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working on #19

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boB Rudis 5 years ago
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  1. 20
      DESCRIPTION
  2. 2
      NAMESPACE
  3. 4
      NEWS.md
  4. 2
      R/aaa.R
  5. 4
      R/cdcfluview-package.R
  6. 68
      R/ilinet.r
  7. 17
      R/pi-mortality.r
  8. 2
      R/utils.r
  9. 25
      README.Rmd
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20
DESCRIPTION
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@ -1,9 +1,10 @@
Package: cdcfluview Package: cdcfluview
Type: Package Type: Package
Encoding: UTF-8 Encoding: UTF-8
Title: Retrieve U.S. Flu Season Data from the CDC 'FluView' Portal Title: Retrieve Flu Season Data from the United States Centers for Disease Control
Version: 0.8.0 and Prevention ('CDC') 'FluView' Portal
Date: 2018-11-23 Version: 0.9.0
Date: 2019-01-23
Authors@R: c( Authors@R: c(
person("Bob", "Rudis", email = "bob@rud.is", role = c("aut", "cre"), 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")),
@ -12,17 +13,18 @@ Authors@R: c(
person("JJ", "Chen", email = "jiajia.chern@gmail.com", role = "ctb", person("JJ", "Chen", email = "jiajia.chern@gmail.com", role = "ctb",
comment = c(ORCID = "0000-0001-8482-8398")), comment = c(ORCID = "0000-0001-8482-8398")),
person("Sebastian", "Meyer", email = "seb.meyer@fau.de", role = "ctb", person("Sebastian", "Meyer", email = "seb.meyer@fau.de", role = "ctb",
comment = c(ORCID = "0000-0002-1791-9449")) comment = c(ORCID = "0000-0002-1791-9449")),
person("James", "Turtle", email = "jturtle@predsci.com", role = "ctb")
) )
Maintainer: Bob Rudis <bob@rud.is> Maintainer: Bob Rudis <bob@rud.is>
Description: The U.S. Centers for Disease Control and Prevention (CDC) maintain Description: The 'U.S.' Centers for Disease Control and Prevention (CDC) maintain
a portal <http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html> for a portal <http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html> for
accessing state, regional and national influenza statistics as well as accessing state, regional and national influenza statistics as well as
mortality surveillance data. The web interface makes it difficult and mortality surveillance data. The web interface makes it difficult and
time-consuming to select and retrieve influenza data. Tools are provided time-consuming to select and retrieve influenza data. Tools are provided
to access the data provided by the portal's underlying API. to access the data provided by the portal's underlying 'API'.
URL: https://github.com/hrbrmstr/cdcfluview URL: https://gitlab.com/hrbrmstr/cdcfluview
BugReports: https://github.com/hrbrmstr/cdcfluview/issues BugReports: https://gitlab.com/hrbrmstr/cdcfluview/issues
License: MIT + file LICENSE License: MIT + file LICENSE
LazyData: true LazyData: true
Suggests: Suggests:
@ -43,4 +45,4 @@ Imports:
readr, readr,
MMWRweek, MMWRweek,
units (>= 0.4-6) units (>= 0.4-6)
RoxygenNote: 6.0.1.9000 RoxygenNote: 6.1.1

2
NAMESPACE
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@ -22,12 +22,14 @@ import(MMWRweek)
import(httr) import(httr)
import(xml2) import(xml2)
importFrom(dplyr,"%>%") importFrom(dplyr,"%>%")
importFrom(dplyr,arrange)
importFrom(dplyr,bind_rows) importFrom(dplyr,bind_rows)
importFrom(dplyr,data_frame) importFrom(dplyr,data_frame)
importFrom(dplyr,filter) importFrom(dplyr,filter)
importFrom(dplyr,left_join) importFrom(dplyr,left_join)
importFrom(dplyr,mutate) importFrom(dplyr,mutate)
importFrom(jsonlite,fromJSON) importFrom(jsonlite,fromJSON)
importFrom(lubridate,epiweek)
importFrom(purrr,discard) importFrom(purrr,discard)
importFrom(purrr,keep) importFrom(purrr,keep)
importFrom(purrr,map) importFrom(purrr,map)

4
NEWS.md
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@ -1,3 +1,7 @@
# cdcfluview 0.9.0
- fix bug in epiweek computation in ilinet() thanks to a bug report by @jturtle (#19)
# cdcfluview 0.7.0 # cdcfluview 0.7.0
* The CDC changed most of their API endpoints to support a new HTML interface and * The CDC changed most of their API endpoints to support a new HTML interface and

2
R/aaa.R
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@ -1,4 +1,4 @@
utils::globalVariables(c(".", "mmwrid", "season", "seasonid")) utils::globalVariables(c(".", "mmwrid", "season", "seasonid", "week_start"))
# CDC U.S. region names to ID map # CDC U.S. region names to ID map
.region_map <- c(national=3, hhs=1, census=2, state=5) .region_map <- c(national=3, hhs=1, census=2, state=5)

4
R/cdcfluview-package.R
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@ -1,4 +1,4 @@
#' Retrieve 'U.S'.' Flu Season Data from the 'CDC' 'FluView' Portal #' Retrieve Flu Season Data from the United States Centers for Disease Control and Prevention ('CDC') 'FluView' Portal
#' #'
#' The U.S. Centers for Disease Control (CDC) maintains a portal #' The U.S. Centers for Disease Control (CDC) maintains a portal
#' <http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html> for #' <http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html> for
@ -17,7 +17,7 @@
#' @importFrom purrr map map_df map_chr map_lgl discard keep #' @importFrom purrr map map_df map_chr map_lgl discard keep
#' @importFrom readr read_csv type_convert #' @importFrom readr read_csv type_convert
#' @importFrom tools file_path_sans_ext #' @importFrom tools file_path_sans_ext
#' @importFrom dplyr left_join bind_rows mutate filter data_frame %>% #' @importFrom dplyr left_join bind_rows mutate filter data_frame %>% arrange
#' @importFrom jsonlite fromJSON #' @importFrom jsonlite fromJSON
#' @importFrom stats setNames #' @importFrom stats setNames
#' @importFrom sf st_read #' @importFrom sf st_read

68
R/ilinet.r
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@ -21,19 +21,22 @@
#' - [ILINet Portal](https://wwwn.cdc.gov/ilinet/) (Login required) #' - [ILINet Portal](https://wwwn.cdc.gov/ilinet/) (Login required)
#' - [WHO/NREVSS](https://www.cdc.gov/surveillance/nrevss/index.html) #' - [WHO/NREVSS](https://www.cdc.gov/surveillance/nrevss/index.html)
#' @export #' @export
#' @examples #' @examples
#' national_ili <- ilinet("national", years=2017) #' national_ili <- ilinet("national", years = 2017)
#' \dontrun{ #' \dontrun{
#' hhs_ili <- ilinet("hhs") #' hhs_ili <- ilinet("hhs")
#' census_ili <- ilinet("census") #' census_ili <- ilinet("census")
#' state_ili <- ilinet("state") #' state_ili <- ilinet("state")
#' #'
#' library(purrr) #' library(purrr)
#' map_df( #' map_df(
#' c("national", "hhs", "census", "state"), #' c("national", "hhs", "census", "state"),
#' ~ilinet(.x)) #' ~ ilinet(.x)
#' )
#' } #' }
ilinet <- function(region=c("national", "hhs", "census", "state"), years=NULL) { ilinet <- function(region = c("national", "hhs", "census", "state"), years = NULL) {
#region="national"; years=1997:2018
region <- match.arg(tolower(region), c("national", "hhs", "census", "state")) region <- match.arg(tolower(region), c("national", "hhs", "census", "state"))
@ -46,10 +49,18 @@ ilinet <- function(region=c("national", "hhs", "census", "state"), years=NULL) {
) -> params ) -> params
params$SubRegionsDT <- switch(region, params$SubRegionsDT <- switch(region,
national = { list(list(ID=0, Name="")) }, national = {
hhs = { lapply(1:10, function(i) list(ID=i, Name=as.character(i))) }, list(list(ID = 0, Name = ""))
census = { lapply(1:9, function(i) list(ID=i, Name=as.character(i))) }, },
state = { lapply(1:59, function(i) list(ID=i, Name=as.character(i))) } hhs = {
lapply(1:10, function(i) list(ID = i, Name = as.character(i)))
},
census = {
lapply(1:9, function(i) list(ID = i, Name = as.character(i)))
},
state = {
lapply(1:59, function(i) list(ID = i, Name = as.character(i)))
}
) )
available_seasons <- sort(meta$seasons$seasonid) available_seasons <- sort(meta$seasons$seasonid)
@ -66,13 +77,14 @@ ilinet <- function(region=c("national", "hhs", "census", "state"), years=NULL) {
if (length(years) == 0) { if (length(years) == 0) {
years <- rev(sort(meta$seasons$seasonid))[1] years <- rev(sort(meta$seasons$seasonid))[1]
curr_season_descr <- meta$seasons[meta$seasons$seasonid == years, "description"] curr_season_descr <- meta$seasons[meta$seasons$seasonid == years, "description"]
message(sprintf("No valid years specified, defaulting to this flu season => ID: %s [%s]", message(sprintf(
years, curr_season_descr)) "No valid years specified, defaulting to this flu season => ID: %s [%s]",
years, curr_season_descr
))
} }
} }
params$SeasonsDT <- lapply(years, function(i) list(ID=i, Name=as.character(i))) params$SeasonsDT <- lapply(years, function(i) list(ID = i, Name = as.character(i)))
tf <- tempfile(fileext = ".zip") tf <- tempfile(fileext = ".zip")
td <- tempdir() td <- tempdir()
@ -97,27 +109,27 @@ ilinet <- function(region=c("national", "hhs", "census", "state"), years=NULL) {
nm <- unzip(tf, overwrite = TRUE, exdir = td) nm <- unzip(tf, overwrite = TRUE, exdir = td)
xdf <- read.csv(nm, skip = 1, stringsAsFactors=FALSE) xdf <- read.csv(nm, skip = 1, stringsAsFactors = FALSE)
xdf <- .mcga(xdf) xdf <- .mcga(xdf)
suppressWarnings(xdf$weighted_ili <- to_num(xdf$weighted_ili)) xdf$weighted_ili <- to_num(xdf$weighted_ili)
suppressWarnings(xdf$unweighted_ili <- to_num(xdf$unweighted_ili)) xdf$unweighted_ili <- to_num(xdf$unweighted_ili)
suppressWarnings(xdf$age_0_4 <- to_num(xdf$age_0_4)) xdf$age_0_4 <- to_num(xdf$age_0_4)
suppressWarnings(xdf$age_25_49 <- to_num(xdf$age_25_49)) xdf$age_25_49 <- to_num(xdf$age_25_49)
suppressWarnings(xdf$age_25_64 <- to_num(xdf$age_25_64)) xdf$age_25_64 <- to_num(xdf$age_25_64)
suppressWarnings(xdf$age_5_24 <- to_num(xdf$age_5_24)) xdf$age_5_24 <- to_num(xdf$age_5_24)
suppressWarnings(xdf$age_50_64 <- to_num(xdf$age_50_64)) xdf$age_50_64 <- to_num(xdf$age_50_64)
suppressWarnings(xdf$age_65 <- to_num(xdf$age_65)) xdf$age_65 <- to_num(xdf$age_65)
suppressWarnings(xdf$ilitotal <- to_num(xdf$ilitotal)) xdf$ilitotal <- to_num(xdf$ilitotal)
suppressWarnings(xdf$num_of_providers <- to_num(xdf$num_of_providers)) xdf$num_of_providers <- to_num(xdf$num_of_providers)
suppressWarnings(xdf$total_patients <- to_num(xdf$total_patients)) xdf$total_patients <- to_num(xdf$total_patients)
suppressWarnings(xdf$week_start <- as.Date(sprintf("%s-%02d-1", xdf$year, xdf$week), "%Y-%U-%u")) xdf$week_start <- MMWRweek::MMWRweek2Date(xdf$year, xdf$week)
if (region == "national") xdf$region <- "National" if (region == "national") xdf$region <- "National"
if (region == "hhs") xdf$region <- factor(xdf$region, levels=sprintf("Region %s", 1:10)) if (region == "hhs") xdf$region <- factor(xdf$region, levels = sprintf("Region %s", 1:10))
class(xdf) <- c("tbl_df", "tbl", "data.frame") class(xdf) <- c("tbl_df", "tbl", "data.frame")
suppressMessages(readr::type_convert(xdf)) arrange(suppressMessages(readr::type_convert(xdf)), week_start)
} }

