test_hosp_age_adjust/data/geodata.csv b/test/test_hosp_age_adjust/data/geodata.csv index b85f29c94..4af00682c 100644 --- a/test/test_hosp_age_adjust/data/geodata.csv +++ b/test/test_hosp_age_adjust/data/geodata.csv @@ -1,3 +1,3 @@ geoid,population 10001,1000 -20002,2000 +01033,2000 diff --git a/test/test_hosp_age_adjust/data/seeding.csv b/test/test_hosp_age_adjust/data/seeding.csv index 80943c4a7..221d74236 100644 --- a/test/test_hosp_age_adjust/data/seeding.csv +++ b/test/test_hosp_age_adjust/data/seeding.csv @@ -1,4 +1,3 @@ place,date,amount 10001,2020-01-31,.1 -20002,2020-01-31,0.01 - +01033,2020-01-31,0.01 diff --git a/test/test_importation/data/geodata.csv b/test/test_importation/data/geodata.csv deleted file mode 100644 index c3b639a6b..000000000 --- a/test/test_importation/data/geodata.csv +++ /dev/null @@ -1,6 +0,0 @@ -id,geoid,pop2010,stateUSPS -0,15001,185079.0,HI -1,15003,953207.0,HI -2,15005,90.0,HI -3,15007,67091.0,HI -4,15009,154834.0,HI diff --git a/test/test_importation/data/mobility.txt b/test/test_importation/data/mobility.txt deleted file mode 100644 index 454fb030a..000000000 --- a/test/test_importation/data/mobility.txt +++ /dev/null @@ -1,5 +0,0 @@ -0.000000000000000000e+00 6.870000000000000000e+02 0.000000000000000000e+00 4.000000000000000000e+00 2.060000000000000000e+02 -6.870000000000000000e+02 0.000000000000000000e+00 0.000000000000000000e+00 2.660000000000000000e+02 1.032000000000000000e+03 -0.000000000000000000e+00 0.000000000000000000e+00 0.000000000000000000e+00 0.000000000000000000e+00 4.000000000000000000e+00 -4.000000000000000000e+00 2.660000000000000000e+02 0.000000000000000000e+00 0.000000000000000000e+00 9.700000000000000000e+01 -2.060000000000000000e+02 1.032000000000000000e+03 4.000000000000000000e+00 9.700000000000000000e+01 0.000000000000000000e+00 diff --git a/test/test_report/config.yml b/test/test_report/config.yml index a9de7f83c..dd82092b5 100644 --- a/test/test_report/config.yml +++ b/test/test_report/config.yml @@ -10,7 +10,7 @@ spatial_setup: base_path: data setup_name: test_report geodata: geodata.csv - mobility: mobility.txt + mobility: mobility.csv popnodes: pop2010 nodenames: geoid census_year: 2018 @@ -109,8 +109,8 @@ report: scenario_labels: - Uncontrolled - Scenario1 - scenario_colors: ["#D95F02", "#7570B3"] - pdeath_labels: ["0.25% IFR", "0.5% IFR"] + scenario_colors: ["#D95F02", "#7570B3", "#111111"] + pdeath_labels: ["0.25% IFR", "0.5% IFR","1% IFR"] display_dates: ["2020-04-01", "2020-05-01"] display_dates2: ["2020-05-01"] continue_on_error: FALSE diff --git a/test/test_report/data/geodata.csv b/test/test_report/data/geodata.csv deleted file mode 100644 index 78dde9654..000000000 --- a/test/test_report/data/geodata.csv +++ /dev/null @@ -1,6 +0,0 @@ -id,geoid,pop2010,include_in_report,USPS -0,15001,185079.0,TRUE,HI -1,15003,953207.0,TRUE,HI -2,15005,90.0,FALSE,HI -3,15007,67091.0,TRUE,HI -4,15009,154834.0,FALSE,HI diff --git a/test/test_report/data/mobility.txt b/test/test_report/data/mobility.txt deleted file mode 100644 index 454fb030a..000000000 --- a/test/test_report/data/mobility.txt +++ /dev/null @@ -1,5 +0,0 @@ -0.000000000000000000e+00 6.870000000000000000e+02 0.000000000000000000e+00 4.000000000000000000e+00 2.060000000000000000e+02 -6.870000000000000000e+02 0.000000000000000000e+00 0.000000000000000000e+00 2.660000000000000000e+02 1.032000000000000000e+03 -0.000000000000000000e+00 0.000000000000000000e+00 0.000000000000000000e+00 0.000000000000000000e+00 4.000000000000000000e+00 -4.000000000000000000e+00 2.660000000000000000e+02 0.000000000000000000e+00 0.000000000000000000e+00 9.700000000000000000e+01 -2.060000000000000000e+02 1.032000000000000000e+03 4.000000000000000000e+00 9.700000000000000000e+01 0.000000000000000000e+00 diff --git a/test/test_simple/config.yml b/test/test_simple/config.yml index 19f28cc75..bd3c3bf11 100644 --- a/test/test_simple/config.yml +++ b/test/test_simple/config.yml @@ -34,7 +34,8 @@ interventions: - Scenario1 settings: None: - template: ReduceR0 + template: Reduce + parameter: r0 period_start_date: 2020-04-01 period_end_date: 2020-05-15 value: @@ -48,11 +49,20 @@ interventions: distribution: uniform low: .14 high: .33 + Place2: + template: Reduce + parameter: gamma + period_start_date: 2020-04-01 + period_end_date: 2020-05-15 + value: + distribution: fixed + value: .3 Scenario1: template: Stacked scenarios: - Place1 - None + - Place2 hospitalization: paths: diff --git a/test/test_simple_x2/config.yml b/test/test_simple_x2/config.yml new file mode 100644 index 000000000..833626f00 --- /dev/null +++ b/test/test_simple_x2/config.yml @@ -0,0 +1,81 @@ +name: test_simple_x2 +start_date: 2020-01-31 +end_date: 2020-05-31 +nsimulations: 1 +dt: 0.25 + +spatial_setup: + base_path: data + setup_name: test1 + geodata: geodata.csv + mobility: mobility.txt + popnodes: population + nodenames: geoid + +seeding: + method: PoissonDistributed + lambda_file: data/seeding.csv + +seir: + parameters: + sigma: 1 / 5.2 + gamma: + distribution: uniform + low: 1 / 6 + high: 1 / 2.6 + R0s: + distribution: uniform + low: 2 + high: 3 + +interventions: + scenarios: + - None + - Scenario1 + settings: + None: + template: