36 changed files with 943 additions and 49 deletions
@ -0,0 +1,25 @@ |
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# Contributor Code of Conduct |
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|
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As contributors and maintainers of this project, we pledge to respect all people who |
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contribute through reporting issues, posting feature requests, updating documentation, |
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submitting pull requests or patches, and other activities. |
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|
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We are committed to making participation in this project a harassment-free experience for |
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everyone, regardless of level of experience, gender, gender identity and expression, |
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sexual orientation, disability, personal appearance, body size, race, ethnicity, age, or religion. |
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|
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Examples of unacceptable behavior by participants include the use of sexual language or |
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imagery, derogatory comments or personal attacks, trolling, public or private harassment, |
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insults, or other unprofessional conduct. |
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|
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Project maintainers have the right and responsibility to remove, edit, or reject comments, |
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commits, code, wiki edits, issues, and other contributions that are not aligned to this |
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Code of Conduct. Project maintainers who do not follow the Code of Conduct may be removed |
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from the project team. |
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|
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Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by |
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opening an issue or contacting one or more of the project maintainers. |
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|
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This Code of Conduct is adapted from the Contributor Covenant |
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(http:contributor-covenant.org), version 1.0.0, available at |
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http://contributor-covenant.org/version/1/0/0/ |
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@ -1,13 +1,24 @@ |
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# Generated by roxygen2: do not edit by hand |
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|
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export(agd_ipt) |
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export(cdc_coverage_map) |
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export(geographic_spread) |
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export(hospitalizations) |
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export(ili_weekly_activity_indicators) |
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export(ilinet) |
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export(pi_mortality) |
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export(state_data_providers) |
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export(surveillance_areas) |
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export(who_nrevss) |
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import(httr) |
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importFrom(dplyr,"%>%") |
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importFrom(dplyr,bind_rows) |
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importFrom(dplyr,filter) |
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importFrom(dplyr,left_join) |
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importFrom(dplyr,mutate) |
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importFrom(jsonlite,fromJSON) |
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importFrom(sf,st_read) |
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importFrom(stats,setNames) |
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importFrom(tools,file_path_sans_ext) |
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importFrom(utils,read.csv) |
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importFrom(utils,unzip) |
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@ -1,2 +1,28 @@ |
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0.1.0 |
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* Initial release |
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# cdcfluview 0.7.0 |
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|
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* The CDC changed most of their API endpoints to support a new HTML interface. |
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There are many breaking changes but also many new data endpoints. |
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|
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# cdcfluview 0.5.2 |
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|
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* Modified behavior of `get_flu_data()` to actually grab current flu season |
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year if a single year was specified and it is the current year and the |
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return is a 0 length data frame (fixes #7) |
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* Added code coverage tests for all API functions. |
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|
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# cdcfluview 0.5.1 |
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* Replaced `http` URLs with `https` as `http` ones no longer work (fixes #6) |
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* Fixed State data download (CDC changed the hidden API) |
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|
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# cdcfluview 0.5.0 |
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* Fixed issue with WHO data format change |
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* Added Mortality Surveillance Data retrieval function |
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* Switched to readr::read_csv() and since it handles column names |
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better this will break your scripts until you use the new |
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column names. |
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# cdcfluview 0.4.0 |
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* First CRAN release |
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@ -1,8 +1,15 @@ |
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# CDC U.S. region names to ID map |
