diff --git a/docs/404.html b/docs/404.html index 69f501e..ac7d2e5 100644 --- a/docs/404.html +++ b/docs/404.html @@ -6,30 +6,30 @@ Page not found (404) • MOSAIC - - - - - - - - - + + + + + + + + + - - + + - Skip to contents + Skip to contents
-

Page not found (404)

+

Page not found (404)

diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html index 1183191..0f94081 100644 --- a/docs/LICENSE-text.html +++ b/docs/LICENSE-text.html @@ -1,5 +1,5 @@ -License • MOSAICLicense • MOSAIC @@ -37,7 +37,7 @@
  • - + diff --git a/docs/_pkgdown.yml b/docs/_pkgdown.yml index fd1bf2e..be54f37 100644 --- a/docs/_pkgdown.yml +++ b/docs/_pkgdown.yml @@ -1,4 +1,4 @@ -url: https://gilesjohnr.github.io/MOSAIC-docs/ +url: institutefordiseasemodeling.github.io/MOSAIC-pkg/ template: bootstrap: 5 @@ -31,7 +31,7 @@ navbar: href: articles/LAUNCH.html right: - icon: fa-github - href: https://github.com/gilesjohnr/MOSAIC-pkg + href: https://github.com/InstituteforDiseaseModeling/MOSAIC-pkg aria-label: GitHub diff --git a/docs/authors.html b/docs/authors.html index 75cb697..d63ce8f 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -1,5 +1,5 @@ -Authors and Citation • MOSAICAuthors and Citation • MOSAIC @@ -37,7 +37,7 @@
    • - + diff --git a/docs/index.html b/docs/index.html index 9574978..26b50aa 100644 --- a/docs/index.html +++ b/docs/index.html @@ -19,7 +19,7 @@ - + Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data • MOSAICCompile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data • MOSAIC @@ -37,7 +37,7 @@
      • - + diff --git a/docs/reference/convert_country_to_iso.html b/docs/reference/convert_country_to_iso.html index 4812a4a..c739b5d 100644 --- a/docs/reference/convert_country_to_iso.html +++ b/docs/reference/convert_country_to_iso.html @@ -1,5 +1,5 @@ -Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso • MOSAICConvert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso • MOSAIC @@ -37,7 +37,7 @@
        • - + diff --git a/docs/reference/convert_iso_codes.html b/docs/reference/convert_iso_codes.html index 62e3a09..ba1156f 100644 --- a/docs/reference/convert_iso_codes.html +++ b/docs/reference/convert_iso_codes.html @@ -1,5 +1,5 @@ -Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes • MOSAICConvert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes • MOSAIC @@ -37,7 +37,7 @@
          • - + diff --git a/docs/reference/convert_iso_to_country.html b/docs/reference/convert_iso_to_country.html index b7d3ff9..d003b9d 100644 --- a/docs/reference/convert_iso_to_country.html +++ b/docs/reference/convert_iso_to_country.html @@ -1,5 +1,5 @@ -Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country • MOSAICConvert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country • MOSAIC @@ -37,7 +37,7 @@
            • - + diff --git a/docs/reference/download_africa_shapefile.html b/docs/reference/download_africa_shapefile.html index 0ba91a9..11ecf84 100644 --- a/docs/reference/download_africa_shapefile.html +++ b/docs/reference/download_africa_shapefile.html @@ -1,5 +1,5 @@ -Download and Save Africa Shapefile — download_africa_shapefile • MOSAICDownload and Save Africa Shapefile — download_africa_shapefile • MOSAIC @@ -37,7 +37,7 @@
              • - + diff --git a/docs/reference/download_all_country_shapefiles.html b/docs/reference/download_all_country_shapefiles.html index 572d936..9d18c9b 100644 --- a/docs/reference/download_all_country_shapefiles.html +++ b/docs/reference/download_all_country_shapefiles.html @@ -1,7 +1,7 @@ Download and Save Shapefiles for All African Countries — download_all_country_shapefiles • MOSAIC @@ -39,7 +39,7 @@
                • - + diff --git a/docs/reference/download_climate_data.html b/docs/reference/download_climate_data.html index 892b6eb..88c1f35 100644 --- a/docs/reference/download_climate_data.html +++ b/docs/reference/download_climate_data.html @@ -1,5 +1,5 @@ -Download and Save Climate Data for Multiple Countries — download_climate_data • MOSAICDownload and Save Climate Data for Multiple Countries — download_climate_data • MOSAIC @@ -37,7 +37,7 @@
                  • - + diff --git a/docs/reference/est_WASH_coverage.html b/docs/reference/est_WASH_coverage.html index bfd952b..7004c2e 100644 --- a/docs/reference/est_WASH_coverage.html +++ b/docs/reference/est_WASH_coverage.html @@ -1,5 +1,5 @@ -Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage • MOSAICEstimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage • MOSAIC @@ -37,7 +37,7 @@
                    • - + diff --git a/docs/reference/est_mobility.html b/docs/reference/est_mobility.html index 05cea7c..c6f2bab 100644 --- a/docs/reference/est_mobility.html +++ b/docs/reference/est_mobility.html @@ -1,5 +1,5 @@ -Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility • MOSAICEstimate and Visualize Mobility Model for MOSAIC Data — est_mobility • MOSAIC @@ -37,7 +37,7 @@
                      • - + diff --git a/docs/reference/est_symptomatic_prop.html b/docs/reference/est_symptomatic_prop.html index 8e2de99..15315ed 100644 --- a/docs/reference/est_symptomatic_prop.html +++ b/docs/reference/est_symptomatic_prop.html @@ -1,5 +1,5 @@ -Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop • MOSAICEstimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop • MOSAIC @@ -37,7 +37,7 @@
                        • - + diff --git a/docs/reference/generate_country_grid_dist.html b/docs/reference/generate_country_grid_dist.html index 159cbc1..9a5cf82 100644 --- a/docs/reference/generate_country_grid_dist.html +++ b/docs/reference/generate_country_grid_dist.html @@ -1,5 +1,5 @@ -Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist • MOSAICGenerate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist • MOSAIC @@ -37,7 +37,7 @@
                          • - + diff --git a/docs/reference/generate_country_grid_n.html b/docs/reference/generate_country_grid_n.html index 4851df7..e27ae65 100644 --- a/docs/reference/generate_country_grid_n.html +++ b/docs/reference/generate_country_grid_n.html @@ -1,5 +1,5 @@ -Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n • MOSAICGenerate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n • MOSAIC @@ -37,7 +37,7 @@
                            • - + diff --git a/docs/reference/get_DMI_forecast.html b/docs/reference/get_DMI_forecast.html index d8d693f..ea26bb0 100644 --- a/docs/reference/get_DMI_forecast.html +++ b/docs/reference/get_DMI_forecast.html @@ -1,5 +1,5 @@ -Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast • MOSAICGet DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast • MOSAIC @@ -37,7 +37,7 @@
                              • - + diff --git a/docs/reference/get_DMI_historical.html b/docs/reference/get_DMI_historical.html index 2e6aa0d..a9a1e52 100644 --- a/docs/reference/get_DMI_historical.html +++ b/docs/reference/get_DMI_historical.html @@ -1,5 +1,5 @@ -Download and Process Historical DMI Data — get_DMI_historical • MOSAICDownload and Process Historical DMI Data — get_DMI_historical • MOSAIC @@ -37,7 +37,7 @@
                                • - + diff --git a/docs/reference/get_ENSO_forecast.html b/docs/reference/get_ENSO_forecast.html index a62bda8..dfcb04d 100644 --- a/docs/reference/get_ENSO_forecast.html +++ b/docs/reference/get_ENSO_forecast.html @@ -1,5 +1,5 @@ -Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast • MOSAICGet ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast • MOSAIC @@ -37,7 +37,7 @@
                                  • - + diff --git a/docs/reference/get_ENSO_historical.html b/docs/reference/get_ENSO_historical.html index 884e2fc..ae56fbb 100644 --- a/docs/reference/get_ENSO_historical.html +++ b/docs/reference/get_ENSO_historical.html @@ -1,5 +1,5 @@ -Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical • MOSAICDownload and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical • MOSAIC @@ -37,7 +37,7 @@
                                    • - + diff --git a/docs/reference/get_WASH_data.html b/docs/reference/get_WASH_data.html index e80c5c0..7127da7 100644 --- a/docs/reference/get_WASH_data.html +++ b/docs/reference/get_WASH_data.html @@ -1,5 +1,5 @@ -Download, Process, and Save WASH Coverage Data — get_WASH_data • MOSAICDownload, Process, and Save WASH Coverage Data — get_WASH_data • MOSAIC @@ -37,7 +37,7 @@
                                      • - + diff --git a/docs/reference/get_centroid.html b/docs/reference/get_centroid.html index bfbb278..d0a3c52 100644 --- a/docs/reference/get_centroid.html +++ b/docs/reference/get_centroid.html @@ -1,5 +1,5 @@ -Calculate the Centroid of a Country from its Shapefile — get_centroid • MOSAICCalculate the Centroid of a Country from its Shapefile — get_centroid • MOSAIC @@ -37,7 +37,7 @@
                                        • - + diff --git a/docs/reference/get_climate_forecast.html b/docs/reference/get_climate_forecast.html index 95bcbe5..75f654e 100644 --- a/docs/reference/get_climate_forecast.html +++ b/docs/reference/get_climate_forecast.html @@ -1,5 +1,5 @@ -Get Climate Forecast Data (Daily) — get_climate_forecast • MOSAICGet Climate Forecast Data (Daily) — get_climate_forecast • MOSAIC @@ -37,7 +37,7 @@
                                          • - + diff --git a/docs/reference/get_climate_future.html b/docs/reference/get_climate_future.html index 0229260..8146a36 100644 --- a/docs/reference/get_climate_future.html +++ b/docs/reference/get_climate_future.html @@ -1,5 +1,5 @@ -Download Future Climate Data for Multiple Locations — get_climate_future • MOSAICDownload Future Climate Data for Multiple Locations — get_climate_future • MOSAIC @@ -37,7 +37,7 @@
                                            • - + diff --git a/docs/reference/get_climate_historical.html b/docs/reference/get_climate_historical.html index c6930fb..f74d7b1 100644 --- a/docs/reference/get_climate_historical.html +++ b/docs/reference/get_climate_historical.html @@ -1,5 +1,5 @@ -Get Historical Climate Data — get_climate_historical • MOSAICGet Historical Climate Data — get_climate_historical • MOSAIC @@ -37,7 +37,7 @@
                                              • - + diff --git a/docs/reference/get_country_shp.html b/docs/reference/get_country_shp.html index ac39e08..a389089 100644 --- a/docs/reference/get_country_shp.html +++ b/docs/reference/get_country_shp.html @@ -1,5 +1,5 @@ -Get a country shapefile from GeoBoundaries API — get_country_shp • MOSAICGet a country shapefile from GeoBoundaries API — get_country_shp • MOSAIC @@ -37,7 +37,7 @@
                                                • - + diff --git a/docs/reference/get_elevation.html b/docs/reference/get_elevation.html index a670cf6..d0d1dc9 100644 --- a/docs/reference/get_elevation.html +++ b/docs/reference/get_elevation.html @@ -1,5 +1,5 @@ -Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation • MOSAICGet Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation • MOSAIC @@ -37,7 +37,7 @@
                                                  • - + diff --git a/docs/reference/get_ggplot_legend.html b/docs/reference/get_ggplot_legend.html index 04b3059..84a2a36 100644 --- a/docs/reference/get_ggplot_legend.html +++ b/docs/reference/get_ggplot_legend.html @@ -1,7 +1,7 @@ Extract the Legend from a ggplot Object — get_ggplot_legend • MOSAIC @@ -39,7 +39,7 @@
                                                    • - + diff --git a/docs/reference/get_paths.html b/docs/reference/get_paths.html index a4e1da9..30934e6 100644 --- a/docs/reference/get_paths.html +++ b/docs/reference/get_paths.html @@ -1,5 +1,5 @@ -Generate Directory Paths for the MOSAIC Project — get_paths • MOSAICGenerate Directory Paths for the MOSAIC Project — get_paths • MOSAIC @@ -37,7 +37,7 @@
                                                      • - + diff --git a/docs/reference/get_symptomatic_prop_data.html b/docs/reference/get_symptomatic_prop_data.html index f8d892a..80c71b8 100644 --- a/docs/reference/get_symptomatic_prop_data.html +++ b/docs/reference/get_symptomatic_prop_data.html @@ -1,5 +1,5 @@ -Get Symptomatic Proportion Data — get_symptomatic_prop_data • MOSAICGet Symptomatic Proportion Data — get_symptomatic_prop_data • MOSAIC @@ -37,7 +37,7 @@
                                                        • - + diff --git a/docs/reference/index.html b/docs/reference/index.html index 4b86a02..f1d1b68 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -1,5 +1,5 @@ -Function reference • MOSAICFunction reference • MOSAIC @@ -37,7 +37,7 @@
                                                          • - + diff --git a/docs/reference/iso_codes_africa.html b/docs/reference/iso_codes_africa.html index c91ed68..2571503 100644 --- a/docs/reference/iso_codes_africa.html +++ b/docs/reference/iso_codes_africa.html @@ -1,5 +1,5 @@ -ISO3 Country Codes for All African Countries — iso_codes_africa • MOSAICISO3 Country Codes for All African Countries — iso_codes_africa • MOSAIC @@ -37,7 +37,7 @@
                                                            • - + diff --git a/docs/reference/iso_codes_africa_central.html b/docs/reference/iso_codes_africa_central.html index 924b675..d94d7c7 100644 --- a/docs/reference/iso_codes_africa_central.html +++ b/docs/reference/iso_codes_africa_central.html @@ -1,5 +1,5 @@ -ISO3 Country Codes for Central African Countries — iso_codes_africa_central • MOSAICISO3 Country Codes for Central African Countries — iso_codes_africa_central • MOSAIC @@ -37,7 +37,7 @@
                                                              • - + diff --git a/docs/reference/iso_codes_africa_east.html b/docs/reference/iso_codes_africa_east.html index 78b4025..95dec5e 100644 --- a/docs/reference/iso_codes_africa_east.html +++ b/docs/reference/iso_codes_africa_east.html @@ -1,5 +1,5 @@ -ISO3 Country Codes for East African Countries — iso_codes_africa_east • MOSAICISO3 Country Codes for East African Countries — iso_codes_africa_east • MOSAIC @@ -37,7 +37,7 @@
                                                                • - + diff --git a/docs/reference/iso_codes_africa_north.html b/docs/reference/iso_codes_africa_north.html index 28f71aa..7506812 100644 --- a/docs/reference/iso_codes_africa_north.html +++ b/docs/reference/iso_codes_africa_north.html @@ -1,5 +1,5 @@ -ISO3 Country Codes for North African Countries — iso_codes_africa_north • MOSAICISO3 Country Codes for North African Countries — iso_codes_africa_north • MOSAIC @@ -37,7 +37,7 @@
                                                                  • - + diff --git a/docs/reference/iso_codes_africa_south.html b/docs/reference/iso_codes_africa_south.html index 30a23dd..121a5ab 100644 --- a/docs/reference/iso_codes_africa_south.html +++ b/docs/reference/iso_codes_africa_south.html @@ -1,5 +1,5 @@ -ISO3 Country Codes for Southern African Countries — iso_codes_africa_south • MOSAICISO3 Country Codes for Southern African Countries — iso_codes_africa_south • MOSAIC @@ -37,7 +37,7 @@
                                                                    • - + diff --git a/docs/reference/iso_codes_africa_west.html b/docs/reference/iso_codes_africa_west.html index c449d0f..45bf1fd 100644 --- a/docs/reference/iso_codes_africa_west.html +++ b/docs/reference/iso_codes_africa_west.html @@ -1,5 +1,5 @@ -ISO3 Country Codes for West African Countries — iso_codes_africa_west • MOSAICISO3 Country Codes for West African Countries — iso_codes_africa_west • MOSAIC @@ -37,7 +37,7 @@
                                                                      • - + diff --git a/docs/reference/iso_codes_mosaic.html b/docs/reference/iso_codes_mosaic.html index 201eab1..ee3b7bb 100644 --- a/docs/reference/iso_codes_mosaic.html +++ b/docs/reference/iso_codes_mosaic.html @@ -1,5 +1,5 @@ -ISO3 Country Codes for MOSAIC Modeling Framework — iso_codes_mosaic • MOSAICISO3 Country Codes for MOSAIC Modeling Framework — iso_codes_mosaic • MOSAIC @@ -37,7 +37,7 @@
                                                                        • - + diff --git a/docs/reference/iso_codes_ssa.html b/docs/reference/iso_codes_ssa.html index 9af8fdf..6ee87c3 100644 --- a/docs/reference/iso_codes_ssa.html +++ b/docs/reference/iso_codes_ssa.html @@ -1,5 +1,5 @@ -ISO3 Country Codes for Sub-Saharan African Countries — iso_codes_ssa • MOSAICISO3 Country Codes for Sub-Saharan African Countries — iso_codes_ssa • MOSAIC @@ -37,7 +37,7 @@
                                                                          • - + diff --git a/docs/reference/iso_codes_who_afro.html b/docs/reference/iso_codes_who_afro.html index a306c85..83580c4 100644 --- a/docs/reference/iso_codes_who_afro.html +++ b/docs/reference/iso_codes_who_afro.html @@ -1,5 +1,5 @@ -ISO3 Country Codes for WHO AFRO Region Countries — iso_codes_who_afro • MOSAICISO3 Country Codes for WHO AFRO Region Countries — iso_codes_who_afro • MOSAIC @@ -37,7 +37,7 @@
                                                                            • - + diff --git a/docs/reference/load_or_install_packages.html b/docs/reference/load_or_install_packages.html index fc1dcc9..c92e040 100644 --- a/docs/reference/load_or_install_packages.html +++ b/docs/reference/load_or_install_packages.html @@ -1,5 +1,5 @@ -Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages • MOSAICLoad or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages • MOSAIC @@ -37,7 +37,7 @@
                                                                              • - + diff --git a/docs/reference/make_param_df.html b/docs/reference/make_param_df.html index 6f9c6e7..920e1bf 100644 --- a/docs/reference/make_param_df.html +++ b/docs/reference/make_param_df.html @@ -1,5 +1,5 @@ -Get Template for Parameter Values — make_param_df • MOSAICGet Template for Parameter Values — make_param_df • MOSAIC @@ -37,7 +37,7 @@
                                                                                • - + diff --git a/docs/reference/plot_ENSO_data.html b/docs/reference/plot_ENSO_data.html index 7025000..835edfe 100644 --- a/docs/reference/plot_ENSO_data.html +++ b/docs/reference/plot_ENSO_data.html @@ -1,5 +1,5 @@ -Plot ENSO and DMI Data — plot_ENSO_data • MOSAICPlot ENSO and DMI Data — plot_ENSO_data • MOSAIC @@ -37,7 +37,7 @@
                                                                                  • - + diff --git a/docs/reference/process_OAG_data.html b/docs/reference/process_OAG_data.html index 4bcd84c..fa15d3d 100644 --- a/docs/reference/process_OAG_data.html +++ b/docs/reference/process_OAG_data.html @@ -3,7 +3,7 @@ location and date conversion, and aggregation. The processed data is saved as CSV files for all African countries and a subset of countries used in the MOSAIC modeling framework.">Process and Save OAG Flight Data for Africa — process_OAG_data • MOSAIC @@ -41,7 +41,7 @@
                                                                                    • - + diff --git a/docs/reference/process_WHO_annual_data.html b/docs/reference/process_WHO_annual_data.html index f6f40c7..c7666a0 100644 --- a/docs/reference/process_WHO_annual_data.html +++ b/docs/reference/process_WHO_annual_data.html @@ -1,5 +1,5 @@ -Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data • MOSAICDownload, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data • MOSAIC @@ -37,7 +37,7 @@
                                                                                      • - + diff --git a/docs/reference/process_WHO_weekly_data.html b/docs/reference/process_WHO_weekly_data.html index 1eb0b49..75c51f1 100644 --- a/docs/reference/process_WHO_weekly_data.html +++ b/docs/reference/process_WHO_weekly_data.html @@ -1,5 +1,5 @@ -Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data • MOSAICProcess Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data • MOSAIC @@ -37,7 +37,7 @@
                                                                                        • - + diff --git a/docs/reference/process_demographics_data.html b/docs/reference/process_demographics_data.html index 63a7ab2..29d62c5 100644 --- a/docs/reference/process_demographics_data.html +++ b/docs/reference/process_demographics_data.html @@ -1,5 +1,5 @@ -Process UN World Prospects Data for African Countries — process_demographics_data • MOSAICProcess UN World Prospects Data for African Countries — process_demographics_data • MOSAIC @@ -37,7 +37,7 @@
                                                                                          • - + diff --git a/docs/reference/run_WHO_annual_data_app.html b/docs/reference/run_WHO_annual_data_app.html index f4f0537..f82f9d5 100644 --- a/docs/reference/run_WHO_annual_data_app.html +++ b/docs/reference/run_WHO_annual_data_app.html @@ -1,5 +1,5 @@ -Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app • MOSAICRun Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app • MOSAIC @@ -37,7 +37,7 @@
                                                                                            • - + diff --git a/docs/reference/set_openmeteo_api_key.html b/docs/reference/set_openmeteo_api_key.html index 8abf59e..270734f 100644 --- a/docs/reference/set_openmeteo_api_key.html +++ b/docs/reference/set_openmeteo_api_key.html @@ -1,7 +1,7 @@ Set OpenMeteo API Key — set_openmeteo_api_key • MOSAIC @@ -39,7 +39,7 @@
                                                                                              • - + diff --git a/docs/reference/set_root_directory.html b/docs/reference/set_root_directory.html index d074cab..7ed9e29 100644 --- a/docs/reference/set_root_directory.html +++ b/docs/reference/set_root_directory.html @@ -1,5 +1,5 @@ -Set Root Directory — set_root_directory • MOSAICSet Root Directory — set_root_directory • MOSAIC @@ -37,7 +37,7 @@
