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#' Retrieve ILINet Surveillance Data
#'
#' The CDC FluView Portal provides in-season and past seasons' national, regional,
#' and state-level outpatient illness and viral surveillance data from both
#' ILINet (Influenza-like Illness Surveillance Network) and WHO/NREVSS
#' (National Respiratory and Enteric Virus Surveillance System).
#'
#' This function retrieves current and historical ILINet surveillance data for
#' the identified region.
#'
#' @md
#' @param region one of "`national`", "`hhs`", "`census`", or "`state`"
#' @param years a vector of years to retrieve data for (i.e. `2014` for CDC
#' flu season 2014-2015). CDC has data for this API going back to 1997.
#' Default value (`NULL`) means retrieve **all** years. NOTE: if you
#' happen to specify a 2-digit season value (i.e. `57` == 2017-2018)
#' the function is smart enough to retrieve by season ID vs convert that
#' to a year.
#' @references
#' - [CDC FluView Portal](https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html)
#' - [ILINet Portal](https://wwwn.cdc.gov/ilinet/) (Login required)
#' - [WHO/NREVSS](https://www.cdc.gov/surveillance/nrevss/index.html)
#' @export
#' @examples
#' national_ili <- ilinet("national")
#' hhs_ili <- ilinet("hhs")
#' census_ili <- ilinet("census")
#' state_ili <- ilinet("state")
#' \dontrun{
#' library(purrr)
#' map_df(
#' c("national", "hhs", "census", "state"),
#' ~ilinet(.x) %>% readr::type_convert())
#' }
ilinet <- function(region=c("national", "hhs", "census", "state"), years=NULL) {
region <- match.arg(tolower(region), c("national", "hhs", "census", "state"))
meta <- jsonlite::fromJSON("https://gis.cdc.gov/grasp/flu2/GetPhase02InitApp?appVersion=Public")
list(
AppVersion = "Public",
DatasourceDT = list(list(ID = 1, Name = "ILINet")),
RegionTypeId = .region_map[region]
) -> params
params$SubRegionsDT <- switch(region,
national = { list(list(ID=0, Name="")) },
hhs = { lapply(1:10, function(i) list(ID=i, Name=as.character(i))) },
census = { lapply(1:9, function(i) list(ID=i, Name=as.character(i))) },
state = { lapply(1:59, function(i) list(ID=i, Name=as.character(i))) }
)
available_seasons <- sort(meta$seasons$seasonid)
if (is.null(years)) { # ALL YEARS
years <- available_seasons
} else { # specified years or seasons or a mix
years <- as.numeric(years)
years <- ifelse(years > 1996, years - 1960, years)
years <- sort(unique(years))
years <- years[years %in% available_seasons]
if (length(years) == 0) {
years <- rev(sort(meta$seasons$seasonid))[1]
curr_season_descr <- meta$seasons[meta$seasons$seasonid == years, "description"]
message(sprintf("No valid years specified, defaulting to this flu season => ID: %s [%s]",
years, curr_season_descr))
}
}
params$SeasonsDT <- lapply(years, function(i) list(ID=i, Name=as.character(i)))
tf <- tempfile(fileext = ".zip")
td <- tempdir()
on.exit(unlink(tf), TRUE)
httr::POST(
url = "https://gis.cdc.gov/grasp/flu2/PostPhase02DataDownload",
httr::user_agent(.cdcfluview_ua),
httr::add_headers(
Origin = "https://gis.cdc.gov",
Accept = "application/json, text/plain, */*",
Referer = "https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html"
),
encode = "json",
body = params,
# httr::verbose(),
httr::write_disk(tf)
) -> res
httr::stop_for_status(res)
nm <- unzip(tf, overwrite = TRUE, exdir = td)
xdf <- read.csv(nm, skip = 1, stringsAsFactors=FALSE)
xdf <- .mcga(xdf)
suppressWarnings(xdf$weighted_ili <- to_num(xdf$weighted_ili))
suppressWarnings(xdf$unweighted_ili <- to_num(xdf$unweighted_ili))
suppressWarnings(xdf$age_0_4 <- to_num(xdf$age_0_4))
suppressWarnings(xdf$age_25_49 <- to_num(xdf$age_25_49))
suppressWarnings(xdf$age_25_64 <- to_num(xdf$age_25_64))
suppressWarnings(xdf$age_5_24 <- to_num(xdf$age_5_24))
suppressWarnings(xdf$age_50_64 <- to_num(xdf$age_50_64))
suppressWarnings(xdf$age_65 <- to_num(xdf$age_65))
suppressWarnings(xdf$ilitotal <- to_num(xdf$ilitotal))
suppressWarnings(xdf$num_of_providers <- to_num(xdf$num_of_providers))
suppressWarnings(xdf$total_patients <- to_num(xdf$total_patients))
suppressWarnings(xdf$week_start <- as.Date(sprintf("%s-%02d-1", xdf$year, xdf$week), "%Y-%U-%u"))
if (region == "national") xdf$region <- "National"
if (region == "hhs") xdf$region <- factor(xdf$region, levels=sprintf("Region %s", 1:10))
class(xdf) <- c("tbl_df", "tbl", "data.frame")
xdf
}