17
R/pi-mortality.r
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@ -136,15 +136,14 @@ pi_mortality <- function(coverage_area=c("national", "state", "region"), years=N
"age_label", "wk_start", "wk_end", "year_wk_num", "mmwrid", "age_label", "wk_start", "wk_end", "year_wk_num", "mmwrid",
"coverage_area", "region_name", "callout")] -> xdf "coverage_area", "region_name", "callout")] -> xdf
suppressWarnings(xdf$baseline <- to_num(xdf$baseline) / 100) xdf$baseline <- to_num(xdf$baseline) / 100
suppressWarnings(xdf$threshold <- to_num(xdf$threshold) / 100) xdf$threshold <- to_num(xdf$threshold) / 100
suppressWarnings(xdf$percent_pni <- to_num(xdf$percent_pni) / 100) xdf$percent_pni <- to_num(xdf$percent_pni) / 100
suppressWarnings(xdf$percent_complete <- to_num(xdf$percent_complete) / 100) xdf$percent_complete <- to_num(xdf$percent_complete) / 100
suppressWarnings(xdf$number_influenza <- to_num(xdf$number_influenza)) xdf$number_influenza <- to_num(xdf$number_influenza)
suppressWarnings(xdf$number_pneumonia <- to_num(xdf$number_pneumonia)) xdf$number_pneumonia <- to_num(xdf$number_pneumonia)
suppressWarnings(xdf$all_deaths <- to_num(xdf$all_deaths)) xdf$all_deaths <- to_num(xdf$all_deaths)
suppressWarnings(xdf$Total_PnI <- to_num(xdf$Total_PnI)) xdf$Total_PnI <- to_num(xdf$Total_PnI)
xdf <- .mcga(xdf) xdf <- .mcga(xdf)
xdf xdf

2
R/utils.r
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@ -20,5 +20,5 @@ 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) x <- gsub(" ", "", x, fixed=TRUE)
as.numeric(x) suppressWarnings(as.numeric(x))
} }

25
README.Rmd
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@ -1,7 +1,7 @@
--- ---
title: ""
pagetitle: ""
output: rmarkdown::github_document output: rmarkdown::github_document
editor_options:
chunk_output_type: console
--- ---
```{r message=FALSE, warning=FALSE, error=FALSE, include=FALSE} ```{r message=FALSE, warning=FALSE, error=FALSE, include=FALSE}
knitr::opts_chunk$set(message=FALSE, warning=FALSE, fig.retina=2) knitr::opts_chunk$set(message=FALSE, warning=FALSE, fig.retina=2)
@ -21,7 +21,7 @@ If there's a particular data set from https://www.cdc.gov/flu/weekly/fluviewinte
# :mask: cdcfluview # :mask: cdcfluview
Retrieve U.S. Flu Season Data from the CDC FluView Portal Retrieve Flu Season Data from the United States Centers for Disease Control and Prevention ('CDC') 'FluView' Portal
## Description ## Description
@ -63,9 +63,22 @@ The following data sets are included:
- `census_regions`: Census Region Table (a data frame with 51 rows and 2 variables) - `census_regions`: Census Region Table (a data frame with 51 rows and 2 variables)
- `mmwrid_map`: MMWR ID to Calendar Mappings (it is exported & available, no need to use `data()`) - `mmwrid_map`: MMWR ID to Calendar Mappings (it is exported & available, no need to use `data()`)
## NOTE
All development happens in branches now with only critical fixes being back-ported to the master branch when necessary.
## Installation ## Installation
```{r eval=FALSE} ```{r eval=FALSE}
# CRAN
install.packages("cdcfluview")
# 0.9.0 branch (where all fixes are)
devtools::install_git("https://sr.ht/~hrbrmstr/cdcfluview", ref= "0.9.0")
devtools::install_git("https://gitlab.com/hrbrmstr/cdcfluview", ref = "0.9.0")
devtools::install_github("hrbrmstr/cdcfluview", ref = "0.9.0")
# master branch
devtools::install_git("https://sr.ht/~hrbrmstr/cdcfluview")
devtools::install_git("https://gitlab.com/hrbrmstr/cdcfluview")
devtools::install_github("hrbrmstr/cdcfluview") devtools::install_github("hrbrmstr/cdcfluview")
``` ```
@ -214,6 +227,12 @@ who_nrevss("census", years=2016)
who_nrevss("state", years=2016) who_nrevss("state", years=2016)
``` ```
## cdcfluview Metrics
```{r echo=FALSE}
cloc::cloc_pkg_md()
```
## Code of Conduct ## 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. 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.