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.region_map <- c(national=3, hhs=1, census=2, state=5) |
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|
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# CDC hospital surveillance region map |
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.hosp_surv_map <- c(flusurv=1, eip=2, ihsp=3) |
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# CDC hospital surveillance surveillance area name to internal pkg use map |
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.surv_map <- c(`FluSurv-NET`="flusurv", `EIP`="eip", `IHSP`="ihsp") |
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.surv_rev_map <- c(flusurv="FluSurv-NET", eip="EIP", ihsp="IHSP") |
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|
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# CDC P&I mortality GepID mapping |
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.geoid_map <- c(national="1", state="2", region="3") |
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|
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# Our bot's user-agent string |
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.cdcfluview_ua <- "Mozilla/5.0 (compatible; R-cdcvluview Bot/2.0; https://github.com/hrbrmstr/cdcfluview)" |
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.cdcfluview_ua <- "Mozilla/5.0 (compatible; R-cdcvluview Bot/2.0; https://github.com/hrbrmstr/cdcfluview)" |
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|
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# CDC Basemap |
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.cdc_basemap <- "https://gis.cdc.gov/grasp/fluview/FluView1References/data/US_States_w_PR_labels.json" |
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#' ... |
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#' Retrieve 'U.S'.' Flu Season Data from the 'CDC' 'FluView' Portal |
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#' |
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#' The U.S. Centers for Disease Control (CDC) maintains a portal |
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#' <http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html> for |
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#' accessing state, regional and national influenza statistics as well as |
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#' Mortality Surveillance Data. The Flash interface makes it difficult and |
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#' time-consuming to select and retrieve influenza data. This package |
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#' provides functions to access the data provided by the portal's underlying API. |
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#' |
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#' @md |
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#' @name cdcfluview |
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#' @docType package |
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#' @author Bob Rudis (bob@@rud.is) |
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#' @import httr |
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#' @importFrom tools file_path_sans_ext |
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#' @importFrom dplyr left_join bind_rows %>% |
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#' @importFrom dplyr left_join bind_rows mutate filter %>% |
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#' @importFrom jsonlite fromJSON |
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#' @importFrom stats setNames |
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#' @importFrom sf st_read |
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#' @importFrom utils read.csv unzip |
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NULL |
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#' Retrieve CDC U.S. Coverage Map |
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#' |
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#' The CDC FluView application uses a composite basemap of coverage areas |
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#' within the United States that elides and scales Alaska, Hawaii and |
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#' Puerto Rico and provides elided and scaled breakouts for New York City |
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#' and the District of Columbia.\cr |
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#' \cr |
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#' The basemap provides polygon identifiers by: |
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#' \cr |
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#' - `STATE_FIPS` |
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#' - `STATE_ABBR` |
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#' - `STATE_NAME` |
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#' - `HHS_Region` |
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#' - `FIPSTXT`) |
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#' \cr |
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#' This function retrieves the shapefile, projects to EPSG:5069 and |
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#' returns it as an `sf` (simple features) object. |
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#' |
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#' @md |
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#' @export |
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#' @examples \dontrun{ |
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#' plot(cdc_coverage_map()) |
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#' } |
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cdc_coverage_map <- function() { |
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xsf <- sf::st_read(.cdc_basemap, quiet=TRUE, stringsAsFactors=FALSE) |
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sf::st_crs(xsf) <- 4326 |
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sf::st_transform(xsf, 5069) |
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} |
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#' @title HHS Region Table |
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#' @description This dataset contains the names, numbers, regional offices for-, |
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#' and states/territories belonging to the (presently) 10 HHS U.S. |
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#' regions in "long" format. It consists of a \code{data.frame} |
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#' with the following columns: |
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#' |
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#' \itemize{ |
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#' \item \code{region}: the official HHS region name (e.g. "\code{Region 1}") |
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#' \item \code{region_number}: the associated region number |
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#' \item \code{regional_office}: the HHS regional office for the entire region |
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#' \item \code{state_or_territory}: state or territory belonging to the region |
