new API coverage & CRAN checks

.Rbuildignore

@@ -8,3 +8,16 @@
 ^\.codecov\.yml$
 ^README_files$
 ^doc$
+^CONDUCT\.md$
+^codecov\.yml$
+^.*\.Rproj$
+^\.Rproj\.user$
+^\.travis\.yml$
+^.*md$
+^crunch/
+^crunch/.*
+^README_files/
+^README_files/.*
+^README-.*
+^cran-comments\.md$
+^codecov\.yml$

.travis.yml

@@ -1,31 +1,16 @@
-language: r
-
-warnings_are_errors: true
+# R for travis: see documentation at https://docs.travis-ci.com/user/languages/r
 
+language: R
 sudo: required
-
 cache: packages
 
+apt_packages:
+  - libv8-dev
+
 r:
  - oldrel
  - release
  - devel
 
-apt_packages:
-  - libv8-dev
-  - xclip
-
-env:
- global:
-   - CRAN: http://cran.rstudio.com
-
 after_success:
   - Rscript -e 'covr::codecov()'
-
-notifications:
-  email:
-    - bob@rud.is
-  irc:
-    channels:
-      - "104.236.112.222#builds"
-    nick: travisci

CONDUCT.md

@@ -0,0 +1,25 @@
+# Contributor Code of Conduct
+
+As contributors and maintainers of this project, we pledge to respect all people who 
+contribute through reporting issues, posting feature requests, updating documentation,
+submitting pull requests or patches, and other activities.
+
+We are committed to making participation in this project a harassment-free experience for
+everyone, regardless of level of experience, gender, gender identity and expression,
+sexual orientation, disability, personal appearance, body size, race, ethnicity, age, or religion.
+
+Examples of unacceptable behavior by participants include the use of sexual language or
+imagery, derogatory comments or personal attacks, trolling, public or private harassment,
+insults, or other unprofessional conduct.
+
+Project maintainers have the right and responsibility to remove, edit, or reject comments,
+commits, code, wiki edits, issues, and other contributions that are not aligned to this 
+Code of Conduct. Project maintainers who do not follow the Code of Conduct may be removed 
+from the project team.
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by 
+opening an issue or contacting one or more of the project maintainers.
+
+This Code of Conduct is adapted from the Contributor Covenant 
+(http:contributor-covenant.org), version 1.0.0, available at 
+http://contributor-covenant.org/version/1/0/0/

DESCRIPTION

@@ -1,18 +1,25 @@
 Package: cdcfluview
 Type: Package
-Title: cdcfluview title goes here otherwise CRAN checks fail
-Version: 0.1.0
+Title: Retrieve 'U.S'.' Flu Season Data from the 'CDC' 'FluView' Portal
+Version: 0.7.0
 Date: 2017-11-04
 Authors@R: c(
     person("Bob", "Rudis", email = "bob@rud.is", role = c("aut", "cre"), 
-           comment = c(ORCID = "0000-0001-5670-2640"))
+           comment = c(ORCID = "0000-0001-5670-2640")),
+    person("Craig", "McGowan", email = "mcgowan.cj@gmail.com", role = "ctb")
   )
 Author: Bob Rudis (bob@rud.is)
 Maintainer: Bob Rudis <bob@rud.is>
-Description: A good description goes here otherwise CRAN checks fail.
+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.
 URL: https://github.com/hrbrmstr/cdcfluview
 BugReports: https://github.com/hrbrmstr/cdcfluview/issues
 License: MIT + file LICENSE
+LazyData: true
 Suggests:
     testthat,
     covr
@@ -23,5 +30,7 @@ Imports:
     tools,
     dplyr,
     jsonlite,
-    stats
+    stats,
+    utils,
+    sf
 RoxygenNote: 6.0.1