Reduce + parameter: r0 + period_start_date: 2020-04-01 + period_end_date: 2020-05-15 + value: + distribution: fixed + value: 0 + Place1: + template: ReduceR0 + period_start_date: 2020-04-01 + period_end_date: 2020-05-15 + value: + distribution: uniform + low: .14 + high: .33 + Place2: + template: Reduce + parameter: gamma + period_start_date: 2020-04-01 + period_end_date: 2020-05-15 + value: + distribution: fixed + value: .3 + Scenario1: + template: Stacked + scenarios: + - Place1 + - None + - Place2 + +hospitalization: + paths: + output_path: hospitalization + parameters: + time_hosp: [1.23, 0.79] + time_disch: [log(11.5), log(1.22)] + time_death: [log(11.25), log(1.15)] + time_ICU: [log(8.25), log(2.2)] + time_ICUdur: [log(16), log(2.96)] + time_vent: [log(10.5), log((10.5-8)/1.35)] + p_death: [.0025, .005, .01] + p_death_names: ["low","med","high"] + p_death_rate: 0.1 + p_ICU: 0.32 + p_vent: 0.15 diff --git a/test/test_simple_x2/data/filter.txt b/test/test_simple_x2/data/filter.txt new file mode 100644 index 000000000..17f9fbd69 --- /dev/null +++ b/test/test_simple_x2/data/filter.txt @@ -0,0 +1,32 @@ +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +0 0 +10 0 diff --git a/test/test_simple_x2/data/geodata.csv b/test/test_simple_x2/data/geodata.csv new file mode 100644 index 000000000..b85f29c94 --- /dev/null +++ b/test/test_simple_x2/data/geodata.csv @@ -0,0 +1,3 @@ +geoid,population +10001,1000 +20002,2000 diff --git a/test/test_simple_x2/data/mobility.txt b/test/test_simple_x2/data/mobility.txt new file mode 100644 index 000000000..454b62fec --- /dev/null +++ b/test/test_simple_x2/data/mobility.txt @@ -0,0 +1,2 @@ +0 .03 +.03 0 diff --git a/test/test_simple_x2/data/seeding.csv b/test/test_simple_x2/data/seeding.csv new file mode 100644 index 000000000..80943c4a7 --- /dev/null +++ b/test/test_simple_x2/data/seeding.csv @@ -0,0 +1,4 @@ +place,date,amount +10001,2020-01-31,.1 +20002,2020-01-31,0.01 + diff --git a/vignettes/how_to.Rmd b/vignettes/how_to.Rmd deleted file mode 100644 index 0fe766361..000000000 --- a/vignettes/how_to.Rmd +++ /dev/null @@ -1,497 +0,0 @@ ---- -title: "Creating COVID19 planning scenario reports" -author: "Joshua Kaminsky" -date: "`r format(Sys.time(), '%d %B, %Y')`" -output: html_document ---- - -# Introduction - -The purpose of htis document is to provide full instruction on how to create a report using the COVIDScenarioPipeline. - -## Scope - -The report you will create discusses planning scenarios for different interventions on COVID19. This is not a forecasting pipeline, and I will provide no explanation about how it may transfer to another disease. - -#### Specific Limitations - - %% POPULATE ME please help scientists - - - Interventions need to be implemented as an effect on `beta`. Some more mechanistic interventions cannot easily be captured this way. - -# Overview - -The pipeline is broken into several stages, each of which can be independently replaced. - -### Pipeline Phases - -#### Seeding - -We run a model to determine the likelihood of importing cases into the region of interest. We maintain an [R package](https://github.com/HopkinsIDD/covidImportation). - - - -#### Epidemic Simulation - -We run a location stratified [SEIR model](https://github.com/HopkinsIDD/COVIDScenarioPipeline/tree/dataseed/SEIR), using a python module in `COVIDScenarioPipeline`. - -#### Hospitalization Estimation - -We estimate secondary effects of infection using infection numbers using the [hospitalization](https://github.com/HopkinsIDD/COVIDScenarioPipeline/tree/dataseed/R/pkgs/hospitalization) R package in `COVIDScenarioPipeline`. - -#### Report Generation - -We provide functions to access results and help produce reports in the [report_generation](https://github.com/HopkinsIDD/COVIDScenarioPipeline/tree/dataseed/R/pkgs/report_generation) R package in `COVIDScenarioPipeline`. - -### Pipeline Configuration - -#### config.yml - -Most of the configuration done for this package is set in this configuration file. A default is provided, but you should feel free to make your own copy tailored to your needs. - -# Getting Set up - -This project uses R, python, pandoc, and make - -#### R - -The code requires R version 3.6 or newer. You can download R from [cran](https://cran.rstudio.com/). We also recommend [rstudio](https://rstudio.com/products/rstudio/download/), an R IDE. We keep a list of [R packages](https://github.com/HopkinsIDD/COVIDScenarioPipeline/blob/dataseed/packages.R). You can source the script to install the versions required (the most recent versions also likely work). - -#### python - -We use python3.6 or newer. There is a python package we use that needs to know about R, so ensure you install R before python. This differs based on operating system. We keep a list of [python modules](https://github.com/HopkinsIDD/COVIDScenarioPipeline/blob/dataseed/requirements.txt). - -##### Windows - -My preference here has been to use windows subsystem for linux (WSL), and use the linux instructions. - -You can find installation instructions [here](https://docs.microsoft.com/en-us/windows/wsl/install-win10) - -If you want to try something else, you can [directly