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#' } |
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#' |
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#' @docType data |
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#' @keywords datasets |
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#' @name hhs_regions |
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#' |
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#' @references \url{https://www.hhs.gov/about/agencies/iea/regional-offices/index.html} |
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#' @usage data(hhs_regions) |
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#' @note Last updated 2015-08-09. |
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#' @format A data frame with 59 rows and 4 variables |
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NULL |
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#' @title Census Region Table |
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#' @description This dataset contains the states belonging to the (presently) 4 |
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#' U.S. Census regions in "long" format. It consists of a \code{data.frame} |
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#' with the following columns: |
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#' |
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#' \itemize{ |
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#' \item \code{region}: the official Census region name (e.g. "\code{East}") |
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#' \item \code{state}: state belonging to the region |
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#' } |
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#' |
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#' @docType data |
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#' @keywords datasets |
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#' @name census_regions |
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#' |
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#' @references \url{https://www.cdc.gov/std/stats12/images/CensusMap.png} |
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#' @usage data(census_regions) |
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#' @note Last updated 2015-08-09. |
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#' @format A data frame with 51 rows and 2 variables |
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NULL |
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#' State and Territorial Epidemiologists Reports of Geographic Spread of Influenza |
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#' |
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#' @export |
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#' @examples \dontrun{ |
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#' geographic_spread() |
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#' } |
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geographic_spread <- function() { |
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meta <- jsonlite::fromJSON("https://gis.cdc.gov/grasp/Flu8/GetPhase08InitApp?appVersion=Public") |
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meta$seasons$seasonid |
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httr::POST( |
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url = "https://gis.cdc.gov/grasp/Flu8/PostPhase08DownloadData", |
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httr::user_agent(.cdcfluview_ua), |
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httr::add_headers( |
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Origin = "https://gis.cdc.gov", |
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Accept = "application/json, text/plain, */*", |
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Referer = "https://gis.cdc.gov/grasp/fluview/FluView8.html" |
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), |
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encode = "json", |
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body = list( |
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AppVersion = "Public", |
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SeasonIDs = paste0(meta$seasons$seasonid, collapse=",") |
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), |
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httr::timeout(60), |
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httr::verbose() |
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) -> res |
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httr::stop_for_status(res) |
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res <- httr::content(res, as="parsed", flatten=TRUE) |
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xdf <- dplyr::bind_rows(res$datadownload) |
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xdf$weekend <- as.Date(xdf$weekend, format="%B-%d-%Y") |
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xdf |
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} |
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#' Retrieve weekly state-level ILI indicators per-state for a given season |
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#' |
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#' @md |
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#' @param season_start_year numeric; start year for flu season (e.g. 2017 for 2017-2018 season) |
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#' @references |
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#' - [ILI Activity Indicator Map Portal](https://gis.cdc.gov/grasp/fluview/main.html) |
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#' @note These statistics use the proportion of outpatient visits to healthcare providers |
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#' for influenza-like illness to measure the ILI activity level within a state. They do |
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#' not, however, measure the extent of geographic spread of flu within a state. Therefore, |
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#' outbreaks occurring in a single city could cause the state to display high activity levels.\cr |
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#' \cr |
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#' Data collected in ILINet may disproportionately represent certain populations within |
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#' a state, and therefore may not accurately depict the full picture of influenza activity |
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#' for the whole state.\cr |
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#' \cr |
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#' All summary statistics are based on either data collected in ILINet, or reports from |
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#' state and territorial epidemiologists. Differences in the summary data presented by |
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#' CDC and state health departments likely represent differing levels of data completeness |