NAMESPACE

@@ -1,13 +1,24 @@
 # Generated by roxygen2: do not edit by hand
 
 export(agd_ipt)
+export(cdc_coverage_map)
+export(geographic_spread)
 export(hospitalizations)
+export(ili_weekly_activity_indicators)
 export(ilinet)
+export(pi_mortality)
+export(state_data_providers)
+export(surveillance_areas)
 export(who_nrevss)
 import(httr)
 importFrom(dplyr,"%>%")
 importFrom(dplyr,bind_rows)
+importFrom(dplyr,filter)
 importFrom(dplyr,left_join)
+importFrom(dplyr,mutate)
 importFrom(jsonlite,fromJSON)
+importFrom(sf,st_read)
 importFrom(stats,setNames)
 importFrom(tools,file_path_sans_ext)
+importFrom(utils,read.csv)
+importFrom(utils,unzip)

NEWS.md

@@ -1,2 +1,28 @@
-0.1.0 
-* Initial release
+# cdcfluview 0.7.0
+
+* The CDC changed most of their API endpoints to support a new HTML interface.
+  There are many breaking changes but also many new data endpoints.
+
+# cdcfluview 0.5.2
+
+* Modified behavior of `get_flu_data()` to actually grab current flu season
+  year if a single year was specified and it is the current year and the
+  return is a 0 length data frame (fixes #7)
+* Added code coverage tests for all API functions.
+  
+# cdcfluview 0.5.1
+
+* Replaced `http` URLs with `https` as `http` ones no longer work (fixes #6)
+* Fixed State data download (CDC changed the hidden API)
+
+# cdcfluview 0.5.0
+
+* Fixed issue with WHO data format change
+* Added Mortality Surveillance Data retrieval function
+* Switched to readr::read_csv() and since it handles column names
+  better this will break your scripts until you use the new
+  column names.
+
+# cdcfluview 0.4.0
+
+* First CRAN release

R/aaa.R

@@ -1,8 +1,15 @@
 # CDC U.S. region names to ID map
 .region_map <- c(national=3, hhs=1, census=2, state=5)
 
-# CDC hospital surveillance region map
-.hosp_surv_map <- c(flusurv=1, eip=2, ihsp=3)
+# CDC hospital surveillance surveillance area name to internal pkg use map
+.surv_map <- c(`FluSurv-NET`="flusurv", `EIP`="eip", `IHSP`="ihsp")
+.surv_rev_map <- c(flusurv="FluSurv-NET", eip="EIP", ihsp="IHSP")
+
+# CDC P&I mortality GepID mapping
+.geoid_map <- c(national="1", state="2", region="3")
 
 # Our bot's user-agent string
-.cdcfluview_ua <- "Mozilla/5.0 (compatible; R-cdcvluview Bot/2.0; https://github.com/hrbrmstr/cdcfluview)"
+.cdcfluview_ua <- "Mozilla/5.0 (compatible; R-cdcvluview Bot/2.0; https://github.com/hrbrmstr/cdcfluview)"
+
+# CDC Basemap
+.cdc_basemap <- "https://gis.cdc.gov/grasp/fluview/FluView1References/data/US_States_w_PR_labels.json"

R/agd-ipt.r

@@ -8,6 +8,9 @@
 #' - [CDC FluView Portal](https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html)
 #' - [AGD IPT Portal](https://gis.cdc.gov/grasp/fluview/flu_by_age_virus.html)
 #' @export
+#' @examples  \dontrun{
+#' agd_ipt()
+#' }
 agd_ipt <- function() {
   httr::GET(
     url = "https://gis.cdc.gov/grasp/fluView6/GetFlu6AllDataP",

R/cdcfluview-package.R

@@ -1,11 +1,21 @@
-#' ...
+#' Retrieve 'U.S'.' Flu Season Data from the 'CDC' 'FluView' Portal
 #'
+#' 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.
+#'
+#' @md
 #' @name cdcfluview
 #' @docType package
 #' @author Bob Rudis (bob@@rud.is)
 #' @import httr
 #' @importFrom tools file_path_sans_ext
-#' @importFrom dplyr left_join bind_rows %>%
+#' @importFrom dplyr left_join bind_rows mutate filter %>%
 #' @importFrom jsonlite fromJSON
 #' @importFrom stats setNames
+#' @importFrom sf st_read
+#' @importFrom utils read.csv unzip
 NULL