                                                                                                • - + diff --git a/docs/search.json b/docs/search.json index 5cd2bea..eb1befc 100644 --- a/docs/search.json +++ b/docs/search.json @@ -1 +1 @@ -[{"path":"https://gilesjohnr.github.io/MOSAIC-docs/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"John R Giles. Author, maintainer.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Giles J (2024). MOSAIC: Metapopulation Outbreak Simulation Interventions Cholera (MOSAIC). R package version 0.0.1.","code":"@Manual{, title = {MOSAIC: Metapopulation Outbreak Simulation And Interventions for Cholera (MOSAIC)}, author = {John R Giles}, year = {2024}, note = {R package version 0.0.1}, }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/index.html","id":"mosaic-the-metapopulation-outbreak-simulation-with-agent-based-implementation-for-cholera-","dir":"","previous_headings":"","what":"Metapopulation Outbreak Simulation And Interventions for Cholera (MOSAIC)","title":"Metapopulation Outbreak Simulation And Interventions for Cholera (MOSAIC)","text":"  Welcome R package MOSAIC framework. MOSAIC R package provides tools simulating cholera transmission dynamics using metapopulation models, estimating mobility patterns drivers transmission environmental forcing, visualizing disease dynamics outbreak projections. Note repo holds code data models , full documentation see: https://institutefordiseasemodeling.github.io/MOSAIC-docs/.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/index.html","id":"mosaic-project-directory-structure","dir":"","previous_headings":"","what":"MOSAIC Project Directory Structure","title":"Metapopulation Outbreak Simulation And Interventions for Cholera (MOSAIC)","text":"MOSAIC R package designed used within triad Github repos functions documented MOSAIC-pkg. package downloads processes required data saved MOSAIC-data prepares model quantities run MOSAIC saved MOSAIC-pkg/model/input. package also produces figures tables used make documentation located MOSAIC-docs. directory structure MOSAIC project:","code":"MOSAIC/ # Local parent directory to hold 3 repositories, root directory in get_paths() ├── MOSAIC-data/ │ ├── raw/ # Raw data files supplied to MOSAIC-pkg │ └── processed/ # Processed data files supplied to MOSAIC-pkg ├── MOSAIC-pkg/ │ ├── [R package] # Contents of MOSAIC R package: https://gilesjohnr.github.io/MOSAIC-pkg/ │ └── model/ │ ├── input/ # Files used as input to MOSAIC framework │ ├── output/ # Location of output from MOSAIC framework │ └── LAUNCH.R # LAUNCH.R file runs data acquisition functions, a priori models, and runs MOSAIC └── MOSAIC-docs/ ├── [Website] # Documentation and model description: https://gilesjohnr.github.io/MOSAIC-docs/ ├── figures/ # Output images and figures from MOSAIC-pkg used in documentation └── tables/ # Output data and parameter values from MOSAIC-pkg used in documentation"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/compile_ENSO_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data","title":"Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data","text":"function compiles historical forecast data DMI ENSO (Niño3, Niño3.4, Niño4) single data frame. data filtered include years specified year_start onwards. function also allows disaggregation monthly data daily weekly values using either linear interpolation spline interpolation.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/compile_ENSO_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data","text":"","code":"compile_ENSO_data(year_start = NULL, frequency = \"monthly\", method = \"linear\")"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/compile_ENSO_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data","text":"year_start integer representing start year filtering data. data year onward included compiled data. value must greater equal 1870. frequency character string specifying time resolution output data. Valid options \"daily\", \"weekly\", \"monthly\". method character string specifying interpolation method use. Valid options \"linear\" (linear interpolation using zoo::na.approx()) \"spline\" (spline interpolation using zoo::na.spline()).","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/compile_ENSO_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data","text":"data frame combined historical forecast data DMI, ENSO3, ENSO34, ENSO4. data frame includes following columns: date: date data (daily, weekly, monthly) YYYY-MM-DD format. variable: variable name, can \"DMI\", \"ENSO3\", \"ENSO34\", \"ENSO4\". value: value variable (sea surface temperature anomaly). year: year corresponding date. month: month corresponding date. week: week year (\"weekly\" \"daily\" frequency). doy: day year (\"daily\" frequency).","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/compile_ENSO_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data","text":"","code":"if (FALSE) { # Compile the ENSO and DMI data from the year 2000 onwards compiled_enso_data <- compile_ENSO_data(2010, \"monthly\") # Display the compiled data head(compiled_enso_data) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_country_to_iso.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","title":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","text":"function converts country names corresponding ISO3 ISO2 country codes. function uses countrycode package, allows multiple spellings variations country names.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_country_to_iso.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","text":"","code":"convert_country_to_iso(x, iso3 = TRUE)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_country_to_iso.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","text":"x character vector country names (e.g., \"United States\", \"UK\", \"Democratic Republic Congo\"). iso3 logical value. TRUE (default), returns ISO3 country codes. FALSE, returns ISO2 country codes.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_country_to_iso.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","text":"character vector ISO3 ISO2 country codes corresponding country names.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_country_to_iso.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","text":"function converts country names ISO3 ISO2 codes using countrycode package. handles various common alternative spellings country names.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_country_to_iso.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","text":"","code":"# Convert a single country name to ISO3 convert_country_to_iso(\"United States\") #> [1] \"USA\" # Convert a vector of country names to ISO2 convert_country_to_iso(c(\"United States\", \"UK\", \"Democratic Republic of Congo\"), iso3 = FALSE) #> [1] \"US\" \"GB\" \"CD\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_codes.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","title":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","text":"function converts vector scalar ISO3 country codes ISO2 country codes, vice versa, based input. function uses countrycode package auto-detects input format.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_codes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","text":"","code":"convert_iso_codes(iso_codes)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_codes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","text":"iso_codes vector scalar ISO2 ISO3 country codes (e.g., \"USA\", \"GBR\", \"ZA\", \"GB\").","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_codes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","text":"character vector converted ISO2 ISO3 country codes corresponding provided input.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_codes.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","text":"function detects whether input ISO2 ISO3 format based code length converts accordingly using countrycode package.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_codes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","text":"","code":"# Convert a vector of ISO3 codes to ISO2 codes convert_iso_codes(c(\"USA\", \"GBR\", \"DZA\")) #> [1] \"US\" \"GB\" \"DZ\" # Convert a vector of ISO2 codes to ISO3 codes convert_iso_codes(c(\"US\", \"GB\", \"DZ\")) #> [1] \"USA\" \"GBR\" \"DZA\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_to_country.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","title":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","text":"function converts vector scalar ISO2 ISO3 country codes corresponding country names using countrycode package.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_to_country.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","text":"","code":"convert_iso_to_country(iso)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_to_country.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","text":"iso vector scalar ISO2 ISO3 country codes (e.g., \"USA\", \"GB\", \"DZA\").","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_to_country.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","text":"character vector country names corresponding provided ISO2 ISO3 country codes.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_to_country.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","text":"function automatically detects input ISO2 ISO3 format returns corresponding country names. Special handling applied Congo Democratic Republic Congo.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_to_country.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","text":"","code":"# Convert a vector of ISO3 and ISO2 codes to country names convert_iso_to_country(c(\"USA\", \"GBR\", \"DZA\", \"COD\")) #> [1] \"United States\" \"United Kingdom\" #> [3] \"Algeria\" \"Democratic Republic of Congo\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_africa_shapefile.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and Save Africa Shapefile — download_africa_shapefile","title":"Download and Save Africa Shapefile — download_africa_shapefile","text":"function downloads shapefile African countries using rnaturalearth package saves specified directory. output directory exist, created.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_africa_shapefile.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and Save Africa Shapefile — download_africa_shapefile","text":"","code":"download_africa_shapefile(PATHS)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_africa_shapefile.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and Save Africa Shapefile — download_africa_shapefile","text":"PATHS list environment containing path structure, PATHS$DATA_PROCESSED specifies directory save processed shapefile.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_africa_shapefile.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and Save Africa Shapefile — download_africa_shapefile","text":"message indicating shapefile saved, including full path saved file.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_africa_shapefile.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and Save Africa Shapefile — download_africa_shapefile","text":"function uses rnaturalearth package download shapefile African continent. shapefile saved AFRICA_ADM0.shp directory specified PATHS$DATA_PROCESSED/shapefiles. function create directory already exist.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_africa_shapefile.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and Save Africa Shapefile — download_africa_shapefile","text":"","code":"if (FALSE) { # Example PATHS object PATHS <- list(DATA_PROCESSED = \"path/to/processed/data\") # Download and save the Africa shapefile download_africa_shapefile(PATHS) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_all_country_shapefiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","title":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","text":"function downloads shapefiles African country saves specified directory. function iterates ISO3 country codes Africa (MOSAIC framework) saves country's shapefile individually.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_all_country_shapefiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","text":"","code":"download_all_country_shapefiles(PATHS)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_all_country_shapefiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","text":"PATHS list containing paths processed data saved. PATHS typically output get_paths() function include: DATA_PROCESSED: Path directory processed shapefiles saved.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_all_country_shapefiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","text":"function return value. downloads shapefiles African country saves individual shapefiles processed data directory.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_all_country_shapefiles.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","text":"function performs following steps: Creates output directory shapefiles exist. Loops list ISO3 country codes African countries. Downloads country's shapefile using MOSAIC::get_country_shp(). Saves shapefile processed data directory ISO3_ADM0.shp.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_all_country_shapefiles.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","text":"","code":"if (FALSE) { # Define paths for processed data using get_paths() PATHS <- get_paths() # Download and save shapefiles for all African countries download_all_country_shapefiles(PATHS) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_climate_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and Save Climate Data for Multiple Countries — download_climate_data","title":"Download and Save Climate Data for Multiple Countries — download_climate_data","text":"function downloads daily climate data list specified countries, saving data CSV files. data includes historical future climate variables grid points within country.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_climate_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and Save Climate Data for Multiple Countries — download_climate_data","text":"","code":"download_climate_data( PATHS, iso_codes, api_key, n_points = 3, date_start = \"1970-01-01\", date_stop = \"2030-12-31\" )"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_climate_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and Save Climate Data for Multiple Countries — download_climate_data","text":"PATHS list containing paths raw processed data stored. PATHS typically output get_paths() function include: DATA_SHAPEFILES: Path directory containing country shapefiles. DATA_CLIMATE: Path directory processed climate data saved. iso_codes character vector ISO3 country codes climate data downloaded. api_key character string representing API key required access climate data API. n_points integer specifying number grid points generate within country climate data downloaded. date_start character string representing start date climate data (\"YYYY-MM-DD\" format). date_stop character string representing end date climate data (\"YYYY-MM-DD\" format).","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_climate_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and Save Climate Data for Multiple Countries — download_climate_data","text":"function return value. downloads climate data country saves results CSV files specified directory.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_climate_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and Save Climate Data for Multiple Countries — download_climate_data","text":"function uses country shapefiles generate grid points within country, climate data downloaded. function retrieves climate data specified date range (date_start date_stop). data saved country CSV file named climate_data___.csv. climate data variables include temperature, wind speed, cloud cover, precipitation, . function retrieves data multiple climate models, including MRI EC Earth models.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/download_climate_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and Save Climate Data for Multiple Countries — download_climate_data","text":"","code":"if (FALSE) { # Define paths for raw and processed data using get_paths() PATHS <- get_paths() # ISO3 country codes for African countries iso_codes <- c(\"ZAF\", \"KEN\", \"NGA\") # API key for climate data API api_key <- \"your-api-key-here\" # Download climate data and save it for the specified countries download_climate_data(PATHS, iso_codes, api_key, n_points = 5, date_start = \"1970-01-01\", date_stop = \"2030-12-31\") }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_WASH_coverage.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","title":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","text":"function processes Water, Sanitation, Hygiene (WASH) coverage data African countries, optimizes weights WASH variables, calculates weighted means, examines correlation cholera incidence. function generates plots tables showing relationships saves results specified paths.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_WASH_coverage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","text":"","code":"est_WASH_coverage(PATHS)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_WASH_coverage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","text":"PATHS list containing paths WASH data, figures, model inputs saved. Typically generated get_paths() function include: DATA_WASH: Path WASH data CSV file. DOCS_FIGURES: Path save output figures. MODEL_INPUT: Path save model input data. DOCS_TABLES: Path save tables used documentation.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_WASH_coverage.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","text":"function return value, generates saves plots CSV files showing WASH coverage estimates, optimized weights WASH variables, correlation cholera incidence.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_WASH_coverage.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","text":"WASH coverage data first normalized (0-1 scale). Risk-related WASH variables (unimproved water sources, surface water, unimproved sanitation, open defecation) converted protective factors taking complement (1 - value). , function: Optimizes weights WASH variable maximize correlation cholera incidence using L-BFGS-B method. Calculates weighted mean WASH variables country. Generates multiple plots showing relationships WASH variables cholera incidence. Saves tables optimized weights weighted mean WASH indices. Data Source: Sikder et al. (2023). Water, Sanitation, Hygiene Coverage Cholera Incidence Sub-Saharan Africa. doi:10.1021/acs.est.3c01317 .","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_WASH_coverage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","text":"","code":"if (FALSE) { # Define paths for saving WASH data, figures, and tables PATHS <- get_paths() # Estimate WASH coverage and correlation with cholera incidence est_WASH_coverage(PATHS) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_mobility.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","title":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","text":"function processes flight data, population data, distance data fit mobility model using mobility package. model estimates probability travel origin country (departure) probability travel origin destination (diffusion). saves model matrices results CSV files generates plots visualization.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_mobility.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","text":"","code":"est_mobility(PATHS)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_mobility.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","text":"PATHS list containing paths directories raw processed data. Typically, PATHS output get_paths() include: DATA_OAG: Path directory containing flight data. DATA_SHAPEFILES: Path directory containing country shapefiles. DATA_DEMOGRAPHICS: Path directory containing demographic data. MODEL_INPUT: Path directory model matrices saved. DOCS_FIGURES: Path directory figures saved.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_mobility.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","text":"function return value. processes data, fits mobility model, saves results CSV files, creates several visualizations saved PNG files.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_mobility.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","text":"function performs following steps: Loads flight data constructs mobility matrix (M). Constructs distance matrix (D) country centroids based shapefiles. Retrieves population sizes (N) demographic data. Ensures dimensions M, D, N match. Fits probability travel (departure) diffusion (origin-destination) using mobility package. Saves results, including mobility matrix (M), distance matrix (D), population vector (N) CSV files. Saves several plots related mobility model, including heatmap flight data, network plot flight data, plots travel probabilities diffusion probabilities.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_mobility.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","text":"","code":"if (FALSE) { # Assuming PATHS is generated from the get_paths function PATHS <- get_paths() # Fit the mobility model and generate outputs est_mobility(PATHS) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_symptomatic_prop.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop","title":"Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop","text":"function reads symptomatic proportion data, fits Beta distribution simulate proportion infections symptomatic, generates visualizations comparing estimates previous studies.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_symptomatic_prop.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop","text":"","code":"est_symptomatic_prop(PATHS)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_symptomatic_prop.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop","text":"PATHS list containing paths symptomatic proportion data figures saved. Typically generated get_paths() function include: DATA_PROCESSED: Path symptomatic proportion data. DOCS_FIGURES: Path save generated plots.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_symptomatic_prop.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop","text":"function return value generates saves plots PNG file.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/est_symptomatic_prop.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop","text":"","code":"if (FALSE) { # Estimate and visualize symptomatic proportion data PATHS <- get_paths() est_symptomatic_prop(PATHS) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_dist.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","title":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","text":"function generates grid points within country's shapefile, points spaced specified distance kilometers.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_dist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","text":"","code":"generate_country_grid_dist(country_shp, distance_km)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_dist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","text":"country_shp sf object representing country's shapefile. distance_km numeric value specifying distance (kilometers) grid points.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_dist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","text":"sf object containing generated grid points within country boundary.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_dist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","text":"function creates regular grid points within polygon defined country's shapefile, spaced according specified distance kilometers.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_dist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","text":"","code":"if (FALSE) { # Example usage with distance in kilometers grid_points_sf <- generate_country_grid_dist(country_shapefile, distance_km = 50) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_n.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","title":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","text":"function generates grid points within country's shapefile, grid contains specified number evenly spaced points.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_n.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","text":"","code":"generate_country_grid_n(country_shp, n_points)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_n.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","text":"country_shp sf object representing country's shapefile. n_points numeric value specifying total number evenly spaced points generate within country boundary.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_n.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","text":"sf object containing generated grid points within country boundary.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_n.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","text":"function creates regular grid points within polygon defined country's shapefile, containing specified number points.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_n.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","text":"","code":"if (FALSE) { # Example usage with a specified number of points grid_points_sf <- generate_country_grid_n(country_shapefile, n_points = 100) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_DMI_forecast.html","id":null,"dir":"Reference","previous_headings":"","what":"Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast","title":"Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast","text":"function retrieves manually extracted Dipole Mode Index (DMI) forecast data Bureau Meteorology's IOD forecast page.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_DMI_forecast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast","text":"","code":"get_DMI_forecast()"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_DMI_forecast.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast","text":"data frame columns year, month (numeric), month_name, variable (DMI), value. DMI measure difference sea surface temperature anomalies western eastern Indian Ocean used describe Indian Ocean Dipole (IOD).","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_DMI_forecast.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast","text":"IOD forecast manually extracted Bureau Meteorology's IOD forecast page: http://www.bom.gov.au/climate/ocean/outlooks/#region=IOD. data includes DMI values series months years, representing forecasts sea surface temperature anomalies. Negative DMI values indicate cooler waters west, positive DMI values indicate warmer waters west Indian Ocean.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_DMI_forecast.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast","text":"","code":"if (FALSE) { # Get the DMI forecast data dmi_forecast <- get_DMI_forecast() # Display the DMI forecast data print(dmi_forecast) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_DMI_historical.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and Process Historical DMI Data — get_DMI_historical","title":"Download and Process Historical DMI Data — get_DMI_historical","text":"function downloads historical Dipole Mode Index (DMI) data NOAA processes data frame columns year, month (1-12), month_name, variable (DMI), value.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_DMI_historical.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and Process Historical DMI Data — get_DMI_historical","text":"","code":"get_DMI_historical()"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_DMI_historical.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and Process Historical DMI Data — get_DMI_historical","text":"data frame columns year, month, month_name, variable (DMI), value.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_DMI_historical.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and Process Historical DMI Data — get_DMI_historical","text":"DMI data downloaded NOAA's historical DMI data page: https://psl.noaa.gov/gcos_wgsp/Timeseries/Data/dmi..long.data. data includes DMI values representing difference sea surface temperature anomalies western eastern Indian Ocean.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_DMI_historical.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and Process Historical DMI Data — get_DMI_historical","text":"","code":"if (FALSE) { # Get the historical DMI data dmi_historical <- get_DMI_historical() # Display the historical DMI data print(dmi_historical) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ENSO_forecast.html","id":null,"dir":"Reference","previous_headings":"","what":"Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast","title":"Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast","text":"function retrieves manually extracted ENSO forecast data, including Niño3, Niño3.4, Niño4 sea surface temperature (SST) anomalies, Bureau Meteorology.