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#' with data presented by the state likely being the more complete. |
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#' @export |
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#' @examples \dontrun{ |
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#' ili_weekly_activity_indicators(2016) |
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#' } |
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ili_weekly_activity_indicators <- function(season_start_year) { |
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jsonlite::fromJSON("https://gis.cdc.gov/grasp/fluView1/Phase1IniP") %>% |
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jsonlite::fromJSON() -> meta |
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season <- season_start_year - 1960 |
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res <- httr::GET(sprintf("https://gis.cdc.gov/grasp/fluView1/Phase1SeasonDataP/%s", |
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season)) |
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httr::stop_for_status(res) |
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res <- httr::content(res, as="parsed") |
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res <- jsonlite::fromJSON(res) |
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setNames( |
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meta$ili_intensity[,c("iliActivityid", "ili_activity_label", "legend")], |
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c("iliactivityid", "ili_activity_label", "ili_activity_group") |
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) -> iliact |
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dplyr::left_join(res$busdata, meta$stateinfo, "stateid") %>% |
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dplyr::left_join(res$mmwr, "mmwrid") %>% |
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dplyr::left_join(iliact, "iliactivityid") -> xdf |
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xdf <- xdf[,c("statename", "ili_activity_label", "ili_activity_group", |
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"statefips", "stateabbr", "weekend", "weeknumber", "year", "seasonid")] |
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xdf$statefips <- trimws(xdf$statefips) |
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xdf$stateabbr <- trimws(xdf$stateabbr) |
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xdf$weekend <- as.Date(xdf$weekend) |
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xdf$ili_activity_label <- factor(xdf$ili_activity_label, |
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levels=iliact$ili_activity_label) |
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class(xdf) <- c("tbl_df", "tbl", "data.frame") |
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xdf |
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} |
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#' Retrieve metadat about U.S. State CDC Provider Data |
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#' |
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#' @md |
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#' @export |
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#' @examples |
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#' state_data_providers() |
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state_data_providers <- function() { |
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jsonlite::fromJSON("https://gis.cdc.gov/grasp/fluView1/Phase1IniP") %>% |
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jsonlite::fromJSON() -> meta |
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state_info <- meta$stateinfo |
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state_info <- state_info[,c("statename", "statehealthdeptname", "url", "statewebsitename", "statefluphonenum")] |
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class(state_info) <- c("tbl_df", "tbl", "data.frame") |
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state_info |
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} |
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#' Pneumonia and Influenza Mortality Surveillance |
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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. NCHS collects death certificate data from state vital |
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#' statistics offices for virtually all deaths occurring in the United States. Pneumonia |
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#' and influenza (P&I) deaths are identified based on ICD-10 |
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#' multiple cause of death codes.\cr |
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#' \cr |
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#' NCHS Mortality Surveillance System data are presented by the week the death occurred |
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#' at the national, state, and HHS Region levels. Data on the percentage of deaths due |
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#' to P&I on a national level are released two weeks after the week of death to allow |
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#' for collection of enough data to produce a stable percentage. States and HHS regions |
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#' with less than 20% of the expected total deaths (average number of total deaths |
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#' reported by week during 2008-2012) will be marked as insufficient data. Collection |
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#' of complete data is not expected at the time of initial report, and a reliable |
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#' percentage of deaths due to P&I is not anticipated at the U.S. Department of Health |
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#' and Human Services region or state level within this two week period. The data for |
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#' earlier weeks are continually revised and the proportion of deaths due to P&I may |
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#' increase or decrease as new and updated death certificate data are received by NCHS.\cr |
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#' \cr |
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#' The seasonal baseline of P&I deaths is calculated using a periodic regression model |
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#' that incorporates a robust regression procedure applied to data from the previous |
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#' five years. An increase of 1.645 standard deviations above the seasonal baseline |
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#' of P&I deaths is considered the "epidemic threshold," i.e., the point at which |
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#' the observed proportion of deaths attributed to pneumonia or influenza was |
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#' significantly higher than would be expected at that time of the year in the |
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#' absence of substantial influenza-related mortality. Baselines and thresholds are |