R/coverage-map.r

@@ -0,0 +1,28 @@
+#' Retrieve CDC U.S. Coverage Map
+#'
+#' 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
+#' - `STATE_FIPS`
+#' - `STATE_ABBR`
+#' - `STATE_NAME`
+#' - `HHS_Region`
+#' - `FIPSTXT`)
+#' \cr
+#' This function retrieves the shapefile, projects to EPSG:5069 and
+#' returns it as an `sf` (simple features) object.
+#'
+#' @md
+#' @export
+#' @examples \dontrun{
+#' plot(cdc_coverage_map())
+#' }
+cdc_coverage_map <- function() {
+  xsf <- sf::st_read(.cdc_basemap, quiet=TRUE, stringsAsFactors=FALSE)
+  sf::st_crs(xsf) <- 4326
+  sf::st_transform(xsf, 5069)
+}

R/datasets.r

@@ -0,0 +1,42 @@
+#' @title HHS Region Table
+#' @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
+#' }
+#'
+#' @docType data
+#' @keywords datasets
+#' @name hhs_regions
+#'
+#' @references \url{https://www.hhs.gov/about/agencies/iea/regional-offices/index.html}
+#' @usage data(hhs_regions)
+#' @note Last updated 2015-08-09.
+#' @format A data frame with 59 rows and 4 variables
+NULL
+
+#' @title Census Region Table
+#' @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
+#' }
+#'
+#' @docType data
+#' @keywords datasets
+#' @name census_regions
+#'
+#' @references \url{https://www.cdc.gov/std/stats12/images/CensusMap.png}
+#' @usage data(census_regions)
+#' @note Last updated 2015-08-09.
+#' @format A data frame with 51 rows and 2 variables
+NULL

R/geographic-spread.R

@@ -0,0 +1,38 @@
+#' State and Territorial Epidemiologists Reports of Geographic Spread of Influenza
+#'
+#' @export
+#' @examples \dontrun{
+#' geographic_spread()
+#' }
+geographic_spread <- function() {
+
+  meta <- jsonlite::fromJSON("https://gis.cdc.gov/grasp/Flu8/GetPhase08InitApp?appVersion=Public")
+  meta$seasons$seasonid
+
+  httr::POST(
+    url = "https://gis.cdc.gov/grasp/Flu8/PostPhase08DownloadData",
+    httr::user_agent(.cdcfluview_ua),
+    httr::add_headers(
+      Origin = "https://gis.cdc.gov",
+      Accept = "application/json, text/plain, */*",
+      Referer = "https://gis.cdc.gov/grasp/fluview/FluView8.html"
+    ),
+    encode = "json",
+    body = list(
+      AppVersion = "Public",
+      SeasonIDs = paste0(meta$seasons$seasonid, collapse=",")
+    ),
+    httr::timeout(60),
+    httr::verbose()
+  ) -> res
+
+  httr::stop_for_status(res)
+
+  res <- httr::content(res, as="parsed", flatten=TRUE)
+
+  xdf <- dplyr::bind_rows(res$datadownload)
+  xdf$weekend <- as.Date(xdf$weekend, format="%B-%d-%Y")
+
+  xdf
+
+}

R/hospital.r

@@ -1,20 +1,38 @@
 #' Laboratory-Confirmed Influenza Hospitalizations
 #'
+#' @md
 #' @param surveillance_area one of "`flusurv`", "`eip`", or "`ihsp`"
+#' @param region Using "`all`" mimics selecting "Entire Network" from the
+#'        CDC FluView application drop down. Individual regions for each
+#'        surveillance area can also be selected. Use [surveillance_areas()] to
+#'        see a list of valid sub-regions for each surveillance area.
 #' @references
 #' - [Hospital Portal](https://gis.cdc.gov/GRASP/Fluview/FluHospRates.html)
 #' @export
-#' @examples
+#' @examples \dontrun{
 #' hosp_fs <- hospitalizations("flusurv")
 #' hosp_eip <- hospitalizations("eip")
 #' hosp_ihsp <- hospitalizations("ihsp")
-hospitalizations <- function(surveillance_area=c("flusurv", "eip", "ihsp")) {
-
-  surveillance_area <- match.arg(tolower(surveillance_area), c("flusurv", "eip", "ihsp"))
+#' }
+hospitalizations <- function(surveillance_area=c("flusurv", "eip", "ihsp"),
+                             region="all") {
 
