12 changed files with 18 additions and 718 deletions
@ -1,188 +0,0 @@ |
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#' Retrieves state, regional or national influenza statistics from the CDC |
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#' |
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#' Uses the data source from the |
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#' \href{https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html}{CDC FluView} |
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#' and provides flu reporting data as either a single data frame or a list of |
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#' data frames (depending on whether either \code{WHO NREVSS} or \code{ILINet} |
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#' (or both) is chosen. |
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#' |
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#' A lookup table between HHS regions and their member states/territories |
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#' is provided in \code{\link{hhs_regions}}. |
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#' |
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#' @param region one of "\code{hhs}", "\code{census}", "\code{national}", |
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#' "\code{state}" |
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#' @param sub_region depends on the \code{region_type}.\cr |
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#' For "\code{national}", the \code{sub_region} should be \code{NA}.\cr |
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#' For "\code{hhs}", should be a vector between \code{1:10}.\cr |
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#' For "\code{census}", should be a vector between \code{1:9}.\cr |
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#' For "\code{state}", should be a vector of state/territory names |
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#' or "\code{all}". |
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#' @param data_source either of "\code{who}" (for WHO NREVSS) or "\code{ilinet}" |
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#' or "\code{all}" (for both) |
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#' @param years a vector of years to retrieve data for (i.e. \code{2014} for CDC |
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#' flu season 2014-2015). Default value is the current year and all |
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#' \code{years} values should be > \code{1997} |
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#' @return If only a single \code{data_source} is specified, then a single |
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#' \code{data.frame} is returned, otherwise a named list with each |
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#' \code{data.frame} is returned. |
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#' @note There is often a noticeable delay when making the API request to the CDC. |
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#' This is not due to a large download size, but the time it takes for their |
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#' servers to crunch the data. Wrap the function call in \code{httr::with_verbose} |
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#' if you would like to see what's going on. |
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#' @export |
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#' @examples \dontrun{ |
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#' flu <- get_flu_data("hhs", 1:10, c("who", "ilinet"), years=2000:2014) |
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#' } |
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get_flu_data <- function(region="hhs", sub_region=1:10, |
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data_source="ilinet", |
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years=as.numeric(format(Sys.Date(), "%Y"))) { |
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|
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region <- tolower(region) |
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data_source <- tolower(data_source) |
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|
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if (!(region %in% c("hhs", "census", "national", "state"))) |
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stop("Error: region must be one of hhs, census or national") |
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|
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if (length(region) != 1) |
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stop("Error: can only select one region") |
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|
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if (region=="national") sub_region = 0 |
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|
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if ((region=="hhs") && !all(sub_region %in% 1:10)) |
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stop("Error: sub_region values must fall between 1:10 when region is 'hhs'") |
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|
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if ((region=="census") && !all(sub_region %in% 1:19)) |
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stop("Error: sub_region values must fall between 1:10 when region is 'census'") |
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|
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if (!all(data_source %in% c("who", "ilinet", "all"))) |
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stop("Error: data_source must be either 'who', 'ilinet', 'all' or c('who', 'ilinet')") |
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|
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if (any(years < 1997)) |
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stop("Error: years should be > 1997") |
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|
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# Match names of states to numbers for API |
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if (region == "state") { |