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ENSO_forecast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast","text":"","code":"get_ENSO_forecast()"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ENSO_forecast.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast","text":"data frame columns year, month (numeric), month_name, variable (ENSO3, ENSO34, ENSO4), value.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ENSO_forecast.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast","text":"ENSO forecast manually extracted Bureau Meteorology's ocean outlook page. data includes SST anomalies Niño3, Niño3.4, Niño4 regions. Negative values indicate cooler sea surface temperatures, positive values indicate warmer temperatures.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ENSO_forecast.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast","text":"","code":"if (FALSE) { # Get the ENSO forecast data enso_forecast <- get_ENSO_forecast() # Display the ENSO forecast data print(enso_forecast) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ENSO_historical.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical","title":"Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical","text":"function downloads historical ENSO data Niño3, Niño3.4, Niño4 NOAA processes single data frame columns year (integer), month, month_name, variable (ENSO3, ENSO34, ENSO4), value.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ENSO_historical.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical","text":"","code":"get_ENSO_historical()"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ENSO_historical.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical","text":"data frame columns year, month, month_name, variable, value.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ENSO_historical.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical","text":"historical ENSO data downloaded NOAA's historical ENSO data pages. data includes sea surface temperature anomalies Niño3, Niño3.4, Niño4 regions.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ENSO_historical.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical","text":"","code":"if (FALSE) { # Get the historical ENSO data enso_historical <- get_ENSO_historical() # Display the historical ENSO data print(enso_historical) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_WASH_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download, Process, and Save WASH Coverage Data — get_WASH_data","title":"Download, Process, and Save WASH Coverage Data — get_WASH_data","text":"function processes WASH (Water, Sanitation, Hygiene) coverage data African countries Sikder et al. (2023). data includes indicators water sanitation access, including piped water, improved sanitation, unimproved water sources, open defecation. processed data saved CSV file specified path.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_WASH_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download, Process, and Save WASH Coverage Data — get_WASH_data","text":"","code":"get_WASH_data(PATHS)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_WASH_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download, Process, and Save WASH Coverage Data — get_WASH_data","text":"PATHS list containing paths WASH data saved. Typically generated get_paths() function include: DATA_WASH: Path directory processed WASH data saved.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_WASH_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download, Process, and Save WASH Coverage Data — get_WASH_data","text":"function return value processes WASH coverage data saves specified directory CSV file.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_WASH_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download, Process, and Save WASH Coverage Data — get_WASH_data","text":"WASH coverage data based percentages population access piped water, improved water sources, septic sewer sanitation, improved sanitation. data also includes proportions population using unimproved water sources, surface water, unimproved sanitation, practicing open defecation. risk-related variables (unimproved water, surface water, unimproved sanitation, open defecation) converted complement (1 - value) reflect protective factors. data scaled 0 1. Data Source: Sikder et al. (2023). Water, Sanitation, Hygiene Coverage Cholera Incidence Sub-Saharan Africa. doi:10.1021/acs.est.3c01317 .","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_WASH_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download, Process, and Save WASH Coverage Data — get_WASH_data","text":"","code":"if (FALSE) { # Define paths for saving WASH data PATHS <- get_paths() # Download, process, and save WASH coverage data get_WASH_data(PATHS) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_centroid.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the Centroid of a Country from its Shapefile — get_centroid","title":"Calculate the Centroid of a Country from its Shapefile — get_centroid","text":"function reads country shapefile, calculates centroid, returns centroid coordinates (longitude latitude) along ISO3 country code.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_centroid.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the Centroid of a Country from its Shapefile — get_centroid","text":"","code":"get_centroid(shapefile)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_centroid.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the Centroid of a Country from its Shapefile — get_centroid","text":"shapefile character string representing file path country shapefile (.shp format).","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_centroid.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the Centroid of a Country from its Shapefile — get_centroid","text":"data frame following columns: iso3: ISO3 country code extracted shapefile name. lon: longitude country's centroid. lat: latitude country's centroid.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_centroid.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate the Centroid of a Country from its Shapefile — get_centroid","text":"function reads shapefile using sf::st_read(), calculates centroid country using sf::st_centroid(), extracts coordinates centroid sf::st_coordinates(). ISO3 code extracted filename shapefile, assuming first three characters shapefile name represent ISO3 country code.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_centroid.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the Centroid of a Country from its Shapefile — get_centroid","text":"","code":"if (FALSE) { # Example usage: # Assuming you have a shapefile \"ZAF_ADM0.shp\" for South Africa shapefile_path <- \"path/to/shapefile/ZAF_ADM0.shp\" centroid_data <- get_centroid(shapefile_path) print(centroid_data) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_forecast.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Climate Forecast Data (Daily) — get_climate_forecast","title":"Get Climate Forecast Data (Daily) — get_climate_forecast","text":"function retrieves daily climate forecast data specified location one climate variables range forecast days using Open-Meteo API.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_forecast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Climate Forecast Data (Daily) — get_climate_forecast","text":"","code":"get_climate_forecast(lat, lon, n_days, climate_variables, api_key = NULL)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_forecast.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Climate Forecast Data (Daily) — get_climate_forecast","text":"lat numeric value representing latitude location. lon numeric value representing longitude location. n_days integer representing number forecast days retrieve (maximum value 15). climate_variables character vector climate variables retrieve (e.g., c(\"temperature_2m_max\", \"precipitation_sum\")). api_key character string representing API key Open-Meteo API.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_forecast.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Climate Forecast Data (Daily) — get_climate_forecast","text":"data frame columns: date date forecast (class Date). climate_variable name climate variable. climate_value value climate variable date.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_forecast.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Climate Forecast Data (Daily) — get_climate_forecast","text":"function queries Open-Meteo API daily weather forecast data specified latitude, longitude, range forecast days (15 days). API request successful, function returns data frame containing date, climate variable, value. request fails, function returns NULL issues warning HTTP status code.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_forecast.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Climate Forecast Data (Daily) — get_climate_forecast","text":"","code":"if (FALSE) { # Example usage to get forecast data for multiple climate variables lat <- 52.52 lon <- 13.41 n_days <- 15 climate_variables <- c(\"temperature_2m_max\", \"precipitation_sum\") api_key <- \"your_api_key_here\" forecast_data <- get_climate_forecast(lat, lon, n_days, climate_variables, api_key) print(forecast_data) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_future.html","id":null,"dir":"Reference","previous_headings":"","what":"Download Future Climate Data for Multiple Locations — get_climate_future","title":"Download Future Climate Data for Multiple Locations — get_climate_future","text":"function retrieves daily future climate data multiple specified locations climate variables specified date range using specified climate models.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_future.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download Future Climate Data for Multiple Locations — get_climate_future","text":"","code":"get_climate_future( lat, lon, start_date, end_date, climate_variables, climate_models, api_key = NULL )"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_future.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download Future Climate Data for Multiple Locations — get_climate_future","text":"lat numeric vector representing latitudes locations. lon numeric vector representing longitudes locations. start_date character string representing start date data \"YYYY-MM-DD\" format. end_date character string representing end date data \"YYYY-MM-DD\" format. climate_variables character vector climate variables retrieve. Valid options include: temperature_2m_mean: Mean 2m air temperature. temperature_2m_max: Maximum 2m air temperature. temperature_2m_min: Minimum 2m air temperature. wind_speed_10m_mean: Mean 10m wind speed. wind_speed_10m_max: Maximum 10m wind speed. cloud_cover_mean: Mean cloud cover. shortwave_radiation_sum: Sum shortwave radiation. relative_humidity_2m_mean: Mean 2m relative humidity. relative_humidity_2m_max: Maximum 2m relative humidity. relative_humidity_2m_min: Minimum 2m relative humidity. dew_point_2m_mean: Mean 2m dew point temperature. dew_point_2m_min: Minimum 2m dew point temperature. dew_point_2m_max: Maximum 2m dew point temperature. precipitation_sum: Total precipitation. rain_sum: Total rainfall. snowfall_sum: Total snowfall. pressure_msl_mean: Mean sea level pressure. soil_moisture_0_to_10cm_mean: Mean soil moisture (0-10 cm depth). et0_fao_evapotranspiration_sum: Sum evapotranspiration (FAO standard). climate_models character vector climate models use. Available models include: CMCC_CM2_VHR4 FGOALS_f3_H HiRAM_SIT_HR MRI_AGCM3_2_S EC_Earth3P_HR MPI_ESM1_2_XR NICAM16_8S api_key character string representing API key climate data API. provided, function assumes API key required.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_future.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download Future Climate Data for Multiple Locations — get_climate_future","text":"data frame columns: date: date climate data. latitude: latitude location. longitude: longitude location. climate_model: climate model used data. variable_name: climate variable retrieved (e.g., temperature_2m_mean, precipitation_sum). value: value climate variable date.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_future.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download Future Climate Data for Multiple Locations — get_climate_future","text":"function retrieves daily future climate data multiple specified locations using Open-Meteo Climate API. downloads specified climate variables latitude longitude provided, using selected climate models. data retrieved date range specified start_date end_date. progress bar displayed indicate download progress.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_future.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download Future Climate Data for Multiple Locations — get_climate_future","text":"","code":"if (FALSE) { # Define latitudes and longitudes for the locations lat <- c(40.7128, 34.0522) lon <- c(-74.0060, -118.2437) # Define the climate variables and models climate_vars <- c(\"temperature_2m_mean\", \"precipitation_sum\") climate_models <- c(\"MRI_AGCM3_2_S\", \"EC_Earth3P_HR\") # Set the date range and API key start_date <- \"2023-01-01\" end_date <- \"2030-12-31\" api_key <- \"your_api_key_here\" # Download the climate data climate_data <- get_climate_future(lat, lon, start_date, end_date, climate_vars, climate_models, api_key) # Display the climate data head(climate_data) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_historical.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Historical Climate Data — get_climate_historical","title":"Get Historical Climate Data — get_climate_historical","text":"function retrieves historical weather data specified location one climate variables date range. uses Open-Meteo API.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_historical.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Historical Climate Data — get_climate_historical","text":"","code":"get_climate_historical( lat, lon, start_date, end_date, climate_variables, api_key = NULL )"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_historical.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Historical Climate Data — get_climate_historical","text":"lat numeric value representing latitude location. lon numeric value representing longitude location. start_date character string representing start date \"YYYY-MM-DD\" format. end_date character string representing end date \"YYYY-MM-DD\" format. climate_variables character vector climate variables retrieve (e.g., c(\"precipitation_sum\", \"temperature_2m_max\")). api_key character string representing API key Open-Meteo API. provided, default key used.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_historical.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Historical Climate Data — get_climate_historical","text":"data frame columns: date date observation (class Date). climate_variable name climate variable. climate_value value climate variable date.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_historical.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Historical Climate Data — get_climate_historical","text":"function queries Open-Meteo API historical weather data given latitude, longitude, climate variables specified date range. API request successful, function returns data frame containing date, climate variable, value. request fails, function returns NULL issues warning HTTP status code.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_historical.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Historical Climate Data — get_climate_historical","text":"","code":"if (FALSE) { # Example usage to get historical data for multiple climate variables lat <- 40.7128 lon <- -74.0060 start_date <- \"2020-01-01\" end_date <- \"2020-12-31\" climate_variables <- c(\"temperature_2m_max\", \"precipitation_sum\") api_key <- \"your_api_key_here\" # Replace with your actual API key climate_data <- get_climate_historical(lat, lon, start_date, end_date, climate_variables, api_key) print(climate_data) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_country_shp.html","id":null,"dir":"Reference","previous_headings":"","what":"Get a country shapefile from GeoBoundaries API — get_country_shp","title":"Get a country shapefile from GeoBoundaries API — get_country_shp","text":"function retrieves shapefile given iso3 code GeoBoundaries data API.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_country_shp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get a country shapefile from GeoBoundaries API — get_country_shp","text":"","code":"get_country_shp(iso3, path_output = NULL)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_country_shp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get a country shapefile from GeoBoundaries API — get_country_shp","text":"iso3 three-letter capitalized character string. Must follow ISO-3166 Alpha-3 country code standard (https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3). path_output file path save country shapefile","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_country_shp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get a country shapefile from GeoBoundaries API — get_country_shp","text":"sf class shapefile","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_country_shp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get a country shapefile from GeoBoundaries API — get_country_shp","text":"","code":"if (FALSE) { tmp <- get_country_shp(iso3 = 'MCO') plot(tmp) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_elevation.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","title":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","text":"function retrieves elevation data specified number points within boundary country's shapefile iso_codes_mosaic list using Open-Meteo API. returns mean elevation country.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_elevation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","text":"","code":"get_elevation(PATHS, n_points, api_key = NULL)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_elevation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","text":"PATHS list containing paths elevation data saved. Typically generated get_paths() function include: DATA_SHAPEFILES: Path directory containing country shapefiles. DATA_ELEVATION: Path directory elevation data saved. n_points integer specifying number points generate within country's boundary. api_key character string representing API key Open-Meteo API.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_elevation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","text":"data frame mean elevation country iso_codes_mosaic.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_elevation.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","text":"function loads shapefiles countries iso_codes_mosaic specified directory, generates n_points random points within country's boundary, queries Open-Meteo API elevation data point. returns mean elevation country saves data CSV file.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_elevation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","text":"","code":"if (FALSE) { # Example usage to get mean elevation data for all countries in iso_codes_mosaic n_points <- 10 api_key <- \"your_api_key_here\" PATHS <- get_paths() mean_elevations <- get_elevation(n_points, api_key, PATHS) print(mean_elevations) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ggplot_legend.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract the Legend from a ggplot Object — get_ggplot_legend","title":"Extract the Legend from a ggplot Object — get_ggplot_legend","text":"function extracts legend ggplot object returns grob (graphical object). extracted legend can used independently, instance, combine legend plots.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ggplot_legend.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract the Legend from a ggplot Object — get_ggplot_legend","text":"","code":"get_ggplot_legend(plot)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ggplot_legend.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract the Legend from a ggplot Object — get_ggplot_legend","text":"plot ggplot object legend extracted.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ggplot_legend.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract the Legend from a ggplot Object — get_ggplot_legend","text":"grob representing legend ggplot object.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ggplot_legend.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract the Legend from a ggplot Object — get_ggplot_legend","text":"function converts ggplot object grob using ggplotGrob() extracts legend, stored grob name \"guide-box\". function can used separate legend plot combine plots needed.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ggplot_legend.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract the Legend from a ggplot Object — get_ggplot_legend","text":"","code":"# Create a simple ggplot object p <- ggplot2::ggplot(mtcars, ggplot2::aes(x = wt, y = mpg, color = factor(gear))) + ggplot2::geom_point() + ggplot2::scale_color_discrete(name = \"Gear\") # Extract the legend from the plot legend <- get_ggplot_legend(p) # Display the extracted legend grid::grid.draw(legend)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_paths.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Directory Paths for the MOSAIC Project — get_paths","title":"Generate Directory Paths for the MOSAIC Project — get_paths","text":"get_paths() function generates structured list file paths different data document directories MOSAIC project, based provided root directory.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_paths.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Directory Paths for the MOSAIC Project — get_paths","text":"","code":"get_paths(root = NULL)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_paths.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Directory Paths for the MOSAIC Project — get_paths","text":"root string specifying root directory MOSAIC project. paths generated relative root.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_paths.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate Directory Paths for the MOSAIC Project — get_paths","text":"named list containing following paths: ROOT root directory provided user. DATA_RAW Path raw data directory (\"MOSAIC-data/data/raw\"). DATA_PROCESSED Path processed data directory (\"MOSAIC-data/data/processed\"). MODEL_INPUT NULL, reserved path model input (applicable). MODEL_OUTPUT NULL, reserved path model output (applicable). DOCS_FIGURES Path figures directory (\"MOSAIC-docs/figures\"). DOCS_TABLES Path tables directory (\"MOSAIC-docs/tables\"). DOCS_PARAMS Path parameters directory (\"MOSAIC-docs/parameters\").","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_paths.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate Directory Paths for the MOSAIC Project — get_paths","text":"function helps organize directory structure data document storage MOSAIC project generating paths raw data, processed data, figures, tables, parameters. paths returned named list can used streamline access various project-related directories.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_paths.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate Directory Paths for the MOSAIC Project — get_paths","text":"","code":"if (FALSE) { root_dir <- \"/{full file path}/MOSAIC\" PATHS <- get_paths(root_dir) print(PATHS$DATA_RAW) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_symptomatic_prop_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Symptomatic Proportion Data — get_symptomatic_prop_data","title":"Get Symptomatic Proportion Data — get_symptomatic_prop_data","text":"function creates data frame studies reporting proportion cholera infections symptomatic saves CSV file.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_symptomatic_prop_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Symptomatic Proportion Data — get_symptomatic_prop_data","text":"","code":"get_symptomatic_prop_data(PATHS)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_symptomatic_prop_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Symptomatic Proportion Data — get_symptomatic_prop_data","text":"PATHS list containing paths symptomatic proportion data saved. Typically generated get_paths() function include: DATA_PROCESSED: Path save symptomatic proportion data.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_symptomatic_prop_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Symptomatic Proportion Data — get_symptomatic_prop_data","text":"function return value saves data frame CSV file.