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751
README.md
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@ -23,7 +23,8 @@ specific as you can (screen shot if possible).
# :mask: cdcfluview # :mask: cdcfluview
Retrieve U.S. Flu Season Data from the CDC FluView Portal Retrieve Flu Season Data from the United States Centers for Disease
Control and Prevention (‘CDC’) ‘FluView’ Portal
## Description ## Description
@ -83,9 +84,23 @@ The following data sets are included:
- `mmwrid_map`: MMWR ID to Calendar Mappings (it is exported & - `mmwrid_map`: MMWR ID to Calendar Mappings (it is exported &
available, no need to use `data()`) available, no need to use `data()`)
## NOTE
All development happens in branches now with only critical fixes being
back-ported to the master branch when necessary.
## Installation ## Installation
``` r ``` r
# CRAN
install.packages("cdcfluview")
# 0.9.0 branch (where all fixes are)
devtools::install_git("https://sr.ht/~hrbrmstr/cdcfluview", ref= "0.9.0")
devtools::install_git("https://gitlab.com/hrbrmstr/cdcfluview", ref = "0.9.0")
devtools::install_github("hrbrmstr/cdcfluview", ref = "0.9.0")
# master branch
devtools::install_git("https://sr.ht/~hrbrmstr/cdcfluview")
devtools::install_git("https://gitlab.com/hrbrmstr/cdcfluview")
devtools::install_github("hrbrmstr/cdcfluview") devtools::install_github("hrbrmstr/cdcfluview")
``` ```
@ -110,22 +125,22 @@ glimpse(age_group_distribution(years=2015))
## Observations: 1,872 ## Observations: 1,872
## Variables: 16 ## Variables: 16
## $ sea_label <chr> "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "... ## $ sea_label <chr> "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "20…
## $ age_label <fct> 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0... ## $ age_label <fct> 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4…
## $ vir_label <fct> A (Subtyping not Performed), A (Subtyping not Performed), A (Subtyping not Performed), A ... ## $ vir_label <fct> A (Subtyping not Performed), A (Subtyping not Performed), A (Subtyping not Performed), A (S…
## $ count <int> 0, 1, 0, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 3, 2, 2, 3, 3, 3, 0, 0, 2, 0, 1, 1, 0,... ## $ count <int> 0, 1, 0, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 3, 2, 2, 3, 3, 3, 0, 0, 2, 0, 1, 1, 0, 0…
## $ mmwrid <int> 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820,... ## $ mmwrid <int> 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2…
## $ seasonid <int> 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 5... ## $ seasonid <int> 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55,…
## $ publishyearweekid <int> 2956, 2956, 2956, 2956, 2956, 2956, 2956, 2956, 2956, 2956, 2956, 2956, 2956, 2956, 2956,... ## $ publishyearweekid <int> 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2…
## $ sea_description <chr> "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16",... ## $ sea_description <chr> "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "…
## $ sea_startweek <int> 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806,... ## $ sea_startweek <int> 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2…
## $ sea_endweek <int> 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857,... ## $ sea_endweek <int> 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2…
## $ vir_description <chr> "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk",... ## $ vir_description <chr> "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "…
## $ vir_startmmwrid <int> 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397,... ## $ vir_startmmwrid <int> 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1…
## $ vir_endmmwrid <int> 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131,... ## $ vir_endmmwrid <int> 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3…
## $ wk_start <date> 2015-10-04, 2015-10-11, 2015-10-18, 2015-10-25, 2015-11-01, 2015-11-08, 2015-11-15, 2015... ## $ wk_start <date> 2015-10-04, 2015-10-11, 2015-10-18, 2015-10-25, 2015-11-01, 2015-11-08, 2015-11-15, 2015-1…
## $ wk_end <date> 2015-10-10, 2015-10-17, 2015-10-24, 2015-10-31, 2015-11-07, 2015-11-14, 2015-11-21, 2015... ## $ wk_end <date> 2015-10-10, 2015-10-17, 2015-10-24, 2015-10-31, 2015-11-07, 2015-11-14, 2015-11-21, 2015-1…
## $ year_wk_num <int> 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12... ## $ year_wk_num <int> 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, …
### Retrieve CDC U.S. Coverage Map ### Retrieve CDC U.S. Coverage Map
@ -171,15 +186,15 @@ plot(cdc_basemap("surv"))
glimpse(geographic_spread()) glimpse(geographic_spread())
``` ```
## Observations: 27,351 ## Observations: 28,151
## Variables: 7 ## Variables: 7
## $ statename <chr> "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "... ## $ statename <chr> "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Al…
## $ url <chr> "http://adph.org/influenza/", "http://adph.org/influenza/", "http://adph.org/influenza/",... ## $ url <chr> "http://adph.org/influenza/", "http://adph.org/influenza/", "http://adph.org/influenza/", "…
## $ website <chr> "Influenza Surveillance", "Influenza Surveillance", "Influenza Surveillance", "Influenza ... ## $ website <chr> "Influenza Surveillance", "Influenza Surveillance", "Influenza Surveillance", "Influenza Su…
## $ activity_estimate <chr> "No Activity", "No Activity", "No Activity", "Local Activity", "Sporadic", "Sporadic", "S... ## $ activity_estimate <chr> "No Activity", "No Activity", "No Activity", "Local Activity", "Sporadic", "Sporadic", "Spo…
## $ weekend <date> 2003-10-04, 2003-10-11, 2003-10-18, 2003-10-25, 2003-11-01, 2003-11-08, 2003-11-15, 2003... ## $ weekend <date> 2003-10-04, 2003-10-11, 2003-10-18, 2003-10-25, 2003-11-01, 2003-11-08, 2003-11-15, 2003-1…
## $ season <chr> "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "... ## $ season <chr> "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "20…
## $ weeknumber <chr> "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "1", ... ## $ weeknumber <chr> "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "1", "2…
### Laboratory-Confirmed Influenza Hospitalizations ### Laboratory-Confirmed Influenza Hospitalizations
@ -215,22 +230,22 @@ surveillance_areas()
glimpse(fs_nat <- hospitalizations("flusurv")) glimpse(fs_nat <- hospitalizations("flusurv"))
``` ```
## Observations: 1,656 ## Observations: 1,746
## Variables: 14 ## Variables: 14
## $ surveillance_area <chr> "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET",... ## $ surveillance_area <chr> "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "…
## $ region <chr> "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network",... ## $ region <chr> "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network", "…
## $ year <int> 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009,... ## $ year <int> 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2…
## $ season <int> 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 4... ## $ season <int> 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49, 49,…
## $ wk_start <date> 2009-08-30, 2009-09-06, 2009-09-13, 2009-09-20, 2009-09-27, 2009-10-04, 2009-10-11, 2009... ## $ wk_start <date> 2009-08-30, 2009-09-06, 2009-09-13, 2009-09-20, 2009-09-27, 2009-10-04, 2009-10-11, 2009-1…
## $ wk_end <date> 2009-09-05, 2009-09-12, 2009-09-19, 2009-09-26, 2009-10-03, 2009-10-10, 2009-10-17, 2009... ## $ wk_end <date> 2009-09-05, 2009-09-12, 2009-09-19, 2009-09-26, 2009-10-03, 2009-10-10, 2009-10-17, 2009-1…
## $ year_wk_num <int> 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 3, 4, 5, 6,... ## $ year_wk_num <int> 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 3, 4, 5, 6, 7…
## $ rate <dbl> 0.5, 2.5, 4.6, 6.7, 10.9, 18.1, 28.3, 39.1, 47.3, 53.3, 57.5, 60.1, 61.6, 62.9, 64.1, 65.... ## $ rate <dbl> 0.5, 2.5, 4.6, 6.7, 10.9, 18.1, 28.3, 39.1, 47.3, 53.3, 57.5, 60.1, 61.6, 62.9, 64.1, 65.1,…
## $ weeklyrate <dbl> 0.5, 2.0, 2.0, 2.1, 4.3, 7.2, 10.2, 10.8, 8.2, 6.0, 4.2, 2.6, 1.5, 1.3, 1.3, 1.0, 1.2, 1.... ## $ weeklyrate <dbl> 0.5, 2.0, 2.0, 2.1, 4.3, 7.2, 10.2, 10.8, 8.2, 6.0, 4.2, 2.6, 1.5, 1.3, 1.3, 1.0, 1.2, 1.1,…
## $ age <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,... ## $ age <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1…
## $ age_label <fct> 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0... ## $ age_label <fct> 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4…
## $ sea_label <chr> "2009-10", "2009-10", "2009-10", "2009-10", "2009-10", "2009-10", "2009-10", "2009-10", "... ## $ sea_label <chr> "2009-10", "2009-10", "2009-10", "2009-10", "2009-10", "2009-10", "2009-10", "2009-10", "20…
## $ sea_description <chr> "Season 2009-10", "Season 2009-10", "Season 2009-10", "Season 2009-10", "Season 2009-10",... ## $ sea_description <chr> "Season 2009-10", "Season 2009-10", "Season 2009-10", "Season 2009-10", "Season 2009-10", "…
## $ mmwrid <int> 2488, 2489, 2490, 2491, 2492, 2493, 2494, 2495, 2496, 2497, 2498, 2499, 2500, 2501, 2502,... ## $ mmwrid <int> 2488, 2489, 2490, 2491, 2492, 2493, 2494, 2495, 2496, 2497, 2498, 2499, 2500, 2501, 2502, 2…
``` r ``` r
ggplot(fs_nat, aes(wk_end, rate)) + ggplot(fs_nat, aes(wk_end, rate)) +
@ -250,20 +265,20 @@ glimpse(hospitalizations("eip", years=2015))
## Observations: 180 ## Observations: 180
## Variables: 14 ## Variables: 14
## $ surveillance_area <chr> "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP"... ## $ surveillance_area <chr> "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", …
## $ region <chr> "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network",... ## $ region <chr> "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network", "…
## $ year <int> 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016,... ## $ year <int> 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 2…
## $ season <int> 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 5... ## $ season <int> 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55,…
## $ wk_start <date> 2015-10-04, 2015-10-11, 2015-10-18, 2015-10-25, 2015-11-01, 2015-11-08, 2015-11-15, 2015... ## $ wk_start <date> 2015-10-04, 2015-10-11, 2015-10-18, 2015-10-25, 2015-11-01, 2015-11-08, 2015-11-15, 2015-1…
## $ wk_end <date> 2015-10-10, 2015-10-17, 2015-10-24, 2015-10-31, 2015-11-07, 2015-11-14, 2015-11-21, 2015... ## $ wk_end <date> 2015-10-10, 2015-10-17, 2015-10-24, 2015-10-31, 2015-11-07, 2015-11-14, 2015-11-21, 2015-1…
## $ year_wk_num <int> 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12... ## $ year_wk_num <int> 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, …
## $ rate <dbl> 0.1, 0.3, 0.4, 0.5, 0.8, 0.8, 1.1, 1.4, 1.6, 1.7, 1.8, 2.1, 2.4, 2.9, 3.2, 3.5, 4.2, 5.3,... ## $ rate <dbl> 0.1, 0.3, 0.4, 0.5, 0.8, 0.8, 1.1, 1.4, 1.6, 1.7, 1.8, 2.1, 2.4, 2.9, 3.2, 3.5, 4.1, 5.3, 6…
## $ weeklyrate <dbl> 0.1, 0.3, 0.1, 0.1, 0.3, 0.0, 0.3, 0.3, 0.2, 0.1, 0.1, 0.3, 0.3, 0.5, 0.3, 0.3, 0.6, 1.2,... ## $ weeklyrate <dbl> 0.1, 0.3, 0.1, 0.1, 0.3, 0.0, 0.3, 0.3, 0.2, 0.1, 0.1, 0.3, 0.3, 0.5, 0.3, 0.3, 0.6, 1.2, 1…
## $ age <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,... ## $ age <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2…
## $ age_label <fct> 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0... ## $ age_label <fct> 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4…
## $ sea_label <chr> "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "... ## $ sea_label <chr> "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "20…
## $ sea_description <chr> "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16",... ## $ sea_description <chr> "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "…
## $ mmwrid <int> 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820,... ## $ mmwrid <int> 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2…
``` r ``` r
glimpse(hospitalizations("eip", "Colorado", years=2015)) glimpse(hospitalizations("eip", "Colorado", years=2015))
@ -271,20 +286,20 @@ glimpse(hospitalizations("eip", "Colorado", years=2015))
## Observations: 180 ## Observations: 180
## Variables: 14 ## Variables: 14
## $ surveillance_area <chr> "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP"... ## $ surveillance_area <chr> "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", …
## $ region <chr> "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colo... ## $ region <chr> "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colora…
## $ year <int> 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016,... ## $ year <int> 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 2…
## $ season <int> 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 5... ## $ season <int> 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55,…
## $ wk_start <date> 2015-10-04, 2015-10-11, 2015-10-18, 2015-10-25, 2015-11-01, 2015-11-08, 2015-11-15, 2015... ## $ wk_start <date> 2015-10-04, 2015-10-11, 2015-10-18, 2015-10-25, 2015-11-01, 2015-11-08, 2015-11-15, 2015-1…
## $ wk_end <date> 2015-10-10, 2015-10-17, 2015-10-24, 2015-10-31, 2015-11-07, 2015-11-14, 2015-11-21, 2015... ## $ wk_end <date> 2015-10-10, 2015-10-17, 2015-10-24, 2015-10-31, 2015-11-07, 2015-11-14, 2015-11-21, 2015-1…
## $ year_wk_num <int> 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12... ## $ year_wk_num <int> 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, …
## $ rate <dbl> 0.0, 0.0, 0.6, 0.6, 0.6, 0.6, 1.2, 1.8, 1.8, 1.8, 1.8, 1.8, 2.9, 3.5, 3.5, 3.5, 4.1, 6.4,... ## $ rate <dbl> 0.0, 0.0, 0.6, 0.6, 0.6, 0.6, 1.2, 1.7, 1.7, 1.7, 1.7, 1.7, 2.9, 3.5, 3.5, 3.5, 4.1, 6.4, 8…
## $ weeklyrate <dbl> 0.0, 0.0, 0.6, 0.0, 0.0, 0.0, 0.6, 0.6, 0.0, 0.0, 0.0, 0.0, 1.2, 0.6, 0.0, 0.0, 0.6, 2.3,... ## $ weeklyrate <dbl> 0.0, 0.0, 0.6, 0.0, 0.0, 0.0, 0.6, 0.6, 0.0, 0.0, 0.0, 0.0, 1.2, 0.6, 0.0, 0.0, 0.6, 2.3, 2…
## $ age <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,... ## $ age <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2…
## $ age_label <fct> 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0... ## $ age_label <fct> 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4…
## $ sea_label <chr> "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "... ## $ sea_label <chr> "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "20…
## $ sea_description <chr> "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16",... ## $ sea_description <chr> "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "…
## $ mmwrid <int> 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820,... ## $ mmwrid <int> 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2…
``` r ``` r
glimpse(hospitalizations("ihsp", years=2015)) glimpse(hospitalizations("ihsp", years=2015))
@ -292,20 +307,20 @@ glimpse(hospitalizations("ihsp", years=2015))
## Observations: 180 ## Observations: 180
## Variables: 14 ## Variables: 14
## $ surveillance_area <chr> "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "... ## $ surveillance_area <chr> "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IH…
## $ region <chr> "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network",... ## $ region <chr> "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network", "…
## $ year <int> 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016,... ## $ year <int> 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 2…
## $ season <int> 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 5... ## $ season <int> 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55,…
## $ wk_start <date> 2015-10-04, 2015-10-11, 2015-10-18, 2015-10-25, 2015-11-01, 2015-11-08, 2015-11-15, 2015... ## $ wk_start <date> 2015-10-04, 2015-10-11, 2015-10-18, 2015-10-25, 2015-11-01, 2015-11-08, 2015-11-15, 2015-1…
## $ wk_end <date> 2015-10-10, 2015-10-17, 2015-10-24, 2015-10-31, 2015-11-07, 2015-11-14, 2015-11-21, 2015... ## $ wk_end <date> 2015-10-10, 2015-10-17, 2015-10-24, 2015-10-31, 2015-11-07, 2015-11-14, 2015-11-21, 2015-1…
## $ year_wk_num <int> 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12... ## $ year_wk_num <int> 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, …
## $ rate <dbl> 0.0, 0.0, 0.4, 0.4, 0.4, 1.1, 1.1, 1.1, 1.1, 1.5, 1.8, 2.2, 2.2, 2.5, 2.5, 2.5, 2.9, 4.0,... ## $ rate <dbl> 0.0, 0.0, 0.4, 0.4, 0.4, 1.1, 1.1, 1.1, 1.1, 1.5, 1.8, 2.2, 2.2, 2.6, 2.6, 2.6, 2.9, 4.0, 5…
## $ weeklyrate <dbl> 0.0, 0.0, 0.4, 0.0, 0.0, 0.7, 0.0, 0.0, 0.0, 0.4, 0.4, 0.4, 0.0, 0.4, 0.0, 0.0, 0.4, 1.1,... ## $ weeklyrate <dbl> 0.0, 0.0, 0.4, 0.0, 0.0, 0.7, 0.0, 0.0, 0.0, 0.4, 0.4, 0.4, 0.0, 0.4, 0.0, 0.0, 0.4, 1.1, 1…
## $ age <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,... ## $ age <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2…
## $ age_label <fct> 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0... ## $ age_label <fct> 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4…
## $ sea_label <chr> "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "... ## $ sea_label <chr> "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "20…
## $ sea_description <chr> "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16",... ## $ sea_description <chr> "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "…
## $ mmwrid <int> 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820,... ## $ mmwrid <int> 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2…
``` r ``` r