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sub_region <- tolower(sub_region) |
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|
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if (any(sub_region == "all")) { |
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sub_region_inpt <- 1:57 |
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} else { |
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state_match <- data.frame(state = tolower(c(sort(c(datasets::state.name, |
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"District of Columbia")), |
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"American Samoa", |
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"Commonwealth of the Northern Mariana Islands", |
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"Puerto Rico", |
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"Virgin Islands", |
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"New York City", |
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"Los Angeles")), |
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num = 1:57, |
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stringsAsFactors = F) |
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|
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sub_region_inpt <- state_match$num[state_match$state %in% sub_region] |
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|
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if (length(sub_region_inpt) == 0) |
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stop("Error: no eligible state/territory names provided") |
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} |
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} else sub_region_inpt <- sub_region |
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|
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# format the input parameters to fit the CDC API |
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|
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years <- years - 1960 |
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reg <- as.numeric(c("hhs"=1, "census"=2, "national"=3, "state" = 5)[[region]]) |
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|
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# Format data source |
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if (data_source == "who") { |
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data_list <- list(list(ID = 0, |
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Name = "WHO_NREVSS")) |
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} else if (data_source == "ilinet") { |
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data_list <- list(list(ID = 1, |
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Name = "ILINet")) |
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} else data_list <- list(list(ID = 0, |
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Name = "WHO_NREVSS"), |
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list(ID = 1, |
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Name = "ILINet")) |
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|
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# Format years |
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year_list <- lapply(seq_along(years), |
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function(x) list(ID = years[x], |
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Name = paste(years[x]))) |
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|
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# Format sub regions |
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sub_reg_list <- lapply(seq_along(sub_region_inpt), |
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function(x) list(ID = sub_region_inpt[x], |
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Name = paste(sub_region_inpt[x]))) |
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|
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params <- list(AppVersion = "Public", |
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DatasourceDT = data_list, |
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RegionTypeId = reg, |
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SeasonsDT = year_list, |
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SubRegionsDT = sub_reg_list) |
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|
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out_file <- tempfile(fileext=".zip") |
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|
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# CDC API returns a ZIP file so we grab, save & expand it to then read in CSVs |
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|
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tmp <- httr::POST("https://gis.cdc.gov/grasp/flu2/PostPhase02DataDownload", |
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body = params, |
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encode = "json", |
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httr::write_disk(out_file)) |
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|
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httr::stop_for_status(tmp) |
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|
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if (!(file.exists(out_file))) |
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stop("Error: cannot process downloaded data") |
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|
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out_dir <- tempdir() |
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files <- unzip(out_file, exdir=out_dir, overwrite=TRUE) |
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pb <- dplyr::progress_estimated(length(files)) |
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purrr::map(files, function(x) { |
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pb$tick()$print() |
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ct <- ifelse(grepl("who", x, ignore.case=TRUE), 1, 1) |
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suppressMessages(readr::read_csv(x, skip=ct)) |
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}) -> file_list |
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|
