You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

725 lines
55 KiB

3 years ago
3 years ago
3 years ago
  1. [![CRAN\_Status\_Badge](http://www.r-pkg.org/badges/version/cdcfluview)](https://cran.r-project.org/package=cdcfluview)
  2. [![Travis-CI Build
  3. Status](https://travis-ci.org/hrbrmstr/cdcfluview.svg?branch=master)](https://travis-ci.org/hrbrmstr/cdcfluview)
  4. [![Coverage
  5. Status](https://img.shields.io/codecov/c/github/hrbrmstr/cdcfluview/master.svg)](https://codecov.io/github/hrbrmstr/cdcfluview?branch=master)
  6. I M P O R T A N T
  7. =================
  8. The CDC migrated to a new non-Flash portal and back-end APIs changed.
  9. This is a complete reimagining of the package and — as such — all your
  10. code is going to break. Please use GitHub issues to identify previous
  11. API functionality you would like ported over. There’s a [release
  12. candidate for
  13. 0.5.2](https://github.com/hrbrmstr/cdcfluview/releases/tag/v0.5.2) which
  14. uses the old API but it likely to break in the near future given the
  15. changes to the hidden API. You can do what with
  16. `devtools::install_github("hrbrmstr/cdcfluview", ref="58c172b")`.
  17. All folks providing feedback, code or suggestions will be added to the
  18. DESCRIPTION file. Please include how you would prefer to be cited in any
  19. issues you file.
  20. If there’s a particular data set from
  21. <https://www.cdc.gov/flu/weekly/fluviewinteractive.htm> that you want
  22. and that isn’t in the package, please file it as an issue and be as
  23. specific as you can (screen shot if possible).
  24. :mask: cdcfluview
  25. =================
  26. Retrieve U.S. Flu Season Data from the CDC FluView Portal
  27. Description
  28. -----------
  29. The U.S. Centers for Disease Control (CDC) maintains a portal
  30. <http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html> for accessing
  31. state, regional and national influenza statistics as well as Mortality
  32. Surveillance Data. The Flash interface makes it difficult and
  33. time-consuming to select and retrieve influenza data. This package
  34. provides functions to access the data provided by the portal’s
  35. underlying API.
  36. What’s Inside The Tin
  37. ---------------------
  38. The following functions are implemented:
  39. - `agd_ipt`: Age Group Distribution of Influenza Positive Tests
  40. Reported by Public Health Laboratories
  41. - `cdc_coverage_map`: Retrieve CDC U.S. Coverage Map
  42. - `geographic_spread`: State and Territorial Epidemiologists Reports
  43. of Geographic Spread of Influenza
  44. - `hospitalizations`: Laboratory-Confirmed Influenza Hospitalizations
  45. - `ilinet`: Retrieve ILINet Surveillance Data
  46. - `ili_weekly_activity_indicators`: Retrieve weekly state-level ILI
  47. indicators per-state for a given season
  48. - `pi_mortality`: Pneumonia and Influenza Mortality Surveillance
  49. - `state_data_providers`: Retrieve metadata about U.S. State CDC
  50. Provider Data
  51. - `surveillance_areas`: Retrieve a list of valid sub-regions for each
  52. surveillance area.
  53. - `who_nrevss`: Retrieve WHO/NREVSS Surveillance Data
  54. The following data sets are included:
  55. - `hhs_regions` HHS Region Table (a data frame with 59 rows and 4
  56. variables)
  57. - `census_regions` Census Region Table (a data frame with 51 rows and
  58. 2 variables)
  59. Installation
  60. ------------
  61. ``` r
  62. devtools::install_github("hrbrmstr/cdcfluview")
  63. ```
  64. Usage
  65. -----
  66. ``` r
  67. library(cdcfluview)
  68. library(tidyverse)
  69. # current verison
  70. packageVersion("cdcfluview")
  71. ```
  72. ## [1] '0.7.0'
  73. ### Age Group Distribution of Influenza Positive Tests Reported by Public Health Laboratories
  74. ``` r
  75. glimpse(agd_ipt())
  76. ```
  77. ## Observations: 36,144
  78. ## Variables: 13
  79. ## $ sea_label <chr> "1997-98", "1997-98", "1997-98", "1997-98", "1997-98", "1997-98", "1997-98", "1997-98", "...
  80. ## $ age_label <chr> "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",...
  81. ## $ vir_label <chr> "A (Subtyping not Performed)", "A (Subtyping not Performed)", "A (Subtyping not Performed...
  82. ## $ count <int> 0, 1, 0, 0, 0, 0, 0, 3, 0, 6, 0, 1, 1, 2, 11, 8, 18, 26, 22, 19, 2, 5, 2, 1, 4, 0, 0, 0, ...