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#' calculated at the national and regional level and by age group. |
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#' |
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#' @md |
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#' @param coverage_area coverage area for data (national, state or region) |
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#' @note Queries for "state" and "region" are not "instantaneous" and can near or over 30s retrieval delays. |
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#' @references |
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#' - [Pneumonia and Influenza Mortality Surveillance Portal](https://gis.cdc.gov/grasp/fluview/mortality.html) |
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#' @export |
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#' @examples \dontrun{ |
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#' ndf <- pi_mortality() |
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#' sdf <- pi_mortality("state") |
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#' rdf <- pi_mortality("region") |
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#' } |
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pi_mortality <- function(coverage_area=c("national", "state", "region")) { |
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coverage_area <- match.arg(tolower(coverage_area), choices = c("national", "state", "region")) |
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us_states <- read.csv("https://gis.cdc.gov/grasp/fluview/Flu7References/Data/USStates.csv", |
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stringsAsFactors=FALSE) |
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us_states <- setNames(us_states, c("region_name", "subgeoid", "state_abbr")) |
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us_states <- us_states[,c("region_name", "subgeoid")] |
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us_states$subgeoid <- as.character(us_states$subgeoid) |
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meta <- jsonlite::fromJSON("https://gis.cdc.gov/grasp/flu7/GetPhase07InitApp?appVersion=Public") |
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mapcode_df <- setNames(meta$nchs_mapcode[,c("mapcode", "description")], c("map_code", "callout")) |
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mapcode_df$map_code <- as.character(mapcode_df$map_code) |
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geo_df <- meta$nchs_geo_dim |
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geo_df$geoid <- as.character(geo_df$geoid) |
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age_df <- setNames(meta$nchs_ages, c("ageid", "age_label")) |
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age_df$ageid <- as.character(age_df$ageid) |
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mwmr_df <- meta$mmwr |
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mwmr_df$mmwrid <- as.character(mwmr_df$mmwrid) |
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mwmr_df <- setNames(mwmr_df, |
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c("mmwrid", "weekend", "mwmr_weeknumber", "weekstart", |
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"year", "yearweek", "mwmr_seasonid", "mwmr_label", "weekendlabel")) |
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sum_df <- meta$nchs_summary |
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sum_df$seasonid <- as.character(sum_df$seasonid) |
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sum_df$ageid <- as.character(sum_df$ageid) |
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sum_df$geoid <- as.character(sum_df$geoid) |
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httr::POST( |
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url = "https://gis.cdc.gov/grasp/flu7/PostPhase07DownloadData", |
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httr::user_agent(.cdcfluview_ua), |
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httr::add_headers( |
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Origin = "https://gis.cdc.gov", |
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Accept = "application/json, text/plain, */*", |
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Referer = "https://gis.cdc.gov/grasp/fluview/mortality.html" |
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), |
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encode = "json", |
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body = list( |
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AppVersion = "Public", |
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AreaParameters = list(list(ID=.geoid_map[coverage_area])), |
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SeasonsParameters = lapply(meta$seasons$seasonid, function(.x) { list(ID=as.integer(.x)) }), |
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AgegroupsParameters = list(list(ID="1")) |
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), |
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httr::timeout(60), |
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httr::verbose() |
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) -> res |
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httr::stop_for_status(res) |
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res <- httr::content(res, as="parsed", flatten=TRUE) |
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dplyr::bind_rows(res$seasons) %>% |
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dplyr::left_join(mapcode_df, "map_code") %>% |
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dplyr::left_join(geo_df, "geoid") %>% |
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dplyr::left_join(age_df, "ageid") %>% |
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dplyr::left_join(mwmr_df, "mmwrid") -> xdf |
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xdf <- dplyr::mutate(xdf, coverage_area = coverage_area) |
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if (coverage_area == "state") { |
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xdf <- dplyr::left_join(xdf, us_states, "subgeoid") |
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} else if (coverage_area == "region") { |
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xdf$region_name <- sprintf("Region %s", xdf$subgeoid) |
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} else { |
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xdf$region_name <- NA_character_ |
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} |
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xdf[,c("seasonid", "baseline", "threshold", "percent_pni", |
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"percent_complete", "number_influenza", "number_pneumonia", |
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"all_deaths", "Total_PnI", "weeknumber", "geo_description", |
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"age_label", "weekend", "weekstart", "year", "yearweek", |
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"coverage_area", "region_name", "callout")] -> xdf |
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|