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/get_symptomatic_prop_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Symptomatic Proportion Data — get_symptomatic_prop_data","text":"","code":"if (FALSE) { # Generate and save symptomatic proportion data PATHS <- get_paths() get_symptomatic_prop_data(PATHS) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for All African Countries — iso_codes_africa","title":"ISO3 Country Codes for All African Countries — iso_codes_africa","text":"character vector containing ISO3 country codes 54 countries Africa.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for All African Countries — iso_codes_africa","text":"","code":"iso_codes_africa"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for All African Countries — iso_codes_africa","text":"character vector ISO3 country codes.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for All African Countries — iso_codes_africa","text":"","code":"# Access ISO3 codes for all African countries iso_codes_africa #> [1] \"DZA\" \"AGO\" \"BEN\" \"BWA\" \"BFA\" \"BDI\" \"CPV\" \"CMR\" \"CAF\" \"TCD\" \"COM\" \"COG\" #> [13] \"COD\" \"CIV\" \"DJI\" \"EGY\" \"GNQ\" \"ERI\" \"SWZ\" \"ETH\" \"GAB\" \"GMB\" \"GHA\" \"GIN\" #> [25] \"GNB\" \"KEN\" \"LSO\" \"LBR\" \"LBY\" \"MDG\" \"MWI\" \"MLI\" \"MRT\" \"MUS\" \"MAR\" \"MOZ\" #> [37] \"NAM\" \"NER\" \"NGA\" \"RWA\" \"STP\" \"SEN\" \"SYC\" \"SLE\" \"SOM\" \"ZAF\" \"SSD\" \"SDN\" #> [49] \"TGO\" \"TUN\" \"UGA\" \"TZA\" \"ZMB\" \"ZWE\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_central.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for Central African Countries — iso_codes_africa_central","title":"ISO3 Country Codes for Central African Countries — iso_codes_africa_central","text":"character vector containing ISO3 country codes 8 countries Central Africa.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_central.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for Central African Countries — iso_codes_africa_central","text":"","code":"iso_codes_africa_central"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_central.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for Central African Countries — iso_codes_africa_central","text":"character vector ISO3 country codes.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_central.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for Central African Countries — iso_codes_africa_central","text":"","code":"# Access ISO3 codes for Central African countries iso_codes_africa_central #> [1] \"AGO\" \"CAF\" \"TCD\" \"COG\" \"COD\" \"GNQ\" \"GAB\" \"STP\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_east.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for East African Countries — iso_codes_africa_east","title":"ISO3 Country Codes for East African Countries — iso_codes_africa_east","text":"character vector containing ISO3 country codes 14 countries East Africa.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_east.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for East African Countries — iso_codes_africa_east","text":"","code":"iso_codes_africa_east"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_east.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for East African Countries — iso_codes_africa_east","text":"character vector ISO3 country codes.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_east.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for East African Countries — iso_codes_africa_east","text":"","code":"# Access ISO3 codes for East African countries iso_codes_africa_east #> [1] \"BDI\" \"COM\" \"DJI\" \"ERI\" \"ETH\" \"KEN\" \"MDG\" \"MWI\" \"RWA\" \"SYC\" \"SOM\" \"SSD\" #> [13] \"TZA\" \"UGA\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_north.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for North African Countries — iso_codes_africa_north","title":"ISO3 Country Codes for North African Countries — iso_codes_africa_north","text":"character vector containing ISO3 country codes 6 countries North Africa.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_north.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for North African Countries — iso_codes_africa_north","text":"","code":"iso_codes_africa_north"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_north.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for North African Countries — iso_codes_africa_north","text":"character vector ISO3 country codes.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_north.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for North African Countries — iso_codes_africa_north","text":"","code":"# Access ISO3 codes for North African countries iso_codes_africa_north #> [1] \"DZA\" \"EGY\" \"LBY\" \"MAR\" \"SDN\" \"TUN\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_south.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for Southern African Countries — iso_codes_africa_south","title":"ISO3 Country Codes for Southern African Countries — iso_codes_africa_south","text":"character vector containing ISO3 country codes 7 countries Southern Africa.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_south.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for Southern African Countries — iso_codes_africa_south","text":"","code":"iso_codes_africa_south"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_south.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for Southern African Countries — iso_codes_africa_south","text":"character vector ISO3 country codes.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_south.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for Southern African Countries — iso_codes_africa_south","text":"","code":"# Access ISO3 codes for Southern African countries iso_codes_africa_south #> [1] \"BWA\" \"LSO\" \"NAM\" \"ZAF\" \"SWZ\" \"ZMB\" \"ZWE\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_west.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for West African Countries — iso_codes_africa_west","title":"ISO3 Country Codes for West African Countries — iso_codes_africa_west","text":"character vector containing ISO3 country codes 16 countries West Africa.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_west.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for West African Countries — iso_codes_africa_west","text":"","code":"iso_codes_africa_west"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_west.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for West African Countries — iso_codes_africa_west","text":"character vector ISO3 country codes.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_west.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for West African Countries — iso_codes_africa_west","text":"","code":"# Access ISO3 codes for West African countries iso_codes_africa_west #> [1] \"BEN\" \"BFA\" \"CPV\" \"CIV\" \"GMB\" \"GHA\" \"GIN\" \"GNB\" \"LBR\" \"MLI\" \"MRT\" \"NER\" #> [13] \"NGA\" \"SEN\" \"SLE\" \"TGO\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_mosaic.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for MOSAIC Modeling Framework — iso_codes_mosaic","title":"ISO3 Country Codes for MOSAIC Modeling Framework — iso_codes_mosaic","text":"character vector containing ISO3 country codes 40 countries modeled MOSAIC framework.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_mosaic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for MOSAIC Modeling Framework — iso_codes_mosaic","text":"","code":"iso_codes_mosaic"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_mosaic.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for MOSAIC Modeling Framework — iso_codes_mosaic","text":"character vector ISO3 country codes.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_mosaic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for MOSAIC Modeling Framework — iso_codes_mosaic","text":"","code":"# Access ISO3 codes for countries modeled in the MOSAIC framework iso_codes_mosaic #> [1] \"AGO\" \"BEN\" \"BWA\" \"BFA\" \"BDI\" \"CMR\" \"CAF\" \"TCD\" \"COG\" \"COD\" \"CIV\" \"GNQ\" #> [13] \"ERI\" \"SWZ\" \"ETH\" \"GAB\" \"GMB\" \"GHA\" \"GIN\" \"GNB\" \"KEN\" \"LSO\" \"LBR\" \"MWI\" #> [25] \"MLI\" \"MRT\" \"MOZ\" \"NAM\" \"NER\" \"NGA\" \"RWA\" \"SEN\" \"SLE\" \"SOM\" \"ZAF\" \"SSD\" #> [37] \"TGO\" \"UGA\" \"TZA\" \"ZMB\" \"ZWE\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_ssa.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for Sub-Saharan African Countries — iso_codes_ssa","title":"ISO3 Country Codes for Sub-Saharan African Countries — iso_codes_ssa","text":"character vector containing ISO3 country codes 48 countries Sub-Saharan Africa.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_ssa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for Sub-Saharan African Countries — iso_codes_ssa","text":"","code":"iso_codes_ssa"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_ssa.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for Sub-Saharan African Countries — iso_codes_ssa","text":"character vector ISO3 country codes.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_ssa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for Sub-Saharan African Countries — iso_codes_ssa","text":"","code":"# Access ISO3 codes for Sub-Saharan African countries iso_codes_ssa #> [1] \"AGO\" \"BEN\" \"BWA\" \"BFA\" \"BDI\" \"CMR\" \"CPV\" \"CAF\" \"TCD\" \"COM\" \"COG\" \"COD\" #> [13] \"CIV\" \"DJI\" \"GNQ\" \"ERI\" \"SWZ\" \"ETH\" \"GAB\" \"GMB\" \"GHA\" \"GIN\" \"GNB\" \"KEN\" #> [25] \"LSO\" \"LBR\" \"MDG\" \"MWI\" \"MLI\" \"MRT\" \"MUS\" \"MOZ\" \"NAM\" \"NER\" \"NGA\" \"RWA\" #> [37] \"STP\" \"SEN\" \"SYC\" \"SLE\" \"SOM\" \"ZAF\" \"SSD\" \"SDN\" \"TGO\" \"UGA\" \"TZA\" \"ZMB\" #> [49] \"ZWE\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_who_afro.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for WHO AFRO Region Countries — iso_codes_who_afro","title":"ISO3 Country Codes for WHO AFRO Region Countries — iso_codes_who_afro","text":"character vector containing ISO3 country codes 47 countries African Region (AFRO).","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_who_afro.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for WHO AFRO Region Countries — iso_codes_who_afro","text":"","code":"iso_codes_who_afro"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_who_afro.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for WHO AFRO Region Countries — iso_codes_who_afro","text":"character vector ISO3 country codes.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_who_afro.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for WHO AFRO Region Countries — iso_codes_who_afro","text":"","code":"# Access ISO3 codes for WHO AFRO Region countries iso_codes_who_afro #> [1] \"DZA\" \"AGO\" \"BEN\" \"BWA\" \"BFA\" \"BDI\" \"CPV\" \"CMR\" \"CAF\" \"TCD\" \"COM\" \"COG\" #> [13] \"COD\" \"CIV\" \"DJI\" \"GNQ\" \"ERI\" \"SWZ\" \"ETH\" \"GAB\" \"GMB\" \"GHA\" \"GIN\" \"GNB\" #> [25] \"KEN\" \"LSO\" \"LBR\" \"MDG\" \"MWI\" \"MLI\" \"MRT\" \"MUS\" \"MOZ\" \"NAM\" \"NER\" \"NGA\" #> [37] \"RWA\" \"STP\" \"SEN\" \"SYC\" \"SLE\" \"SOM\" \"ZAF\" \"SSD\" \"SDN\" \"TGO\" \"UGA\" \"TZA\" #> [49] \"ZMB\" \"ZWE\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/load_or_install_packages.html","id":null,"dir":"Reference","previous_headings":"","what":"Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages","title":"Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages","text":"function checks whether specified packages installed. package installed, installed. Special handling included mobility, propvacc, MOSAIC, installed GitHub.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/load_or_install_packages.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages","text":"","code":"load_or_install_packages(packages)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/load_or_install_packages.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages","text":"packages character vector package names load install.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/load_or_install_packages.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages","text":"packages, function installs CRAN already installed. Special cases handled following packages: mobility: Installed GitHub https://github.com/COVID-19-Mobility-Data-Network/mobility. propvacc: Installed GitHub https://github.com/gilesjohnr/propvacc. MOSAIC: Installed GitHub https://github.com/InstituteforDiseaseModeling/MOSAIC-pkg.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/load_or_install_packages.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages","text":"","code":"if (FALSE) { load_or_install_packages(c(\"ggplot2\", \"mobility\", \"propvacc\", \"MOSAIC\")) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/make_param_df.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Template for Parameter Values — make_param_df","title":"Get Template for Parameter Values — make_param_df","text":"function generates template long-form data frame parameter values, including origin (), destination (j), time (t), used simulate variables sigma.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/make_param_df.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Template for Parameter Values — make_param_df","text":"","code":"make_param_df( variable_name = NULL, variable_description = NULL, parameter_distribution = NULL, i = NULL, j = NULL, t = NULL, parameter_name = NULL, parameter_value = NULL )"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/make_param_df.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Template for Parameter Values — make_param_df","text":"variable_name character string representing name variable (e.g., 'sigma'). variable_description character string describing variable (e.g., 'proportion symptomatic'). parameter_distribution character string representing distribution parameter (e.g., 'beta'). vector representing origin locations. j vector representing destination locations. t vector representing time points. parameter_name character vector parameter names (e.g., shape1, shape2 beta distribution). parameter_value numeric vector parameter values (corresponding parameter names).","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/make_param_df.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Template for Parameter Values — make_param_df","text":"data frame containing long-form template parameter values. arguments NULL, empty data frame returned.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/make_param_df.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Template for Parameter Values — make_param_df","text":"","code":"# Example usage for sigma prm <- list(shape1 = 2, shape2 = 5) param_df <- make_param_df(\"sigma\", \"proportion symptomatic\", \"beta\", i = \"A\", j = \"B\", t = 1, names(prm), unlist(prm)) print(param_df) #> variable_name variable_description parameter_distribution i j t #> 1 sigma proportion symptomatic beta A B 1 #> 2 sigma proportion symptomatic beta A B 1 #> parameter_name parameter_value #> 1 shape1 2 #> 2 shape2 5"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/plot_ENSO_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot ENSO and DMI Data — plot_ENSO_data","title":"Plot ENSO and DMI Data — plot_ENSO_data","text":"function creates facet plot visualize ENSO DMI data time, separate panels variable (DMI, ENSO3, ENSO34, ENSO4). horizontal line zero included indicate neutral value, vertical line marks current date, date displayed vertically left side line.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/plot_ENSO_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot ENSO and DMI Data — plot_ENSO_data","text":"","code":"plot_ENSO_data(compiled_data)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/plot_ENSO_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot ENSO and DMI Data — plot_ENSO_data","text":"compiled_data data frame containing ENSO DMI data, columns date, variable, value. data typically generated compile_ENSO_data function.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/plot_ENSO_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot ENSO and DMI Data — plot_ENSO_data","text":"ggplot facet plot showing time series DMI, ENSO3, ENSO34, ENSO4 time. plot includes: horizontal solid line zero indicate neutral sea surface temperature anomaly. vertical dashed line indicate current date, current date displayed vertical text. Facets variable, allowing easy comparison DMI ENSO regions.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/plot_ENSO_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot ENSO and DMI Data — plot_ENSO_data","text":"function uses ggplot2 create line plot facets variable (DMI, ENSO3, ENSO34, ENSO4). adds horizontal reference line zero vertical line representing current date. current date displayed vertical text aligned left vertical line. data expected date, variable, value format.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/plot_ENSO_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot ENSO and DMI Data — plot_ENSO_data","text":"","code":"if (FALSE) { # Compile the ENSO and DMI data from the year 2000 onwards compiled_enso_data <- compile_ENSO_data(2010, \"daily\") # Plot the data plot_ENSO_data(compiled_enso_data) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_OAG_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Process and Save OAG Flight Data for Africa — process_OAG_data","title":"Process and Save OAG Flight Data for Africa — process_OAG_data","text":"function processes raw OAG flight data African countries, including data cleaning, location date conversion, aggregation. processed data saved CSV files African countries subset countries used MOSAIC modeling framework.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_OAG_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process and Save OAG Flight Data for Africa — process_OAG_data","text":"","code":"process_OAG_data(PATHS)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_OAG_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process and Save OAG Flight Data for Africa — process_OAG_data","text":"PATHS list containing paths raw processed data stored. PATHS typically output get_paths() function include following components: DATA_RAW: Path directory containing raw data files. DATA_PROCESSED: Path directory processed data saved.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_OAG_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process and Save OAG Flight Data for Africa — process_OAG_data","text":"function return value. processes OAG flight data saves aggregated results specified processed data paths.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_OAG_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Process and Save OAG Flight Data for Africa — process_OAG_data","text":"function performs following steps: Loads raw OAG flight data CSV file. Cleans formats data, including converting country codes date information. Aggregates data year calculates mean weekly passenger counts. Saves aggregated data African countries MOSAIC framework countries separate CSV files. output files saved processed data directory defined PATHS$DATA_PROCESSED.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_OAG_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Process and Save OAG Flight Data for Africa — process_OAG_data","text":"","code":"if (FALSE) { # Define paths for raw and processed data using get_paths() PATHS <- get_paths() # Process the OAG data and save the results process_OAG_data(PATHS) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_annual_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","title":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","text":"function compiles historical cholera data African countries (AFRO region) years 1949 2024. data processed saved MOSAIC directory structure. includes reported cholera cases, deaths, case fatality ratios (CFR).","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_annual_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","text":"","code":"process_WHO_annual_data(PATHS)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_annual_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","text":"PATHS list containing paths raw processed data directories. Typically generated get_paths() include: DATA_RAW: Path directory containing raw cholera data. DATA_WHO_ANNUAL: Path directory processed cholera data saved.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_annual_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","text":"function return value processes saves historical cholera data CSV files processed data directory.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_annual_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","text":"function compiles cholera data African countries (AFRO region) processing historical data 1949-2024. data sources follows: 1949-2021: Data compiled annual reports World Data. See https://ourworldindata.org. 2022: Data manually extracted annual report. 2023-2024: Data downloaded directly AWD GIS dashboard. Additionally, function calculates 95% binomial confidence intervals CFR applicable, data saved CSV files processed data directory.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_annual_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","text":"","code":"if (FALSE) { # Assuming PATHS is generated from get_paths() PATHS <- get_paths() # Download and process WHO annual cholera data process_WHO_annual_data(PATHS) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_weekly_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","title":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","text":"function processes cholera data converting country names ISO3 codes, filtering AFRO region countries, cleaning organizing data analysis.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_weekly_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","text":"","code":"process_WHO_weekly_data(PATHS)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_weekly_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","text":"PATHS list containing paths raw processed data directories. Typically generated get_paths() function include: DATA_RAW: Path raw cholera data file (e.g., cholera_country_weekly.csv). DATA_PROCESSED: Path save processed cholera data (e.g., cholera_country_weekly_processed.csv).","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_weekly_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","text":"function return value processes cholera data saves specified file CSV.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_weekly_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","text":"function reads cholera data, converts country names ISO3 codes (vice versa), filters countries AFRO region, ensures data cleaned organized year week. also handles special cases renaming Democratic Republic Congo Congo (Republic) modifies column names consistency.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_weekly_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","text":"","code":"if (FALSE) { # Assuming PATHS is generated from get_paths() PATHS <- get_paths() # Process cholera data process_WHO_weekly_data(PATHS) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_demographics_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Process UN World Prospects Data for African Countries — process_demographics_data","title":"Process UN World Prospects Data for African Countries — process_demographics_data","text":"function processes demographic data UN World Population Prospects African countries. filters data specified years, calculates population, birth rates, death rates per day, saves processed data CSV file.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_demographics_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process UN World Prospects Data for African Countries — process_demographics_data","text":"","code":"process_demographics_data(PATHS)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_demographics_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process UN World Prospects Data for African Countries — process_demographics_data","text":"PATHS list containing paths raw processed data stored. PATHS typically output get_paths() function include following components: DATA_RAW: Path directory containing raw UN World Population Prospects data. DATA_PROCESSED: Path directory processed demographic data saved.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_demographics_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process UN World Prospects Data for African Countries — process_demographics_data","text":"function return value. processes UN demographic data saves aggregated results CSV file specified directory.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_demographics_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Process UN World Prospects Data for African Countries — process_demographics_data","text":"function performs following steps: Loads raw demographic data CSV file. Filters data specified years African countries. Calculates population, birth rate, death rate per day country. Saves processed data CSV file processed data directory. processed data file saved PATHS$DATA_PROCESSED/demographics/ directory, filename includes year range data.