-  network_id <- .hosp_surv_map[surveillance_area]
+  sarea <- match.arg(tolower(surveillance_area), choices = c("flusurv", "eip", "ihsp"))
+  sarea <- .surv_rev_map[sarea]
 
   meta <- jsonlite::fromJSON("https://gis.cdc.gov/GRASP/Flu3/GetPhase03InitApp?appVersion=Public")
+  areas <- setNames(meta$catchments[,c("networkid", "name", "area", "catchmentid")],
+                    c("networkid", "surveillance_area", "region", "id"))
+
+  reg <- region
+  if (reg == "all") reg <- "Entire Network"
+
+  tgt <- dplyr::filter(areas, (surveillance_area == sarea) & (region == reg))
+
+  if (nrow(tgt) == 0) {
+    stop("Region not found. Use `surveillance_areas()` to see a list of valid inputs.",
+         call.=FALSE)
+  }
 
   httr::POST(
     url = "https://gis.cdc.gov/GRASP/Flu3/PostPhase03GetData",
@@ -27,9 +45,9 @@ hospitalizations <- function(surveillance_area=c("flusurv", "eip", "ihsp")) {
     encode = "json",
     body = list(
       appversion = "Public",
-      networkid = network_id,
-      cacthmentid = "22"
-      ),
+      networkid = tgt$networkid,
+      cacthmentid = tgt$id
+    ),
     httr::verbose()
   ) -> res
 
@@ -62,6 +80,23 @@ hospitalizations <- function(surveillance_area=c("flusurv", "eip", "ihsp")) {
 
   dplyr::left_join(xdf, mmwr_df, c("mmwrid", "weeknumber")) %>%
     dplyr::left_join(age_df, "age") %>%
-    dplyr::left_join(sea_df, "seasonid")
+    dplyr::left_join(sea_df, "seasonid") %>%
+    dplyr::mutate(
+      surveillance_area = sarea,
+      region = reg
+    )
 
 }
+
+#' Retrieve a list of valid sub-regions for each surveillance area.
+#'
+#' @md
+#' @export
+#' @examples
+#' surveillance_areas()
+surveillance_areas <- function() {
+  meta <- jsonlite::fromJSON("https://gis.cdc.gov/GRASP/Flu3/GetPhase03InitApp?appVersion=Public")
+  xdf <- setNames(meta$catchments[,c("name", "area")], c("surveillance_area", "region"))
+  xdf$surveillance_area <- .surv_map[xdf$surveillance_area]
+  xdf
+}

R/ili-weekly-state.r

@@ -0,0 +1,80 @@
+#' Retrieve weekly state-level ILI indicators per-state for a given season
+#'
+#' @md
+#' @param season_start_year numeric; start year for flu season (e.g. 2017 for 2017-2018 season)
+#' @references
+#' - [ILI Activity Indicator Map Portal](https://gis.cdc.gov/grasp/fluview/main.html)
+#' @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.
+#' @export
+#' @examples \dontrun{
+#' ili_weekly_activity_indicators(2016)
+#' }
+ili_weekly_activity_indicators <- function(season_start_year) {
+
+  jsonlite::fromJSON("https://gis.cdc.gov/grasp/fluView1/Phase1IniP") %>%
+    jsonlite::fromJSON() -> meta
+
+  season <- season_start_year - 1960
+
+  res <- httr::GET(sprintf("https://gis.cdc.gov/grasp/fluView1/Phase1SeasonDataP/%s",
+                           season))
+
+  httr::stop_for_status(res)
+
+  res <- httr::content(res, as="parsed")
+  res <- jsonlite::fromJSON(res)
+
+  setNames(
+    meta$ili_intensity[,c("iliActivityid", "ili_activity_label", "legend")],
+    c("iliactivityid", "ili_activity_label", "ili_activity_group")
+  ) -> iliact
+
+  dplyr::left_join(res$busdata, meta$stateinfo, "stateid") %>%
+    dplyr::left_join(res$mmwr, "mmwrid") %>%
+    dplyr::left_join(iliact, "iliactivityid") -> xdf
+
+  xdf <- xdf[,c("statename", "ili_activity_label", "ili_activity_group",
+                "statefips", "stateabbr", "weekend", "weeknumber", "year", "seasonid")]
+
+  xdf$statefips <- trimws(xdf$statefips)
+  xdf$stateabbr <- trimws(xdf$stateabbr)
+  xdf$weekend <- as.Date(xdf$weekend)
+  xdf$ili_activity_label <- factor(xdf$ili_activity_label,
+                                   levels=iliact$ili_activity_label)
+
+  class(xdf) <- c("tbl_df", "tbl", "data.frame")
+
+  xdf
+
+}
+
+#' Retrieve metadat about U.S. State CDC Provider Data
+#'
+#' @md
+#' @export
+#' @examples
+#' state_data_providers()
+state_data_providers <- function() {
+
+  jsonlite::fromJSON("https://gis.cdc.gov/grasp/fluView1/Phase1IniP") %>%
+    jsonlite::fromJSON() -> meta
+
+  state_info <- meta$stateinfo
+  state_info <- state_info[,c("statename", "statehealthdeptname", "url", "statewebsitename", "statefluphonenum")]
+  class(state_info) <- c("tbl_df", "tbl", "data.frame")
+
+  state_info
+
+}