glimpse(hospitalizations("ihsp", "Oklahoma", years=2015)) glimpse(hospitalizations("ihsp", "Oklahoma", years=2015))
@ -313,20 +328,20 @@ glimpse(hospitalizations("ihsp", "Oklahoma", years=2015))
## Observations: 180 ## Observations: 180
## Variables: 14 ## Variables: 14
## $ surveillance_area <chr> "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "... ## $ surveillance_area <chr> "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IH…
## $ region <chr> "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Okla... ## $ region <chr> "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklaho…
## $ year <int> 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2011, 2011,... ## $ year <int> 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2011, 2011, 2…
## $ season <int> 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 5... ## $ season <int> 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,…
## $ wk_start <date> 2010-10-03, 2010-10-10, 2010-10-17, 2010-10-24, 2010-10-31, 2010-11-07, 2010-11-14, 2010... ## $ wk_start <date> 2010-10-03, 2010-10-10, 2010-10-17, 2010-10-24, 2010-10-31, 2010-11-07, 2010-11-14, 2010-1…
## $ wk_end <date> 2010-10-09, 2010-10-16, 2010-10-23, 2010-10-30, 2010-11-06, 2010-11-13, 2010-11-20, 2010... ## $ wk_end <date> 2010-10-09, 2010-10-16, 2010-10-23, 2010-10-30, 2010-11-06, 2010-11-13, 2010-11-20, 2010-1…
## $ year_wk_num <int> 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12... ## $ year_wk_num <int> 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, …
## $ rate <dbl> 0.0, 0.0, 1.3, 1.3, 1.3, 1.3, 1.3, 1.3, 1.3, 2.6, 2.6, 6.6, 15.9, 18.5, 35.7, 54.2, 83.4,... ## $ rate <dbl> 0.0, 0.0, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 2.4, 2.4, 6.1, 14.6, 17.0, 32.8, 49.9, 76.6, 9…
## $ weeklyrate <dbl> 0.0, 0.0, 1.3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.3, 0.0, 4.0, 9.3, 2.6, 17.2, 18.5, 29.1, 2... ## $ weeklyrate <dbl> 0.0, 0.0, 1.2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.2, 0.0, 3.6, 8.5, 2.4, 15.8, 17.0, 26.8, 21.…
## $ age <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,... ## $ age <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2…
## $ age_label <fct> 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0... ## $ age_label <fct> 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4 yr, 0-4…
## $ sea_label <chr> "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "... ## $ sea_label <chr> "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "20…
## $ sea_description <chr> "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11",... ## $ sea_description <chr> "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11", "…
## $ mmwrid <int> 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559,... ## $ mmwrid <int> 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559, 2…
### Retrieve ILINet Surveillance Data ### Retrieve ILINet Surveillance Data
@ -349,146 +364,146 @@ walk(c("national", "hhs", "census", "state"), ~{
}) })
``` ```
## Observations: 1,093 ## Observations: 1,111
## Variables: 16 ## Variables: 16
## $ region_type <chr> "National", "National", "National", "National", "National", "National", "National", "Natio... ## $ region_type <chr> "National", "National", "National", "National", "National", "National", "National", "Nationa…
## $ region <chr> "National", "National", "National", "National", "National", "National", "National", "Natio... ## $ region <chr> "National", "National", "National", "National", "National", "National", "National", "Nationa…
## $ year <int> 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1998, ... ## $ year <int> 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1998, 19…
## $ week <int> 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,... ## $ week <int> 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1…
## $ weighted_ili <dbl> 1.101480, 1.200070, 1.378760, 1.199200, 1.656180, 1.413260, 1.986800, 2.447490, 1.739010, ... ## $ weighted_ili <dbl> 1.101480, 1.200070, 1.378760, 1.199200, 1.656180, 1.413260, 1.986800, 2.447490, 1.739010, 1.…
## $ unweighted_ili <dbl> 1.216860, 1.280640, 1.239060, 1.144730, 1.261120, 1.282750, 1.445790, 1.647960, 1.675170, ... ## $ unweighted_ili <dbl> 1.216860, 1.280640, 1.239060, 1.144730, 1.261120, 1.282750, 1.445790, 1.647960, 1.675170, 1.…
## $ age_0_4 <dbl> 179, 199, 228, 188, 217, 178, 294, 288, 268, 299, 346, 348, 510, 579, 639, 690, 856, 824, ... ## $ age_0_4 <dbl> 179, 199, 228, 188, 217, 178, 294, 288, 268, 299, 346, 348, 510, 579, 639, 690, 856, 824, 88…
## $ age_25_49 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ age_25_49 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ age_25_64 <dbl> 157, 151, 153, 193, 162, 148, 240, 293, 206, 282, 268, 235, 404, 584, 759, 654, 679, 817, ... ## $ age_25_64 <dbl> 157, 151, 153, 193, 162, 148, 240, 293, 206, 282, 268, 235, 404, 584, 759, 654, 679, 817, 76…
## $ age_5_24 <dbl> 205, 242, 266, 236, 280, 281, 328, 456, 343, 415, 388, 362, 492, 576, 810, 1121, 1440, 160... ## $ age_5_24 <dbl> 205, 242, 266, 236, 280, 281, 328, 456, 343, 415, 388, 362, 492, 576, 810, 1121, 1440, 1600,…
## $ age_50_64 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ age_50_64 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ age_65 <dbl> 29, 23, 34, 36, 41, 48, 70, 63, 69, 102, 81, 59, 113, 207, 207, 148, 151, 196, 233, 146, 1... ## $ age_65 <dbl> 29, 23, 34, 36, 41, 48, 70, 63, 69, 102, 81, 59, 113, 207, 207, 148, 151, 196, 233, 146, 119…
## $ ilitotal <dbl> 570, 615, 681, 653, 700, 655, 932, 1100, 886, 1098, 1083, 1004, 1519, 1946, 2415, 2613, 31... ## $ ilitotal <dbl> 570, 615, 681, 653, 700, 655, 932, 1100, 886, 1098, 1083, 1004, 1519, 1946, 2415, 2613, 3126…
## $ num_of_providers <dbl> 192, 191, 219, 213, 213, 195, 248, 256, 252, 253, 242, 190, 251, 250, 254, 255, 245, 245, ... ## $ num_of_providers <dbl> 192, 191, 219, 213, 213, 195, 248, 256, 252, 253, 242, 190, 251, 250, 254, 255, 245, 245, 23…
## $ total_patients <dbl> 46842, 48023, 54961, 57044, 55506, 51062, 64463, 66749, 52890, 67887, 61314, 47719, 48429,... ## $ total_patients <dbl> 46842, 48023, 54961, 57044, 55506, 51062, 64463, 66749, 52890, 67887, 61314, 47719, 48429, 5…
## $ week_start <date> 1997-10-06, 1997-10-13, 1997-10-20, 1997-10-27, 1997-11-03, 1997-11-10, 1997-11-17, 1997-... ## $ week_start <date> 1997-09-28, 1997-10-05, 1997-10-12, 1997-10-19, 1997-10-26, 1997-11-02, 1997-11-09, 1997-11…
## # A tibble: 1,093 x 16 ## # A tibble: 1,111 x 16
## region_type region year week weighted_ili unweighted_ili age_0_4 age_25_49 age_25_64 age_5_24 age_50_64 age_65 ## region_type region year week weighted_ili unweighted_ili age_0_4 age_25_49 age_25_64 age_5_24 age_50_64 age_65
## <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 National National 1997 40 1.10 1.22 179 NA 157 205 NA 29 ## 1 National Natio… 1997 40 1.10 1.22 179 NA 157 205 NA 29
## 2 National National 1997 41 1.20 1.28 199 NA 151 242 NA 23 ## 2 National Natio… 1997 41 1.20 1.28 199 NA 151 242 NA 23
## 3 National National 1997 42 1.38 1.24 228 NA 153 266 NA 34 ## 3 National Natio… 1997 42 1.38 1.24 228 NA 153 266 NA 34
## 4 National National 1997 43 1.20 1.14 188 NA 193 236 NA 36 ## 4 National Natio… 1997 43 1.20 1.14 188 NA 193 236 NA 36
## 5 National National 1997 44 1.66 1.26 217 NA 162 280 NA 41 ## 5 National Natio… 1997 44 1.66 1.26 217 NA 162 280 NA 41
## 6 National National 1997 45 1.41 1.28 178 NA 148 281 NA 48 ## 6 National Natio… 1997 45 1.41 1.28 178 NA 148 281 NA 48
## 7 National National 1997 46 1.99 1.45 294 NA 240 328 NA 70 ## 7 National Natio… 1997 46 1.99 1.45 294 NA 240 328 NA 70
## 8 National National 1997 47 2.45 1.65 288 NA 293 456 NA 63 ## 8 National Natio… 1997 47 2.45 1.65 288 NA 293 456 NA 63
## 9 National National 1997 48 1.74 1.68 268 NA 206 343 NA 69 ## 9 National Natio… 1997 48 1.74 1.68 268 NA 206 343 NA 69
## 10 National National 1997 49 1.94 1.62 299 NA 282 415 NA 102 ## 10 National Natio… 1997 49 1.94 1.62 299 NA 282 415 NA 102
## # ... with 1,083 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>, ## # … with 1,101 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>,
## # week_start <date> ## # week_start <date>
<img src="README_files/figure-gfm/ili-df-1.png" width="672" /> <img src="README_files/figure-gfm/ili-df-1.png" width="672" />
## Observations: 10,930 ## Observations: 11,110
## Variables: 16 ## Variables: 16
## $ region_type <chr> "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", ... ## $ region_type <chr> "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "H…
## $ region <fct> Region 1, Region 2, Region 3, Region 4, Region 5, Region 6, Region 7, Region 8, Region 9, ... ## $ region <fct> Region 1, Region 2, Region 3, Region 4, Region 5, Region 6, Region 7, Region 8, Region 9, Re…
## $ year <int> 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, ... ## $ year <int> 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 19…
## $ week <int> 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 42... ## $ week <int> 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 42, …
## $ weighted_ili <dbl> 0.498535, 0.374963, 1.354280, 0.400338, 1.229260, 1.018980, 0.871791, 0.516017, 1.807610, ... ## $ weighted_ili <dbl> 0.498535, 0.374963, 1.354280, 0.400338, 1.229260, 1.018980, 0.871791, 0.516017, 1.807610, 4.…
## $ unweighted_ili <dbl> 0.623848, 0.384615, 1.341720, 0.450010, 0.901266, 0.747384, 1.152860, 0.422654, 2.258780, ... ## $ unweighted_ili <dbl> 0.623848, 0.384615, 1.341720, 0.450010, 0.901266, 0.747384, 1.152860, 0.422654, 2.258780, 4.…
## $ age_0_4 <dbl> 15, 0, 6, 12, 31, 2, 0, 2, 80, 31, 14, 0, 4, 21, 36, 2, 0, 0, 103, 19, 35, 0, 3, 19, 66, 2... ## $ age_0_4 <dbl> 15, 0, 6, 12, 31, 2, 0, 2, 80, 31, 14, 0, 4, 21, 36, 2, 0, 0, 103, 19, 35, 0, 3, 19, 66, 2, …
## $ age_25_49 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ age_25_49 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ age_25_64 <dbl> 7, 3, 7, 23, 24, 1, 4, 0, 76, 12, 14, 2, 19, 7, 23, 2, 0, 1, 76, 7, 15, 0, 17, 15, 29, 2, ... ## $ age_25_64 <dbl> 7, 3, 7, 23, 24, 1, 4, 0, 76, 12, 14, 2, 19, 7, 23, 2, 0, 1, 76, 7, 15, 0, 17, 15, 29, 2, 3,…
## $ age_5_24 <dbl> 22, 0, 15, 11, 30, 2, 18, 3, 74, 30, 29, 0, 16, 14, 41, 2, 13, 8, 84, 35, 35, 0, 24, 18, 7... ## $ age_5_24 <dbl> 22, 0, 15, 11, 30, 2, 18, 3, 74, 30, 29, 0, 16, 14, 41, 2, 13, 8, 84, 35, 35, 0, 24, 18, 75,…
## $ age_50_64 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ age_50_64 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ age_65 <dbl> 0, 0, 4, 0, 4, 0, 5, 0, 13, 3, 0, 0, 3, 2, 4, 0, 2, 0, 11, 1, 0, 1, 2, 2, 16, 0, 2, 0, 9, ... ## $ age_65 <dbl> 0, 0, 4, 0, 4, 0, 5, 0, 13, 3, 0, 0, 3, 2, 4, 0, 2, 0, 11, 1, 0, 1, 2, 2, 16, 0, 2, 0, 9, 2,…
## $ ilitotal <dbl> 44, 3, 32, 46, 89, 5, 27, 5, 243, 76, 57, 2, 42, 44, 104, 6, 15, 9, 274, 62, 85, 1, 46, 54... ## $ ilitotal <dbl> 44, 3, 32, 46, 89, 5, 27, 5, 243, 76, 57, 2, 42, 44, 104, 6, 15, 9, 274, 62, 85, 1, 46, 54, …
## $ num_of_providers <dbl> 32, 7, 16, 29, 49, 4, 14, 5, 23, 13, 29, 7, 17, 31, 48, 4, 14, 6, 23, 12, 40, 7, 15, 33, 6... ## $ num_of_providers <dbl> 32, 7, 16, 29, 49, 4, 14, 5, 23, 13, 29, 7, 17, 31, 48, 4, 14, 6, 23, 12, 40, 7, 15, 33, 64,…
## $ total_patients <dbl> 7053, 780, 2385, 10222, 9875, 669, 2342, 1183, 10758, 1575, 6987, 872, 2740, 11310, 9618, ... ## $ total_patients <dbl> 7053, 780, 2385, 10222, 9875, 669, 2342, 1183, 10758, 1575, 6987, 872, 2740, 11310, 9618, 68…
## $ week_start <date> 1997-10-06, 1997-10-06, 1997-10-06, 1997-10-06, 1997-10-06, 1997-10-06, 1997-10-06, 1997-... ## $ week_start <date> 1997-09-28, 1997-09-28, 1997-09-28, 1997-09-28, 1997-09-28, 1997-09-28, 1997-09-28, 1997-09…
## # A tibble: 10,930 x 16 ## # A tibble: 11,110 x 16
## region_type region year week weighted_ili unweighted_ili age_0_4 age_25_49 age_25_64 age_5_24 age_50_64 age_65 ## region_type region year week weighted_ili unweighted_ili age_0_4 age_25_49 age_25_64 age_5_24 age_50_64 age_65
## <chr> <fct> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## <chr> <fct> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 HHS Regions Region 1 1997 40 0.499 0.624 15 NA 7 22 NA 0 ## 1 HHS Regions Regio… 1997 40 0.499 0.624 15 NA 7 22 NA 0
## 2 HHS Regions Region 2 1997 40 0.375 0.385 0 NA 3 0 NA 0 ## 2 HHS Regions Regio… 1997 40 0.375 0.385 0 NA 3 0 NA 0
## 3 HHS Regions Region 3 1997 40 1.35 1.34 6 NA 7 15 NA 4 ## 3 HHS Regions Regio… 1997 40 1.35 1.34 6 NA 7 15 NA 4
## 4 HHS Regions Region 4 1997 40 0.400 0.450 12 NA 23 11 NA 0 ## 4 HHS Regions Regio… 1997 40 0.400 0.450 12 NA 23 11 NA 0
## 5 HHS Regions Region 5 1997 40 1.23 0.901 31 NA 24 30 NA 4 ## 5 HHS Regions Regio… 1997 40 1.23 0.901 31 NA 24 30 NA 4
## 6 HHS Regions Region 6 1997 40 1.02 0.747 2 NA 1 2 NA 0 ## 6 HHS Regions Regio… 1997 40 1.02 0.747 2 NA 1 2 NA 0
## 7 HHS Regions Region 7 1997 40 0.872 1.15 0 NA 4 18 NA 5 ## 7 HHS Regions Regio… 1997 40 0.872 1.15 0 NA 4 18 NA 5
## 8 HHS Regions Region 8 1997 40 0.516 0.423 2 NA 0 3 NA 0 ## 8 HHS Regions Regio… 1997 40 0.516 0.423 2 NA 0 3 NA 0
## 9 HHS Regions Region 9 1997 40 1.81 2.26 80 NA 76 74 NA 13 ## 9 HHS Regions Regio… 1997 40 1.81 2.26 80 NA 76 74 NA 13
## 10 HHS Regions Region 10 1997 40 4.74 4.83 31 NA 12 30 NA 3 ## 10 HHS Regions Regio… 1997 40 4.74 4.83 31 NA 12 30 NA 3
## # ... with 10,920 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>, ## # … with 11,100 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>,
## # week_start <date> ## # week_start <date>
<img src="README_files/figure-gfm/ili-df-2.png" width="672" /> <img src="README_files/figure-gfm/ili-df-2.png" width="672" />
