--- title: "" pagetitle: "" output: rmarkdown::github_document --- [![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 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: - `age_group_distribution`: Age Group Distribution of Influenza Positive Tests Reported by Public Health Laboratories - `cdc_basemap`: Retrieve CDC U.S. Basemaps - `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 metadata 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 - `mmwr_week`: Convert a Date to an MMWR day+week+year - `mmwr_weekday`: Convert a Date to an MMWR weekday - `mmwr_week_to_date`: Convert an MMWR year+week or year+week+day to a Date object 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) - `mmwrid_map`: MMWR ID to Calendar Mappings (it is exported & available, no need to use `data()`) ## Installation ```{r eval=FALSE} devtools::install_github("hrbrmstr/cdcfluview") ``` ```{r message=FALSE, warning=FALSE, error=FALSE, include=FALSE} options(width=120) ``` ## Usage ```{r message=FALSE, warning=FALSE, error=FALSE} library(cdcfluview) library(hrbrthemes) library(tidyverse) # current verison packageVersion("cdcfluview") ``` ### Age Group Distribution of Influenza Positive Tests Reported by Public Health Laboratories ```{r message=FALSE, warning=FALSE} glimpse(age_group_distribution()) ``` ### Retrieve CDC U.S. Coverage Map ```{r message=FALSE, warning=FALSE} plot(cdc_basemap("national")) plot(cdc_basemap("hhs")) plot(cdc_basemap("census")) plot(cdc_basemap("states")) plot(cdc_basemap("spread")) plot(cdc_basemap("surv")) ``` ### State and Territorial Epidemiologists Reports of Geographic Spread of Influenza ```{r message=FALSE, warning=FALSE} glimpse(geographic_spread()) ``` ### Laboratory-Confirmed Influenza Hospitalizations ```{r message=FALSE, warning=FALSE, fig.width=10, fig.height=7.5} surveillance_areas() glimpse(fs_nat <- hospitalizations("flusurv")) ggplot(fs_nat, aes(wk_end, rate)) + geom_line(aes(color=age_label, group=age_label)) + facet_wrap(~sea_description, scales="free_x") + scale_color_ipsum(name=NULL) + labs(x=NULL, y="Rates per 100,000 population", title="FluSurv-NET :: Entire Network :: All Seasons :: Cumulative Rate") + theme_ipsum_rc() glimpse(hospitalizations("eip")) glimpse(hospitalizations("eip", "Colorado")) glimpse(hospitalizations("ihsp")) glimpse(hospitalizations("ihsp", "Oklahoma")) ``` ### Retrieve ILINet Surveillance Data ```{r message=FALSE, warning=FALSE} walk(c("national", "hhs", "census", "state"), ~{ ili_df <- ilinet(region = .x) print(glimpse(ili_df)) ggplot(ili_df, aes(week_start, unweighted_ili, group=region, color=region)) + geom_line() + viridis::scale_color_viridis(discrete=TRUE) + labs(x=NULL, y="Unweighted ILI", title=ili_df$region_type[1]) + theme_ipsum_rc(grid="XY") + theme(legend.position = "none") -> gg print(gg) }) ``` ### Retrieve weekly state-level ILI indicators per-state for a given season ```{r message=FALSE, warning=FALSE, fig.width=10, fig.height=5} ili_weekly_activity_indicators(2017) xdf <- map_df(2008:2017, ili_weekly_activity_indicators) count(xdf, weekend, ili_activity_label) %>% complete(weekend, ili_activity_label) %>% ggplot(aes(weekend, ili_activity_label, fill=n)) + geom_tile(color="#c2c2c2", size=0.1) + scale_x_date(expand=c(0,0)) + viridis::scale_fill_viridis(name="# States", na.value="White") + labs(x=NULL, y=NULL, title="Weekly ILI Indicators (all states)") + coord_fixed(100/1) + theme_ipsum_rc(grid="") + theme(legend.position="bottom") ``` ### Pneumonia and Influenza Mortality Surveillance ```{r message=FALSE, warning=FALSE} (nat_pi <- pi_mortality("national")) select(nat_pi, wk_end, percent_pni, baseline, threshold) %>% gather(measure, value, -wk_end) %>% ggplot(aes(wk_end, value)) + geom_line(aes(group=measure, color=measure)) + scale_y_percent() + scale_color_ipsum(name = NULL, labels=c("Baseline", "Percent P&I", "Threshold")) + labs(x=NULL, y="% of all deaths due to P&I", title="Percentage of all deaths due to pneumonia and influenza, National Summary") + theme_ipsum_rc(grid="XY") + theme(legend.position="bottom") (st_pi <- pi_mortality("state")) (reg_pi <- pi_mortality("region")) ``` ### Retrieve metadata about U.S. State CDC Provider Data ```{r message=FALSE, warning=FALSE} state_data_providers() ``` ### Retrieve WHO/NREVSS Surveillance Data ```{r message=FALSE, warning=FALSE} glimpse(xdat <- who_nrevss("national")) mutate(xdat$combined_prior_to_2015_16, percent_positive = percent_positive / 100) %>% ggplot(aes(wk_date, percent_positive)) + geom_line() + scale_y_percent(name="% Positive") + labs(x=NULL, title="WHO/NREVSS Surveillance Data (National)") + theme_ipsum_rc(grid="XY") who_nrevss("hhs") who_nrevss("census") who_nrevss("state") ``` ## 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.