download](https://www.python.org/downloads/release/python-382/) python. During installation, be sure to add it to your path, or make won't work. - -##### Linux (Debian) - -``` -# apt install python3 python3-pip -``` - -##### Mac - -%% POPULATE ME - can someone who has a mac make sure this works? - -[This webpage](https://docs.python-guide.org/starting/install3/osx/) has a guide to installing python3 and pip on mac - -### pandoc - -Pandoc is part of R markdown, but needs to be installed separately. You can download it [here](https://github.com/jgm/pandoc/releases/tag/2.9.2) - -### make - -Make should already come with your system - -# Seeding - -The code for this section is in an [R package](https://github.com/HopkinsIDD/covidImportation). - -Calculate the expected number of cases imported from outside of the region of interest. - -# Epidemic Simulation - -The code for this section is in the [SEIR](https://github.com/HopkinsIDD/COVIDScenarioPipeline/tree/dataseed/SEIR) python module in `COVIDScenarioPipeline`. - -We have code for a SEIR compartmental model with three infectious states. -Within each geographic location, we assume even mixing. -Between locations, we have a movement model based on empirical data you will need to provide. - -## SEIR parameters -The epidemic is controlled by sigma, gamma, and R0 - -## Geographic Data - -This file contains the geographic information over which the simulation should be run. -It should have one line per location, and at least two columns containing information about those locations: -- `geoid` A column containing a unique identifier for the location -- `popnodes` A column containing the population of that location - -## Mobility File - -A matrix (stored as a space delimited scientific notation e.g., 0.000000000000000000e+00). The matrix is used to calculate movement rates between geoids. The number of people who move from `source` to `dest` is binomially distributed with probability `1 - exp( - mobility[source,dest] / popnodes[source] * dt)` - -## Filter - -A matrix (number of days simulated x number of geographic nodes). Each value contains a minimum number of cases for that time and place. The SEIR simulation throws out simulations that are inconsistent with these reports. - -Currently, the filter is strict, meaning that any simulation that doesn't pass it exactly is rejected. We expect to provide a more relaxed version that provides a tolerance parameter. - -## Seeding or importation - -in the `config.yaml` file: - -``` -seeding: - method: FolderDraw - folder_path: model_output/importation/ -# OR ! -seeding: - method: PoissonDistributed - lambda_file: data/west-coast-AZ-NV/seeding.csv -``` - - -`FolderDraw`: each sim will pull importation from file `importation_{$UID}.csv` in folder `folder_path`. If there is more sims than files in this folder, it’ll loop. `$UID` starts 1 to match R 1-based indexing. -`PoissonDistributed`: will draw a poisson with lambda specified in à `lambda_file` - -In both methods, csv files needs to have at least three columns named `place,date,amount` . `place` are places that match exactly a `place` in the `geodata.csv`. `date` are cases dates in any sensible format, and `amount` either the number of importation (`FolderDraw`) or the lambda parameter of the poisson (`PoissonDistributed`). - -in the CA repo, in `data/west-coast-AZ-NV/seeding.csv` there is an example file. I created it taking cum cases until the model start date, multiplied by 5 and adding 0.1 (so there is a chance in every county). This is a good way to start if the importation module is not availble for you. - - - -## Interventions - -In order to allow flexibility in interventions, we currently use an R script to define an intervention. We provide several exampes in the NPI folder. In the future, we expect to move away from this model and toward specifying interventions directly in the config files. - -To write an intervention, you need to write an R script that creates a matrix of your intervention's effects on `beta` by providing `NPI`, a matrix of percentage reduction for each location and time. To reduce beta by 20% deterministically, one could use - -```{r, eval=FALSE} -## This block sets default values so the NPI can be tested outside of python -if (!from_python) { # or whatever values you use to test. - ti_str <- '2020-01-31' - tf_str <- '2020-08-31' - foldername <- 'west-coast/' -} - -## This pulls data to determine the size of the location x time matrix -county.status <- read.csv(paste0(foldername,'geodata.csv')) -dates <- seq.Date(as.Date(ti_str), as.Date(tf_str), 1) - -## This creates and sets the location x time matrix. -NPI <- as.data.frame(matrix(0.2, dim(county.status)[1],length(dates)), dimnames = list() -``` - -# Hospitalization and Outcome Generation - -The code for this section is in the [hospitalization](https://github.com/HopkinsIDD/COVIDScenarioPipeline/tree/dataseed/R/pkgs/hospitalization). -After you have run a simulation, and have infection rates, we use those results to calculate hospitalizations, icu admittances, ventilator use, deaths (and it would be relatively easy to add other outcomes if you have data). - -### Probability Parameters - -There are currently 5 variables that we measure track. Infection (I), Hospitalization (H), death (D), ICU admittance (ICU), and Ventilator use (Vent). They are calculated from eachother starting from infection, which we get from the Epidemic simulation. Each parameter has an associated probability (p_H, p_D, etc.) which represents that probability of that event conditional on another event. The dependence of the parameters is summarized by the following flowchart - - -The current flow looks like this: - -```{r,echo=FALSE} - -DiagrammeR::grViz("digraph flowchart { - # node definitions with substituted label text - node [fontname = Helvetica, shape = rectangle] - tab1 [label = '@@1'] - tab2 [label = '@@2'] - tab3 [label = '@@3'] - tab4 [label = '@@4'] - tab5 [label = '@@5'] - - # edge definitions with the node IDs - tab1 -> tab2 [label = 'p_hosp']; - tab2 -> tab3 [label = 'p_death']; - tab2 -> tab4 [label = 'p_ICU']; - tab4 -> tab5 [label = 'p_vent']; - } - - [1]: 'Infection' - [2]: 'Hospitalization' - [3]: 'Death' - [4]: 'ICU' - [5]: 'Ventilation' - ") -``` - -### Duration Parameters - -For each event that has a probability, there is an associated time parameter, which measures expected time before that event from infection. The parameter is given as two numbers, and the expectation is calculated as `round(exp(time_X_pars[1] + X_pars[2]^2 / 2))`. - -%% POPULATE ME - Need explanation for why the parameters are of the above form - -There are two other parameters that calculate different amounts of time. They are in the same form, but measure the duration of one of the above events. time_ICUdur_pars, and time_dischdur_pars measure the length of ICU stay and hospital stay respectively. - -# Report Generation - -We provide a [package](https://github.com/HopkinsIDD/COVIDScenarioPipeline/tree/dataseed/R/pkgs/report_generation) to help utilize the previous parts of the pipeline to create meaningful reports. This support comes in the form of functions to help load the output of previous steps (it is sometimes quite large), and R Markdown templates to allow the easy creation of customizable reports without requiring the user to start from scratch. - -## Functions - -We provide two functions to load the results from the [Epidemic Simulation] and [Hospitalization and Outcome Generation], `load_scenario_sims_filtered` and `load_hosp_sims_filtered` respectively. These functions perform the same function on the two different data sources. Because of the nature of the data, they do have different syntax though - -#### load_scenario_sims_filtered - -```{r, eval = FALSE} -load_scenario_sims_filtered <- function( - scenario_dir, - post_process=function(x) {x}, - pre_process=function(x){x} -) -``` - - - `scenario_dir` is the directory containing the output of the [Epidemic Simulation]. The function assumes it is in the `model_output` subdirectory of this directory. You can access this by %POPULATE ME - how to use - - `pre_process` is a function to be performed on each simulation file before transforming into a long data frame. - - `post_process` A function to be performed on each simulation file after transforming into a long data frame. - -#### load_hosp_sims_filtered - -```{r, eval = FALSE} -load_hosp_sims_filtered <- function( - scenario_dir, - name_filter=function(x) {x}, - post_process=function(x){x} -) -``` - - - `scenario_dir` is the directory containing the output of the [Hospitalization and Outcome Generation]. The function assumes it is in the `hospitalization/model_output` subdirectory of this directory. You can access this by %POPULATE ME - how to use - - `post_process` A function to be performed on each simulation file after each piece of data is loaded. - - `name_filter` A string that all filenames need to match. This is intended for distinguishing between different hospitalization parameterization scenarios, which are stored with the scenario as part of the filename. - -## Templates - -We have generated templates to help create reports of different types. Templates are complete reports that you can use as a base of your output. Currently, we have the beginning of one template intended for state level reports. - -#### Using templates - -To start a draft from a template, you can use, for example: - -```{r, eval = FALSE} -rmarkdown::draft("Maryland_Report.Rmd", template = "state_report", package = "report_generation") -``` - - -# Appendixes - -### Implemented interventions - -Each intervention is associated with a start and end date and a range of values to sample from. - -### None - -This is a non-intervention scenario. It does not reduce `R0`. -```{r None} -None: - template: ReduceR0 - period_start_date: YYYY-MM-DD - period_end_date: YYYY-MM-DD - value: - distribution: fixed - value: 0 -``` - -### SchoolClosure - -This intervention represents school closures. It reduces `R0` by 16-30%. - -```{r School Closure} -SchoolClosure: - template: ReduceR0 - period_start_date: YYYY-MM-DD - period_end_date: YYYY-MM-DD - value: - distribution: truncnorm - a: 0.16 - b: 0.30 - mean: 0.18 - sd: 0.05 -``` - - - -### Influenza1918 - -This intervention represents the influence of different social distancing