## Observations: 9,837 ## Observations: 9,999
## Variables: 16 ## Variables: 16
## $ region_type <chr> "Census Regions", "Census Regions", "Census Regions", "Census Regions", "Census Regions", ... ## $ region_type <chr> "Census Regions", "Census Regions", "Census Regions", "Census Regions", "Census Regions", "C…
## $ region <chr> "New England", "Mid-Atlantic", "East North Central", "West North Central", "South Atlantic... ## $ region <chr> "New England", "Mid-Atlantic", "East North Central", "West North Central", "South Atlantic",…
## $ year <int> 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, ... ## $ year <int> 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 19…
## $ week <int> 40, 40, 40, 40, 40, 40, 40, 40, 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 42, 42, 42... ## $ week <int> 40, 40, 40, 40, 40, 40, 40, 40, 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 42, 42, 42, …
## $ weighted_ili <dbl> 0.4985350, 0.8441440, 0.7924860, 1.7640500, 0.5026620, 0.0542283, 1.0189800, 2.2587800, 2.... ## $ weighted_ili <dbl> 0.4985350, 0.8441440, 0.7924860, 1.7640500, 0.5026620, 0.0542283, 1.0189800, 2.2587800, 2.04…
## $ unweighted_ili <dbl> 0.6238480, 1.3213800, 0.8187380, 1.2793900, 0.7233800, 0.0688705, 0.7473840, 2.2763300, 3.... ## $ unweighted_ili <dbl> 0.6238480, 1.3213800, 0.8187380, 1.2793900, 0.7233800, 0.0688705, 0.7473840, 2.2763300, 3.23…
## $ age_0_4 <dbl> 15, 4, 28, 3, 14, 0, 2, 87, 26, 14, 4, 36, 0, 21, 0, 2, 93, 29, 35, 3, 65, 1, 19, 0, 2, 84... ## $ age_0_4 <dbl> 15, 4, 28, 3, 14, 0, 2, 87, 26, 14, 4, 36, 0, 21, 0, 2, 93, 29, 35, 3, 65, 1, 19, 0, 2, 84, …
## $ age_25_49 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ age_25_49 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ age_25_64 <dbl> 7, 8, 20, 8, 22, 3, 1, 71, 17, 14, 13, 23, 1, 14, 1, 2, 72, 11, 15, 11, 27, 5, 21, 0, 2, 5... ## $ age_25_64 <dbl> 7, 8, 20, 8, 22, 3, 1, 71, 17, 14, 13, 23, 1, 14, 1, 2, 72, 11, 15, 11, 27, 5, 21, 0, 2, 55,…
## $ age_5_24 <dbl> 22, 12, 28, 20, 14, 0, 2, 71, 36, 29, 8, 39, 18, 22, 0, 2, 80, 44, 35, 16, 74, 9, 24, 2, 2... ## $ age_5_24 <dbl> 22, 12, 28, 20, 14, 0, 2, 71, 36, 29, 8, 39, 18, 22, 0, 2, 80, 44, 35, 16, 74, 9, 24, 2, 2, …
## $ age_50_64 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ age_50_64 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ age_65 <dbl> 0, 4, 3, 6, 0, 0, 0, 15, 1, 0, 2, 2, 4, 3, 0, 0, 10, 2, 0, 3, 12, 6, 2, 0, 0, 9, 2, 0, 1, ... ## $ age_65 <dbl> 0, 4, 3, 6, 0, 0, 0, 15, 1, 0, 2, 2, 4, 3, 0, 0, 10, 2, 0, 3, 12, 6, 2, 0, 0, 9, 2, 0, 1, 14…
## $ ilitotal <dbl> 44, 28, 79, 37, 50, 3, 5, 244, 80, 57, 27, 100, 23, 60, 1, 6, 255, 86, 85, 33, 178, 21, 66... ## $ ilitotal <dbl> 44, 28, 79, 37, 50, 3, 5, 244, 80, 57, 27, 100, 23, 60, 1, 6, 255, 86, 85, 33, 178, 21, 66, …
## $ num_of_providers <dbl> 32, 13, 47, 17, 30, 9, 4, 16, 24, 29, 13, 46, 17, 32, 10, 4, 17, 23, 40, 12, 62, 16, 33, 1... ## $ num_of_providers <dbl> 32, 13, 47, 17, 30, 9, 4, 16, 24, 29, 13, 46, 17, 32, 10, 4, 17, 23, 40, 12, 62, 16, 33, 10,…
## $ total_patients <dbl> 7053, 2119, 9649, 2892, 6912, 4356, 669, 10719, 2473, 6987, 2384, 9427, 2823, 7591, 4947, ... ## $ total_patients <dbl> 7053, 2119, 9649, 2892, 6912, 4356, 669, 10719, 2473, 6987, 2384, 9427, 2823, 7591, 4947, 68…
## $ week_start <date> 1997-10-06, 1997-10-06, 1997-10-06, 1997-10-06, 1997-10-06, 1997-10-06, 1997-10-06, 1997-... ## $ week_start <date> 1997-09-28, 1997-09-28, 1997-09-28, 1997-09-28, 1997-09-28, 1997-09-28, 1997-09-28, 1997-09…
## # A tibble: 9,837 x 16 ## # A tibble: 9,999 x 16
## region_type region year week weighted_ili unweighted_ili age_0_4 age_25_49 age_25_64 age_5_24 age_50_64 age_65 ## region_type region year week weighted_ili unweighted_ili age_0_4 age_25_49 age_25_64 age_5_24 age_50_64 age_65
## <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Census Regi… New Engl… 1997 40 0.499 0.624 15 NA 7 22 NA 0 ## 1 Census Reg… New E… 1997 40 0.499 0.624 15 NA 7 22 NA 0
## 2 Census Regi… Mid-Atla… 1997 40 0.844 1.32 4 NA 8 12 NA 4 ## 2 Census Reg… Mid-A… 1997 40 0.844 1.32 4 NA 8 12 NA 4
## 3 Census Regi… East Nor… 1997 40 0.792 0.819 28 NA 20 28 NA 3 ## 3 Census Reg… East … 1997 40 0.792 0.819 28 NA 20 28 NA 3
## 4 Census Regi… West Nor… 1997 40 1.76 1.28 3 NA 8 20 NA 6 ## 4 Census Reg… West … 1997 40 1.76 1.28 3 NA 8 20 NA 6
## 5 Census Regi… South At… 1997 40 0.503 0.723 14 NA 22 14 NA 0 ## 5 Census Reg… South… 1997 40 0.503 0.723 14 NA 22 14 NA 0
## 6 Census Regi… East Sou… 1997 40 0.0542 0.0689 0 NA 3 0 NA 0 ## 6 Census Reg… East … 1997 40 0.0542 0.0689 0 NA 3 0 NA 0
## 7 Census Regi… West Sou… 1997 40 1.02 0.747 2 NA 1 2 NA 0 ## 7 Census Reg… West … 1997 40 1.02 0.747 2 NA 1 2 NA 0
## 8 Census Regi… Mountain 1997 40 2.26 2.28 87 NA 71 71 NA 15 ## 8 Census Reg… Mount… 1997 40 2.26 2.28 87 NA 71 71 NA 15
## 9 Census Regi… Pacific 1997 40 2.05 3.23 26 NA 17 36 NA 1 ## 9 Census Reg… Pacif… 1997 40 2.05 3.23 26 NA 17 36 NA 1
## 10 Census Regi… New Engl… 1997 41 0.643 0.816 14 NA 14 29 NA 0 ## 10 Census Reg… New E… 1997 41 0.643 0.816 14 NA 14 29 NA 0
## # ... with 9,827 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>, ## # … with 9,989 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>,
## # week_start <date> ## # week_start <date>
<img src="README_files/figure-gfm/ili-df-3.png" width="672" /> <img src="README_files/figure-gfm/ili-df-3.png" width="672" />
## Observations: 22,148 ## Observations: 23,120
## Variables: 16 ## Variables: 16
## $ region_type <chr> "States", "States", "States", "States", "States", "States", "States", "States", "States", ... ## $ region_type <chr> "States", "States", "States", "States", "States", "States", "States", "States", "States", "S…
## $ region <chr> "Alabama", "Alaska", "Arizona", "Arkansas", "California", "Colorado", "Connecticut", "Dela... ## $ region <chr> "Alabama", "Alaska", "Arizona", "Arkansas", "California", "Colorado", "Connecticut", "Delawa…
## $ year <int> 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, ... ## $ year <int> 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 20…
## $ week <int> 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40... ## $ week <int> 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, …
## $ weighted_ili <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ weighted_ili <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ unweighted_ili <dbl> 2.1347700, 0.8751460, 0.6747210, 0.6960560, 1.9541200, 0.6606840, 0.0783085, 0.1001250, 2.... ## $ unweighted_ili <dbl> 2.1347700, 0.8751460, 0.6747210, 0.6960560, 1.9541200, 0.6606840, 0.0783085, 0.1001250, 2.80…
## $ age_0_4 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ age_0_4 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ age_25_49 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ age_25_49 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ age_25_64 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ age_25_64 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ age_5_24 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ age_5_24 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ age_50_64 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ age_50_64 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ age_65 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA... ## $ age_65 <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ ilitotal <dbl> 249, 15, 172, 18, 632, 134, 3, 4, 73, NA, 647, 20, 19, 505, 65, 10, 39, 19, 391, 22, 117, ... ## $ ilitotal <dbl> 249, 15, 172, 18, 632, 134, 3, 4, 73, NA, 647, 20, 19, 505, 65, 10, 39, 19, 391, 22, 117, 16…
## $ num_of_providers <dbl> 35, 7, 49, 15, 112, 14, 12, 13, 4, NA, 62, 18, 12, 74, 44, 6, 40, 14, 41, 30, 17, 56, 47, ... ## $ num_of_providers <dbl> 35, 7, 49, 15, 112, 14, 12, 13, 4, NA, 62, 18, 12, 74, 44, 6, 40, 14, 41, 30, 17, 56, 47, 17…
## $ total_patients <dbl> 11664, 1714, 25492, 2586, 32342, 20282, 3831, 3995, 2599, NA, 40314, 1943, 4579, 39390, 12... ## $ total_patients <dbl> 11664, 1714, 25492, 2586, 32342, 20282, 3831, 3995, 2599, NA, 40314, 1943, 4579, 39390, 1252…
## $ week_start <date> 2010-10-04, 2010-10-04, 2010-10-04, 2010-10-04, 2010-10-04, 2010-10-04, 2010-10-04, 2010-... ## $ week_start <date> 2010-10-03, 2010-10-03, 2010-10-03, 2010-10-03, 2010-10-03, 2010-10-03, 2010-10-03, 2010-10…
## # A tibble: 22,148 x 16 ## # A tibble: 23,120 x 16
## region_type region year week weighted_ili unweighted_ili age_0_4 age_25_49 age_25_64 age_5_24 age_50_64 age_65 ## region_type region year week weighted_ili unweighted_ili age_0_4 age_25_49 age_25_64 age_5_24 age_50_64 age_65
## <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 States Alabama 2010 40 NA 2.13 NA NA NA NA NA NA ## 1 States Alaba… 2010 40 NA 2.13 NA NA NA NA NA NA
## 2 States Alaska 2010 40 NA 0.875 NA NA NA NA NA NA ## 2 States Alaska 2010 40 NA 0.875 NA NA NA NA NA NA
## 3 States Arizona 2010 40 NA 0.675 NA NA NA NA NA NA ## 3 States Arizo… 2010 40 NA 0.675 NA NA NA NA NA NA
## 4 States Arkansas 2010 40 NA 0.696 NA NA NA NA NA NA ## 4 States Arkan… 2010 40 NA 0.696 NA NA NA NA NA NA
## 5 States California 2010 40 NA 1.95 NA NA NA NA NA NA ## 5 States Calif… 2010 40 NA 1.95 NA NA NA NA NA NA
## 6 States Colorado 2010 40 NA 0.661 NA NA NA NA NA NA ## 6 States Color… 2010 40 NA 0.661 NA NA NA NA NA NA
## 7 States Connectic… 2010 40 NA 0.0783 NA NA NA NA NA NA ## 7 States Conne… 2010 40 NA 0.0783 NA NA NA NA NA NA
## 8 States Delaware 2010 40 NA 0.100 NA NA NA NA NA NA ## 8 States Delaw… 2010 40 NA 0.100 NA NA NA NA NA NA
## 9 States District … 2010 40 NA 2.81 NA NA NA NA NA NA ## 9 States Distr… 2010 40 NA 2.81 NA NA NA NA NA NA
## 10 States Florida 2010 40 NA NA NA NA NA NA NA NA ## 10 States Flori… 2010 40 NA NA NA NA NA NA NA NA
## # ... with 22,138 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>, ## # … with 23,110 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>,
## # week_start <date> ## # week_start <date>
<img src="README_files/figure-gfm/ili-df-4.png" width="672" /> <img src="README_files/figure-gfm/ili-df-4.png" width="672" />
@ -499,20 +514,20 @@ walk(c("national", "hhs", "census", "state"), ~{
ili_weekly_activity_indicators(2017) ili_weekly_activity_indicators(2017)
``` ```
## # A tibble: 1,782 x 8 ## # A tibble: 2,805 x 8
## statename url website activity_level activity_level_label weekend season weeknumber ## statename url website activity_level activity_level_l… weekend season weeknumber
## * <chr> <chr> <chr> <dbl> <chr> <date> <chr> <dbl> ## * <chr> <chr> <chr> <dbl> <chr> <date> <chr> <dbl>
## 1 Virgin Islands http://doh.vi.gov/ Influenza 0 Insufficient Data 2017-10-07 2017-18 40 ## 1 Alabama http://adph.org/influenza/ Influenza Sur… 2 Minimal 2017-10-07 2017-… 40
## 2 Virgin Islands http://doh.vi.gov/ Influenza 0 Insufficient Data 2017-10-14 2017-18 41 ## 2 Alaska "http://dhss.alaska.gov/dp… Influenza Sur… 1 Minimal 2017-10-07 2017-… 40
## 3 Virgin Islands http://doh.vi.gov/ Influenza 0 Insufficient Data 2017-10-21 2017-18 42 ## 3 Arizona http://www.azdhs.gov/phs/o… Influenza & R… 2 Minimal 2017-10-07 2017-… 40
## 4 Virgin Islands http://doh.vi.gov/ Influenza 0 Insufficient Data 2017-10-28 2017-18 43 ## 4 Arkansas http://www.healthy.arkansa… Communicable … 1 Minimal 2017-10-07 2017-… 40
## 5 Virgin Islands http://doh.vi.gov/ Influenza 0 Insufficient Data 2017-11-04 2017-18 44 ## 5 California https://www.cdph.ca.gov/Pr… Influenza (Fl… 2 Minimal 2017-10-07 2017-… 40
## 6 Virgin Islands http://doh.vi.gov/ Influenza 0 Insufficient Data 2017-11-11 2017-18 45 ## 6 Colorado https://www.colorado.gov/p… Influenza Sur… 1 Minimal 2017-10-07 2017-… 40
## 7 Virgin Islands http://doh.vi.gov/ Influenza 0 Insufficient Data 2017-12-02 2017-18 48 ## 7 Connecticut http://www.portal.ct.gov/D… Flu Statistics 1 Minimal 2017-10-07 2017-… 40
## 8 Virgin Islands http://doh.vi.gov/ Influenza 0 Insufficient Data 2017-12-09 2017-18 49 ## 8 Delaware http://dhss.delaware.gov/d… Weekly Influe… 1 Minimal 2017-10-07 2017-… 40
## 9 Virgin Islands http://doh.vi.gov/ Influenza 0 Insufficient Data 2017-12-23 2017-18 51 ## 9 District of… http://doh.dc.gov/page/inf… Influenza Inf… 2 Minimal 2017-10-07 2017-… 40
## 10 Virgin Islands http://doh.vi.gov/ Influenza 0 Insufficient Data 2017-12-30 2017-18 52 ## 10 Florida "http://www.floridahealth.… Weekly Influe… 1 Minimal 2017-10-07 2017-… 40
## # ... with 1,772 more rows ## # … with 2,795 more rows
``` r ``` r
xdf <- map_df(2008:2017, ili_weekly_activity_indicators) xdf <- map_df(2008:2017, ili_weekly_activity_indicators)
@ -537,20 +552,20 @@ count(xdf, weekend, activity_level_label) %>%
(nat_pi <- pi_mortality("national")) (nat_pi <- pi_mortality("national"))
``` ```
## # A tibble: 464 x 19 ## # A tibble: 483 x 19
## seasonid baseline threshold percent_pni percent_complete number_influenza number_pneumonia all_deaths total_pni ## seasonid baseline threshold percent_pni percent_complete number_influenza number_pneumonia all_deaths total_pni
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 57 0.057 0.06 0.0580 1 16 3020 52110 3036 ## 1 58 0.055 0.0580 0.0560 1 10 2880 51416 2890
## 2 57 0.0580 0.061 0.059 1 18 3000 51572 3018 ## 2 58 0.0560 0.059 0.055 1 12 2765 50411 2777
## 3 57 0.059 0.062 0.061 1 28 3154 52222 3182 ## 3 58 0.0560 0.06 0.0560 1 18 2802 50742 2820
## 4 57 0.06 0.063 0.063 1 23 3279 52548 3302 ## 4 58 0.057 0.061 0.057 1 22 2895 51425 2917
## 5 57 0.06 0.063 0.061 1 36 3214 53679 3250 ## 5 58 0.0580 0.062 0.0560 1 23 2819 51136 2842
## 6 57 0.061 0.064 0.06 1 45 3177 53258 3222 ## 6 58 0.059 0.063 0.0560 1 28 2819 50945 2847
## 7 57 0.062 0.065 0.063 1 50 3315 53771 3365 ## 7 58 0.06 0.064 0.0580 1 25 2953 51618 2978
## 8 57 0.063 0.066 0.06 1 48 3200 54120 3248 ## 8 58 0.061 0.065 0.057 1 31 2905 51109 2936
## 9 57 0.064 0.067 0.065 1 83 3491 54760 3574 ## 9 58 0.062 0.066 0.059 1 34 2923 49720 2957
## 10 57 0.065 0.068 0.066 1 118 3526 55595 3644 ## 10 58 0.064 0.067 0.06 1 48 2857 48381 2905
## # ... with 454 more rows, and 10 more variables: weeknumber <chr>, geo_description <chr>, age_label <chr>, ## # … with 473 more rows, and 10 more variables: weeknumber <chr>, geo_description <chr>, age_label <chr>,
## # wk_start <date>, wk_end <date>, year_wk_num <int>, mmwrid <chr>, coverage_area <chr>, region_name <chr>, ## # wk_start <date>, wk_end <date>, year_wk_num <int>, mmwrid <chr>, coverage_area <chr>, region_name <chr>,
## # callout <chr> ## # callout <chr>
@ -578,7 +593,7 @@ select(nat_pi, wk_end, percent_pni, baseline, threshold) %>%
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 55 NA NA 0.047 1 0 46 979 46 ## 1 55 NA NA 0.047 1 0 46 979 46
## 2 55 NA NA 0.038 0.963 0 34 889 34 ## 2 55 NA NA 0.038 0.963 0 34 889 34
## 3 55 NA NA 0.053 1 0 52 977 52 ## 3 55 NA NA 0.053 1 0 52 978 52
## 4 55 NA NA 0.07 1 0 68 968 68 ## 4 55 NA NA 0.07 1 0 68 968 68
## 5 55 NA NA 0.053 0.981 0 48 906 48 ## 5 55 NA NA 0.053 0.981 0 48 906 48
## 6 55 NA NA 0.0580 1 0 56 968 56 ## 6 55 NA NA 0.0580 1 0 56 968 56
@ -586,7 +601,7 @@ select(nat_pi, wk_end, percent_pni, baseline, threshold) %>%
## 8 55 NA NA 0.062 1 1 63 1031 64 ## 8 55 NA NA 0.062 1 1 63 1031 64
## 9 55 NA NA 0.0560 1 0 55 976 55 ## 9 55 NA NA 0.0560 1 0 55 976 55
## 10 55 NA NA 0.054 1 0 56 1045 56 ## 10 55 NA NA 0.054 1 0 56 1045 56
## # ... with 2,694 more rows, and 10 more variables: weeknumber <chr>, geo_description <chr>, age_label <chr>, ## # … with 2,694 more rows, and 10 more variables: weeknumber <chr>, geo_description <chr>, age_label <chr>,
## # wk_start <date>, wk_end <date>, year_wk_num <int>, mmwrid <chr>, coverage_area <chr>, region_name <chr>, ## # wk_start <date>, wk_end <date>, year_wk_num <int>, mmwrid <chr>, coverage_area <chr>, region_name <chr>,
## # callout <chr> ## # callout <chr>
@ -597,17 +612,17 @@ select(nat_pi, wk_end, percent_pni, baseline, threshold) %>%
## # A tibble: 520 x 19 ## # A tibble: 520 x 19
## seasonid baseline threshold percent_pni percent_complete number_influenza number_pneumonia all_deaths total_pni ## seasonid baseline threshold percent_pni percent_complete number_influenza number_pneumonia all_deaths total_pni
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 55 0.066 0.073 0.071 1 0 178 2520 178 ## 1 55 0.065 0.072 0.07 1 0 178 2525 178
## 2 55 0.067 0.074 0.063 1 0 159 2505 159 ## 2 55 0.065 0.073 0.064 1 0 160 2512 160
## 3 55 0.067 0.075 0.0580 1 1 141 2452 142 ## 3 55 0.066 0.074 0.0580 1 1 141 2457 142
## 4 55 0.068 0.076 0.071 1 0 171 2422 171 ## 4 55 0.067 0.075 0.07 1 0 171 2426 171
## 5 55 0.07 0.077 0.066 1 2 166 2554 168 ## 5 55 0.068 0.076 0.065 1 2 166 2565 168
## 6 55 0.071 0.078 0.067 1 1 160 2404 161 ## 6 55 0.069 0.077 0.067 1 1 162 2415 163
## 7 55 0.072 0.079 0.079 1 0 195 2478 195 ## 7 55 0.071 0.078 0.079 1 0 198 2491 198
## 8 55 0.073 0.081 0.072 1 1 176 2463 177 ## 8 55 0.072 0.08 0.072 1 1 176 2469 177
## 9 55 0.074 0.0820 0.067 1 3 154 2347 157 ## 9 55 0.073 0.081 0.067 1 3 154 2353 157
## 10 55 0.076 0.083 0.062 1 0 151 2437 151 ## 10 55 0.075 0.0820 0.062 1 0 151 2441 151
## # ... with 510 more rows, and 10 more variables: weeknumber <chr>, geo_description <chr>, age_label <chr>, ## # … with 510 more rows, and 10 more variables: weeknumber <chr>, geo_description <chr>, age_label <chr>,
## # wk_start <date>, wk_end <date>, year_wk_num <int>, mmwrid <chr>, coverage_area <chr>, region_name <chr>, ## # wk_start <date>, wk_end <date>, year_wk_num <int>, mmwrid <chr>, coverage_area <chr>, region_name <chr>,
## # callout <chr> ## # callout <chr>
@ -618,19 +633,19 @@ state_data_providers()
``` ```