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suppressWarnings(xdf$baseline <- to_num(xdf$baseline)) |
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suppressWarnings(xdf$threshold <- to_num(xdf$threshold)) |
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suppressWarnings(xdf$percent_pni <- to_num(xdf$percent_pni) / 100) |
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suppressWarnings(xdf$percent_complete <- to_num(xdf$percent_complete) / 100) |
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suppressWarnings(xdf$number_influenza <- to_num(xdf$number_influenza)) |
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suppressWarnings(xdf$number_pneumonia <- to_num(xdf$number_pneumonia)) |
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suppressWarnings(xdf$all_deaths <- to_num(xdf$all_deaths)) |
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suppressWarnings(xdf$Total_PnI <- to_num(xdf$Total_PnI)) |
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suppressWarnings(xdf$weekend <- as.Date(xdf$weekend)) |
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suppressWarnings(xdf$weekstart <- as.Date(xdf$weekstart)) |
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|
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xdf <- .mcga(xdf) |
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xdf |
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|
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} |
|||
|
|||
|
|||
@ -0,0 +1,11 @@ |
|||
# this is only used during active development phases before/after CRAN releases |
|||
|
|||
.onAttach <- function(...) { |
|||
|
|||
if (!interactive()) return() |
|||
|
|||
packageStartupMessage(paste0("cdcfluview is under *active* development. ", |
|||
"There are *MASSIVE* breaking changes*. ", |
|||
"See https://github.com/hrbrmstr/cdcfluview for info/news.")) |
|||
|
|||
} |
|||
@ -0,0 +1,101 @@ |
|||
|
|||
[](https://cran.r-project.org/package=cdcfluview) |
|||
[](https://travis-ci.org/hrbrmstr/cdcfluview) |
|||
[](https://codecov.io/github/hrbrmstr/cdcfluview?branch=master) |
|||
|
|||
I M P O R T A N T |
|||
================= |
|||
|
|||
The CDC migrated to a new non-Flash portal and back-end APIs changed. |
|||
This is a complete reimagining of the package and — as such — all your |
|||
code is going to break. Please use GitHub issues to identify previous |
|||
API functionality you would like ported over. There’s a [release |
|||
candidate for |
|||
0.5.2](https://github.com/hrbrmstr/cdcfluview/releases/tag/v0.5.2) which |
|||
uses the old API but it likely to break in the near future given the |
|||
changes to the hidden API. You can do what with |
|||
`devtools::install_github("hrbrmstr/cdcfluview", ref="58c172b")`. |
|||
|
|||
All folks providing feedback, code or suggestions will be added to the |
|||
DESCRIPTION file. Please include how you would prefer to be cited in any |
|||
issues you file. |
|||
|
|||
If there’s a particular data set from |
|||
<https://www.cdc.gov/flu/weekly/fluviewinteractive.htm> that you want |
|||
and that isn’t in the package, please file it as an issue and be as |
|||
specific as you can (screen shot if possible). |
|||
|
|||
:mask: cdcfluview |
|||
================= |
|||
|
|||
Retrieve U.S. Flu Season Data from the CDC FluView Portal |
|||
|
|||
Description |
|||
----------- |
|||
|
|||
The U.S. Centers for Disease Control (CDC) maintains a portal |
|||
<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. |
|||
|
|||
What’s Inside The Tin |
|||
--------------------- |
|||
|
|||
The following functions are implemented: |
|||
|
|||
- `agd_ipt`: Age Group Distribution of Influenza Positive Tests |
|||
Reported by Public Health Laboratories |
|||
- `cdcfluview`: Tools to Work with the ‘CDC’ ‘FluView’ ‘API’ |
|||
- `cdc_coverage_map`: Retrieve CDC U.S. Coverage Map |
|||
- `geographic_spread`: State and Territorial Epidemiologists Reports |
|||
of Geographic Spread of Influenza |
|||
- `hospitalizations`: Laboratory-Confirmed Influenza Hospitalizations |
|||
- `ilinet`: Retrieve ILINet Surveillance Data |
|||
- `ili_weekly_activity_indicators`: Retrieve weekly state-level ILI |
|||
indicators per-state for a given season |
|||
- `pi_mortality`: Pneumonia and Influenza Mortality Surveillance |
|||
- `state_data_providers`: Retrieve metadat about U.S. State CDC |
|||
Provider Data |
|||
- `surveillance_areas`: Retrieve a list of valid sub-regions for each |
|||
surveillance area. |
|||
- `who_nrevss`: Retrieve WHO/NREVSS Surveillance Data |
|||
|
|||
The following data sets are included: |
|||
|
|||
- `hhs_regions` HHS Region Table (a data frame with 59 rows and 4 |
|||
variables) |
|||
- `census_regions` Census Region Table (a data frame with 51 rows and |
|||
2 variables) |
|||
|
|||
Installation |
|||
------------ |
|||
|
|||
``` r |
|||
devtools::install_github("hrbrmstr/cdcfluview") |
|||
``` |
|||
|
|||
Usage |
|||
----- |
|||
|
|||
``` r |
|||
library(cdcfluview) |
|||
|
|||
# current verison |
|||
packageVersion("cdcfluview") |
|||
``` |
|||
|
|||
## [1] '0.7.0' |
|||
|
|||
### EXAMPLES COMING SOON |
|||
|
|||
Code of Conduct |
|||
--------------- |
|||
|
|||
Please note that this project is released with a [Contributor Code of |
|||
Conduct](CONDUCT.md). By participating in this project you agree to |
|||
abide by its terms. |
|||
@ -0,0 +1 @@ |
|||
comment: false |
|||
@ -0,0 +1,37 @@ |
|||
hhs_regions <- read.table(text="region;region_number;regional_office;state_or_territory |
|||
Region 1;1;Boston;Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont |
|||
Region 2;2;New York;New Jersey, New York, Puerto Rico, Virgin Islands |
|||
Region 3;3;Philadelphia;Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia |
|||
Region 4;4;Atlanta;Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee |
|||
Region 5;5;Chicago;Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin |
|||
Region 6;6;Dallas;Arkansas, Louisiana, New Mexico, Oklahoma, Texas |
|||
Region 7;7;Kansas City;Iowa, Kansas, Missouri, Nebraska |
|||
Region 8;8;Denver;Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming |
|||
Region 9;9;San Francisco;Arizona, California, Hawaii, Nevada, American Samoa, Commonwealth of the Northern Mariana Islands, Federated States of Micronesia, Guam, Marshall Islands, Republic of Palau |
|||
Region 10;10;Seattle;Alaska, Idaho, Oregon, Washington", sep=";", stringsAsFactors=FALSE, header=TRUE) |
|||
|
|||
library(stringr) |
|||
do.call(rbind.data.frame, lapply(1:nrow(hhs_regions), function(i) { |
|||
x <- hhs_regions[i,] |
|||
rownames(x) <- NULL |
|||
out <- data.frame(x[, c(1:3)], |
|||
str_split(x$state_or_territory, ", ")[1], |
|||
stringsAsFactors=FALSE) |
|||
colnames(out) <- c("region", "region_number", "regional_office", "state_or_territory") |
|||
out |
|||
})) -> hhs_regions |
|||
|
|||
str(hhs_regions) |
|||
|
|||
library(rvest) |
|||
library(magrittr) |
|||
|
|||
pg <- html("http://www.cdc.gov/std/stats11/census.htm") |
|||
pg %>% html_table() %>% extract2(1) %>% as.list -> cens |
|||
do.call(rbind.data.frame, lapply(names(cens), function(x) { |
|||
data.frame(region=x, |
|||
state=cens[[x]][cens[[x]]!=""], |
|||
stringsAsFactors=FALSE) |
|||
})) -> census_regions |
|||
|
|||
devtools::use_data(hhs_regions, census_regions, overwrite=TRUE) |
|||
Binary file not shown.
Binary file not shown.
