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8.1 KiB

NOTE If there's a particular data set from http://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).


The U.S. Centers for Disease Control (CDC) maintains a portal 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)
  • Version 0.2 released : added state-level data retrieval
  • Version 0.1 released

Installation

devtools::install_github("hrbrmstr/cdcfluview")

Usage

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()

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())

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

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