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/process_demographics_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Process UN World Prospects Data for African Countries — process_demographics_data","text":"","code":"if (FALSE) { # Define paths for raw and processed data using get_paths() PATHS <- get_paths() # Process the UN World Prospects data and save the results process_demographics_data(PATHS) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/run_WHO_annual_data_app.html","id":null,"dir":"Reference","previous_headings":"","what":"Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app","title":"Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app","text":"function launches Shiny app visualizes cholera cases, deaths, case fatality rate (CFR) countries AFRO region 1970 2024. Users can select metric (cases, deaths, CFR) filter specific countries.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/run_WHO_annual_data_app.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app","text":"","code":"run_WHO_annual_data_app(PATHS)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/run_WHO_annual_data_app.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app","text":"PATHS list containing paths processed cholera data file. Typically generated get_paths() function include: DATA_WHO_ANNUAL: Path directory containing processed cholera data file (e.g., who_afro_annual_1949_2024.csv).","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/run_WHO_annual_data_app.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app","text":"function creates Shiny app allows users explore cholera incidence data across AFRO countries 1970 2024. Users can choose viewing cases, deaths, CFR can select specific countries visualization. app generates bar plots cases deaths, point plots error bars CFR.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/run_WHO_annual_data_app.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app","text":"","code":"if (FALSE) { # Define paths for processed data PATHS <- get_paths() # Run the cholera Shiny app run_WHO_annual_data_app(PATHS) }"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/set_openmeteo_api_key.html","id":null,"dir":"Reference","previous_headings":"","what":"Set OpenMeteo API Key — set_openmeteo_api_key","title":"Set OpenMeteo API Key — set_openmeteo_api_key","text":"function sets OpenMeteo API key stores global option called openmeteo_api_key. API key provided argument, used. , function prompt key interactively.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/set_openmeteo_api_key.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set OpenMeteo API Key — set_openmeteo_api_key","text":"","code":"set_openmeteo_api_key(api_key = NULL)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/set_openmeteo_api_key.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set OpenMeteo API Key — set_openmeteo_api_key","text":"api_key character string representing OpenMeteo API key. NULL, function prompt key interactively.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/set_openmeteo_api_key.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set OpenMeteo API Key — set_openmeteo_api_key","text":"message confirming API key set, instructions retrieving key.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/set_openmeteo_api_key.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Set OpenMeteo API Key — set_openmeteo_api_key","text":"API key stored global option called openmeteo_api_key using options(). key can retrieved time using getOption(\"openmeteo_api_key\").","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/set_openmeteo_api_key.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Set OpenMeteo API Key — set_openmeteo_api_key","text":"","code":"# Set the OpenMeteo API key interactively set_openmeteo_api_key() #> Please enter your OpenMeteo API key: #> Error in set_openmeteo_api_key(): API key cannot be empty. Please provide a valid API key. # Set the OpenMeteo API key programmatically set_openmeteo_api_key(\"your-api-key-here\") #> OpenMeteo API key set successfully. #> Retrieve with getOption('openmeteo_api_key') # Access the API key getOption(\"openmeteo_api_key\") #> [1] \"your-api-key-here\""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/set_root_directory.html","id":null,"dir":"Reference","previous_headings":"","what":"Set Root Directory — set_root_directory","title":"Set Root Directory — set_root_directory","text":"function sets root directory user-specified path , provided, prompts user enter root directory interactively. directory path stored global option called root_directory also returned.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/set_root_directory.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set Root Directory — set_root_directory","text":"","code":"set_root_directory(root = NULL)"},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/set_root_directory.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set Root Directory — set_root_directory","text":"root character string representing path root directory. NULL, function prompt user enter root directory interactively.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/set_root_directory.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set Root Directory — set_root_directory","text":"character string representing root directory. root directory also stored globally option root_directory.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/set_root_directory.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Set Root Directory — set_root_directory","text":"function uses either user-specified path path provided interactively set root directory. path validated ensure exists. validated, path stored global option root_directory, can accessed using getOption(\"root_directory\"). path invalid (.e., exist), function throws error.","code":""},{"path":"https://gilesjohnr.github.io/MOSAIC-docs/reference/set_root_directory.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Set Root Directory — set_root_directory","text":"","code":"if (FALSE) { # Set and display the root directory interactively root_dir <- set_root_directory() cat(\"Root directory:\", root_dir, \"\\n\") # Set the root directory programmatically root_dir <- set_root_directory(\"/path/to/root\") cat(\"Root directory:\", root_dir, \"\\n\") # Access the root directory from the global options getOption(\"root_directory\") }"}] +[{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"John R Giles. Author, maintainer.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Giles J (2024). MOSAIC: Metapopulation Outbreak Simulation Interventions Cholera (MOSAIC). R package version 0.0.1.","code":"@Manual{, title = {MOSAIC: Metapopulation Outbreak Simulation And Interventions for Cholera (MOSAIC)}, author = {John R Giles}, year = {2024}, note = {R package version 0.0.1}, }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/index.html","id":"mosaic-the-metapopulation-outbreak-simulation-with-agent-based-implementation-for-cholera-","dir":"","previous_headings":"","what":"Metapopulation Outbreak Simulation And Interventions for Cholera (MOSAIC)","title":"Metapopulation Outbreak Simulation And Interventions for Cholera (MOSAIC)","text":"  Welcome R package MOSAIC framework. MOSAIC R package provides tools simulating cholera transmission dynamics using metapopulation models, estimating mobility patterns drivers transmission environmental forcing, visualizing disease dynamics outbreak projections. Note repo holds code data models , full documentation see: https://institutefordiseasemodeling.github.io/MOSAIC-docs/.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/index.html","id":"mosaic-project-directory-structure","dir":"","previous_headings":"","what":"MOSAIC Project Directory Structure","title":"Metapopulation Outbreak Simulation And Interventions for Cholera (MOSAIC)","text":"MOSAIC R package designed used within triad Github repos functions documented MOSAIC-pkg. package downloads processes required data saved MOSAIC-data prepares model quantities run MOSAIC saved MOSAIC-pkg/model/input. package also produces figures tables used make documentation located MOSAIC-docs. directory structure MOSAIC project. See ./src/mosiac_setup.sh project setup script.","code":"MOSAIC/ # Local parent directory to hold 3 repositories, root directory in get_paths() ├── MOSAIC-data/ │ ├── raw/ # Raw data files supplied to MOSAIC-pkg │ └── processed/ # Processed data files supplied to MOSAIC-pkg ├── MOSAIC-pkg/ │ ├── [R package] # Contents of MOSAIC R package: https://gilesjohnr.github.io/MOSAIC-pkg/ │ └── model/ │ ├── input/ # Files used as input to MOSAIC framework │ ├── output/ # Location of output from MOSAIC framework │ └── LAUNCH.R # LAUNCH.R file runs data acquisition functions, a priori models, and runs MOSAIC └── MOSAIC-docs/ ├── [Website] # Documentation and model description: https://gilesjohnr.github.io/MOSAIC-docs/ ├── figures/ # Output images and figures from MOSAIC-pkg used in documentation └── tables/ # Output data and parameter values from MOSAIC-pkg used in documentation"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/index.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"Metapopulation Outbreak Simulation And Interventions for Cholera (MOSAIC)","text":"questions information MOSAIC project, please contact: John Giles: john.giles@gatesfoundation.org Jillian Gauld: jillian.gauld@gatesfoundation.org Rajiv Sodhi: rajiv.sodhi@gatesfoundation.org","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/compile_ENSO_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data","title":"Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data","text":"function compiles historical forecast data DMI ENSO (Niño3, Niño3.4, Niño4) single data frame. data filtered include years specified year_start onwards. function also allows disaggregation monthly data daily weekly values using either linear interpolation spline interpolation.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/compile_ENSO_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data","text":"","code":"compile_ENSO_data(year_start = NULL, frequency = \"monthly\", method = \"linear\")"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/compile_ENSO_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data","text":"year_start integer representing start year filtering data. data year onward included compiled data. value must greater equal 1870. frequency character string specifying time resolution output data. Valid options \"daily\", \"weekly\", \"monthly\". method character string specifying interpolation method use. Valid options \"linear\" (linear interpolation using zoo::na.approx()) \"spline\" (spline interpolation using zoo::na.spline()).","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/compile_ENSO_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data","text":"data frame combined historical forecast data DMI, ENSO3, ENSO34, ENSO4. data frame includes following columns: date: date data (daily, weekly, monthly) YYYY-MM-DD format. variable: variable name, can \"DMI\", \"ENSO3\", \"ENSO34\", \"ENSO4\". value: value variable (sea surface temperature anomaly). year: year corresponding date. month: month corresponding date. week: week year (\"weekly\" \"daily\" frequency). doy: day year (\"daily\" frequency).","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/compile_ENSO_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compile ENSO and DMI Data (Historical and Forecast) — compile_ENSO_data","text":"","code":"if (FALSE) { # Compile the ENSO and DMI data from the year 2000 onwards compiled_enso_data <- compile_ENSO_data(2010, \"monthly\") # Display the compiled data head(compiled_enso_data) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_country_to_iso.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","title":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","text":"function converts country names corresponding ISO3 ISO2 country codes. function uses countrycode package, allows multiple spellings variations country names.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_country_to_iso.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","text":"","code":"convert_country_to_iso(x, iso3 = TRUE)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_country_to_iso.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","text":"x character vector country names (e.g., \"United States\", \"UK\", \"Democratic Republic Congo\"). iso3 logical value. TRUE (default), returns ISO3 country codes. FALSE, returns ISO2 country codes.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_country_to_iso.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","text":"character vector ISO3 ISO2 country codes corresponding country names.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_country_to_iso.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","text":"function converts country names ISO3 ISO2 codes using countrycode package. handles various common alternative spellings country names.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_country_to_iso.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert Country Names to ISO3 or ISO2 Country Codes — convert_country_to_iso","text":"","code":"# Convert a single country name to ISO3 convert_country_to_iso(\"United States\") #> [1] \"USA\" # Convert a vector of country names to ISO2 convert_country_to_iso(c(\"United States\", \"UK\", \"Democratic Republic of Congo\"), iso3 = FALSE) #> [1] \"US\" \"GB\" \"CD\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_codes.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","title":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","text":"function converts vector scalar ISO3 country codes ISO2 country codes, vice versa, based input. function uses countrycode package auto-detects input format.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_codes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","text":"","code":"convert_iso_codes(iso_codes)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_codes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","text":"iso_codes vector scalar ISO2 ISO3 country codes (e.g., \"USA\", \"GBR\", \"ZA\", \"GB\").","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_codes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","text":"character vector converted ISO2 ISO3 country codes corresponding provided input.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_codes.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","text":"function detects whether input ISO2 ISO3 format based code length converts accordingly using countrycode package.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_codes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert ISO3 to ISO2 or ISO2 to ISO3 Country Codes — convert_iso_codes","text":"","code":"# Convert a vector of ISO3 codes to ISO2 codes convert_iso_codes(c(\"USA\", \"GBR\", \"DZA\")) #> [1] \"US\" \"GB\" \"DZ\" # Convert a vector of ISO2 codes to ISO3 codes convert_iso_codes(c(\"US\", \"GB\", \"DZ\")) #> [1] \"USA\" \"GBR\" \"DZA\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_to_country.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","title":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","text":"function converts vector scalar ISO2 ISO3 country codes corresponding country names using countrycode package.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_to_country.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","text":"","code":"convert_iso_to_country(iso)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_to_country.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","text":"iso vector scalar ISO2 ISO3 country codes (e.g., \"USA\", \"GB\", \"DZA\").","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_to_country.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","text":"character vector country names corresponding provided ISO2 ISO3 country codes.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_to_country.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","text":"function automatically detects input ISO2 ISO3 format returns corresponding country names. Special handling applied Congo Democratic Republic Congo.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_to_country.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert ISO2 or ISO3 Country Codes to Country Names — convert_iso_to_country","text":"","code":"# Convert a vector of ISO3 and ISO2 codes to country names convert_iso_to_country(c(\"USA\", \"GBR\", \"DZA\", \"COD\")) #> [1] \"United States\" \"United Kingdom\" #> [3] \"Algeria\" \"Democratic Republic of Congo\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_africa_shapefile.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and Save Africa Shapefile — download_africa_shapefile","title":"Download and Save Africa Shapefile — download_africa_shapefile","text":"function downloads shapefile African countries using rnaturalearth package saves specified directory. output directory exist, created.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_africa_shapefile.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and Save Africa Shapefile — download_africa_shapefile","text":"","code":"download_africa_shapefile(PATHS)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_africa_shapefile.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and Save Africa Shapefile — download_africa_shapefile","text":"PATHS list environment containing path structure, PATHS$DATA_PROCESSED specifies directory save processed shapefile.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_africa_shapefile.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and Save Africa Shapefile — download_africa_shapefile","text":"message indicating shapefile saved, including full path saved file.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_africa_shapefile.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and Save Africa Shapefile — download_africa_shapefile","text":"function uses rnaturalearth package download shapefile African continent. shapefile saved AFRICA_ADM0.shp directory specified PATHS$DATA_PROCESSED/shapefiles. function create directory already exist.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_africa_shapefile.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and Save Africa Shapefile — download_africa_shapefile","text":"","code":"if (FALSE) { # Example PATHS object PATHS <- list(DATA_PROCESSED = \"path/to/processed/data\") # Download and save the Africa shapefile download_africa_shapefile(PATHS) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_all_country_shapefiles.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","title":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","text":"function downloads shapefiles African country saves specified directory. function iterates ISO3 country codes Africa (MOSAIC framework) saves country's shapefile individually.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_all_country_shapefiles.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","text":"","code":"download_all_country_shapefiles(PATHS)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_all_country_shapefiles.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","text":"PATHS list containing paths processed data saved. PATHS typically output get_paths() function include: DATA_PROCESSED: Path directory processed shapefiles saved.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_all_country_shapefiles.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","text":"function return value. downloads shapefiles African country saves individual shapefiles processed data directory.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_all_country_shapefiles.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","text":"function performs following steps: Creates output directory shapefiles exist. Loops list ISO3 country codes African countries. Downloads country's shapefile using MOSAIC::get_country_shp(). Saves shapefile processed data directory ISO3_ADM0.shp.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_all_country_shapefiles.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and Save Shapefiles for All African Countries — download_all_country_shapefiles","text":"","code":"if (FALSE) { # Define paths for processed data using get_paths() PATHS <- get_paths() # Download and save shapefiles for all African countries download_all_country_shapefiles(PATHS) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_climate_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and Save Climate Data for Multiple Countries — download_climate_data","title":"Download and Save Climate Data for Multiple Countries — download_climate_data","text":"function downloads daily climate data list specified countries, saving data CSV files. data includes historical future climate variables grid points within country.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_climate_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and Save Climate Data for Multiple Countries — download_climate_data","text":"","code":"download_climate_data( PATHS, iso_codes, api_key, n_points = 3, date_start = \"1970-01-01\", date_stop = \"2030-12-31\" )"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_climate_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and Save Climate Data for Multiple Countries — download_climate_data","text":"PATHS list containing paths raw processed data stored. PATHS typically output get_paths() function include: DATA_SHAPEFILES: Path directory containing country shapefiles. DATA_CLIMATE: Path directory processed climate data saved. iso_codes character vector ISO3 country codes climate data downloaded. api_key character string representing API key required access climate data API. n_points integer specifying number grid points generate within country climate data downloaded. date_start character string representing start date climate data (\"YYYY-MM-DD\" format). date_stop character string representing end date climate data (\"YYYY-MM-DD\" format).","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_climate_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and Save Climate Data for Multiple Countries — download_climate_data","text":"function return value. downloads climate data country saves results CSV files specified directory.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_climate_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and Save Climate Data for Multiple Countries — download_climate_data","text":"function uses country shapefiles generate grid points within country, climate data downloaded. function retrieves climate data specified date range (date_start date_stop). data saved country CSV file named climate_data___.csv. climate data variables include temperature, wind speed, cloud cover, precipitation, . function retrieves data multiple climate models, including MRI EC Earth models.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_climate_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and Save Climate Data for Multiple Countries — download_climate_data","text":"","code":"if (FALSE) { # Define paths for raw and processed data using get_paths() PATHS <- get_paths() # ISO3 country codes for African countries iso_codes <- c(\"ZAF\", \"KEN\", \"NGA\") # API key for climate data API api_key <- \"your-api-key-here\" # Download climate data and save it for the specified countries download_climate_data(PATHS, iso_codes, api_key, n_points = 5, date_start = \"1970-01-01\", date_stop = \"2030-12-31\") }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_WASH_coverage.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","title":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","text":"function processes Water, Sanitation, Hygiene (WASH) coverage data African countries, optimizes weights WASH variables, calculates weighted means, examines correlation cholera incidence. function generates plots tables showing relationships saves results specified paths.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_WASH_coverage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","text":"","code":"est_WASH_coverage(PATHS)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_WASH_coverage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","text":"PATHS list containing paths WASH data, figures, model inputs saved. Typically generated get_paths() function include: DATA_WASH: Path WASH data CSV file. DOCS_FIGURES: Path save output figures. MODEL_INPUT: Path save model input data. DOCS_TABLES: Path save tables used documentation.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_WASH_coverage.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","text":"function return value, generates saves plots CSV files showing WASH coverage estimates, optimized weights WASH variables, correlation cholera incidence.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_WASH_coverage.