@ -0,0 +1,32 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/coverage-map.r |
|||
\name{cdc_coverage_map} |
|||
\alias{cdc_coverage_map} |
|||
\title{Retrieve CDC U.S. Coverage Map} |
|||
\usage{ |
|||
cdc_coverage_map() |
|||
} |
|||
\description{ |
|||
The CDC FluView application uses a composite basemap of coverage areas |
|||
within the United States that elides and scales Alaska, Hawaii and |
|||
Puerto Rico and provides elided and scaled breakouts for New York City |
|||
and the District of Columbia.\cr |
|||
\cr |
|||
The basemap provides polygon identifiers by: |
|||
\cr |
|||
\itemize{ |
|||
\item \code{STATE_FIPS} |
|||
\item \code{STATE_ABBR} |
|||
\item \code{STATE_NAME} |
|||
\item \code{HHS_Region} |
|||
\item \code{FIPSTXT}) |
|||
\cr |
|||
This function retrieves the shapefile, projects to EPSG:5069 and |
|||
returns it as an \code{sf} (simple features) object. |
|||
} |
|||
} |
|||
\examples{ |
|||
\dontrun{ |
|||
plot(cdc_coverage_map()) |
|||
} |
|||
} |
|||
@ -0,0 +1,27 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/datasets.r |
|||
\docType{data} |
|||
\name{census_regions} |
|||
\alias{census_regions} |
|||
\title{Census Region Table} |
|||
\format{A data frame with 51 rows and 2 variables} |
|||
\usage{ |
|||
data(census_regions) |
|||
} |
|||
\description{ |
|||
This dataset contains the states belonging to the (presently) 4 |
|||
U.S. Census regions in "long" format. It consists of a \code{data.frame} |
|||
with the following columns: |
|||
|
|||
\itemize{ |
|||
\item \code{region}: the official Census region name (e.g. "\code{East}") |
|||
\item \code{state}: state belonging to the region |
|||
} |
|||
} |
|||
\note{ |
|||
Last updated 2015-08-09. |
|||
} |
|||
\references{ |
|||
\url{https://www.cdc.gov/std/stats12/images/CensusMap.png} |
|||
} |
|||
\keyword{datasets} |
|||
@ -0,0 +1,16 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/geographic-spread.R |
|||
\name{geographic_spread} |
|||
\alias{geographic_spread} |
|||
\title{State and Territorial Epidemiologists Reports of Geographic Spread of Influenza} |
|||
\usage{ |
|||
geographic_spread() |
|||
} |
|||
\description{ |
|||
State and Territorial Epidemiologists Reports of Geographic Spread of Influenza |
|||
} |
|||
\examples{ |
|||
\dontrun{ |
|||
geographic_spread() |
|||
} |
|||
} |
|||
@ -0,0 +1,30 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/datasets.r |
|||
\docType{data} |
|||
\name{hhs_regions} |
|||
\alias{hhs_regions} |
|||
\title{HHS Region Table} |
|||
\format{A data frame with 59 rows and 4 variables} |
|||
\usage{ |
|||
data(hhs_regions) |
|||
} |
|||
\description{ |
|||
This dataset contains the names, numbers, regional offices for-, |
|||
and states/territories belonging to the (presently) 10 HHS U.S. |
|||
regions in "long" format. It consists of a \code{data.frame} |
|||
with the following columns: |
|||
|
|||
\itemize{ |
|||
\item \code{region}: the official HHS region name (e.g. "\code{Region 1}") |
|||
\item \code{region_number}: the associated region number |
|||
\item \code{regional_office}: the HHS regional office for the entire region |
|||
\item \code{state_or_territory}: state or territory belonging to the region |
|||
} |
|||
} |
|||
\note{ |
|||
Last updated 2015-08-09. |
|||
} |
|||
\references{ |
|||
\url{https://www.hhs.gov/about/agencies/iea/regional-offices/index.html} |
|||
} |
|||
\keyword{datasets} |
|||
@ -0,0 +1,39 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/ili-weekly-state.r |
|||
\name{ili_weekly_activity_indicators} |
|||
\alias{ili_weekly_activity_indicators} |
|||
\title{Retrieve weekly state-level ILI indicators per-state for a given season} |
|||
\usage{ |
|||
ili_weekly_activity_indicators(season_start_year) |
|||
} |
|||
\arguments{ |
|||
\item{season_start_year}{numeric; start year for flu season (e.g. 2017 for 2017-2018 season)} |
|||
} |
|||
\description{ |
|||
Retrieve weekly state-level ILI indicators per-state for a given season |
|||
} |
|||
\note{ |
|||
These statistics use the proportion of outpatient visits to healthcare providers |
|||
for influenza-like illness to measure the ILI activity level within a state. They do |
|||
not, however, measure the extent of geographic spread of flu within a state. Therefore, |
|||
outbreaks occurring in a single city could cause the state to display high activity levels.\cr |
|||
\cr |
|||
Data collected in ILINet may disproportionately represent certain populations within |
|||
a state, and therefore may not accurately depict the full picture of influenza activity |