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names(file_list) <- substr(basename(files), 1, nchar(basename(files)) - 4) |
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|
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# If data are missing, X causes numeric columns to be read as character |
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purrr::map(file_list, function(x) { |
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# Create list of columns that should be numeric - exclude character columns |
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cols <- which(!colnames(x) %in% c("REGION", "REGION TYPE", |
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"SEASON_DESCRIPTION")) |
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suppressWarnings(x[cols] <- purrr::map(x[cols], as.numeric)) |
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return(x) |
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}) -> file_list |
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|
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# Depending on the parameters, there could be more than one |
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# file returned. When there's only one, return a more usable |
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# structure. |
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if (length(file_list) == 1) { |
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file_list <- file_list[[1]] |
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|
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# when no rows, then it's likely the caller specified the |
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# current year and the flu season has technically not started yet. |
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# so help them out and move the year back and get current flu |
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# season data. |
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|
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if ((nrow(file_list) == 0) && |
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(length(years)==1) && |
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(years == (as.numeric(format(Sys.Date(), "%Y"))-1960))) { |
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message("Adjusting [years] to get current season...") |
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return(get_flu_data(region=region, sub_region=sub_region, |
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data_source=data_source, years=years+1960-1)) |
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} else { |
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return(file_list) |
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} |
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|
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} else { |
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return(file_list) |
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} |
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|
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} |
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@ -1,119 +0,0 @@ |
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#' Retrieves influenza hospitalization statistics from the CDC |
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#' |
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#' Uses the data source from the |
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#' \href{https://gis.cdc.gov/GRASP/Fluview/FluHospRates.html}{CDC FluView} |
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#' and provides influenza hospitalization reporting data as a data frame. |
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#' |
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#' @param area one of "\code{flusurvnet}", "\code{eip}", "\code{ihsp}", or two |
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#' digit state abbreviation for an individual site. Exceptions are |
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#' New York - Albany ("\code{nya}") and New York - Rochester |
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#' ("\code{nyr}") |
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#' @param age_group a vector of age groups to pull data for. Possible values are: |
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#' "\code{overall}", "\code{0-4y}", "\code{5-17y}, "\code{18-49y}, |
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#' "\code{50-64y}, "\code{65+y}". |
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#' @param years a vector of years to retrieve data for (i.e. \code{2014} for CDC |
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#' flu season 2014-2015). Default value is the current year and all |
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#' \code{years} values should be >= \code{2009} |
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#' @return A single \code{data.frame}. |
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#' @note There is often a noticeable delay when making the API request to the CDC. |
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#' This is not due to a large download size, but the time it takes for their |
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#' servers to crunch the data. Wrap the function call in \code{httr::with_verbose} |
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#' if you would like to see what's going on. |
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#' @export |
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#' @examples \dontrun{ |
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#' # All of FluSurv-NET, 50-64 years old, 2010/11-2014/15 flu seasons |
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#' flu <- get_hosp_data("flusurvnet", "50-64y", years=2010:2014) |
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#' } |
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get_hosp_data <- function(area="flusurvnet", age_group="overall", |
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years=as.numeric(format(Sys.Date(), "%Y")) - 1) { |
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area <- tolower(area) |