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","text":"WASH coverage data first normalized (0-1 scale). Risk-related WASH variables (unimproved water sources, surface water, unimproved sanitation, open defecation) converted protective factors taking complement (1 - value). , function: Optimizes weights WASH variable maximize correlation cholera incidence using L-BFGS-B method. Calculates weighted mean WASH variables country. Generates multiple plots showing relationships WASH variables cholera incidence. Saves tables optimized weights weighted mean WASH indices. Data Source: Sikder et al. (2023). Water, Sanitation, Hygiene Coverage Cholera Incidence Sub-Saharan Africa. doi:10.1021/acs.est.3c01317 .","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_WASH_coverage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate and Visualize WASH Coverage and Correlation with Cholera Incidence — est_WASH_coverage","text":"","code":"if (FALSE) { # Define paths for saving WASH data, figures, and tables PATHS <- get_paths() # Estimate WASH coverage and correlation with cholera incidence est_WASH_coverage(PATHS) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_mobility.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","title":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","text":"function processes flight data, population data, distance data fit mobility model using mobility package. model estimates probability travel origin country (departure) probability travel origin destination (diffusion). saves model matrices results CSV files generates plots visualization.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_mobility.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","text":"","code":"est_mobility(PATHS)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_mobility.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","text":"PATHS list containing paths directories raw processed data. Typically, PATHS output get_paths() include: DATA_OAG: Path directory containing flight data. DATA_SHAPEFILES: Path directory containing country shapefiles. DATA_DEMOGRAPHICS: Path directory containing demographic data. MODEL_INPUT: Path directory model matrices saved. DOCS_FIGURES: Path directory figures saved.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_mobility.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","text":"function return value. processes data, fits mobility model, saves results CSV files, creates several visualizations saved PNG files.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_mobility.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","text":"function performs following steps: Loads flight data constructs mobility matrix (M). Constructs distance matrix (D) country centroids based shapefiles. Retrieves population sizes (N) demographic data. Ensures dimensions M, D, N match. Fits probability travel (departure) diffusion (origin-destination) using mobility package. Saves results, including mobility matrix (M), distance matrix (D), population vector (N) CSV files. Saves several plots related mobility model, including heatmap flight data, network plot flight data, plots travel probabilities diffusion probabilities.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_mobility.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate and Visualize Mobility Model for MOSAIC Data — est_mobility","text":"","code":"if (FALSE) { # Assuming PATHS is generated from the get_paths function PATHS <- get_paths() # Fit the mobility model and generate outputs est_mobility(PATHS) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_symptomatic_prop.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop","title":"Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop","text":"function reads symptomatic proportion data, fits Beta distribution simulate proportion infections symptomatic, generates visualizations comparing estimates previous studies.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_symptomatic_prop.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop","text":"","code":"est_symptomatic_prop(PATHS)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_symptomatic_prop.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop","text":"PATHS list containing paths symptomatic proportion data figures saved. Typically generated get_paths() function include: DATA_PROCESSED: Path symptomatic proportion data. DOCS_FIGURES: Path save generated plots.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_symptomatic_prop.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop","text":"function return value generates saves plots PNG file.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_symptomatic_prop.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate and Visualize Symptomatic Proportion Data — est_symptomatic_prop","text":"","code":"if (FALSE) { # Estimate and visualize symptomatic proportion data PATHS <- get_paths() est_symptomatic_prop(PATHS) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_dist.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","title":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","text":"function generates grid points within country's shapefile, points spaced specified distance kilometers.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_dist.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","text":"","code":"generate_country_grid_dist(country_shp, distance_km)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_dist.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","text":"country_shp sf object representing country's shapefile. distance_km numeric value specifying distance (kilometers) grid points.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_dist.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","text":"sf object containing generated grid points within country boundary.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_dist.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","text":"function creates regular grid points within polygon defined country's shapefile, spaced according specified distance kilometers.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_dist.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a Grid of Points Within a Country's Shapefile Based on Distance — generate_country_grid_dist","text":"","code":"if (FALSE) { # Example usage with distance in kilometers grid_points_sf <- generate_country_grid_dist(country_shapefile, distance_km = 50) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_n.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","title":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","text":"function generates grid points within country's shapefile, grid contains specified number evenly spaced points.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_n.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","text":"","code":"generate_country_grid_n(country_shp, n_points)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_n.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","text":"country_shp sf object representing country's shapefile. n_points numeric value specifying total number evenly spaced points generate within country boundary.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_n.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","text":"sf object containing generated grid points within country boundary.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_n.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","text":"function creates regular grid points within polygon defined country's shapefile, containing specified number points.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_n.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a Grid of Points Within a Country's Shapefile Based on Number of Points — generate_country_grid_n","text":"","code":"if (FALSE) { # Example usage with a specified number of points grid_points_sf <- generate_country_grid_n(country_shapefile, n_points = 100) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_DMI_forecast.html","id":null,"dir":"Reference","previous_headings":"","what":"Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast","title":"Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast","text":"function retrieves manually extracted Dipole Mode Index (DMI) forecast data Bureau Meteorology's IOD forecast page.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_DMI_forecast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast","text":"","code":"get_DMI_forecast()"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_DMI_forecast.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast","text":"data frame columns year, month (numeric), month_name, variable (DMI), value. DMI measure difference sea surface temperature anomalies western eastern Indian Ocean used describe Indian Ocean Dipole (IOD).","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_DMI_forecast.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast","text":"IOD forecast manually extracted Bureau Meteorology's IOD forecast page: http://www.bom.gov.au/climate/ocean/outlooks/#region=IOD. data includes DMI values series months years, representing forecasts sea surface temperature anomalies. Negative DMI values indicate cooler waters west, positive DMI values indicate warmer waters west Indian Ocean.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_DMI_forecast.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get DMI (Dipole Mode Index) Forecast Data — get_DMI_forecast","text":"","code":"if (FALSE) { # Get the DMI forecast data dmi_forecast <- get_DMI_forecast() # Display the DMI forecast data print(dmi_forecast) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_DMI_historical.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and Process Historical DMI Data — get_DMI_historical","title":"Download and Process Historical DMI Data — get_DMI_historical","text":"function downloads historical Dipole Mode Index (DMI) data NOAA processes data frame columns year, month (1-12), month_name, variable (DMI), value.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_DMI_historical.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and Process Historical DMI Data — get_DMI_historical","text":"","code":"get_DMI_historical()"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_DMI_historical.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and Process Historical DMI Data — get_DMI_historical","text":"data frame columns year, month, month_name, variable (DMI), value.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_DMI_historical.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and Process Historical DMI Data — get_DMI_historical","text":"DMI data downloaded NOAA's historical DMI data page: https://psl.noaa.gov/gcos_wgsp/Timeseries/Data/dmi..long.data. data includes DMI values representing difference sea surface temperature anomalies western eastern Indian Ocean.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_DMI_historical.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and Process Historical DMI Data — get_DMI_historical","text":"","code":"if (FALSE) { # Get the historical DMI data dmi_historical <- get_DMI_historical() # Display the historical DMI data print(dmi_historical) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ENSO_forecast.html","id":null,"dir":"Reference","previous_headings":"","what":"Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast","title":"Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast","text":"function retrieves manually extracted ENSO forecast data, including Niño3, Niño3.4, Niño4 sea surface temperature (SST) anomalies, Bureau Meteorology.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ENSO_forecast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast","text":"","code":"get_ENSO_forecast()"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ENSO_forecast.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast","text":"data frame columns year, month (numeric), month_name, variable (ENSO3, ENSO34, ENSO4), value.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ENSO_forecast.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast","text":"ENSO forecast manually extracted Bureau Meteorology's ocean outlook page. data includes SST anomalies Niño3, Niño3.4, Niño4 regions. Negative values indicate cooler sea surface temperatures, positive values indicate warmer temperatures.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ENSO_forecast.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get ENSO (Niño3, Niño3.4, and Niño4) Forecast Data — get_ENSO_forecast","text":"","code":"if (FALSE) { # Get the ENSO forecast data enso_forecast <- get_ENSO_forecast() # Display the ENSO forecast data print(enso_forecast) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ENSO_historical.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical","title":"Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical","text":"function downloads historical ENSO data Niño3, Niño3.4, Niño4 NOAA processes single data frame columns year (integer), month, month_name, variable (ENSO3, ENSO34, ENSO4), value.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ENSO_historical.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical","text":"","code":"get_ENSO_historical()"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ENSO_historical.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical","text":"data frame columns year, month, month_name, variable, value.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ENSO_historical.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical","text":"historical ENSO data downloaded NOAA's historical ENSO data pages. data includes sea surface temperature anomalies Niño3, Niño3.4, Niño4 regions.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ENSO_historical.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and Process Historical ENSO Data (Niño3, Niño3.4, Niño4) — get_ENSO_historical","text":"","code":"if (FALSE) { # Get the historical ENSO data enso_historical <- get_ENSO_historical() # Display the historical ENSO data print(enso_historical) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_WASH_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download, Process, and Save WASH Coverage Data — get_WASH_data","title":"Download, Process, and Save WASH Coverage Data — get_WASH_data","text":"function processes WASH (Water, Sanitation, Hygiene) coverage data African countries Sikder et al. (2023). data includes indicators water sanitation access, including piped water, improved sanitation, unimproved water sources, open defecation. processed data saved CSV file specified path.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_WASH_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download, Process, and Save WASH Coverage Data — get_WASH_data","text":"","code":"get_WASH_data(PATHS)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_WASH_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download, Process, and Save WASH Coverage Data — get_WASH_data","text":"PATHS list containing paths WASH data saved. Typically generated get_paths() function include: DATA_WASH: Path directory processed WASH data saved.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_WASH_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download, Process, and Save WASH Coverage Data — get_WASH_data","text":"function return value processes WASH coverage data saves specified directory CSV file.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_WASH_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download, Process, and Save WASH Coverage Data — get_WASH_data","text":"WASH coverage data based percentages population access piped water, improved water sources, septic sewer sanitation, improved sanitation. data also includes proportions population using unimproved water sources, surface water, unimproved sanitation, practicing open defecation. risk-related variables (unimproved water, surface water, unimproved sanitation, open defecation) converted complement (1 - value) reflect protective factors. data scaled 0 1. Data Source: Sikder et al. (2023). Water, Sanitation, Hygiene Coverage Cholera Incidence Sub-Saharan Africa. doi:10.1021/acs.est.3c01317 .","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_WASH_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download, Process, and Save WASH Coverage Data — get_WASH_data","text":"","code":"if (FALSE) { # Define paths for saving WASH data PATHS <- get_paths() # Download, process, and save WASH coverage data get_WASH_data(PATHS) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_centroid.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the Centroid of a Country from its Shapefile — get_centroid","title":"Calculate the Centroid of a Country from its Shapefile — get_centroid","text":"function reads country shapefile, calculates centroid, returns centroid coordinates (longitude latitude) along ISO3 country code.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_centroid.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the Centroid of a Country from its Shapefile — get_centroid","text":"","code":"get_centroid(shapefile)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_centroid.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the Centroid of a Country from its Shapefile — get_centroid","text":"shapefile character string representing file path country shapefile (.shp format).","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_centroid.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the Centroid of a Country from its Shapefile — get_centroid","text":"data frame following columns: iso3: ISO3 country code extracted shapefile name. lon: longitude country's centroid. lat: latitude country's centroid.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_centroid.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate the Centroid of a Country from its Shapefile — get_centroid","text":"function reads shapefile using sf::st_read(), calculates centroid country using sf::st_centroid(), extracts coordinates centroid sf::st_coordinates(). ISO3 code extracted filename shapefile, assuming first three characters shapefile name represent ISO3 country code.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_centroid.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the Centroid of a Country from its Shapefile — get_centroid","text":"","code":"if (FALSE) { # Example usage: # Assuming you have a shapefile \"ZAF_ADM0.shp\" for South Africa shapefile_path <- \"path/to/shapefile/ZAF_ADM0.shp\" centroid_data <- get_centroid(shapefile_path) print(centroid_data) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_forecast.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Climate Forecast Data (Daily) — get_climate_forecast","title":"Get Climate Forecast Data (Daily) — get_climate_forecast","text":"function retrieves daily climate forecast data specified location one climate variables range forecast days using Open-Meteo API.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_forecast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Climate Forecast Data (Daily) — get_climate_forecast","text":"","code":"get_climate_forecast(lat, lon, n_days, climate_variables, api_key = NULL)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_forecast.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Climate Forecast Data (Daily) — get_climate_forecast","text":"lat numeric value representing latitude location. lon numeric value representing longitude location. n_days integer representing number forecast days retrieve (maximum value 15). climate_variables character vector climate variables retrieve (e.g., c(\"temperature_2m_max\", \"precipitation_sum\")). api_key character string representing API key Open-Meteo API.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_forecast.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Climate Forecast Data (Daily) — get_climate_forecast","text":"data frame columns: date date forecast (class Date). climate_variable name climate variable. climate_value value climate variable date.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_forecast.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Climate Forecast Data (Daily) — get_climate_forecast","text":"function queries Open-Meteo API daily weather forecast data specified latitude, longitude, range forecast days (15 days). API request successful, function returns data frame containing date, climate variable, value. request fails, function returns NULL issues warning HTTP status code.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_forecast.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Climate Forecast Data (Daily) — get_climate_forecast","text":"","code":"if (FALSE) { # Example usage to get forecast data for multiple climate variables lat <- 52.52 lon <- 13.41 n_days <- 15 climate_variables <- c(\"temperature_2m_max\", \"precipitation_sum\") api_key <- \"your_api_key_here\" forecast_data <- get_climate_forecast(lat, lon, n_days, climate_variables, api_key) print(forecast_data) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_future.html","id":null,"dir":"Reference","previous_headings":"","what":"Download Future Climate Data for Multiple Locations — get_climate_future","title":"Download Future Climate Data for Multiple Locations — get_climate_future","text":"function retrieves daily future climate data multiple specified locations climate variables specified date range using specified climate models.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_future.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download Future Climate Data for Multiple Locations — get_climate_future","text":"","code":"get_climate_future( lat, lon, start_date, end_date, climate_variables, climate_models, api_key = NULL )"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_future.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download Future Climate Data for Multiple Locations — get_climate_future","text":"lat numeric vector representing latitudes locations. lon numeric vector representing longitudes locations. start_date character string representing start date data \"YYYY-MM-DD\" format. end_date character string representing end date data \"YYYY-MM-DD\" format. climate_variables character vector climate variables retrieve. Valid options include: temperature_2m_mean: Mean 2m air temperature. temperature_2m_max: Maximum 2m air temperature. temperature_2m_min: Minimum 2m air temperature. wind_speed_10m_mean: Mean 10m wind speed. wind_speed_10m_max: Maximum 10m wind speed. cloud_cover_mean: Mean cloud cover. shortwave_radiation_sum: Sum shortwave radiation. relative_humidity_2m_mean: Mean 2m relative humidity. relative_humidity_2m_max: Maximum 2m relative humidity. relative_humidity_2m_min: Minimum 2m relative humidity. dew_point_2m_mean: Mean 2m dew point temperature. dew_point_2m_min: Minimum 2m dew point temperature. dew_point_2m_max: Maximum 2m dew point temperature. precipitation_sum: Total precipitation. rain_sum: Total rainfall. snowfall_sum: Total snowfall. pressure_msl_mean: Mean sea level pressure. soil_moisture_0_to_10cm_mean: Mean soil moisture (0-10 cm depth). et0_fao_evapotranspiration_sum: Sum evapotranspiration (FAO standard). climate_models character vector climate models use. Available models include: CMCC_CM2_VHR4 FGOALS_f3_H HiRAM_SIT_HR MRI_AGCM3_2_S EC_Earth3P_HR MPI_ESM1_2_XR NICAM16_8S api_key character string representing API key climate data API. provided, function assumes API key required.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_future.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download Future Climate Data for Multiple Locations — get_climate_future","text":"data frame columns: date: date climate data. latitude: latitude location. longitude: longitude location. climate_model: climate model used data. variable_name: climate variable retrieved (e.g., temperature_2m_mean, precipitation_sum). value: value climate variable date.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_future.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download Future Climate Data for Multiple Locations — get_climate_future","text":"function retrieves daily future climate data multiple specified locations using Open-Meteo Climate API. downloads specified climate variables latitude longitude provided, using selected climate models. data retrieved date range specified start_date end_date. progress bar displayed indicate download progress.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_future.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download Future Climate Data for Multiple Locations — get_climate_future","text":"","code":"if (FALSE) { # Define latitudes and longitudes for the locations lat <- c(40.7128, 34.0522) lon <- c(-74.0060, -118.2437) # Define the climate variables and models climate_vars <- c(\"temperature_2m_mean\", \"precipitation_sum\") climate_models <- c(\"MRI_AGCM3_2_S\", \"EC_Earth3P_HR\") # Set the date range and API key start_date <- \"2023-01-01\" end_date <- \"2030-12-31\" api_key <- \"your_api_key_here\" # Download the climate data climate_data <- get_climate_future(lat, lon, start_date, end_date, climate_vars, climate_models, api_key) # Display the climate data head(climate_data) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_historical.