## # A tibble: 59 x 5 ## # A tibble: 59 x 5
## statename statehealthdeptname url statewebsitename statefluphonenum ## statename statehealthdeptname url statewebsitename statefluphonenum
## * <chr> <chr> <chr> <chr> <chr> ## * <chr> <chr> <chr> <chr> <chr>
## 1 Alabama Alabama Department of Public Health http://… Influenza Surve… 334-206-5300 ## 1 Alabama Alabama Department of Publi… http://adph.org/influenza/ Influenza Surveillance 334-206-5300
## 2 Alaska State of Alaska Health and Social Services "http:/… Influenza Surve… 907-269-8000 ## 2 Alaska State of Alaska Health and … "http://dhss.alaska.gov/dph/Epi/… Influenza Surveillance… 907-269-8000
## 3 Arizona Arizona Department of Health Services http://… Influenza & RSV… 602-542-1025 ## 3 Arizona Arizona Department of Healt… http://www.azdhs.gov/phs/oids/ep… Influenza & RSV Survei… 602-542-1025
## 4 Arkansas Arkansas Department of Health http://… Communicable Di… 501-661-2000 ## 4 Arkansas Arkansas Department of Heal… http://www.healthy.arkansas.gov/… Communicable Disease a… 501-661-2000
## 5 California California Department of Public Health https:/… Influenza (Flu) 916-558-1784 ## 5 California California Department of Pu… https://www.cdph.ca.gov/Programs… Influenza (Flu) 916-558-1784
## 6 Colorado Colorado Department of Public Health and Environment https:/… Influenza Surve… 303-692-2000 ## 6 Colorado Colorado Department of Publ… https://www.colorado.gov/pacific… Influenza Surveillance 303-692-2000
## 7 Connecticut Connecticut Department of Public Health http://… Flu Statistics 860-509-8000 ## 7 Connecticut Connecticut Department of P… http://www.portal.ct.gov/DPH/Inf… Flu Statistics 860-509-8000
## 8 Delaware Delaware Health and Social Services http://… Weekly Influenz… 302-744-4700 ## 8 Delaware Delaware Health and Social … http://dhss.delaware.gov/dhss/dp… Weekly Influenza Surve… 302-744-4700
## 9 District of Columbia District of Columbia Department of Health http://… Influenza Infor… 202-442-5955 ## 9 District of … District of Columbia Depart… http://doh.dc.gov/page/influenza… Influenza Information 202-442-5955
## 10 Florida Florida Department of Health "http:/… Weekly Influenz… 850-245-4300 ## 10 Florida Florida Department of Health "http://www.floridahealth.gov/di… Weekly Influenza Surve… 850-245-4300
## # ... with 49 more rows ## # … with 49 more rows
### Retrieve WHO/NREVSS Surveillance Data ### Retrieve WHO/NREVSS Surveillance Data
@ -654,32 +669,32 @@ glimpse(xdat <- who_nrevss("national"))
## ..$ b : int [1:940] 0 0 1 0 0 0 1 1 1 1 ... ## ..$ b : int [1:940] 0 0 1 0 0 0 1 1 1 1 ...
## ..$ h3n2v : int [1:940] 0 0 0 0 0 0 0 0 0 0 ... ## ..$ h3n2v : int [1:940] 0 0 0 0 0 0 0 0 0 0 ...
## ..$ wk_date : Date[1:940], format: "1997-09-28" "1997-10-05" "1997-10-12" "1997-10-19" ... ## ..$ wk_date : Date[1:940], format: "1997-09-28" "1997-10-05" "1997-10-12" "1997-10-19" ...
## $ public_health_labs :Classes 'tbl_df', 'tbl' and 'data.frame': 153 obs. of 13 variables: ## $ public_health_labs :Classes 'tbl_df', 'tbl' and 'data.frame': 171 obs. of 13 variables:
## ..$ region_type : chr [1:153] "National" "National" "National" "National" ... ## ..$ region_type : chr [1:171] "National" "National" "National" "National" ...
## ..$ region : chr [1:153] "National" "National" "National" "National" ... ## ..$ region : chr [1:171] "National" "National" "National" "National" ...
## ..$ year : int [1:153] 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 ... ## ..$ year : int [1:171] 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 ...
## ..$ week : int [1:153] 40 41 42 43 44 45 46 47 48 49 ... ## ..$ week : int [1:171] 40 41 42 43 44 45 46 47 48 49 ...
## ..$ total_specimens : int [1:153] 1139 1152 1198 1244 1465 1393 1458 1157 1550 1518 ... ## ..$ total_specimens : int [1:171] 1139 1152 1198 1244 1465 1393 1458 1157 1550 1518 ...
## ..$ a_2009_h1n1 : int [1:153] 4 5 10 9 4 11 17 17 27 38 ... ## ..$ a_2009_h1n1 : int [1:171] 4 5 10 9 4 11 17 17 27 38 ...
## ..$ a_h3 : int [1:153] 65 41 50 31 23 34 42 24 36 37 ... ## ..$ a_h3 : int [1:171] 65 41 50 31 23 34 42 24 36 37 ...
## ..$ a_subtyping_not_performed: int [1:153] 2 2 1 4 4 1 1 0 3 3 ... ## ..$ a_subtyping_not_performed: int [1:171] 2 2 1 4 4 1 1 0 3 3 ...
## ..$ b : int [1:153] 10 7 8 9 9 10 4 4 9 11 ... ## ..$ b : int [1:171] 10 7 8 9 9 10 4 4 9 11 ...
## ..$ bvic : int [1:153] 0 3 3 1 1 4 0 3 3 2 ... ## ..$ bvic : int [1:171] 0 3 3 1 1 4 0 3 3 2 ...
## ..$ byam : int [1:153] 1 0 2 4 4 2 4 9 12 11 ... ## ..$ byam : int [1:171] 1 0 2 4 4 2 4 9 12 11 ...
## ..$ h3n2v : int [1:153] 0 0 0 0 0 0 0 0 0 0 ... ## ..$ h3n2v : int [1:171] 0 0 0 0 0 0 0 0 0 0 ...
## ..$ wk_date : Date[1:153], format: "2015-10-04" "2015-10-11" "2015-10-18" "2015-10-25" ... ## ..$ wk_date : Date[1:171], format: "2015-10-04" "2015-10-11" "2015-10-18" "2015-10-25" ...
## $ clinical_labs :Classes 'tbl_df', 'tbl' and 'data.frame': 153 obs. of 11 variables: ## $ clinical_labs :Classes 'tbl_df', 'tbl' and 'data.frame': 171 obs. of 11 variables:
## ..$ region_type : chr [1:153] "National" "National" "National" "National" ... ## ..$ region_type : chr [1:171] "National" "National" "National" "National" ...
## ..$ region : chr [1:153] "National" "National" "National" "National" ... ## ..$ region : chr [1:171] "National" "National" "National" "National" ...
## ..$ year : int [1:153] 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 ... ## ..$ year : int [1:171] 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 ...
## ..$ week : int [1:153] 40 41 42 43 44 45 46 47 48 49 ... ## ..$ week : int [1:171] 40 41 42 43 44 45 46 47 48 49 ...
## ..$ total_specimens : int [1:153] 12029 13111 13441 13537 14687 15048 15250 15234 16201 16673 ... ## ..$ total_specimens : int [1:171] 12029 13111 13441 13537 14687 15048 15250 15234 16201 16673 ...
## ..$ total_a : int [1:153] 84 116 97 98 97 122 84 119 145 140 ... ## ..$ total_a : int [1:171] 84 116 97 98 97 122 84 119 145 140 ...
## ..$ total_b : int [1:153] 43 54 52 52 68 86 98 92 81 106 ... ## ..$ total_b : int [1:171] 43 54 52 52 68 86 98 92 81 106 ...
## ..$ percent_positive: num [1:153] 1.06 1.3 1.11 1.11 1.12 ... ## ..$ percent_positive: num [1:171] 1.06 1.3 1.11 1.11 1.12 ...
## ..$ percent_a : num [1:153] 0.698 0.885 0.722 0.724 0.66 ... ## ..$ percent_a : num [1:171] 0.698 0.885 0.722 0.724 0.66 ...
## ..$ percent_b : num [1:153] 0.357 0.412 0.387 0.384 0.463 ... ## ..$ percent_b : num [1:171] 0.357 0.412 0.387 0.384 0.463 ...
## ..$ wk_date : Date[1:153], format: "2015-10-04" "2015-10-11" "2015-10-18" "2015-10-25" ... ## ..$ wk_date : Date[1:171], format: "2015-10-04" "2015-10-11" "2015-10-18" "2015-10-25" ...
``` r ``` r
mutate(xdat$combined_prior_to_2015_16, mutate(xdat$combined_prior_to_2015_16,
@ -699,19 +714,19 @@ who_nrevss("hhs", years=2016)
## $public_health_labs ## $public_health_labs
## # A tibble: 520 x 13 ## # A tibble: 520 x 13
## region_type region year week total_specimens a_2009_h1n1 a_h3 a_subtyping_not… b bvic byam h3n2v wk_date ## region_type region year week total_specimens a_2009_h1n1 a_h3 a_subtyping_not… b bvic byam h3n2v wk_date
## <chr> <chr> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <date> ## <chr> <chr> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <date>
## 1 HHS Regions Regio… 2016 40 31 0 6 0 0 0 0 0 2016-10-02 ## 1 HHS Regions Region… 2016 40 31 0 6 0 0 0 0 0 2016-10-02
## 2 HHS Regions Regio… 2016 40 31 0 6 0 0 2 0 0 2016-10-02 ## 2 HHS Regions Region… 2016 40 31 0 6 0 0 2 0 0 2016-10-02
## 3 HHS Regions Regio… 2016 40 112 2 2 0 0 0 0 0 2016-10-02 ## 3 HHS Regions Region… 2016 40 112 2 2 0 0 0 0 0 2016-10-02
## 4 HHS Regions Regio… 2016 40 112 1 11 0 1 2 0 0 2016-10-02 ## 4 HHS Regions Region… 2016 40 112 1 11 0 1 2 0 0 2016-10-02
## 5 HHS Regions Regio… 2016 40 204 0 7 0 0 0 1 0 2016-10-02 ## 5 HHS Regions Region… 2016 40 204 0 7 0 0 0 1 0 2016-10-02
## 6 HHS Regions Regio… 2016 40 39 1 1 0 0 0 0 0 2016-10-02 ## 6 HHS Regions Region… 2016 40 39 1 1 0 0 0 0 0 2016-10-02
## 7 HHS Regions Regio… 2016 40 24 0 2 0 0 1 0 0 2016-10-02 ## 7 HHS Regions Region… 2016 40 24 0 2 0 0 1 0 0 2016-10-02
## 8 HHS Regions Regio… 2016 40 46 2 8 0 0 0 0 0 2016-10-02 ## 8 HHS Regions Region… 2016 40 46 2 8 0 0 0 0 0 2016-10-02
## 9 HHS Regions Regio… 2016 40 186 3 27 0 0 0 3 0 2016-10-02 ## 9 HHS Regions Region… 2016 40 186 3 27 0 0 0 3 0 2016-10-02
## 10 HHS Regions Regio… 2016 40 113 0 17 0 0 0 0 0 2016-10-02 ## 10 HHS Regions Region… 2016 40 113 0 17 0 0 0 0 0 2016-10-02
## # ... with 510 more rows ## # … with 510 more rows
## ##
## $clinical_labs ## $clinical_labs
## # A tibble: 520 x 11 ## # A tibble: 520 x 11
@ -727,7 +742,7 @@ who_nrevss("hhs", years=2016)
## 8 HHS Regions Region 8 2016 40 913 8 0 0.876 0.876 0 2016-10-02 ## 8 HHS Regions Region 8 2016 40 913 8 0 0.876 0.876 0 2016-10-02
## 9 HHS Regions Region 9 2016 40 992 6 1 0.706 0.605 0.101 2016-10-02 ## 9 HHS Regions Region 9 2016 40 992 6 1 0.706 0.605 0.101 2016-10-02
## 10 HHS Regions Region 10 2016 40 590 14 0 2.37 2.37 0 2016-10-02 ## 10 HHS Regions Region 10 2016 40 590 14 0 2.37 2.37 0 2016-10-02
## # ... with 510 more rows ## # … with 510 more rows
``` r ``` r
who_nrevss("census", years=2016) who_nrevss("census", years=2016)
@ -735,35 +750,35 @@ who_nrevss("census", years=2016)
## $public_health_labs ## $public_health_labs
## # A tibble: 468 x 13 ## # A tibble: 468 x 13
## region_type region year week total_specimens a_2009_h1n1 a_h3 a_subtyping_not… b bvic byam h3n2v wk_date ## region_type region year week total_specimens a_2009_h1n1 a_h3 a_subtyping_not… b bvic byam h3n2v wk_date
## <chr> <chr> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <date> ## <chr> <chr> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int> <date>
## 1 Census Reg… New E… 2016 40 31 0 6 0 0 0 0 0 2016-10-02 ## 1 Census Regi… New E… 2016 40 31 0 6 0 0 0 0 0 2016-10-02
## 2 Census Reg… Mid-A… 2016 40 50 0 8 0 0 2 0 0 2016-10-02 ## 2 Census Regi… Mid-A… 2016 40 50 0 8 0 0 2 0 0 2016-10-02
## 3 Census Reg… East … 2016 40 139 0 4 0 0 0 1 0 2016-10-02 ## 3 Census Regi… East … 2016 40 139 0 4 0 0 0 1 0 2016-10-02
## 4 Census Reg… West … 2016 40 103 0 6 0 0 1 0 0 2016-10-02 ## 4 Census Regi… West … 2016 40 103 0 6 0 0 1 0 0 2016-10-02
## 5 Census Reg… South… 2016 40 181 3 11 0 1 2 0 0 2016-10-02 ## 5 Census Regi… South… 2016 40 181 3 11 0 1 2 0 0 2016-10-02
## 6 Census Reg… East … 2016 40 24 0 0 0 0 0 0 0 2016-10-02 ## 6 Census Regi… East … 2016 40 24 0 0 0 0 0 0 0 2016-10-02
## 7 Census Reg… West … 2016 40 27 0 1 0 0 0 0 0 2016-10-02 ## 7 Census Regi… West … 2016 40 27 0 1 0 0 0 0 0 2016-10-02
## 8 Census Reg… Mount… 2016 40 54 3 10 0 0 0 1 0 2016-10-02 ## 8 Census Regi… Mount… 2016 40 54 3 10 0 0 0 1 0 2016-10-02
## 9 Census Reg… Pacif… 2016 40 289 3 41 0 0 0 2 0 2016-10-02 ## 9 Census Regi… Pacif… 2016 40 289 3 41 0 0 0 2 0 2016-10-02
## 10 Census Reg… New E… 2016 41 14 0 2 0 0 0 0 0 2016-10-09 ## 10 Census Regi… New E… 2016 41 14 0 2 0 0 0 0 0 2016-10-09
## # ... with 458 more rows ## # … with 458 more rows
## ##
## $clinical_labs ## $clinical_labs
## # A tibble: 468 x 11 ## # A tibble: 468 x 11
## region_type region year week total_specimens total_a total_b percent_positive percent_a percent_b wk_date ## region_type region year week total_specimens total_a total_b percent_positive percent_a percent_b wk_date
## <chr> <chr> <int> <int> <int> <int> <int> <dbl> <dbl> <dbl> <date> ## <chr> <chr> <int> <int> <int> <int> <int> <dbl> <dbl> <dbl> <date>
## 1 Census Regions New Engl… 2016 40 654 5 1 0.917 0.765 0.153 2016-10-02 ## 1 Census Regio… New England 2016 40 654 5 1 0.917 0.765 0.153 2016-10-02
## 2 Census Regions Mid-Atla… 2016 40 1579 10 4 0.887 0.633 0.253 2016-10-02 ## 2 Census Regio… Mid-Atlant… 2016 40 1579 10 4 0.887 0.633 0.253 2016-10-02
## 3 Census Regions East Nor… 2016 40 2176 6 5 0.506 0.276 0.230 2016-10-02 ## 3 Census Regio… East North… 2016 40 2176 6 5 0.506 0.276 0.230 2016-10-02
## 4 Census Regions West Nor… 2016 40 1104 3 0 0.272 0.272 0 2016-10-02 ## 4 Census Regio… West North… 2016 40 1104 3 0 0.272 0.272 0 2016-10-02
## 5 Census Regions South At… 2016 40 2785 43 62 3.77 1.54 2.23 2016-10-02 ## 5 Census Regio… South Atla… 2016 40 2785 43 62 3.77 1.54 2.23 2016-10-02
## 6 Census Regions East Sou… 2016 40 844 4 4 0.948 0.474 0.474 2016-10-02 ## 6 Census Regio… East South… 2016 40 844 4 4 0.948 0.474 0.474 2016-10-02
## 7 Census Regions West Sou… 2016 40 1738 21 13 1.96 1.21 0.748 2016-10-02 ## 7 Census Regio… West South… 2016 40 1738 21 13 1.96 1.21 0.748 2016-10-02
## 8 Census Regions Mountain 2016 40 1067 8 0 0.750 0.750 0 2016-10-02 ## 8 Census Regio… Mountain 2016 40 1067 8 0 0.750 0.750 0 2016-10-02
## 9 Census Regions Pacific 2016 40 1433 20 1 1.47 1.40 0.0698 2016-10-02 ## 9 Census Regio… Pacific 2016 40 1433 20 1 1.47 1.40 0.0698 2016-10-02
## 10 Census Regions New Engl… 2016 41 810 5 1 0.741 0.617 0.123 2016-10-09 ## 10 Census Regio… New England 2016 41 810 5 1 0.741 0.617 0.123 2016-10-09
## # ... with 458 more rows ## # … with 458 more rows
``` r ``` r
who_nrevss("state", years=2016) who_nrevss("state", years=2016)
@ -771,35 +786,43 @@ who_nrevss("state", years=2016)
## $public_health_labs ## $public_health_labs
## # A tibble: 54 x 12 ## # A tibble: 54 x 12
## region_type region season_descript… total_specimens a_2009_h1n1 a_h3 a_subtyping_not_p… b bvic byam h3n2v ## region_type region season_descript… total_specimens a_2009_h1n1 a_h3 a_subtyping_not… b bvic byam h3n2v
## <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> ## <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 States Alabama Season 2016-17 570 3 227 1 2 15 14 0 ## 1 States Alaba… Season 2016-17 570 3 227 1 2 15 14 0
## 2 States Alaska Season 2016-17 5222 14 905 3 252 2 11 0 ## 2 States Alaska Season 2016-17 5222 14 905 3 252 2 11 0
## 3 States Arizona Season 2016-17 2975 63 1630 0 5 227 578 0 ## 3 States Arizo… Season 2016-17 2975 63 1630 0 5 227 578 0
## 4 States Arkansas Season 2016-17 121 0 51 0 0 4 0 0 ## 4 States Arkan… Season 2016-17 121 0 51 0 0 4 0 0
## 5 States California Season 2016-17 14074 184 4696 120 116 28 152 0 ## 5 States Calif… Season 2016-17 14074 184 4696 120 116 28 152 0
## 6 States Colorado Season 2016-17 714 3 267 2 4 31 219 0 ## 6 States Color… Season 2016-17 714 3 267 2 4 31 219 0
## 7 States Connectic… Season 2016-17 1348 19 968 0 0 62 263 0 ## 7 States Conne… Season 2016-17 1348 19 968 0 0 62 263 0
## 8 States Delaware Season 2016-17 3090 5 659 4 11 27 127 1 ## 8 States Delaw… Season 2016-17 3090 5 659 4 11 27 127 1
## 9 States District … Season 2016-17 73 1 34 0 3 0 4 0 ## 9 States Distr… Season 2016-17 73 1 34 0 3 0 4 0
## 10 States Florida Season 2016-17 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> ## 10 States Flori… Season 2016-17 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## # ... with 44 more rows, and 1 more variable: wk_date <date> ## # … with 44 more rows, and 1 more variable: wk_date <date>
## ##
## $clinical_labs ## $clinical_labs
## # A tibble: 2,808 x 11 ## # A tibble: 2,808 x 11
## region_type region year week total_specimens total_a total_b percent_positive percent_a percent_b wk_date ## region_type region year week total_specimens total_a total_b percent_positive percent_a percent_b wk_date
## <chr> <chr> <int> <int> <chr> <chr> <chr> <chr> <chr> <chr> <date> ## <chr> <chr> <int> <int> <chr> <chr> <chr> <chr> <chr> <chr> <date>
## 1 States Alabama 2016 40 406 4 1 1.23 0.99 0.25 2016-10-02 ## 1 States Alabama 2016 40 406 4 1 1.23 0.99 0.25 2016-10-02
## 2 States Alaska 2016 40 <NA> <NA> <NA> <NA> <NA> <NA> 2016-10-02 ## 2 States Alaska 2016 40 <NA> <NA> <NA> <NA> <NA> <NA> 2016-10-02
## 3 States Arizona 2016 40 133 0 0 0 0 0 2016-10-02 ## 3 States Arizona 2016 40 133 0 0 0 0 0 2016-10-02
## 4 States Arkansas 2016 40 47 0 0 0 0 0 2016-10-02 ## 4 States Arkansas 2016 40 47 0 0 0 0 0 2016-10-02
## 5 States California 2016 40 668 2 0 0.3 0.3 0 2016-10-02 ## 5 States California 2016 40 668 2 0 0.3 0.3 0 2016-10-02
## 6 States Colorado 2016 40 260 0 0 0 0 0 2016-10-02 ## 6 States Colorado 2016 40 260 0 0 0 0 0 2016-10-02
## 7 States Connecticut 2016 40 199 3 0 1.51 1.51 0 2016-10-02 ## 7 States Connecticut 2016 40 199 3 0 1.51 1.51 0 2016-10-02
## 8 States Delaware 2016 40 40 0 0 0 0 0 2016-10-02 ## 8 States Delaware 2016 40 40 0 0 0 0 0 2016-10-02
## 9 States District of… 2016 40 <NA> <NA> <NA> <NA> <NA> <NA> 2016-10-02 ## 9 States District of … 2016 40 <NA> <NA> <NA> <NA> <NA> <NA> 2016-10-02
## 10 States Florida 2016 40 <NA> <NA> <NA> <NA> <NA> <NA> 2016-10-02 ## 10 States Florida 2016 40 <NA> <NA> <NA> <NA> <NA> <NA> 2016-10-02
## # ... with 2,798 more rows ## # … with 2,798 more rows
## cdcfluview Metrics
| Lang | \# Files | (%) | LoC | (%) | Blank lines | (%) | \# Lines | (%) |
| :--- | -------: | ---: | --: | ---: | ----------: | ---: | -------: | ---: |
| R | 21 | 0.91 | 837 | 0.88 | 302 | 0.79 | 521 | 0.85 |
| Rmd | 1 | 0.04 | 83 | 0.09 | 67 | 0.18 | 88 | 0.14 |
| make | 1 | 0.04 | 32 | 0.03 | 11 | 0.03 | 1 | 0.00 |
## Code of Conduct ## Code of Conduct