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age_group <- tolower(age_group) |
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if (!(area %in% c("flusurvnet", "eip", "ihsp", "ca", "co", "ct", "ga", "md", |
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"mn", "nm", "nya", "nyr", "or", "tn", "id", "ia", "mi", |
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"oh", "ok", "ri", "sd", "ut"))) |
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stop("Error: area must be one of flusurvnet, eip, ihsp, or a valid state abbreviation") |
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if (length(area) != 1) |
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stop("Error: can only select one area") |
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|
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if (!all(age_group %in% c("overall", "0-4y", "5-17y", "18-49y", |
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"50-64y", "65+y"))) |
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stop("Error: invalid age group specified") |
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|
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if (any(years < 2009)) |
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stop("Error: years should be >= 2009") |
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|
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# Match names of age groups to numbers for API |
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age_match <- data.frame(age_group = c("overall", "0-4y", "5-17y", |
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"18-49y", "50-64y", "65+y"), |
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code = c(6, 1, 2, 3, 4, 5)) |
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|
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age_group_num <- age_match$code[age_match$age_group %in% age_group] |
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|
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|
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# format the input parameters to fit the CDC API |
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|
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years <- years - 1960 |
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|
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area_match <- data.frame(area = c("flusurvnet", "eip", "ca", "co", "ct", |
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"ga", "md", "mn", "nm", "nya", "nyr", "or", |
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"tn", "ihsp", "id", "ia", "mi", "oh", "ok", |
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"ri", "sd", "ut"), |
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catch = c(22, 22, 1, 2, 3, 4, 7, 9, 11, 13, 14, 17, |
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20, 22, 6, 5, 8, 15, 16, 18, 19, 21), |
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network = c(1, rep(2, 12), rep(3, 9))) |
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|
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# Format years |
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year_list <- lapply(seq_along(years), |
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function(x) list(ID = years[x])) |
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|
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# Format age group |
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age_list <- lapply(seq_along(age_group_num), |
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function(x) list(ID = age_group_num[x])) |
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|
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params <- list(AppVersion = "Public", |
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agegroups = age_list, |
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catchmentid = area_match$catch[area_match$area == area], |
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networkid = area_match$network[area_match$area == area], |
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seasons = year_list) |
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|
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out_file <- tempfile(fileext=".json") |
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|
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# CDC API returns a ZIP file so we grab, save & expand it to then read in CSVs |
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|
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tmp <- httr::POST("https://gis.cdc.gov/GRASP/Flu3/PostPhase03DownloadData", |
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body = params, |
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encode = "json", |
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httr::write_disk(out_file, overwrite = T)) |
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|
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httr::stop_for_status(tmp) |
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|
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if (!(file.exists(out_file))) |
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stop("Error: cannot process downloaded data") |
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|
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file <- jsonlite::fromJSON(out_file)[[1]] |
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|
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# pb <- dplyr::progress_estimated(length(file)) |
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# purrr::map(file, function(x) { |
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# pb$tick()$print() |
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# ct <- ifelse(grepl("who", x, ignore.case=TRUE), 1, 1) |
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# suppressMessages(readr::read_csv(x, skip=ct)) |
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# }) -> file_list |
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|
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# names(file_list) <- substr(basename(files), 1, nchar(basename(files)) - 4) |
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|