scenarios observed in the 1918 Influenza. It reduces `R0` by 44-65%, based on values observed in Milwaukee, Wisconsin. These values can be altered to reflect different cities and scenarios reported by M.Bootsma & N.M.Ferguson in https://www.pnas.org/content/104/18/7588.long - -```{r Influenza1918} -Influenza1918: - template: ReduceR0 - period_start_date: YYYY-MM-DD - period_end_date: YYYY-MM-DD - value: - distribution: uniform - low: .44 - high: .65 -``` - -### Wuhan - -This intervention represents shelter in place similar to what was done in Wuhan at the beginning of the outbreak. It reduces `R0` by 81-89%. - -```{r Wuhan} -Wuhan: - template: ReduceR0 - period_start_date: YYYY-MM-DD - period_end_date: YYYY-MM-DD - value: - distribution: uniform - low: .81 - high: .89 -``` - -### TestIsolate - -This intervention represents rapid testing and isolation of cases, similar to what was done in Wuhan at the beginning of the outbreak. It reduces `R0` by 45-96%. - -```{r TestIsolate} -TestIsolate: - template: ReduceR0 - period_start_date: YYYY-MM-DD - period_end_date: YYYY-MM-DD - value: - distribution: uniform - low: .45 - high: .96 -``` - -### Mild - -This intervention has two sequential interventions: School closures followed by a Wuhan-style lockdown. - -```{r Mild} -Mild: - template: Stacked - scenarios: - - SchoolClosure - - Wuhan -``` -### Mid - -This intervention has three sequential interventions: School closures, followed by a Wuhan-style lockdown, followed by social distancing practices used during the 1918 Influenza pandemic. - -```{r Mid} -Mid: - template: Stacked - scenarios: - - SchoolClosure - - Wuhan - - Influenza1918 -``` - -### Severe - -This intervention has three sequential interventions: School closures, followed by a Wuhan-style lockdown, followed by rapid testing and isolation. - -```{r Severe} -Severe: - template: Stacked - scenarios: - - SchoolClosure - - Wuhan - - TestIsolate -``` - - -## Actual Steps I went through to create a minimal working repository (by commit) - - - - Install python packages - - ```{sh, eval=FALSE} - pip3 install -r https://raw.githubusercontent.com/HopkinsIDD/COVIDScenarioPipeline/dataseed/requirements.txt - ``` - - - Install cran R dependencies - - ```{r,eval=FALSE,echo=TRUE} - source_url("https://raw.github.com/lcolladotor/ballgownR-devel/master/ballgownR/R/infoGene.R") - ``` - - - Install all relevant R packages from github: - - ```{r,eval=FALSE,echo=TRUE} - devtools::install_github(repo='HopkinsIDD/COVIDScenarioPipeline', ref='dataseed', subdir='R/pkgs/covidcommon') - devtools::install_github(repo='HopkinsIDD/COVIDScenarioPipeline', ref='dataseed', subdir='R/pkgs/hospitalization') - devtools::install_github(repo='HopkinsIDD/COVIDScenarioPipeline', ref='dataseed', subdir='R/pkgs/report_generation') - ``` - - - Clone github repo - ```{sh, eval=FALSE} - git clone https://github.com/HopkinsIDD/COVIDScenarioPipeline.git - ``` - - - Copy the config.yml file from the COVIDScenarioPipeline repository to your current repository - ```{sh, eval=FALSE} - cp COVIDScenarioPipeline/config.yml config.yml - ``` - - - Remove all references to the COVIDScenarioPipeline repo from config.yml - - ```{eval=FALSE} - 1c1 - < name: mid-west-coast-AZ-NV - --- - > name: minimal - 5c5 - < dynfilter_path: data/west-coast-AZ-NV/filtergithub.txt - --- - > dynfilter_path: data/filtergithub.txt - 8c8 - < base_path: data/west-coast-AZ-NV - --- - > base_path: data - 10c10 - < setup_name: west-coast-AZ-NV - --- - > setup_name: minimal - 16c16 - < scripts_path: COVIDScenarioPipeline/NPI - --- - > scripts_path: NPI - ``` - - - Make an Intervention - - ```{sh, eval=FALSE} - mkdir NPI - cp COVIDScenarioPipeline/NPI/None.R NPI/ - ``` - - - Aquire geodata - - ```{sh, eval=FALSE} - mkdir data - echo "geoind,population -10001,1000 -20002,2000" > data/geodata.csv - ``` - Edit the config file so spatial_setup::base_path = data - Edit the config file so spatial_setup::geodata = geodata.csv - - - Aquire mobility data - - ```{sh, eval = FALSE} - echo "0 .03 -.03 0" > data/mobility.txt - ``` - Edit the config file so spatial_setup::mobility = mobility.csv - Note that geodata and mobility data live in the same directory (basepath) - - - Aquire filter - - ```{sh, eval=FALSE} - echo "0 0" > data/filter.txt - echo "0 0" >> data/filter.txt - echo "0 0" >> data/filter.txt - echo "0 0" >> data/filter.txt - echo "0 0" >> data/filter.txt - echo "0 0" >> data/filter.txt - echo "0 0" >> data/filter.txt - echo "0 0" >> data/filter.txt - echo "0 0" >> data/filter.txt - echo "0 0" >> data/filter.txt - ``` - The number of columns should be the number of geoids - The number of time steps should be end_date - start_date in days - dynfilter_path should be a path to this file - - - Run simulate.py - - ```{sh, eval=FALSE} - python3 COVIDScenarioPipeline/simulate.py -c config.yml -s None -n 15 - ``` - - - diff --git a/vignettes/how_to.html b/vignettes/how_to.html deleted file mode 100644 index 3ce1ab7e6..000000000 --- a/vignettes/how_to.html +++ /dev/null @@ -1,512 +0,0 @@ - - - - - - - - - - - - - - -Creating COVID19 planning scenario reports - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Introduction

