matti_jms_collabs/covid19/CTIS_script_for_james.R

# Setup data

## https://gisumd.github.io/COVID-19-API-Documentation/

library(tidyverse)
library(dplyr)

country_in_question <- "Finland"

## World Survey

# Ask for an indicator that's not found:
path <- "https://covidmap.umd.edu/api/resources?indicator=all&type=smoothed&country=Finland&daterange=20201115-20201130"
request <- httr::GET(url = path)
response <- httr::content(request, as = "text", encoding = "UTF-8")

# The error message contains all available indicators
returned_error <- jsonlite::fromJSON(response, flatten = TRUE) %>% data.frame()

# Pull available indicators
all_indicators <- returned_error %>% 
  dplyr::pull(error) %>% 
  stringr::str_replace_all(string = .,
                           pattern = "\'",
                           replacement = "") %>% 
  stringr::str_replace_all(string = .,
                           pattern = "need parameter:|indicator:",
                           replacement = "") %>% 
  stringr::str_replace_all(string = .,
                           pattern = "[]\\[]",
                           replacement = "") %>% 
  # Split based on "or", preceded or followed by any number of spaces 
  strsplit("[ \t]+or[ \t]+|[ \t]+or")  %>% 
  purrr::map(.x = .,
             .f = ~gsub(pattern = " ", replacement = "", x = .x)) %>% 
  unlist()


worldsurvey_df <- list()

for (i in 1:length(all_indicators)){
  print(all_indicators[i])
  # add url
  path <- paste0("https://covidmap.umd.edu/api/resources?indicator=",
                 all_indicators[i],
                 "&type=daily&country=",
                 country_in_question,
                 "&daterange=20200101-20221130")
  
  # request data from api
  request <- httr::GET(url = path)
  
  # make sure the content is encoded with 'UTF-8'
  response <- httr::content(request, as = "text", encoding = "UTF-8")
  
  # now we have a dataframe for use!
  worldsurvey_df[[i]] <- jsonlite::fromJSON(response, flatten = FALSE)[[1]] %>% 
    # If there's no data for the indicator, return empty data frame
    {if(is.list(.)) data.frame(.) else 
      data.frame(empty = character(),
                 data.survey_date = as.Date(character())) }
  
}

worldsurvey_df_nonempty <- purrr::discard(worldsurvey_df, ~nrow(.) == 0)

worldsurvey_df_selected <- purrr::map(.x = worldsurvey_df_nonempty,
                                      .f = ~.x %>% 
                                        dplyr::select(1, "survey_date"))

worldsurvey_df_selected_full <- purrr::map(.x = worldsurvey_df_nonempty,
                                           .f = ~.x %>% 
                                             dplyr::select(1, std_error = 2, 
                                                           "survey_date") %>% 
                                             dplyr::mutate(name = names(.[[1]]))) %>%
  
  purrr::reduce(.x = .,
                .f = dplyr::full_join,
                by = "survey_date")

worldsurvey_analysis_allvars <- purrr::reduce(.x = worldsurvey_df_selected,
                                              .f = dplyr::full_join,
                                              by = "survey_date") %>% 
  dplyr::arrange(survey_date) %>% 
  dplyr::mutate(date = as.Date(survey_date, format = "%Y%m%d")) %>% 
  dplyr::select(-survey_date)


### DATA FOR PCA
data_for_pca <- worldsurvey_analysis_allvars %>%
  dplyr::filter(date > "2021-06-08") %>% 
  dplyr::arrange(date) %>% 
  dplyr::select(date,
                where(~sum(is.na(.x)) <= 10),
                -contains("vaccin")) %>% 
  tidyr::drop_na()

latest_date <- data_for_pca$date %>% tail(1) 

readr::write_csv(x = data_for_pca,
                 file = paste0("shield-complexity/data/",
                               country_in_question, 
                               "_worldsurvey_nonmissing_since_2021-06-08_to_",
                               latest_date, ".csv"))

#### Coefficient of variation

worldsurvey_df_selected_cov <- purrr::map(
  .x = worldsurvey_df_nonempty,
  .f = ~.x %>%
    dplyr::select("survey_date",
                  1,
                  std_error = 2,
                  sample_size) %>%
    dplyr::mutate(std_dev = std_error * sqrt(sample_size),
                  coef_of_variation = std_dev/.[[2]])
)

worldsurvey_df_selected_cov_filtered <-
  purrr::map(.x = worldsurvey_df_selected_cov,
             .f = ~.x %>%
               dplyr::mutate(date = as.Date(survey_date,
                                            format = "%Y%m%d")) %>%
               dplyr::filter(date > "2021-06-08"))


coevar_data_from_2021_06_08_long <- 
  purrr::map(.x = worldsurvey_df_selected_cov_filtered,
             .f = ~.x %>%
               dplyr::mutate(name = names(.x[2]),
                             value = coef_of_variation) %>%
               dplyr::select(date, name, value,
                             sample_size, std_error)) %>%
  purrr::reduce(.x = .,
                .f = full_join) 

coevar_data_from_2021_06_08 <- coevar_data_from_2021_06_08_long %>%
  dplyr::select(-sample_size, -std_error) %>% 
  tidyr::pivot_wider() 

worldsurvey_sample_sizes_from_2021_06_08 <- 
  coevar_data_from_2021_06_08_long %>%
  dplyr::select(date,
                name,
                sample_size)

worldsurvey_std_errors_from_2021_06_08 <- 
  coevar_data_from_2021_06_08_long %>%
  dplyr::select(date,
                name,
                std_error)

coevar_data_from_2021_06_08_dropna <- coevar_data_from_2021_06_08 %>%
  dplyr::select(date,
                where(~sum(is.na(.x)) <= 10),
                -contains("vaccin")) %>% 
  tidyr::drop_na()

latest_date_coevar <- coevar_data_from_2021_06_08_dropna$date %>% max()

coevar_data_from_2021_06_08_dropna %>%
  readr::write_csv(file = paste0(
    "shield-complexity/data/", 
    country_in_question, 
    "_worldsurvey_nonmissing_c_of_v_since_2021-06-08_to_",
    latest_date_coevar, ".csv"))

worldsurvey_sample_sizes_from_2021_06_08 %>% 
  readr::write_csv(file = paste0(
    "shield-complexity/data/", 
    country_in_question, 
    "_sample_sizes_since_2021-06-08",
    ".csv"))

worldsurvey_std_errors_from_2021_06_08 %>% 
  readr::write_csv(file = paste0(
    "shield-complexity/data/", 
    country_in_question, 
    "_std_errors_since_2021-06-08",
    ".csv"))