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# Depending on the parameters, there could be more than one |
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# file returned. When there's only one, return a more usable |
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# structure. |
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|
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# when no rows, then it's likely the caller specified the |
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# current year and the flu season has technically not started yet. |
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# so help them out and move the year back and get current flu |
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# season data. |
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|
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return(file) |
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|
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} |
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@ -1,53 +0,0 @@ |
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#' Retrieves state/territory-level influenza statistics from the CDC |
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#' |
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#' Uses the data source from the CDC' State-levelFluView |
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#' \url{https://gis.cdc.gov/grasp/fluview/main.html} and provides state flu |
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#' reporting data as a single data frame.\cr |
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#' \cr |
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#' This function provides similar data to \code{\link{get_weekly_flu_report}} but |
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#' provides more metadata about the reporting sources and has access to more |
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#' historical infomation. |
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#' |
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#' @param years a vector of years to retrieve data for (i.e. \code{2014} for CDC |
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#' flu season 2014-2015). Default value is the current year and all |
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#' \code{years} values should be >= \code{2008} |
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#' @return A \code{data.frame} of state-level data for the specified seasons |
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#' (also classed as \code{cdcstatedata}) |
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#' @export |
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#' @note There is often a noticeable delay when making the API request to the CDC. This |
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#' is not due to a large download size, but the time it takes for their |
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#' servers to crunch the data. Wrap the function call in \code{httr::with_verbose} |
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#' if you would like to see what's going on. |
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#' @examples \dontrun{ |
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#' get_state_data(2014) |
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#' get_state_data(c(2013, 2014)) |
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#' get_state_data(2010:2014) |
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#' httr::with_verbose(get_state_data(2009:2015)) |
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#' } |
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get_state_data <- function(years=as.numeric(format(Sys.Date(), "%Y"))) { |
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|
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if (any(years < 2008)) |
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stop("Error: years should be >= 2008") |
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|
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years <- c((years - 1960), 1) |
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years <- paste0(years, collapse=",") |
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|
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tmp <- httr::GET(sprintf("https://gis.cdc.gov/grasp/fluView1/Phase1DownloadDataP/%s", years)) |
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stop_for_status(tmp) |
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|
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# the API doesn't return actual JSON. It returns a JavaScript data structre |
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# which is why we need the assistance of the super handy V8 pkg. |
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|
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res <- httr::content(tmp, as="parsed") |
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|
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ctx <- V8::v8() |
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ctx$eval(V8::JS(sprintf("var dat=%s;", res))) |
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res <- ctx$get("dat", flatten=FALSE) |
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out <- suppressMessages(readr::type_convert(res$datadownload)) |
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class(out) <- c("cdcstatedata", class(out)) |
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out |
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} |
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@ -1,58 +0,0 @@ |
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#' Retrieves (high-level) weekly influenza surveillance report from the CDC |
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#' |
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#' The CDC publishes a \href{https://www.cdc.gov/flu/weekly/usmap.htm}{weekly |
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#' influenza report} detailing high-level flu activity per-state. They also |
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#' publish a data file (see \code{References}) of historical report readings. |