R/pi-mortality.r

@@ -0,0 +1,135 @@
+#' Pneumonia and Influenza Mortality Surveillance
+#'
+#' 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.
+#'
+#' @md
+#' @param coverage_area coverage area for data (national, state or region)
+#' @note Queries for "state" and "region" are not "instantaneous" and can near or over 30s retrieval delays.
+#' @references
+#' - [Pneumonia and Influenza Mortality Surveillance Portal](https://gis.cdc.gov/grasp/fluview/mortality.html)
+#' @export
+#' @examples \dontrun{
+#' ndf <- pi_mortality()
+#' sdf <- pi_mortality("state")
+#' rdf <- pi_mortality("region")
+#' }
+pi_mortality <- function(coverage_area=c("national", "state", "region")) {
+
+  coverage_area <- match.arg(tolower(coverage_area), choices = c("national", "state", "region"))
+
+  us_states <- read.csv("https://gis.cdc.gov/grasp/fluview/Flu7References/Data/USStates.csv",
+                        stringsAsFactors=FALSE)
+  us_states <- setNames(us_states, c("region_name", "subgeoid", "state_abbr"))
+  us_states <- us_states[,c("region_name", "subgeoid")]
+  us_states$subgeoid <- as.character(us_states$subgeoid)
+
+  meta <- jsonlite::fromJSON("https://gis.cdc.gov/grasp/flu7/GetPhase07InitApp?appVersion=Public")
+
+  mapcode_df <- setNames(meta$nchs_mapcode[,c("mapcode", "description")], c("map_code", "callout"))
+  mapcode_df$map_code <- as.character(mapcode_df$map_code)
+
+  geo_df <- meta$nchs_geo_dim
+  geo_df$geoid <- as.character(geo_df$geoid)
+
+  age_df <- setNames(meta$nchs_ages, c("ageid", "age_label"))
+  age_df$ageid <- as.character(age_df$ageid)
+
+  mwmr_df <- meta$mmwr
+  mwmr_df$mmwrid <- as.character(mwmr_df$mmwrid)
+  mwmr_df <- setNames(mwmr_df,
+                      c("mmwrid", "weekend", "mwmr_weeknumber", "weekstart",
+                        "year", "yearweek", "mwmr_seasonid", "mwmr_label", "weekendlabel"))
+
+  sum_df <- meta$nchs_summary
+  sum_df$seasonid <- as.character(sum_df$seasonid)
+  sum_df$ageid <- as.character(sum_df$ageid)
+  sum_df$geoid <- as.character(sum_df$geoid)
+
+  httr::POST(
+    url = "https://gis.cdc.gov/grasp/flu7/PostPhase07DownloadData",
+    httr::user_agent(.cdcfluview_ua),
+    httr::add_headers(
+      Origin = "https://gis.cdc.gov",
+      Accept = "application/json, text/plain, */*",
+      Referer = "https://gis.cdc.gov/grasp/fluview/mortality.html"
+    ),
+    encode = "json",
+    body = list(
+      AppVersion = "Public",
+      AreaParameters = list(list(ID=.geoid_map[coverage_area])),
+      SeasonsParameters = lapply(meta$seasons$seasonid, function(.x) { list(ID=as.integer(.x)) }),
+      AgegroupsParameters = list(list(ID="1"))
+    ),
+    httr::timeout(60),
+    httr::verbose()
+  ) -> res
+
+  httr::stop_for_status(res)
+
+  res <- httr::content(res, as="parsed", flatten=TRUE)
+
+  dplyr::bind_rows(res$seasons) %>%
+    dplyr::left_join(mapcode_df, "map_code") %>%
+    dplyr::left_join(geo_df, "geoid") %>%
+    dplyr::left_join(age_df, "ageid") %>%
+    dplyr::left_join(mwmr_df, "mmwrid") -> xdf
+
+  xdf <- dplyr::mutate(xdf, coverage_area = coverage_area)
+
+  if (coverage_area == "state") {
+    xdf <- dplyr::left_join(xdf, us_states, "subgeoid")
+  } else if (coverage_area == "region") {
+    xdf$region_name <- sprintf("Region %s", xdf$subgeoid)
+  } else {
+    xdf$region_name <- NA_character_
+  }
+
+  xdf[,c("seasonid", "baseline", "threshold", "percent_pni",
+         "percent_complete", "number_influenza", "number_pneumonia",
+         "all_deaths", "Total_PnI", "weeknumber", "geo_description",
+         "age_label", "weekend", "weekstart", "year", "yearweek",
+         "coverage_area", "region_name", "callout")] -> xdf
+
+  suppressWarnings(xdf$baseline <- to_num(xdf$baseline))
+  suppressWarnings(xdf$threshold <- to_num(xdf$threshold))
+  suppressWarnings(xdf$percent_pni <- to_num(xdf$percent_pni) / 100)
+  suppressWarnings(xdf$percent_complete <- to_num(xdf$percent_complete) / 100)
+  suppressWarnings(xdf$number_influenza <- to_num(xdf$number_influenza))
+  suppressWarnings(xdf$number_pneumonia <- to_num(xdf$number_pneumonia))
+  suppressWarnings(xdf$all_deaths <- to_num(xdf$all_deaths))
+  suppressWarnings(xdf$Total_PnI <- to_num(xdf$Total_PnI))
+  suppressWarnings(xdf$weekend <- as.Date(xdf$weekend))
+  suppressWarnings(xdf$weekstart <- as.Date(xdf$weekstart))
+
+  xdf <- .mcga(xdf)
+
+  xdf
+
+}
+
+