|||
for the whole state.\cr |
|||
\cr |
|||
All summary statistics are based on either data collected in ILINet, or reports from |
|||
state and territorial epidemiologists. Differences in the summary data presented by |
|||
CDC and state health departments likely represent differing levels of data completeness |
|||
with data presented by the state likely being the more complete. |
|||
} |
|||
\examples{ |
|||
\dontrun{ |
|||
ili_weekly_activity_indicators(2016) |
|||
} |
|||
} |
|||
\references{ |
|||
\itemize{ |
|||
\item \href{https://gis.cdc.gov/grasp/fluview/main.html}{ILI Activity Indicator Map Portal} |
|||
} |
|||
} |
|||
@ -0,0 +1,54 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/pi-mortality.r |
|||
\name{pi_mortality} |
|||
\alias{pi_mortality} |
|||
\title{Pneumonia and Influenza Mortality Surveillance} |
|||
\usage{ |
|||
pi_mortality(coverage_area = c("national", "state", "region")) |
|||
} |
|||
\arguments{ |
|||
\item{coverage_area}{coverage area for data (national, state or region)} |
|||
} |
|||
\description{ |
|||
The National Center for Health Statistics (NCHS) collects and disseminates the Nation's |
|||
official vital statistics. NCHS collects death certificate data from state vital |
|||
statistics offices for virtually all deaths occurring in the United States. Pneumonia |
|||
and influenza (P&I) deaths are identified based on ICD-10 |
|||
multiple cause of death codes.\cr |
|||
\cr |
|||
NCHS Mortality Surveillance System data are presented by the week the death occurred |
|||
at the national, state, and HHS Region levels. Data on the percentage of deaths due |
|||
to P&I on a national level are released two weeks after the week of death to allow |
|||
for collection of enough data to produce a stable percentage. States and HHS regions |
|||
with less than 20% of the expected total deaths (average number of total deaths |
|||
reported by week during 2008-2012) will be marked as insufficient data. Collection |
|||
of complete data is not expected at the time of initial report, and a reliable |
|||
percentage of deaths due to P&I is not anticipated at the U.S. Department of Health |
|||
and Human Services region or state level within this two week period. The data for |
|||
earlier weeks are continually revised and the proportion of deaths due to P&I may |
|||
increase or decrease as new and updated death certificate data are received by NCHS.\cr |
|||
\cr |
|||
The seasonal baseline of P&I deaths is calculated using a periodic regression model |
|||
that incorporates a robust regression procedure applied to data from the previous |
|||
five years. An increase of 1.645 standard deviations above the seasonal baseline |
|||
of P&I deaths is considered the "epidemic threshold," i.e., the point at which |
|||
the observed proportion of deaths attributed to pneumonia or influenza was |
|||
significantly higher than would be expected at that time of the year in the |
|||
absence of substantial influenza-related mortality. Baselines and thresholds are |
|||
calculated at the national and regional level and by age group. |
|||
} |
|||
\note{ |
|||
Queries for "state" and "region" are not "instantaneous" and can near or over 30s retrieval delays. |
|||
} |
|||
\examples{ |
|||
\dontrun{ |
|||
ndf <- pi_mortality() |
|||
sdf <- pi_mortality("state") |
|||
rdf <- pi_mortality("region") |
|||
} |
|||
} |
|||
\references{ |
|||
\itemize{ |
|||
\item \href{https://gis.cdc.gov/grasp/fluview/mortality.html}{Pneumonia and Influenza Mortality Surveillance Portal} |
|||
} |
|||
} |
|||
@ -0,0 +1,14 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/ili-weekly-state.r |
|||
\name{state_data_providers} |
|||
\alias{state_data_providers} |
|||
\title{Retrieve metadat about U.S. State CDC Provider Data} |
|||
\usage{ |
|||
state_data_providers() |
|||
} |
|||
\description{ |
|||
Retrieve metadat about U.S. State CDC Provider Data |
|||
} |
|||
\examples{ |
|||
state_data_providers() |
|||
} |
|||
@ -0,0 +1,14 @@ |
|||
% Generated by roxygen2: do not edit by hand |
|||
% Please edit documentation in R/hospital.r |
|||
\name{surveillance_areas} |
|||
\alias{surveillance_areas} |
|||
\title{Retrieve a list of valid sub-regions for each surveillance area.} |
|||
\usage{ |
|||
surveillance_areas() |
|||
} |
|||
\description{ |
|||
Retrieve a list of valid sub-regions for each surveillance area. |
|||
} |
|||
\examples{ |
|||
surveillance_areas() |
|||
} |
|||
Loading…
Reference in new issue