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The purpose of htis document is to provide full instruction on how to create a report using the COVIDScenarioPipeline.

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Scope

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The report you will create discusses planning scenarios for different interventions on COVID19. This is not a forecasting pipeline, and I will provide no explanation about how it may transfer to another disease.

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Specific Limitations

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%% POPULATE ME please help scientists

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  • Interventions need to be implemented as an effect on beta. Some more mechanistic interventions cannot easily be captured this way.
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Overview

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The pipeline is broken into several stages, each of which can be independently replaced.

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Pipeline Phases

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Seeding

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We run a model to determine the likelihood of importing cases into the region of interest. We maintain an R package.

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Epidemic Simulation

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We run a location stratified SEIR model, using a python module in COVIDScenarioPipeline.

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Hospitalization Estimation

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We estimate secondary effects of infection using infection numbers using the hospitalization R package in COVIDScenarioPipeline.

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Report Generation

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We provide functions to access results and help produce reports in the report_generation R package in COVIDScenarioPipeline.

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Pipeline Configuration

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config.yml

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Most of the configuration done for this package is set in this configuration file. A default is provided, but you should feel free to make your own copy tailored to your needs.

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Getting Set up

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This project uses R, python, pandoc, and make

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R

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The code requires R version 3.6 or newer. You can download R from cran. We also recommend rstudio, an R IDE. We keep a list of R packages. You can source the script to install the versions required (the most recent versions also likely work).

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python

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We use python3.6 or newer. There is a python package we use that needs to know about R, so ensure you install R before python. This differs based on operating system. We keep a list of python modules.

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Windows
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My preference here has been to use windows subsystem for linux (WSL), and use the linux instructions.

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You can find installation instructions here

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If you want to try something else, you can directly download python. During installation, be sure to add it to your path, or make won’t work.

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Linux (Debian)
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# apt install python3 python3-pip
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Mac
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%% POPULATE ME - can someone who has a mac make sure this works?