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5
man/get_flu_data.Rd
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@ -4,8 +4,9 @@
\alias{get_flu_data} \alias{get_flu_data}
\title{Retrieves state, regional or national influenza statistics from the CDC (deprecated)} \title{Retrieves state, regional or national influenza statistics from the CDC (deprecated)}
\usage{ \usage{
get_flu_data(region = "hhs", sub_region = 1:10, data_source = "ilinet", get_flu_data(region = "hhs", sub_region = 1:10,
years = as.numeric(format(Sys.Date(), "\%Y"))) data_source = "ilinet", years = as.numeric(format(Sys.Date(),
"\%Y")))
} }
\arguments{ \arguments{
\item{region}{one of "\code{hhs}", "\code{census}", "\code{national}", \item{region}{one of "\code{hhs}", "\code{census}", "\code{national}",

5
man/ilinet.Rd
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@ -27,7 +27,7 @@ This function retrieves current and historical ILINet surveillance data for
the identified region. the identified region.
} }
\examples{ \examples{
national_ili <- ilinet("national", years=2017) national_ili <- ilinet("national", years = 2017)
\dontrun{ \dontrun{
hhs_ili <- ilinet("hhs") hhs_ili <- ilinet("hhs")
census_ili <- ilinet("census") census_ili <- ilinet("census")
@ -36,7 +36,8 @@ state_ili <- ilinet("state")
library(purrr) library(purrr)
map_df( map_df(
c("national", "hhs", "census", "state"), c("national", "hhs", "census", "state"),
~ilinet(.x)) ~ ilinet(.x)
)
} }
} }
\references{ \references{