  83. ## $ mmwrid <int> 1866, 1867, 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877, 1878, 1879, 1880,...
  84. ## $ seasonid <int> 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 3...
  85. ## $ publishyearweekid <int> 2913, 2913, 2913, 2913, 2913, 2913, 2913, 2913, 2913, 2913, 2913, 2913, 2913, 2913, 2913,...
  86. ## $ sea_description <chr> "Season 1997-98", "Season 1997-98", "Season 1997-98", "Season 1997-98", "Season 1997-98",...
  87. ## $ sea_startweek <int> 1866, 1866, 1866, 1866, 1866, 1866, 1866, 1866, 1866, 1866, 1866, 1866, 1866, 1866, 1866,...
  88. ## $ sea_endweek <int> 1918, 1918, 1918, 1918, 1918, 1918, 1918, 1918, 1918, 1918, 1918, 1918, 1918, 1918, 1918,...
  89. ## $ vir_description <chr> "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk",...
  90. ## $ vir_startmmwrid <int> 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397,...
  91. ## $ vir_endmmwrid <int> 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131,...
  92. ### Retrieve CDC U.S. Coverage Map
  93. ``` r
  94. plot(cdc_coverage_map())
  95. ```
  96. ![](README_files/figure-markdown_github-ascii_identifiers/unnamed-chunk-5-1.png)
  97. ### State and Territorial Epidemiologists Reports of Geographic Spread of Influenza
  98. ``` r
  99. glimpse(geographic_spread())
  100. ```
  101. ## Observations: 25,795
  102. ## Variables: 7
  103. ## $ statename <chr> "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "...
  104. ## $ url <chr> "http://adph.org/influenza/", "http://adph.org/influenza/", "http://adph.org/influenza/",...
  105. ## $ website <chr> "Influenza Surveillance", "Influenza Surveillance", "Influenza Surveillance", "Influenza ...
  106. ## $ activity_estimate <chr> "No Activity", "No Activity", "No Activity", "Local Activity", "Sporadic", "Sporadic", "S...
  107. ## $ weekend <date> 2003-10-04, 2003-10-11, 2003-10-18, 2003-10-25, 2003-11-01, 2003-11-08, 2003-11-15, 2003...
  108. ## $ season <chr> "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "...
  109. ## $ weeknumber <chr> "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "1", ...
  110. ### Laboratory-Confirmed Influenza Hospitalizations
  111. ``` r
  112. surveillance_areas()
  113. ```
  114. ## surveillance_area region
  115. ## 1 flusurv Entire Network
  116. ## 2 eip California
  117. ## 3 eip Colorado
  118. ## 4 eip Connecticut
  119. ## 5 eip Entire Network
  120. ## 6 eip Georgia
  121. ## 7 eip Maryland
  122. ## 8 eip Minnesota
  123. ## 9 eip New Mexico
  124. ## 10 eip New York - Albany
  125. ## 11 eip New York - Rochester
  126. ## 12 eip Oregon
  127. ## 13 eip Tennessee
  128. ## 14 ihsp Entire Network
  129. ## 15 ihsp Idaho
  130. ## 16 ihsp Iowa
  131. ## 17 ihsp Michigan
  132. ## 18 ihsp Ohio
  133. ## 19 ihsp Oklahoma
  134. ## 20 ihsp Rhode Island
  135. ## 21 ihsp South Dakota
  136. ## 22 ihsp Utah
  137. ``` r
  138. glimpse(hospitalizations("flusurv"))
  139. ```
  140. ## Observations: 1,476
  141. ## Variables: 20
  142. ## $ mmwrid <int> 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559,...
  143. ## $ weeknumber <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...
  144. ## $ rate <dbl> 0.0, 0.0, 0.0, 0.1, 0.1, 0.2, 0.3, 0.3, 0.4, 0.6, 0.8, 1.3, 1.7, 2.2, 2.8, 3.6, 4.4, 5.4,...
  145. ## $ weeklyrate <dbl> 0.0, 0.0, 0.0, 0.0, 0.1, 0.0, 0.1, 0.1, 0.1, 0.2, 0.2, 0.4, 0.4, 0.5, 0.5, 0.8, 0.8, 1.0,...
  146. ## $ age <int> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,...
  147. ## $ 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...
  148. ## $ weekend <chr> "2010-10-09", "2010-10-16", "2010-10-23", "2010-10-30", "2010-11-06", "2010-11-13", "2010...
  149. ## $ weekstart <chr> "2010-10-03", "2010-10-10", "2010-10-17", "2010-10-24", "2010-10-31", "2010-11-07", "2010...