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#' This function reads that XML file and produces a long \code{data_frame} |
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#' with the historical surveillance readings.\cr |
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#' \cr |
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#' This function provides similar data to \code{\link{get_state_data}} but without |
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#' the reporting source metadata and a limit on the historical flu information. |
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#' |
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#' @references \url{https://www.cdc.gov/flu/weekly/flureport.xml} |
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#' @return \code{tbl_df} (also classed with \code{cdcweeklyreport}) with six |
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#' columns: \code{year}, \code{week_number}, \code{state}, \code{color}, |
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#' \code{label}, \code{subtitle} |
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#' @export |
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#' @examples \dontrun{ |
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#' get_weekly_flu_report() |
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#' } |
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get_weekly_flu_report <- function() { |
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|
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# grab the report |
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doc <- read_xml("https://www.cdc.gov/flu/weekly/flureport.xml") |
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|
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# extract the time periods |
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periods <- xml_attrs(xml_find_all(doc, "timeperiod")) |
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|
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# for each period extract the state information and |
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# shove it all into a data frame |
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pb <- progress_estimated(length(periods)) |
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purrr::map_df(periods, function(period) { |
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|
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pb$tick()$print() |
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|
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tp <- sprintf("//timeperiod[@number='%s' and @year='%s']", |
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period["number"], period["year"]) |
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|
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weeks <- xml_find_first(doc, tp) |
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kids <- xml_children(weeks) |
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|
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abbrev <- xml_text(xml_find_all(kids, "abbrev"), TRUE) |
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color <- xml_text(xml_find_all(kids, "color"), TRUE) |
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label <- xml_text(xml_find_all(kids, "label"), TRUE) |
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|
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data_frame(year=period["year"], |
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week_number=period["number"], |
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state=abbrev, |
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color=color, |
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label=label, |
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subtitle=period["subtitle"]) |
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|
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}) -> out |
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|
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class(out) <- c("cdcweeklyreport", class(out)) |
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|
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out |
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|
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} |
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@ -1,89 +0,0 @@ |
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#' Mortality Surveillance Data from the National Center for Health Statistics |
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#' |
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#' The National Center for Health Statistics (NCHS) collects and disseminates the Nation's |
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#' official vital statistics. These statistics are based on data provided to NCHS through |
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#' contracts with the vital registration systems operated in the various jurisdictions |
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#' legally responsible for the registration of deaths (i.e., death certificates) and other |
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#' vital events. These data have previously only been released as annual final data files |
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#' 12 months or more after the end of the data year. Recent NCHS efforts to improve the |
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#' timeliness of jurisdiction reporting and modernize the national vital statistics |
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#' infrastructure have created a system capable of supporting near real-time surveillance. |
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#' Capitalizing on these new capabilities, NCHS and CDC’s Influenza Division have |
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#' partnered to pilot the use of NCHS mortality surveillance data for Pneumonia and |
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#' Influenza (P&I) mortality surveillance. |
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#' |
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#' NCHS mortality surveillance data are presented by the week the death occurred. |
