## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", eval = FALSE ) ## ----install-cran------------------------------------------------------------- # install.packages("climatehealth") ## ----install-github----------------------------------------------------------- # install.packages("remotes") # remotes::install_github("onssoschi/climatehealth") ## ----install-optional--------------------------------------------------------- # climatehealth::install_INLA() # climatehealth::install_terra() ## ----load--------------------------------------------------------------------- # library(climatehealth) ## ----temp-mortality-basic----------------------------------------------------- # res <- climatehealth::temp_mortality_do_analysis( # data_path = "path/to/your/data.csv", # date_col = "date", # region_col = "region", # temperature_col = "tmean", # health_outcome_col = "deaths", # population_col = "population", # meta_analysis = FALSE, # save_fig = FALSE, # save_csv = FALSE # ) ## ----temp-mortality-results--------------------------------------------------- # res$data_raw # the input data as loaded # res$analysis_results # model coefficients and confidence intervals # res$meta_results # pooled estimates (when meta_analysis = TRUE) ## ----temp-mortality-covariates------------------------------------------------ # res <- climatehealth::temp_mortality_do_analysis( # data_path = "path/to/your/data.csv", # date_col = "date", # region_col = "region", # temperature_col = "tmean", # health_outcome_col = "deaths", # population_col = "population", # independent_cols = c("humidity", "ozone"), # control_cols = c("dow", "holiday_flag"), # meta_analysis = FALSE, # save_fig = FALSE, # save_csv = FALSE # ) ## ----temp-mortality-meta------------------------------------------------------ # res <- climatehealth::temp_mortality_do_analysis( # data_path = "path/to/your/data.csv", # date_col = "date", # region_col = "region", # temperature_col = "tmean", # health_outcome_col = "deaths", # population_col = "population", # country = "National", # meta_analysis = TRUE, # save_fig = FALSE, # save_csv = FALSE # ) ## ----air-pollution------------------------------------------------------------ # res <- climatehealth::air_pollution_do_analysis( # data_path = "path/to/your/data.csv", # save_outputs = FALSE, # run_descriptive = TRUE, # run_power = TRUE # ) ## ----air-pollution-standards-------------------------------------------------- # res <- climatehealth::air_pollution_do_analysis( # data_path = "path/to/your/data.csv", # reference_standards = list( # list(value = 15, name = "WHO"), # list(value = 25, name = "National") # ), # save_outputs = FALSE, # run_power = TRUE # ) ## ----wildfire----------------------------------------------------------------- # res <- climatehealth::wildfire_do_analysis( # data_path = "path/to/your/data.csv", # date_col = "date", # region_col = "region", # exposure_col = "pm25_fire", # health_outcome_col = "respiratory_admissions", # population_col = "population", # meta_analysis = FALSE, # save_fig = FALSE, # save_csv = FALSE # ) ## ----suicides----------------------------------------------------------------- # res <- climatehealth::suicides_heat_do_analysis( # data_path = "path/to/your/data.csv", # date_col = "date", # region_col = "region", # temperature_col = "tmean", # health_outcome_col = "suicides", # population_col = "population", # meta_analysis = FALSE, # save_fig = FALSE, # save_csv = FALSE # ) ## ----diarrhea----------------------------------------------------------------- # res <- climatehealth::diarrhea_do_analysis( # data_path = "path/to/your/data.csv", # date_col = "date", # region_col = "region", # temperature_col = "tmean", # health_outcome_col = "diarrhea_cases", # population_col = "population", # meta_analysis = FALSE, # save_fig = FALSE, # save_csv = FALSE # ) ## ----malaria------------------------------------------------------------------ # res <- climatehealth::malaria_do_analysis( # data_path = "path/to/your/data.csv", # date_col = "date", # region_col = "region", # temperature_col = "tmean", # health_outcome_col = "malaria_cases", # population_col = "population", # meta_analysis = FALSE, # save_fig = FALSE, # save_csv = FALSE # ) ## ----descriptive-basic-------------------------------------------------------- # df <- read.csv("path/to/your/data.csv") # # desc <- climatehealth::run_descriptive_stats( # data = df, # output_path = "path/to/output/folder", # aggregation_column = "region", # dependent_col = "deaths", # independent_cols = c("tmean", "humidity", "rainfall"), # plot_corr_matrix = TRUE, # plot_dist = TRUE, # plot_na_counts = TRUE, # plot_scatter = TRUE, # plot_box = TRUE, # create_base_dir = TRUE # ) ## ----descriptive-advanced----------------------------------------------------- # desc <- climatehealth::run_descriptive_stats( # data = df, # output_path = "path/to/output/folder", # aggregation_column = "region", # population_col = "population", # dependent_col = "deaths", # independent_cols = c("tmean", "humidity", "rainfall"), # units = c( # deaths = "count", # tmean = "C", # humidity = "%", # rainfall = "mm" # ), # timeseries_col = "date", # plot_corr_matrix = TRUE, # plot_dist = TRUE, # plot_ma = TRUE, # ma_days = 30, # plot_seasonal = TRUE, # plot_regional = TRUE, # plot_total = TRUE, # detect_outliers = TRUE, # calculate_rate = TRUE, # create_base_dir = TRUE # ) ## ----descriptive-results------------------------------------------------------ # desc$run_output_path # folder where all outputs were saved # desc$region_output_paths # per-region output sub-folders ## ----saving------------------------------------------------------------------- # res <- climatehealth::temp_mortality_do_analysis( # data_path = "path/to/your/data.csv", # date_col = "date", # region_col = "region", # temperature_col = "tmean", # health_outcome_col = "deaths", # population_col = "population", # meta_analysis = TRUE, # save_fig = TRUE, # save_csv = TRUE, # output_folder_path = "path/to/output/folder" # ) ## ----error-handling----------------------------------------------------------- # result <- tryCatch( # climatehealth::temp_mortality_do_analysis( # data_path = "path/to/your/data.csv", # date_col = "wrong_column_name", # health_outcome_col = "deaths", # population_col = "population" # ), # climate_error = function(e) { # message("climatehealth error: ", conditionMessage(e)) # NULL # } # ) ## ----is-climate-error--------------------------------------------------------- # climatehealth::is_climate_error(e)