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This webpage has a guide to installing python3 and pip on mac

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pandoc

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Pandoc is part of R markdown, but needs to be installed separately. You can download it here

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make

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Make should already come with your system

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Seeding

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The code for this section is in an R package.

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Calculate the expected number of cases imported from outside of the region of interest.

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Epidemic Simulation

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The code for this section is in the SEIR python module in COVIDScenarioPipeline.

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We have code for a SEIR compartmental model with three infectious states. Within each geographic location, we assume even mixing. Between locations, we have a movement model based on empirical data you will need to provide.

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SEIR parameters

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The epidemic is controlled by sigma, gamma, and R0

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Geographic Data

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This file contains the geographic information over which the simulation should be run. It should have one line per location, and at least two columns containing information about those locations: - geoid A column containing a unique identifier for the location - popnodes A column containing the population of that location

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Mobility File

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A matrix (stored as a space delimited scientific notation e.g., 0.000000000000000000e+00). The matrix is used to calculate movement rates between geoids. The number of people who move from source to dest is binomially distributed with probability 1 - exp( - mobility[source,dest] / popnodes[source] * dt)

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Filter

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A matrix (number of days simulated x number of geographic nodes). Each value contains a minimum number of cases for that time and place. The SEIR simulation throws out simulations that are inconsistent with these reports.

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Currently, the filter is strict, meaning that any simulation that doesn’t pass it exactly is rejected. We expect to provide a more relaxed version that provides a tolerance parameter.

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Interventions

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In order to allow flexibility in interventions, we currently use an R script to define an intervention. We provide several exampes in the NPI folder. In the future, we expect to move away from this model and toward specifying interventions directly in the config files.

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To write an intervention, you need to write an R script that creates a matrix of your intervention’s effects on beta by providing NPI, a matrix of percentage reduction for each location and time. To reduce beta by 20% deterministically, one could use

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## This block sets default values so the NPI can be tested outside of python
-if (!from_python) {         # or whatever values you use to test.
-    ti_str <- '2020-01-31'
-    tf_str <- '2020-08-31'
-    foldername <- 'west-coast/'
-}
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-## This pulls data to determine the size of the location x time matrix
-county.status <- read.csv(paste0(foldername,'geodata.csv'))
-dates <- seq.Date(as.Date(ti_str), as.Date(tf_str), 1)
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-## This creates and sets the location x time matrix.
-NPI <- as.data.frame(matrix(0.2, dim(county.status)[1],length(dates)), dimnames = list()
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Hospitalization and Outcome Generation

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The code for this section is in the hospitalization. After you have run a simulation, and have infection rates, we use those results to calculate hospitalizations, icu admittances, ventilator use, deaths (and it would be relatively easy to add other outcomes if you have data).

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Probability Parameters

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There are currently 5 variables that we measure track. Infection (I), Hospitalization (H), death (D), ICU admittance (ICU), and Ventilator use (Vent). They are calculated from eachother starting from infection, which we get from the Epidemic simulation. Each parameter has an associated probability (p_H, p_D, etc.) which represents that probability of that event conditional on another event. The dependence of the parameters is summarized by the following flowchart

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The current flow looks like this:

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Duration Parameters

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For each event that has a probability, there is an associated time parameter, which measures expected time before that event from infection. The parameter is given as two numbers, and the expectation is calculated as round(exp(time_X_pars[1] + X_pars[2]^2 / 2)).

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%% POPULATE ME - Need explanation for why the parameters are of the above form

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There are two other parameters that calculate different amounts of time. They are in the same form, but measure the duration of one of the above events. time_ICUdur_pars, and time_dischdur_pars measure the length of ICU stay and hospital stay respectively.

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Report Generation

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We provide a package to help utilize the previous parts of the pipeline to create meaningful reports. This support comes in the form of functions to help load the output of previous steps (it is sometimes quite large), and R Markdown templates to allow the easy creation of customizable reports without requiring the user to start from scratch.

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Functions

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We provide two functions to load the results from the Epidemic Simulation and Hospitalization and Outcome Generation, load_scenario_sims_filtered and load_hosp_sims_filtered respectively. These functions perform the same function on the two different data sources. Because of the nature of the data, they do have different syntax though

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load_scenario_sims_filtered

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load_scenario_sims_filtered <- function(
-  scenario_dir,
-  post_process=function(x) {x},
-  pre_process=function(x){x}
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  • scenario_dir is the directory containing the output of the Epidemic Simulation. The function assumes it is in the model_output subdirectory of this directory. You can access this by %POPULATE ME - how to use
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  • pre_process is a function to be performed on each simulation file before transforming into a long data frame.
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  • post_process A function to be performed on each simulation file after transforming into a long data frame.
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load_hosp_sims_filtered

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load_hosp_sims_filtered <- function(
-  scenario_dir,
-  name_filter=function(x) {x},
-  post_process=function(x){x}
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  • scenario_dir is the directory containing the output of the Hospitalization and Outcome Generation. The function assumes it is in the hospitalization/model_output subdirectory of this directory. You can access this by %POPULATE ME - how to use
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  • post_process A function to be performed on each simulation file after each piece of data is loaded.
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  • name_filter A string that all filenames need to match. This is intended for distinguishing between different hospitalization parameterization scenarios, which are stored with the scenario as part of the filename.
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Templates

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We have generated templates to help create reports of different types. Templates are complete reports that you can use as a base of your output. Currently, we have the beginning of one template intended for state level reports.