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#' Nationally P&I percentages are released two weeks after the week of death to allow for |
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#' collection of enough data to produce a stable P&I percentage at the national level. |
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#' Collection of complete data is not expected, and reliable P&I ratios are not expected |
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#' at the region and state level within this two week period. State and Region level |
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#' counts will be released only after 20% of the expected number of deaths are reported |
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#' through the system. |
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#' |
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#' @references \url{https://www.cdc.gov/flu/weekly/nchs.htm} |
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#' @return a list of \code{tbl_df}s |
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#' @export |
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#' @examples \dontrun{ |
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#' get_mortality_surveillance_data() |
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#' } |
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get_mortality_surveillance_data <- function() { |
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|
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# scrape (ugh) web page to get data file links for state mortality data |
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|
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pg <- xml2::read_html("https://www.cdc.gov/flu/weekly/nchs.htm") |
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|
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PREFIX <- "https://www.cdc.gov" |
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|
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xml2::xml_find_all(pg, ".//select[@id='State']/option[contains(@value, 'csv') and |
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contains(@value, 'State_')]") %>% |
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xml2::xml_attr("value") %>% |
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sprintf("%s%s", PREFIX, .) -> targets |
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|
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pb <- dplyr::progress_estimated(length(targets)) |
|||
purrr::map_df(targets, function(x) { |
|||
pb$tick()$print() |
|||
suppressMessages(read_csv(URLencode(x), col_types="ciidii")) |
|||
}) -> influenza_mortality_by_state |
|||
|
|||
# scrape (ugh) web page to get data file links for regional mortality data |
|||
|
|||
xml2::xml_find_all(pg, ".//select[@id='Regional Data']/ |
|||
option[contains(@value, 'csv') and |
|||
not(contains(@value, 'Week_'))]") %>% |
|||
xml2::xml_attr("value") %>% |
|||
sprintf("%s%s", PREFIX, .) -> targets |
|||
|
|||
pb <- dplyr::progress_estimated(length(targets)) |
|||
purrr::map_df(targets, function(x) { |
|||
pb$tick()$print() |
|||
suppressMessages(read_csv(URLencode(x), col_types="ciidii")) |
|||
}) -> influenza_mortality_by_region |
|||
|
|||
# scrape (ugh) web page to get data file links for weekly mortality data |
|||
|
|||
xml2::xml_find_all(pg, ".//select[@id='Regional Data']/ |
|||
option[contains(@value, 'csv') and |
|||
contains(@value, 'Week_')]") %>% |
|||
xml2::xml_attr("value") %>% |
|||
sprintf("%s%s", PREFIX, .) -> targets |
|||
|
|||
pb <- dplyr::progress_estimated(length(targets)) |
|||
purrr::map_df(targets, function(x) { |
|||
pb$tick()$print() |
|||
suppressMessages(read_csv(URLencode(x), col_types="ciidii")) |
|||
}) -> influenza_mortality_by_week |
|||
|
|||
# if return it all |
|||
|
|||
list( |
|||
by_state = influenza_mortality_by_state, |
|||
by_region = influenza_mortality_by_region, |
|||
by_week = influenza_mortality_by_week |
|||
) -> out |
|||
|
|||
class(out) <- c("cfv_mortality", class(out)) |
|||
|
|||
out |
|||
|
|||
} |
|||
|
|||
@ -0,0 +1,18 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/cdcfluview-package.R |
|||
\docType{package} |
|||
\name{cdcfluview} |
|||
\alias{cdcfluview} |
|||
\alias{cdcfluview-package} |
|||
\title{Retrieve 'U.S'.' Flu Season Data from the 'CDC' 'FluView' Portal} |
|||
\description{ |
|||
The U.S. Centers for Disease Control (CDC) maintains a portal |
|||
\url{http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html} for |
|||
accessing state, regional and national influenza statistics as well as |
|||
Mortality Surveillance Data. The Flash interface makes it difficult and |
|||
time-consuming to select and retrieve influenza data. This package |
|||
provides functions to access the data provided by the portal's underlying API. |
|||
} |
|||
\author{ |
|||
Bob Rudis (bob@rud.is) |
|||
} |
|||
@ -1,54 +0,0 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/get_flu_data.r |
|||
\name{get_flu_data} |
|||
\alias{get_flu_data} |
|||
\title{Retrieves state, regional or national influenza statistics from the CDC} |
|||
\usage{ |
|||
get_flu_data(region = "hhs", sub_region = 1:10, data_source = "ilinet", |
|||
years = as.numeric(format(Sys.Date(), "\%Y"))) |
|||
} |
|||
\arguments{ |
|||
\item{region}{one of "\code{hhs}", "\code{census}", "\code{national}", |
|||
"\code{state}"} |
|||
|
|||
\item{sub_region}{depends on the \code{region_type}.\cr |
|||
For "\code{national}", the \code{sub_region} should be \code{NA}.\cr |
|||
For "\code{hhs}", should be a vector between \code{1:10}.\cr |
|||
For "\code{census}", should be a vector between \code{1:9}.\cr |
|||
For "\code{state}", should be a vector of state/territory names |
|||
or "\code{all}".} |
|||
|
|||
\item{data_source}{either of "\code{who}" (for WHO NREVSS) or "\code{ilinet}" |
|||
or "\code{all}" (for both)} |
|||
|
|||
\item{years}{a vector of years to retrieve data for (i.e. \code{2014} for CDC |
|||
flu season 2014-2015). Default value is the current year and all |
|||
\code{years} values should be > \code{1997}} |
|||
} |
|||
\value{ |
|||
If only a single \code{data_source} is specified, then a single |
|||
\code{data.frame} is returned, otherwise a named list with each |
|||
\code{data.frame} is returned. |
|||
} |
|||
\description{ |
