**NOTE** If there's a particular data set from 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). ------------------------------------------------------------------------ The U.S. Centers for Disease Control (CDC) maintains a [portal](http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html) for accessing state, regional and national influenza statistics. The portal's Flash interface makes it difficult and time-consuming to select and retrieve influenza data. This package provides functions to access the data provided by portal's underlying API. The following functions are implemented: - `get_flu_data`: Retrieves state, regional or national influenza statistics from the CDC - `get_state_data`: Retrieves state/territory-level influenza statistics from the CDC - `get_weekly_flu_report`: Retrieves weekly influenza surveillance report from the CDC The following data sets are included: - `hhs_regions` HHS Region Table (a data frame with 59 rows and 4 variables) ### News - Version 0.4.0.999 released : another fix for the CDC API (for region parameter); added data file for region lookups; added weekly high-level flu report retrieval - Version 0.3 released : fix for the CDC API (it changed how year & region params are encoded in the request) - Version 0.2.1 released : bumped up `httr` version \# requirement in `DESCRIPTION` (via Issue [1](https://github.com/hrbrmstr/cdcfluview/issues/1)) - Version 0.2 released : added state-level data retrieval - Version 0.1 released ### Installation ``` r devtools::install_github("hrbrmstr/cdcfluview") ``` ### Usage ``` r suppressPackageStartupMessages(library(cdcfluview)) suppressPackageStartupMessages(library(ggplot2)) suppressPackageStartupMessages(library(dplyr)) suppressPackageStartupMessages(library(statebins)) # current verison packageVersion("cdcfluview") #> [1] '0.4.0.9000' flu <- get_flu_data("hhs", sub_region=1:10, "ilinet", years=2014) glimpse(flu) #> Observations: 440 #> Variables: #> $ REGION.TYPE (chr) "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions",... #> $ REGION (chr) "Region 1", "Region 2", "Region 3", "Region 4", "Region 5", "Region 6", "Region 7", "Regi... #> $ YEAR (int) 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014,... #> $ WEEK (int) 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 4... #> $ ILITOTAL (int) 352, 2254, 1696, 1182, 1083, 1844, 220, 348, 1329, 61, 386, 2129, 1747, 1517, 1117, 2165,... #> $ TOTAL.PATIENTS (int) 51688, 137157, 129302, 130419, 107261, 103975, 50272, 37014, 88421, 11172, 51169, 132513,... #> $ NUM..OF.PROVIDERS (int) 147, 285, 245, 305, 267, 241, 84, 117, 237, 55, 151, 274, 241, 310, 277, 250, 84, 114, 24... #> $ X..WEIGHTED.ILI (dbl) 0.8306102, 1.7759176, 1.1477759, 0.8167958, 0.7370374, 1.8252298, 0.6970221, 0.6731439, 1... #> $ X.UNWEIGHTED.ILI (dbl) 0.6810091, 1.6433722, 1.3116580, 0.9063097, 1.0096867, 1.7735032, 0.4376194, 0.9401848, 1... #> $ AGE.0.4 (int) 101, 869, 395, 333, 358, 465, 50, 82, 310, 22, 109, 837, 404, 356, 339, 560, 57, 58, 335,... #> $ AGE.5.24 (int) 185, 757, 629, 536, 400, 711, 98, 152, 577, 30, 199, 677, 670, 774, 443, 809, 124, 146, 5... #> $ AGE.25.64 (lgl) NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N... #> $ AGE.25.49 (int) 44, 363, 455, 187, 181, 469, 43, 87, 220, 7, 37, 349, 466, 249, 182, 509, 56, 87, 225, 20... #> $ AGE.50.64 (int) 13, 157, 127, 80, 80, 121, 15, 19, 110, 1, 24, 151, 132, 74, 105, 187, 18, 23, 118, 10, 2... #> $ AGE.65 (int) 9, 108, 