#' Mortality Surveillance Data from the National Center for Health Statistics
#'
#' The National Center for Health Statistics (NCHS) collects and disseminates the Nation's
#' official vital statistics. These statistics are based on data provided to NCHS through
#' contracts with the vital registration systems operated in the various jurisdictions
#' legally responsible for the registration of deaths (i.e., death certificates) and other
#' vital events. These data have previously only been released as annual final data files
#' 12 months or more after the end of the data year. Recent NCHS efforts to improve the
#' timeliness of jurisdiction reporting and modernize the national vital statistics
#' infrastructure have created a system capable of supporting near real-time surveillance.
#' Capitalizing on these new capabilities, NCHS and CDC’s Influenza Division have
#' partnered to pilot the use of NCHS mortality surveillance data for Pneumonia and
#' Influenza (P&I) mortality surveillance.
#'
#' NCHS mortality surveillance data are presented by the week the death occurred.
#' Nationally P&I percentages are released two weeks after the week of death to allow for
#' collection of enough data to produce a stable P&I percentage at the national level.
#' Collection of complete data is not expected, and reliable P&I ratios are not expected
#' at the region and state level within this two week period. State and Region level
#' counts will be released only after 20% of the expected number of deaths are reported
#' through the system.
#'
#' @references \url{https://www.cdc.gov/flu/weekly/nchs.htm}
#' @return a list of \code{tbl_df}s
#' @export
#' @examples \dontrun{
#' get_mortality_surveillance_data()
#' }
get_mortality_surveillance_data <- function() {

  pg <- read_html("https://www.cdc.gov/flu/weekly/nchs.htm")

  PREFIX <- "https://www.cdc.gov"

  xml_find_all(pg, ".//select[@id='State']/option[contains(@value, 'csv') and
                                                contains(@value, 'State_')]") %>%
    xml_attr("value") %>%
    sprintf("%s%s", PREFIX, .) -> targets

  pb <- progress_estimated(length(targets))
  map_df(targets, function(x) {
    pb$tick()$print()
    suppressMessages(read_csv(URLencode(x), col_types="ciidii"))
  }) -> influenza_mortality_by_state


  xml_find_all(pg, ".//select[@id='Regional Data']/
                       option[contains(@value, 'csv') and
                              not(contains(@value, 'Week_'))]") %>%
    xml_attr("value") %>%
    sprintf("%s%s", PREFIX, .) -> targets

  pb <- progress_estimated(length(targets))
  map_df(targets, function(x) {
    pb$tick()$print()
    suppressMessages(read_csv(URLencode(x), col_types="ciidii"))
  }) -> influenza_mortality_by_region


  xml_find_all(pg, ".//select[@id='Regional Data']/
                       option[contains(@value, 'csv') and
                              contains(@value, 'Week_')]") %>%
    xml_attr("value") %>%
    sprintf("%s%s", PREFIX, .) -> targets

  pb <- progress_estimated(length(targets))
  map_df(targets, function(x) {
    pb$tick()$print()
    suppressMessages(read_csv(URLencode(x), col_types="ciidii"))
  }) -> influenza_mortality_by_week

  list(
    by_state=influenza_mortality_by_state,
    by_region=influenza_mortality_by_region,
    by_week=influenza_mortality_by_week
  )

}