|||
Uses the data source from the |
|||
\href{https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html}{CDC FluView} |
|||
and provides flu reporting data as either a single data frame or a list of |
|||
data frames (depending on whether either \code{WHO NREVSS} or \code{ILINet} |
|||
(or both) is chosen. |
|||
} |
|||
\details{ |
|||
A lookup table between HHS regions and their member states/territories |
|||
is provided in \code{\link{hhs_regions}}. |
|||
} |
|||
\note{ |
|||
There is often a noticeable delay when making the API request to the CDC. |
|||
This is not due to a large download size, but the time it takes for their |
|||
servers to crunch the data. Wrap the function call in \code{httr::with_verbose} |
|||
if you would like to see what's going on. |
|||
} |
|||
\examples{ |
|||
\dontrun{ |
|||
flu <- get_flu_data("hhs", 1:10, c("who", "ilinet"), years=2000:2014) |
|||
} |
|||
} |
|||
@ -1,44 +0,0 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/get_hosp_data.R |
|||
\name{get_hosp_data} |
|||
\alias{get_hosp_data} |
|||
\title{Retrieves influenza hospitalization statistics from the CDC} |
|||
\usage{ |
|||
get_hosp_data(area = "flusurvnet", age_group = "overall", |
|||
years = as.numeric(format(Sys.Date(), "\%Y")) - 1) |
|||
} |
|||
\arguments{ |
|||
\item{area}{one of "\code{flusurvnet}", "\code{eip}", "\code{ihsp}", or two |
|||
digit state abbreviation for an individual site. Exceptions are |
|||
New York - Albany ("\code{nya}") and New York - Rochester |
|||
("\code{nyr}")} |
|||
|
|||
|
|||
\item{age_group}{a vector of age groups to pull data for. Possible values are: |
|||
"\code{overall}", "\code{0-4y}", "\code{5-17y}, "\code{18-49y}, |
|||
"\code{50-64y}, "\code{65+y}".} |
|||
|
|||
\item{years}{a vector of years to retrieve data for (i.e. \code{2014} for CDC |
|||
flu season 2014-2015). Default value is the current year and all |
|||
\code{years} values should be >= \code{2009}} |
|||
} |
|||
\value{ |
|||
A single \code{data.frame}. |
|||
} |
|||
\description{ |
|||
Uses the data source from the |
|||
\href{https://gis.cdc.gov/GRASP/Fluview/FluHospRates.html}{CDC FluView} |
|||
and provides influenza hospitalization reporting data as a data frame. |
|||
} |
|||
\note{ |
|||
There is often a noticeable delay when making the API request to the CDC. |
|||
This is not due to a large download size, but the time it takes for their |
|||
servers to crunch the data. Wrap the function call in \code{httr::with_verbose} |
|||
if you would like to see what's going on. |
|||
} |
|||
\examples{ |
|||
\dontrun{ |
|||
# All of FluSurv-NET, 50-64 years old, 2010/11-2014/15 flu seasons |
|||
flu <- get_hosp_data("flusurvnet", "50-64y", years=2010:2014) |
|||
} |
|||
} |
|||
@ -1,41 +0,0 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/mortalty.r |
|||
\name{get_mortality_surveillance_data} |
|||
\alias{get_mortality_surveillance_data} |
|||
\title{Mortality Surveillance Data from the National Center for Health Statistics} |
|||
\usage{ |
|||
get_mortality_surveillance_data() |
|||
} |
|||
\value{ |
|||
a list of \code{tbl_df}s |
|||
} |
|||
\description{ |
|||
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. |
|||
} |
|||
\details{ |
|||
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. |
|||
} |
|||
\examples{ |
|||
\dontrun{ |
|||
get_mortality_surveillance_data() |
|||
} |
|||
} |
|||
\references{ |
|||
\url{https://www.cdc.gov/flu/weekly/nchs.htm} |
|||
} |
|||
@ -1,40 +0,0 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/get_state_data.r |
|||
\name{get_state_data} |
|||
\alias{get_state_data} |
|||
\title{Retrieves state/territory-level influenza statistics from the CDC} |
|||
\usage{ |
|||
get_state_data(years = as.numeric(format(Sys.Date(), "\%Y"))) |
|||
} |
|||
\arguments{ |
|||
\item{years}{a vector of years to retrieve data for (i.e. \code{2014} for CDC |
|||
flu season 2014-2015). Default value is the current year and all |
|||
\code{years} values should be >= \code{2008}} |
|||
} |
|||
\value{ |
|||
A \code{data.frame} of state-level data for the specified seasons |
|||
(also classed as \code{cdcstatedata}) |
|||
} |
|||
\description{ |
|||
Uses the data source from the CDC' State-levelFluView |
|||
\url{https://gis.cdc.gov/grasp/fluview/main.html} and provides state flu |
|||
reporting data as a single data frame.\cr |
|||
\cr |
|||
This function provides similar data to \code{\link{get_weekly_flu_report}} but |
|||
provides more metadata about the reporting sources and has access to more |
|||
historical infomation. |
|||
} |
|||
\note{ |
|||
There is often a noticeable delay when making the API request to the CDC. This |
|||
is not due to a large download size, but the time it takes for their |
|||
servers to crunch the data. Wrap the function call in \code{httr::with_verbose} |
|||
if you would like to see what's going on. |
|||
} |
|||
\examples{ |
|||
\dontrun{ |
|||
get_state_data(2014) |
|||
get_state_data(c(2013, 2014)) |
|||
get_state_data(2010:2014) |
|||
httr::with_verbose(get_state_data(2009:2015)) |
|||
} |
|||
} |
|||
@ -1,31 +0,0 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/get_weekly_flu_report.r |
|||
\name{get_weekly_flu_report} |
|||
\alias{get_weekly_flu_report} |
|||
\title{Retrieves (high-level) weekly influenza surveillance report from the CDC} |
|||
\usage{ |
|||
get_weekly_flu_report() |
|||
} |
|||
\value{ |
|||
\code{tbl_df} (also classed with \code{cdcweeklyreport}) with six |
|||
columns: \code{year}, \code{week_number}, \code{state}, \code{color}, |
|||
\code{label}, \code{subtitle} |
|||
} |
|||
\description{ |
|||
The CDC publishes a \href{https://www.cdc.gov/flu/weekly/usmap.htm}{weekly |
|||
influenza report} detailing high-level flu activity per-state. They also |
|||
publish a data file (see \code{References}) of historical report readings. |
|||
This function reads that XML file and produces a long \code{data_frame} |
|||
with the historical surveillance readings.\cr |
|||
\cr |
|||
This function provides similar data to \code{\link{get_state_data}} but without |
|||
the reporting source metadata and a limit on the historical flu information. |
|||
} |
|||
\examples{ |
|||
\dontrun{ |
|||
get_weekly_flu_report() |
|||
} |
|||
} |
|||
\references{ |
|||
\url{https://www.cdc.gov/flu/weekly/flureport.xml} |
|||
} |
|||
Loading…
Reference in new issue