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Historical Climate Data — get_climate_historical","title":"Get Historical Climate Data — get_climate_historical","text":"function retrieves historical weather data specified location one climate variables date range. uses Open-Meteo API.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_historical.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Historical Climate Data — get_climate_historical","text":"","code":"get_climate_historical( lat, lon, start_date, end_date, climate_variables, api_key = NULL )"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_historical.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Historical Climate Data — get_climate_historical","text":"lat numeric value representing latitude location. lon numeric value representing longitude location. start_date character string representing start date \"YYYY-MM-DD\" format. end_date character string representing end date \"YYYY-MM-DD\" format. climate_variables character vector climate variables retrieve (e.g., c(\"precipitation_sum\", \"temperature_2m_max\")). api_key character string representing API key Open-Meteo API. provided, default key used.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_historical.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Historical Climate Data — get_climate_historical","text":"data frame columns: date date observation (class Date). climate_variable name climate variable. climate_value value climate variable date.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_historical.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Historical Climate Data — get_climate_historical","text":"function queries Open-Meteo API historical weather data given latitude, longitude, climate variables specified date range. API request successful, function returns data frame containing date, climate variable, value. request fails, function returns NULL issues warning HTTP status code.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_historical.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Historical Climate Data — get_climate_historical","text":"","code":"if (FALSE) { # Example usage to get historical data for multiple climate variables lat <- 40.7128 lon <- -74.0060 start_date <- \"2020-01-01\" end_date <- \"2020-12-31\" climate_variables <- c(\"temperature_2m_max\", \"precipitation_sum\") api_key <- \"your_api_key_here\" # Replace with your actual API key climate_data <- get_climate_historical(lat, lon, start_date, end_date, climate_variables, api_key) print(climate_data) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_country_shp.html","id":null,"dir":"Reference","previous_headings":"","what":"Get a country shapefile from GeoBoundaries API — get_country_shp","title":"Get a country shapefile from GeoBoundaries API — get_country_shp","text":"function retrieves shapefile given iso3 code GeoBoundaries data API.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_country_shp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get a country shapefile from GeoBoundaries API — get_country_shp","text":"","code":"get_country_shp(iso3, path_output = NULL)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_country_shp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get a country shapefile from GeoBoundaries API — get_country_shp","text":"iso3 three-letter capitalized character string. Must follow ISO-3166 Alpha-3 country code standard (https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3). path_output file path save country shapefile","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_country_shp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get a country shapefile from GeoBoundaries API — get_country_shp","text":"sf class shapefile","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_country_shp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get a country shapefile from GeoBoundaries API — get_country_shp","text":"","code":"if (FALSE) { tmp <- get_country_shp(iso3 = 'MCO') plot(tmp) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_elevation.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","title":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","text":"function retrieves elevation data specified number points within boundary country's shapefile iso_codes_mosaic list using Open-Meteo API. returns mean elevation country.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_elevation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","text":"","code":"get_elevation(PATHS, n_points, api_key = NULL)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_elevation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","text":"PATHS list containing paths elevation data saved. Typically generated get_paths() function include: DATA_SHAPEFILES: Path directory containing country shapefiles. DATA_ELEVATION: Path directory elevation data saved. n_points integer specifying number points generate within country's boundary. api_key character string representing API key Open-Meteo API.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_elevation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","text":"data frame mean elevation country iso_codes_mosaic.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_elevation.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","text":"function loads shapefiles countries iso_codes_mosaic specified directory, generates n_points random points within country's boundary, queries Open-Meteo API elevation data point. returns mean elevation country saves data CSV file.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_elevation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Mean Elevation Data for Multiple Countries Using Shapefiles — get_elevation","text":"","code":"if (FALSE) { # Example usage to get mean elevation data for all countries in iso_codes_mosaic n_points <- 10 api_key <- \"your_api_key_here\" PATHS <- get_paths() mean_elevations <- get_elevation(n_points, api_key, PATHS) print(mean_elevations) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ggplot_legend.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract the Legend from a ggplot Object — get_ggplot_legend","title":"Extract the Legend from a ggplot Object — get_ggplot_legend","text":"function extracts legend ggplot object returns grob (graphical object). extracted legend can used independently, instance, combine legend plots.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ggplot_legend.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract the Legend from a ggplot Object — get_ggplot_legend","text":"","code":"get_ggplot_legend(plot)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ggplot_legend.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract the Legend from a ggplot Object — get_ggplot_legend","text":"plot ggplot object legend extracted.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ggplot_legend.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract the Legend from a ggplot Object — get_ggplot_legend","text":"grob representing legend ggplot object.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ggplot_legend.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract the Legend from a ggplot Object — get_ggplot_legend","text":"function converts ggplot object grob using ggplotGrob() extracts legend, stored grob name \"guide-box\". function can used separate legend plot combine plots needed.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ggplot_legend.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract the Legend from a ggplot Object — get_ggplot_legend","text":"","code":"# Create a simple ggplot object p <- ggplot2::ggplot(mtcars, ggplot2::aes(x = wt, y = mpg, color = factor(gear))) + ggplot2::geom_point() + ggplot2::scale_color_discrete(name = \"Gear\") # Extract the legend from the plot legend <- get_ggplot_legend(p) # Display the extracted legend grid::grid.draw(legend)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_paths.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Directory Paths for the MOSAIC Project — get_paths","title":"Generate Directory Paths for the MOSAIC Project — get_paths","text":"get_paths() function generates structured list file paths different data document directories MOSAIC project, based provided root directory.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_paths.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Directory Paths for the MOSAIC Project — get_paths","text":"","code":"get_paths(root = NULL)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_paths.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Directory Paths for the MOSAIC Project — get_paths","text":"root string specifying root directory MOSAIC project. paths generated relative root.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_paths.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate Directory Paths for the MOSAIC Project — get_paths","text":"named list containing following paths: ROOT root directory provided user. DATA_RAW Path raw data directory (\"MOSAIC-data/data/raw\"). DATA_PROCESSED Path processed data directory (\"MOSAIC-data/data/processed\"). MODEL_INPUT NULL, reserved path model input (applicable). MODEL_OUTPUT NULL, reserved path model output (applicable). DOCS_FIGURES Path figures directory (\"MOSAIC-docs/figures\"). DOCS_TABLES Path tables directory (\"MOSAIC-docs/tables\"). DOCS_PARAMS Path parameters directory (\"MOSAIC-docs/parameters\").","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_paths.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate Directory Paths for the MOSAIC Project — get_paths","text":"function helps organize directory structure data document storage MOSAIC project generating paths raw data, processed data, figures, tables, parameters. paths returned named list can used streamline access various project-related directories.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_paths.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate Directory Paths for the MOSAIC Project — get_paths","text":"","code":"if (FALSE) { root_dir <- \"/{full file path}/MOSAIC\" PATHS <- get_paths(root_dir) print(PATHS$DATA_RAW) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_symptomatic_prop_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Symptomatic Proportion Data — get_symptomatic_prop_data","title":"Get Symptomatic Proportion Data — get_symptomatic_prop_data","text":"function creates data frame studies reporting proportion cholera infections symptomatic saves CSV file.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_symptomatic_prop_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Symptomatic Proportion Data — get_symptomatic_prop_data","text":"","code":"get_symptomatic_prop_data(PATHS)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_symptomatic_prop_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Symptomatic Proportion Data — get_symptomatic_prop_data","text":"PATHS list containing paths symptomatic proportion data saved. Typically generated get_paths() function include: DATA_PROCESSED: Path save symptomatic proportion data.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_symptomatic_prop_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Symptomatic Proportion Data — get_symptomatic_prop_data","text":"function return value saves data frame CSV file.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_symptomatic_prop_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Symptomatic Proportion Data — get_symptomatic_prop_data","text":"","code":"if (FALSE) { # Generate and save symptomatic proportion data PATHS <- get_paths() get_symptomatic_prop_data(PATHS) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for All African Countries — iso_codes_africa","title":"ISO3 Country Codes for All African Countries — iso_codes_africa","text":"character vector containing ISO3 country codes 54 countries Africa.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for All African Countries — iso_codes_africa","text":"","code":"iso_codes_africa"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for All African Countries — iso_codes_africa","text":"character vector ISO3 country codes.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for All African Countries — iso_codes_africa","text":"","code":"# Access ISO3 codes for all African countries iso_codes_africa #> [1] \"DZA\" \"AGO\" \"BEN\" \"BWA\" \"BFA\" \"BDI\" \"CPV\" \"CMR\" \"CAF\" \"TCD\" \"COM\" \"COG\" #> [13] \"COD\" \"CIV\" \"DJI\" \"EGY\" \"GNQ\" \"ERI\" \"SWZ\" \"ETH\" \"GAB\" \"GMB\" \"GHA\" \"GIN\" #> [25] \"GNB\" \"KEN\" \"LSO\" \"LBR\" \"LBY\" \"MDG\" \"MWI\" \"MLI\" \"MRT\" \"MUS\" \"MAR\" \"MOZ\" #> [37] \"NAM\" \"NER\" \"NGA\" \"RWA\" \"STP\" \"SEN\" \"SYC\" \"SLE\" \"SOM\" \"ZAF\" \"SSD\" \"SDN\" #> [49] \"TGO\" \"TUN\" \"UGA\" \"TZA\" \"ZMB\" \"ZWE\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_central.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for Central African Countries — iso_codes_africa_central","title":"ISO3 Country Codes for Central African Countries — iso_codes_africa_central","text":"character vector containing ISO3 country codes 8 countries Central Africa.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_central.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for Central African Countries — iso_codes_africa_central","text":"","code":"iso_codes_africa_central"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_central.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for Central African Countries — iso_codes_africa_central","text":"character vector ISO3 country codes.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_central.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for Central African Countries — iso_codes_africa_central","text":"","code":"# Access ISO3 codes for Central African countries iso_codes_africa_central #> [1] \"AGO\" \"CAF\" \"TCD\" \"COG\" \"COD\" \"GNQ\" \"GAB\" \"STP\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_east.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for East African Countries — iso_codes_africa_east","title":"ISO3 Country Codes for East African Countries — iso_codes_africa_east","text":"character vector containing ISO3 country codes 14 countries East Africa.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_east.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for East African Countries — iso_codes_africa_east","text":"","code":"iso_codes_africa_east"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_east.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for East African Countries — iso_codes_africa_east","text":"character vector ISO3 country codes.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_east.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for East African Countries — iso_codes_africa_east","text":"","code":"# Access ISO3 codes for East African countries iso_codes_africa_east #> [1] \"BDI\" \"COM\" \"DJI\" \"ERI\" \"ETH\" \"KEN\" \"MDG\" \"MWI\" \"RWA\" \"SYC\" \"SOM\" \"SSD\" #> [13] \"TZA\" \"UGA\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_north.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for North African Countries — iso_codes_africa_north","title":"ISO3 Country Codes for North African Countries — iso_codes_africa_north","text":"character vector containing ISO3 country codes 6 countries North Africa.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_north.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for North African Countries — iso_codes_africa_north","text":"","code":"iso_codes_africa_north"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_north.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for North African Countries — iso_codes_africa_north","text":"character vector ISO3 country codes.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_north.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for North African Countries — iso_codes_africa_north","text":"","code":"# Access ISO3 codes for North African countries iso_codes_africa_north #> [1] \"DZA\" \"EGY\" \"LBY\" \"MAR\" \"SDN\" \"TUN\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_south.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for Southern African Countries — iso_codes_africa_south","title":"ISO3 Country Codes for Southern African Countries — iso_codes_africa_south","text":"character vector containing ISO3 country codes 7 countries Southern Africa.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_south.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for Southern African Countries — iso_codes_africa_south","text":"","code":"iso_codes_africa_south"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_south.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for Southern African Countries — iso_codes_africa_south","text":"character vector ISO3 country codes.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_south.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for Southern African Countries — iso_codes_africa_south","text":"","code":"# Access ISO3 codes for Southern African countries iso_codes_africa_south #> [1] \"BWA\" \"LSO\" \"NAM\" \"ZAF\" \"SWZ\" \"ZMB\" \"ZWE\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_west.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for West African Countries — iso_codes_africa_west","title":"ISO3 Country Codes for West African Countries — iso_codes_africa_west","text":"character vector containing ISO3 country codes 16 countries West Africa.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_west.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for West African Countries — iso_codes_africa_west","text":"","code":"iso_codes_africa_west"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_west.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for West African Countries — iso_codes_africa_west","text":"character vector ISO3 country codes.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_west.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for West African Countries — iso_codes_africa_west","text":"","code":"# Access ISO3 codes for West African countries iso_codes_africa_west #> [1] \"BEN\" \"BFA\" \"CPV\" \"CIV\" \"GMB\" \"GHA\" \"GIN\" \"GNB\" \"LBR\" \"MLI\" \"MRT\" \"NER\" #> [13] \"NGA\" \"SEN\" \"SLE\" \"TGO\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_mosaic.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for MOSAIC Modeling Framework — iso_codes_mosaic","title":"ISO3 Country Codes for MOSAIC Modeling Framework — iso_codes_mosaic","text":"character vector containing ISO3 country codes 40 countries modeled MOSAIC framework.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_mosaic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for MOSAIC Modeling Framework — iso_codes_mosaic","text":"","code":"iso_codes_mosaic"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_mosaic.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for MOSAIC Modeling Framework — iso_codes_mosaic","text":"character vector ISO3 country codes.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_mosaic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for MOSAIC Modeling Framework — iso_codes_mosaic","text":"","code":"# Access ISO3 codes for countries modeled in the MOSAIC framework iso_codes_mosaic #> [1] \"AGO\" \"BEN\" \"BWA\" \"BFA\" \"BDI\" \"CMR\" \"CAF\" \"TCD\" \"COG\" \"COD\" \"CIV\" \"GNQ\" #> [13] \"ERI\" \"SWZ\" \"ETH\" \"GAB\" \"GMB\" \"GHA\" \"GIN\" \"GNB\" \"KEN\" \"LSO\" \"LBR\" \"MWI\" #> [25] \"MLI\" \"MRT\" \"MOZ\" \"NAM\" \"NER\" \"NGA\" \"RWA\" \"SEN\" \"SLE\" \"SOM\" \"ZAF\" \"SSD\" #> [37] \"TGO\" \"UGA\" \"TZA\" \"ZMB\" \"ZWE\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_ssa.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for Sub-Saharan African Countries — iso_codes_ssa","title":"ISO3 Country Codes for Sub-Saharan African Countries — iso_codes_ssa","text":"character vector containing ISO3 country codes 48 countries Sub-Saharan Africa.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_ssa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for Sub-Saharan African Countries — iso_codes_ssa","text":"","code":"iso_codes_ssa"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_ssa.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for Sub-Saharan African Countries — iso_codes_ssa","text":"character vector ISO3 country codes.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_ssa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for Sub-Saharan African Countries — iso_codes_ssa","text":"","code":"# Access ISO3 codes for Sub-Saharan African countries iso_codes_ssa #> [1] \"AGO\" \"BEN\" \"BWA\" \"BFA\" \"BDI\" \"CMR\" \"CPV\" \"CAF\" \"TCD\" \"COM\" \"COG\" \"COD\" #> [13] \"CIV\" \"DJI\" \"GNQ\" \"ERI\" \"SWZ\" \"ETH\" \"GAB\" \"GMB\" \"GHA\" \"GIN\" \"GNB\" \"KEN\" #> [25] \"LSO\" \"LBR\" \"MDG\" \"MWI\" \"MLI\" \"MRT\" \"MUS\" \"MOZ\" \"NAM\" \"NER\" \"NGA\" \"RWA\" #> [37] \"STP\" \"SEN\" \"SYC\" \"SLE\" \"SOM\" \"ZAF\" \"SSD\" \"SDN\" \"TGO\" \"UGA\" \"TZA\" \"ZMB\" #> [49] \"ZWE\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_who_afro.html","id":null,"dir":"Reference","previous_headings":"","what":"ISO3 Country Codes for WHO AFRO Region Countries — iso_codes_who_afro","title":"ISO3 Country Codes for WHO AFRO Region Countries — iso_codes_who_afro","text":"character vector containing ISO3 country codes 47 countries African Region (AFRO).","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_who_afro.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ISO3 Country Codes for WHO AFRO Region Countries — iso_codes_who_afro","text":"","code":"iso_codes_who_afro"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_who_afro.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"ISO3 Country Codes for WHO AFRO Region Countries — iso_codes_who_afro","text":"character vector ISO3 country codes.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_who_afro.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ISO3 Country Codes for WHO AFRO Region Countries — iso_codes_who_afro","text":"","code":"# Access ISO3 codes for WHO AFRO Region countries iso_codes_who_afro #> [1] \"DZA\" \"AGO\" \"BEN\" \"BWA\" \"BFA\" \"BDI\" \"CPV\" \"CMR\" \"CAF\" \"TCD\" \"COM\" \"COG\" #> [13] \"COD\" \"CIV\" \"DJI\" \"GNQ\" \"ERI\" \"SWZ\" \"ETH\" \"GAB\" \"GMB\" \"GHA\" \"GIN\" \"GNB\" #> [25] \"KEN\" \"LSO\" \"LBR\" \"MDG\" \"MWI\" \"MLI\" \"MRT\" \"MUS\" \"MOZ\" \"NAM\" \"NER\" \"NGA\" #> [37] \"RWA\" \"STP\" \"SEN\" \"SYC\" \"SLE\" \"SOM\" \"ZAF\" \"SSD\" \"SDN\" \"TGO\" \"UGA\" \"TZA\" #> [49] \"ZMB\" \"ZWE\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/load_or_install_packages.html","id":null,"dir":"Reference","previous_headings":"","what":"Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages","title":"Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages","text":"function checks whether specified packages installed. package installed, installed. Special handling included mobility, propvacc, MOSAIC, installed GitHub.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/load_or_install_packages.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages","text":"","code":"load_or_install_packages(packages)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/load_or_install_packages.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages","text":"packages character vector package names load install.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/load_or_install_packages.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages","text":"packages, function installs CRAN already installed. Special cases handled following packages: mobility: Installed GitHub https://github.com/COVID-19-Mobility-Data-Network/mobility. propvacc: Installed GitHub https://github.com/gilesjohnr/propvacc. MOSAIC: Installed GitHub https://github.com/InstituteforDiseaseModeling/MOSAIC-pkg.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/load_or_install_packages.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Load or Install Required Packages (with GitHub handling for mobility, propvacc, and MOSAIC) — load_or_install_packages","text":"","code":"if (FALSE) { load_or_install_packages(c(\"ggplot2\", \"mobility\", \"propvacc\", \"MOSAIC\")) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/make_param_df.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Template for Parameter Values — make_param_df","title":"Get Template for Parameter Values — make_param_df","text":"function generates template long-form data frame parameter values, including origin (), destination (j), time (t), used simulate variables sigma.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/make_param_df.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Template for Parameter Values — make_param_df","text":"","code":"make_param_df( variable_name = NULL, variable_description = NULL, parameter_distribution = NULL, i = NULL, j = NULL, t = NULL, parameter_name = NULL, parameter_value = NULL )"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/make_param_df.