3
man/pi_mortality.Rd
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@ -4,7 +4,8 @@
\alias{pi_mortality} \alias{pi_mortality}
\title{Pneumonia and Influenza Mortality Surveillance} \title{Pneumonia and Influenza Mortality Surveillance}
\usage{ \usage{
pi_mortality(coverage_area = c("national", "state", "region"), years = NULL) pi_mortality(coverage_area = c("national", "state", "region"),
years = NULL)
} }
\arguments{ \arguments{
\item{coverage_area}{coverage area for data (national, state or region)} \item{coverage_area}{coverage area for data (national, state or region)}

3
man/who_nrevss.Rd
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@ -4,7 +4,8 @@
\alias{who_nrevss} \alias{who_nrevss}
\title{Retrieve WHO/NREVSS Surveillance Data} \title{Retrieve WHO/NREVSS Surveillance Data}
\usage{ \usage{
who_nrevss(region = c("national", "hhs", "census", "state"), years = NULL) who_nrevss(region = c("national", "hhs", "census", "state"),
years = NULL)
} }
\arguments{ \arguments{
\item{region}{one of "\code{national}", "\code{hhs}", "\code{census}", or "\code{state}"} \item{region}{one of "\code{national}", "\code{hhs}", "\code{census}", or "\code{state}"}

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