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Using templates

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To start a draft from a template, you can use, for example:

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rmarkdown::draft("Maryland_Report.Rmd", template = "state_report", package = "report_generation")
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Appendixes

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Implemented interventions

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Each intervention is associated with a start and end date and a range of values to sample from.

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None

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This is a non-intervention scenario. It does not reduce R0.

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SchoolClosure

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This intervention represents school closures. It reduces R0 by 16-30%.

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Influenza1918

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This intervention represents the influence of different social distancing scenarios observed in the 1918 Influenza. It reduces R0 by 44-65%, based on values observed in Milwaukee, Wisconsin. These values can be altered to reflect different cities and scenarios reported by M.Bootsma & N.M.Ferguson in https://www.pnas.org/content/104/18/7588.long

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Wuhan

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This intervention represents shelter in place similar to what was done in Wuhan at the beginning of the outbreak. It reduces R0 by 81-89%.

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TestIsolate

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This intervention represents rapid testing and isolation of cases, similar to what was done in Wuhan at the beginning of the outbreak. It reduces R0 by 45-96%.

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Mild

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This intervention has two sequential interventions: School closures followed by a Wuhan-style lockdown.

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Mid

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This intervention has three sequential interventions: School closures, followed by a Wuhan-style lockdown, followed by social distancing practices used during the 1918 Influenza pandemic.

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Severe

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This intervention has three sequential interventions: School closures, followed by a Wuhan-style lockdown, followed by rapid testing and isolation.

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Actual Steps I went through to create a minimal working repository (by commit)

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  • Install python packages
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sh pip3 install -r https://raw.githubusercontent.com/HopkinsIDD/COVIDScenarioPipeline/dataseed/requirements.txt

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  • Install cran R dependencies
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r source_url("https://raw.github.com/lcolladotor/ballgownR-devel/master/ballgownR/R/infoGene.R")

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  • Install all relevant R packages from github:
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r devtools::install_github(repo='HopkinsIDD/COVIDScenarioPipeline', ref='dataseed', subdir='R/pkgs/covidcommon') devtools::install_github(repo='HopkinsIDD/COVIDScenarioPipeline', ref='dataseed', subdir='R/pkgs/hospitalization') devtools::install_github(repo='HopkinsIDD/COVIDScenarioPipeline', ref='dataseed', subdir='R/pkgs/report_generation')

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  • Clone github repo
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sh git clone https://github.com/HopkinsIDD/COVIDScenarioPipeline.git

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  • Copy the config.yml file from the COVIDScenarioPipeline repository to your current repository
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sh cp COVIDScenarioPipeline/config.yml config.yml

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  • Remove all references to the COVIDScenarioPipeline repo from config.yml
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{eval=FALSE} 1c1 < name: mid-west-coast-AZ-NV --- > name: minimal 5c5 < dynfilter_path: data/west-coast-AZ-NV/filtergithub.txt --- > dynfilter_path: data/filtergithub.txt 8c8 < base_path: data/west-coast-AZ-NV --- > base_path: data 10c10 < setup_name: west-coast-AZ-NV --- > setup_name: minimal 16c16 < scripts_path: COVIDScenarioPipeline/NPI --- > scripts_path: NPI

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  • Make an Intervention
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sh mkdir NPI cp COVIDScenarioPipeline/NPI/None.R NPI/

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  • Aquire geodata
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sh mkdir data echo "geoind,population 10001,1000 20002,2000" > data/geodata.csv Edit the config file so spatial_setup::base_path = data Edit the config file so spatial_setup::geodata = geodata.csv

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  • Aquire mobility data
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sh echo "0 .03 .03 0" > data/mobility.txt Edit the config file so spatial_setup::mobility = mobility.csv Note that geodata and mobility data live in the same directory (basepath)

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  • Aquire filter
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sh echo "0 0" > data/filter.txt echo "0 0" >> data/filter.txt echo "0 0" >> data/filter.txt echo "0 0" >> data/filter.txt echo "0 0" >> data/filter.txt echo "0 0" >> data/filter.txt echo "0 0" >> data/filter.txt echo "0 0" >> data/filter.txt echo "0 0" >> data/filter.txt echo "0 0" >> data/filter.txt The number of columns should be the number of geoids The number of time steps should be end_date - start_date in days dynfilter_path should be a path to this file

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  • Run simulate.py
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sh python3 COVIDScenarioPipeline/simulate.py -c config.yml -s None -n 15

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