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Template for Parameter Values — make_param_df","text":"variable_name character string representing name variable (e.g., 'sigma'). variable_description character string describing variable (e.g., 'proportion symptomatic'). parameter_distribution character string representing distribution parameter (e.g., 'beta'). vector representing origin locations. j vector representing destination locations. t vector representing time points. parameter_name character vector parameter names (e.g., shape1, shape2 beta distribution). parameter_value numeric vector parameter values (corresponding parameter names).","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/make_param_df.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Template for Parameter Values — make_param_df","text":"data frame containing long-form template parameter values. arguments NULL, empty data frame returned.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/make_param_df.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Template for Parameter Values — make_param_df","text":"","code":"# Example usage for sigma prm <- list(shape1 = 2, shape2 = 5) param_df <- make_param_df(\"sigma\", \"proportion symptomatic\", \"beta\", i = \"A\", j = \"B\", t = 1, names(prm), unlist(prm)) print(param_df) #> variable_name variable_description parameter_distribution i j t #> 1 sigma proportion symptomatic beta A B 1 #> 2 sigma proportion symptomatic beta A B 1 #> parameter_name parameter_value #> 1 shape1 2 #> 2 shape2 5"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/plot_ENSO_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot ENSO and DMI Data — plot_ENSO_data","title":"Plot ENSO and DMI Data — plot_ENSO_data","text":"function creates facet plot visualize ENSO DMI data time, separate panels variable (DMI, ENSO3, ENSO34, ENSO4). horizontal line zero included indicate neutral value, vertical line marks current date, date displayed vertically left side line.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/plot_ENSO_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot ENSO and DMI Data — plot_ENSO_data","text":"","code":"plot_ENSO_data(compiled_data)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/plot_ENSO_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot ENSO and DMI Data — plot_ENSO_data","text":"compiled_data data frame containing ENSO DMI data, columns date, variable, value. data typically generated compile_ENSO_data function.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/plot_ENSO_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot ENSO and DMI Data — plot_ENSO_data","text":"ggplot facet plot showing time series DMI, ENSO3, ENSO34, ENSO4 time. plot includes: horizontal solid line zero indicate neutral sea surface temperature anomaly. vertical dashed line indicate current date, current date displayed vertical text. Facets variable, allowing easy comparison DMI ENSO regions.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/plot_ENSO_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot ENSO and DMI Data — plot_ENSO_data","text":"function uses ggplot2 create line plot facets variable (DMI, ENSO3, ENSO34, ENSO4). adds horizontal reference line zero vertical line representing current date. current date displayed vertical text aligned left vertical line. data expected date, variable, value format.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/plot_ENSO_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot ENSO and DMI Data — plot_ENSO_data","text":"","code":"if (FALSE) { # Compile the ENSO and DMI data from the year 2000 onwards compiled_enso_data <- compile_ENSO_data(2010, \"daily\") # Plot the data plot_ENSO_data(compiled_enso_data) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_OAG_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Process and Save OAG Flight Data for Africa — process_OAG_data","title":"Process and Save OAG Flight Data for Africa — process_OAG_data","text":"function processes raw OAG flight data African countries, including data cleaning, location date conversion, aggregation. processed data saved CSV files African countries subset countries used MOSAIC modeling framework.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_OAG_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process and Save OAG Flight Data for Africa — process_OAG_data","text":"","code":"process_OAG_data(PATHS)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_OAG_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process and Save OAG Flight Data for Africa — process_OAG_data","text":"PATHS list containing paths raw processed data stored. PATHS typically output get_paths() function include following components: DATA_RAW: Path directory containing raw data files. DATA_PROCESSED: Path directory processed data saved.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_OAG_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process and Save OAG Flight Data for Africa — process_OAG_data","text":"function return value. processes OAG flight data saves aggregated results specified processed data paths.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_OAG_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Process and Save OAG Flight Data for Africa — process_OAG_data","text":"function performs following steps: Loads raw OAG flight data CSV file. Cleans formats data, including converting country codes date information. Aggregates data year calculates mean weekly passenger counts. Saves aggregated data African countries MOSAIC framework countries separate CSV files. output files saved processed data directory defined PATHS$DATA_PROCESSED.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_OAG_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Process and Save OAG Flight Data for Africa — process_OAG_data","text":"","code":"if (FALSE) { # Define paths for raw and processed data using get_paths() PATHS <- get_paths() # Process the OAG data and save the results process_OAG_data(PATHS) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_annual_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","title":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","text":"function compiles historical cholera data African countries (AFRO region) years 1949 2024. data processed saved MOSAIC directory structure. includes reported cholera cases, deaths, case fatality ratios (CFR).","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_annual_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","text":"","code":"process_WHO_annual_data(PATHS)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_annual_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","text":"PATHS list containing paths raw processed data directories. Typically generated get_paths() include: DATA_RAW: Path directory containing raw cholera data. DATA_WHO_ANNUAL: Path directory processed cholera data saved.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_annual_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","text":"function return value processes saves historical cholera data CSV files processed data directory.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_annual_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","text":"function compiles cholera data African countries (AFRO region) processing historical data 1949-2024. data sources follows: 1949-2021: Data compiled annual reports World Data. See https://ourworldindata.org. 2022: Data manually extracted annual report. 2023-2024: Data downloaded directly AWD GIS dashboard. Additionally, function calculates 95% binomial confidence intervals CFR applicable, data saved CSV files processed data directory.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_annual_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download, Process, and Save Historical Annual WHO Cholera Data for Africa — process_WHO_annual_data","text":"","code":"if (FALSE) { # Assuming PATHS is generated from get_paths() PATHS <- get_paths() # Download and process WHO annual cholera data process_WHO_annual_data(PATHS) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_weekly_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","title":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","text":"function processes cholera data converting country names ISO3 codes, filtering AFRO region countries, cleaning organizing data analysis.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_weekly_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","text":"","code":"process_WHO_weekly_data(PATHS)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_weekly_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","text":"PATHS list containing paths raw processed data directories. Typically generated get_paths() function include: DATA_RAW: Path raw cholera data file (e.g., cholera_country_weekly.csv). DATA_PROCESSED: Path save processed cholera data (e.g., cholera_country_weekly_processed.csv).","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_weekly_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","text":"function return value processes cholera data saves specified file CSV.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_weekly_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","text":"function reads cholera data, converts country names ISO3 codes (vice versa), filters countries AFRO region, ensures data cleaned organized year week. also handles special cases renaming Democratic Republic Congo Congo (Republic) modifies column names consistency.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_weekly_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Process Weekly Cholera Data: Convert Country Names to ISO3 and Filter by AFRO Countries — process_WHO_weekly_data","text":"","code":"if (FALSE) { # Assuming PATHS is generated from get_paths() PATHS <- get_paths() # Process cholera data process_WHO_weekly_data(PATHS) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_demographics_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Process UN World Prospects Data for African Countries — process_demographics_data","title":"Process UN World Prospects Data for African Countries — process_demographics_data","text":"function processes demographic data UN World Population Prospects African countries. filters data specified years, calculates population, birth rates, death rates per day, saves processed data CSV file.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_demographics_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process UN World Prospects Data for African Countries — process_demographics_data","text":"","code":"process_demographics_data(PATHS)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_demographics_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process UN World Prospects Data for African Countries — process_demographics_data","text":"PATHS list containing paths raw processed data stored. PATHS typically output get_paths() function include following components: DATA_RAW: Path directory containing raw UN World Population Prospects data. DATA_PROCESSED: Path directory processed demographic data saved.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_demographics_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process UN World Prospects Data for African Countries — process_demographics_data","text":"function return value. processes UN demographic data saves aggregated results CSV file specified directory.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_demographics_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Process UN World Prospects Data for African Countries — process_demographics_data","text":"function performs following steps: Loads raw demographic data CSV file. Filters data specified years African countries. Calculates population, birth rate, death rate per day country. Saves processed data CSV file processed data directory. processed data file saved PATHS$DATA_PROCESSED/demographics/ directory, filename includes year range data.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_demographics_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Process UN World Prospects Data for African Countries — process_demographics_data","text":"","code":"if (FALSE) { # Define paths for raw and processed data using get_paths() PATHS <- get_paths() # Process the UN World Prospects data and save the results process_demographics_data(PATHS) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/run_WHO_annual_data_app.html","id":null,"dir":"Reference","previous_headings":"","what":"Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app","title":"Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app","text":"function launches Shiny app visualizes cholera cases, deaths, case fatality rate (CFR) countries AFRO region 1970 2024. Users can select metric (cases, deaths, CFR) filter specific countries.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/run_WHO_annual_data_app.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app","text":"","code":"run_WHO_annual_data_app(PATHS)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/run_WHO_annual_data_app.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app","text":"PATHS list containing paths processed cholera data file. Typically generated get_paths() function include: DATA_WHO_ANNUAL: Path directory containing processed cholera data file (e.g., who_afro_annual_1949_2024.csv).","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/run_WHO_annual_data_app.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app","text":"function creates Shiny app allows users explore cholera incidence data across AFRO countries 1970 2024. Users can choose viewing cases, deaths, CFR can select specific countries visualization. app generates bar plots cases deaths, point plots error bars CFR.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/run_WHO_annual_data_app.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Run Shiny Application for Visualizing WHO Annual Cholera Data in AFRO Countries — run_WHO_annual_data_app","text":"","code":"if (FALSE) { # Define paths for processed data PATHS <- get_paths() # Run the cholera Shiny app run_WHO_annual_data_app(PATHS) }"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_openmeteo_api_key.html","id":null,"dir":"Reference","previous_headings":"","what":"Set OpenMeteo API Key — set_openmeteo_api_key","title":"Set OpenMeteo API Key — set_openmeteo_api_key","text":"function sets OpenMeteo API key stores global option called openmeteo_api_key. API key provided argument, used. , function prompt key interactively.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_openmeteo_api_key.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set OpenMeteo API Key — set_openmeteo_api_key","text":"","code":"set_openmeteo_api_key(api_key = NULL)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_openmeteo_api_key.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set OpenMeteo API Key — set_openmeteo_api_key","text":"api_key character string representing OpenMeteo API key. NULL, function prompt key interactively.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_openmeteo_api_key.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set OpenMeteo API Key — set_openmeteo_api_key","text":"message confirming API key set, instructions retrieving key.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_openmeteo_api_key.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Set OpenMeteo API Key — set_openmeteo_api_key","text":"API key stored global option called openmeteo_api_key using options(). key can retrieved time using getOption(\"openmeteo_api_key\").","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_openmeteo_api_key.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Set OpenMeteo API Key — set_openmeteo_api_key","text":"","code":"# Set the OpenMeteo API key interactively set_openmeteo_api_key() #> Please enter your OpenMeteo API key: #> Error in set_openmeteo_api_key(): API key cannot be empty. Please provide a valid API key. # Set the OpenMeteo API key programmatically set_openmeteo_api_key(\"your-api-key-here\") #> OpenMeteo API key set successfully. #> Retrieve with getOption('openmeteo_api_key') # Access the API key getOption(\"openmeteo_api_key\") #> [1] \"your-api-key-here\""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_root_directory.html","id":null,"dir":"Reference","previous_headings":"","what":"Set Root Directory — set_root_directory","title":"Set Root Directory — set_root_directory","text":"function sets root directory user-specified path , provided, prompts user enter root directory interactively. directory path stored global option called root_directory also returned.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_root_directory.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set Root Directory — set_root_directory","text":"","code":"set_root_directory(root = NULL)"},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_root_directory.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set Root Directory — set_root_directory","text":"root character string representing path root directory. NULL, function prompt user enter root directory interactively.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_root_directory.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set Root Directory — set_root_directory","text":"character string representing root directory. root directory also stored globally option root_directory.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_root_directory.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Set Root Directory — set_root_directory","text":"function uses either user-specified path path provided interactively set root directory. path validated ensure exists. validated, path stored global option root_directory, can accessed using getOption(\"root_directory\"). path invalid (.e., exist), function throws error.","code":""},{"path":"institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_root_directory.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Set Root Directory — set_root_directory","text":"","code":"if (FALSE) { # Set and display the root directory interactively root_dir <- set_root_directory() cat(\"Root directory:\", root_dir, \"\\n\") # Set the root directory programmatically root_dir <- set_root_directory(\"/path/to/root\") cat(\"Root directory:\", root_dir, \"\\n\") # Access the root directory from the global options getOption(\"root_directory\") }"}] diff --git a/docs/sitemap.xml b/docs/sitemap.xml index 3c6760f..a68887a 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -1,159 +1,159 @@ - https://gilesjohnr.github.io/MOSAIC-docs/404.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/404.html - https://gilesjohnr.github.io/MOSAIC-docs/LICENSE-text.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/LICENSE-text.html - https://gilesjohnr.github.io/MOSAIC-docs/authors.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/authors.html - https://gilesjohnr.github.io/MOSAIC-docs/index.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/index.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/compile_ENSO_data.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/compile_ENSO_data.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_country_to_iso.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_country_to_iso.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_codes.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_codes.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/convert_iso_to_country.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/convert_iso_to_country.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/download_africa_shapefile.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_africa_shapefile.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/download_all_country_shapefiles.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_all_country_shapefiles.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/download_climate_data.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/download_climate_data.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/est_WASH_coverage.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_WASH_coverage.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/est_mobility.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_mobility.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/est_symptomatic_prop.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/est_symptomatic_prop.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/fit_mobility_model.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/fit_mobility_model.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_dist.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_dist.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/generate_country_grid_n.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/generate_country_grid_n.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_DMI_forecast.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_DMI_forecast.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_DMI_historical.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_DMI_historical.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ENSO_forecast.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ENSO_forecast.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ENSO_historical.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ENSO_historical.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_WASH_data.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_WASH_data.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_WHO_annual_data.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_WHO_annual_data.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_centroid.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_centroid.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_forecast.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_forecast.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_future.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_future.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_climate_historical.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_climate_historical.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_country_shp.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_country_shp.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_elevation.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_elevation.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_ggplot_legend.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_ggplot_legend.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_paths.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_paths.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/get_symptomatic_prop_data.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/get_symptomatic_prop_data.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/index.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/index.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_central.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_central.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_east.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_east.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_north.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_north.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_south.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_south.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_africa_west.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_africa_west.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_mosaic.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_mosaic.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_ssa.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_ssa.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/iso_codes_who_afro.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/iso_codes_who_afro.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/load_or_install_packages.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/load_or_install_packages.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/make_param_df.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/make_param_df.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/plot_ENSO_data.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/plot_ENSO_data.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/process_OAG_data.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_OAG_data.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_annual_data.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_annual_data.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/process_WHO_weekly_data.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_WHO_weekly_data.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/process_demographics_data.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/process_demographics_data.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/run_WHO_annual_data_app.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/run_WHO_annual_data_app.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/set_openmeteo_api_key.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_openmeteo_api_key.html - https://gilesjohnr.github.io/MOSAIC-docs/reference/set_root_directory.html + institutefordiseasemodeling.github.io/MOSAIC-pkg/reference/set_root_directory.html