90, 46, 64, 78, 14, 8, 112, 1, 17, 115, 75, 64, 48, 100, 14, 12, 103, 3, 9, 110, ... state_flu <- get_state_data(years=2014) glimpse(state_flu) #> Observations: 2809 #> Variables: #> $ STATENAME (chr) "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama"... #> $ URL (chr) "http://adph.org/influenza/", "http://adph.org/influenza/", "http://adph.org/influenza... #> $ WEBSITE (chr) "Influenza Surveillance", "Influenza Surveillance", "Influenza Surveillance", "Influen... #> $ ACTIVITY.LEVEL (chr) "Level 1", "Level 1", "Level 1", "Level 1", "Level 1", "Level 1", "Level 5", "Level 10... #> $ ACTIVITY.LEVEL.LABEL (chr) "Minimal", "Minimal", "Minimal", "Minimal", "Minimal", "Minimal", "Low", "High", "High... #> $ WEEKEND (chr) "Oct-04-2014", "Oct-11-2014", "Oct-18-2014", "Oct-25-2014", "Nov-01-2014", "Nov-08-201... #> $ 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,... #> $ SEASON (chr) "2014-15", "2014-15", "2014-15", "2014-15", "2014-15", "2014-15", "2014-15", "2014-15"... gg <- ggplot(flu, aes(x=WEEK, y=X..WEIGHTED.ILI, group=REGION)) gg <- gg + geom_line() gg <- gg + facet_wrap(~REGION, ncol=2) gg <- gg + theme_bw() ``` ``` r dat <- get_flu_data(region="hhs", sub_region=1:10, data_source="ilinet", years=2000:2014) dat %>% mutate(REGION=factor(REGION, levels=unique(REGION), labels=c("Boston", "New York", "Philadelphia", "Atlanta", "Chicago", "Dallas", "Kansas City", "Denver", "San Francisco", "Seattle"), ordered=TRUE)) %>% mutate(season_week=ifelse(WEEK>=40, WEEK-40, WEEK), season=ifelse(WEEK<40, sprintf("%d-%d", YEAR-1, YEAR), sprintf("%d-%d", YEAR, YEAR+1))) -> dat prev_years <- dat %>% filter(season != "2014-2015") curr_year <- dat %>% filter(season == "2014-2015") curr_week <- tail(dat, 1)$season_week gg <- ggplot() gg <- gg + geom_point(data=prev_years, aes(x=season_week, y=X..WEIGHTED.ILI, group=season), color="#969696", size=1, alpa=0.25) gg <- gg + geom_point(data=curr_year, aes(x=season_week, y=X..WEIGHTED.ILI, group=season), color="red", size=1.25, alpha=1) gg <- gg + geom_line(data=curr_year, aes(x=season_week, y=X..WEIGHTED.ILI, group=season), size=1.25, color="#d7301f") gg <- gg + geom_vline(xintercept=curr_week, color="#d7301f", size=0.5, linetype="dashed", alpha=0.5) gg <- gg + facet_wrap(~REGION, ncol=3) gg <- gg + labs(x=NULL, y="Weighted ILI Index", title="ILINet - 1999-2015 year weighted flu index history by CDC region\nWeek Ending Jan 3, 2015 (Red == 2014-2015 season)\n") gg <- gg + theme_bw() gg <- gg + theme(panel.grid=element_blank()) gg <- gg + theme(strip.background=element_blank()) gg <- gg + theme(axis.ticks.x=element_blank()) gg <- gg + theme(axis.text.x=element_blank()) ``` ``` r gg_s <- state_flu %>% filter(WEEKEND=="Jan-03-2015") %>% select(state=STATENAME, value=ACTIVITY.LEVEL) %>% filter(!(state %in% c("Puerto Rico", "New York City"))) %>% # need to add PR to statebins mutate(value=as.numeric(gsub("Level ", "", value))) %>% statebins(brewer_pal="RdPu", breaks=4, labels=c("Minimal", "Low", "Moderate", "High"), legend_position="bottom", legend_title="ILI Activity Level") + ggtitle("CDC State FluView (2015-01-03)") ``` ### Test Results ``` r suppressPackageStartupMessages(library(cdcfluview)) suppressPackageStartupMessages(library(testthat)) date() #> [1] "Sun Aug 9 09:40:34 2015" test_dir("tests/") #> testthat results ======================================================================================================== #> OK: 0 SKIPPED: 0 FAILED: 0 #> #> DONE ```