R/utils.r

@@ -13,3 +13,12 @@
   tbl
 
 }
+
+to_num <- function(x) {
+  x <- gsub("%", "", x, fixed=TRUE)
+  x <- gsub(">", "", x, fixed=TRUE)
+  x <- gsub("<", "", x, fixed=TRUE)
+  x <- gsub(",", "", x, fixed=TRUE)
+  x <- gsub(" ", "", x, fixed=TRUE)
+  as.numeric(x)
+}

R/who-nrvess.r

@@ -24,11 +24,12 @@
 #' - [ILINet Portal](https://wwwn.cdc.gov/ilinet/) (Login required)
 #' - [WHO/NREVSS](https://www.cdc.gov/surveillance/nrevss/index.html)
 #' @export
-#' @examples
+#' @examples \dontrun{
 #' national_who <- who_nrevss("national")
 #' hhs_who <- who_nrevss("hhs")
 #' census_who <- who_nrevss("census")
 #' state_who <- who_nrevss("state")
+#' }
 who_nrevss <- function(region=c("national", "hhs", "census", "state")) {
 
   region <- match.arg(tolower(region), c("national", "hhs", "census", "state"))

R/zzz.r

@@ -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."))
+
+}

README.Rmd

@@ -1,15 +1,50 @@
 ---
+title: ""
+pagetitle: ""
 output: rmarkdown::github_document
 ---
 
-# cdcfluview
+[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/cdcfluview)](https://cran.r-project.org/package=cdcfluview)
+[![Travis-CI Build Status](https://travis-ci.org/hrbrmstr/cdcfluview.svg?branch=master)](https://travis-ci.org/hrbrmstr/cdcfluview)
+[![Coverage Status](https://img.shields.io/codecov/c/github/hrbrmstr/cdcfluview/master.svg)](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 eval=FALSE}
@@ -27,6 +62,10 @@ library(cdcfluview)
 
 # current verison
 packageVersion("cdcfluview")
-
 ```
 
+### 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.

README.md

@@ -0,0 +1,101 @@
+
+[![CRAN\_Status\_Badge](http://www.r-pkg.org/badges/version/cdcfluview)](https://cran.r-project.org/package=cdcfluview)
+[![Travis-CI Build
+Status](https://travis-ci.org/hrbrmstr/cdcfluview.svg?branch=master)](https://travis-ci.org/hrbrmstr/cdcfluview)
+[![Coverage
+Status](https://img.shields.io/codecov/c/github/hrbrmstr/cdcfluview/master.svg)](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.

codecov.yml

@@ -0,0 +1 @@
+comment: false

crunch/mkdata.r

@@ -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)

man/agd_ipt.Rd

@@ -11,6 +11,11 @@ Retrieves the age group distribution of influenza positive tests that are report
 public health laboratories by influenza virus type and subtype/lineage. Laboratory data
 from multiple seasons and different age groups is provided.
 }
+\examples{
+ \dontrun{
+agd_ipt()
+}
+}
 \references{
 - [CDC FluView Portal](https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html)
 - [AGD IPT Portal](https://gis.cdc.gov/grasp/fluview/flu_by_age_virus.html)

man/cdc_coverage_map.Rd

@@ -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())
+}
+}

man/cdcfluview.Rd

@@ -4,9 +4,14 @@
 \name{cdcfluview}
 \alias{cdcfluview}
 \alias{cdcfluview-package}
-\title{...}
+\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)

man/census_regions.Rd

@@ -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}

man/geographic_spread.Rd

@@ -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()
+}
+}

man/hhs_regions.Rd

@@ -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}

man/hospitalizations.Rd

@@ -4,19 +4,29 @@
 \alias{hospitalizations}
 \title{Laboratory-Confirmed Influenza Hospitalizations}
 \usage{
-hospitalizations(surveillance_area = c("flusurv", "eip", "ihsp"))
+hospitalizations(surveillance_area = c("flusurv", "eip", "ihsp"),
+  region = "all")
 }
 \arguments{
-\item{surveillance_area}{one of "`flusurv`", "`eip`", or "`ihsp`"}
+\item{surveillance_area}{one of "\code{flusurv}", "\code{eip}", or "\code{ihsp}"}
+
+\item{region}{Using "\code{all}" mimics selecting "Entire Network" from the
+CDC FluView application drop down. Individual regions for each
+surveillance area can also be selected. Use \code{\link[=surveillance_areas]{surveillance_areas()}} to
+see a list of valid sub-regions for each surveillance area.}
 }
 \description{
 Laboratory-Confirmed Influenza Hospitalizations
 }
 \examples{
+\dontrun{
 hosp_fs <- hospitalizations("flusurv")
 hosp_eip <- hospitalizations("eip")
 hosp_ihsp <- hospitalizations("ihsp")
 }
+}
 \references{
-- [Hospital Portal](https://gis.cdc.gov/GRASP/Fluview/FluHospRates.html)
+\itemize{
+\item \href{https://gis.cdc.gov/GRASP/Fluview/FluHospRates.html}{Hospital Portal}
+}
 }

man/ili_weekly_activity_indicators.Rd

@@ -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}
+}
+}

man/pi_mortality.Rd

@@ -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}
+}
+}

man/state_data_providers.Rd

@@ -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()
+}

man/surveillance_areas.Rd

@@ -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()
+}

man/who_nrevss.Rd

@@ -35,11 +35,13 @@ laboratories are presented separately in the weekly influenza update. This is
 the reason why a list of data frames is returned.
 }
 \examples{
+\dontrun{
 national_who <- who_nrevss("national")
 hhs_who <- who_nrevss("hhs")
 census_who <- who_nrevss("census")
 state_who <- who_nrevss("state")
 }
+}
 \references{
 \itemize{
 \item \href{https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html}{CDC FluView Portal}