  150. ## $ year <int> 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2011, 2011,...
  151. ## $ yearweek <int> 201040, 201041, 201042, 201043, 201044, 201045, 201046, 201047, 201048, 201049, 201050, 2...
  152. ## $ seasonid <int> 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 5...
  153. ## $ weekendlabel <chr> "Oct 09, 2010", "Oct 16, 2010", "Oct 23, 2010", "Oct 30, 2010", "Nov 06, 2010", "Nov 13, ...
  154. ## $ weekendlabel2 <chr> "Oct-09-2010", "Oct-16-2010", "Oct-23-2010", "Oct-30-2010", "Nov-06-2010", "Nov-13-2010",...
  155. ## $ age_label <chr> "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-4...
  156. ## $ sea_label <chr> "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "...
  157. ## $ sea_description <chr> "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11",...
  158. ## $ sea_startweek <int> 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545,...
  159. ## $ sea_endweek <int> 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596,...
  160. ## $ surveillance_area <chr> "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET",...
  161. ## $ region <chr> "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network",...
  162. ``` r
  163. glimpse(hospitalizations("eip"))
  164. ```
  165. ## Observations: 2,385
  166. ## Variables: 20
  167. ## $ mmwrid <int> 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559,...
  168. ## $ weeknumber <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...
  169. ## $ rate <dbl> 0.0, 0.0, 0.0, 0.1, 0.1, 0.1, 0.2, 0.3, 0.4, 0.5, 0.8, 1.1, 1.4, 1.9, 2.3, 2.8, 3.6, 4.5,...
  170. ## $ weeklyrate <dbl> 0.0, 0.0, 0.0, 0.0, 0.1, 0.0, 0.1, 0.1, 0.1, 0.1, 0.2, 0.4, 0.3, 0.4, 0.4, 0.5, 0.8, 1.0,...
  171. ## $ age <int> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,...
  172. ## $ 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...
  173. ## $ weekend <chr> "2010-10-09", "2010-10-16", "2010-10-23", "2010-10-30", "2010-11-06", "2010-11-13", "2010...
  174. ## $ weekstart <chr> "2010-10-03", "2010-10-10", "2010-10-17", "2010-10-24", "2010-10-31", "2010-11-07", "2010...
  175. ## $ year <int> 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2011, 2011,...
  176. ## $ yearweek <int> 201040, 201041, 201042, 201043, 201044, 201045, 201046, 201047, 201048, 201049, 201050, 2...
  177. ## $ seasonid <int> 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 5...
  178. ## $ weekendlabel <chr> "Oct 09, 2010", "Oct 16, 2010", "Oct 23, 2010", "Oct 30, 2010", "Nov 06, 2010", "Nov 13, ...
  179. ## $ weekendlabel2 <chr> "Oct-09-2010", "Oct-16-2010", "Oct-23-2010", "Oct-30-2010", "Nov-06-2010", "Nov-13-2010",...
  180. ## $ age_label <chr> "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-4...
  181. ## $ sea_label <chr> "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "...
  182. ## $ sea_description <chr> "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11",...
  183. ## $ sea_startweek <int> 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545,...
  184. ## $ sea_endweek <int> 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596,...
  185. ## $ surveillance_area <chr> "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP"...
  186. ## $ region <chr> "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network",...
  187. ``` r
  188. glimpse(hospitalizations("eip", "Colorado"))
  189. ```
  190. ## Observations: 2,385
  191. ## Variables: 20
  192. ## $ mmwrid <int> 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559,...
  193. ## $ weeknumber <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...
  194. ## $ rate <dbl> 0.0, 0.1, 0.1, 0.1, 0.3, 0.3, 0.4, 0.4, 0.5, 0.6, 0.8, 1.3, 1.8, 2.1, 2.6, 3.4, 4.2, 5.6,...
  195. ## $ weeklyrate <dbl> 0.0, 0.1, 0.0, 0.0, 0.2, 0.0, 0.1, 0.1, 0.1, 0.1, 0.2, 0.5, 0.4, 0.4, 0.4, 0.9, 0.8, 1.4,...
  196. ## $ age <int> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,...
  197. ## $ 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...
  198. ## $ weekend <chr> "2010-10-09", "2010-10-16", "2010-10-23", "2010-10-30", "2010-11-06", "2010-11-13", "2010...
  199. ## $ weekstart <chr> "2010-10-03", "2010-10-10", "2010-10-17", "2010-10-24", "2010-10-31", "2010-11-07", "2010...
  200. ## $ year <int> 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2011, 2011,...
  201. ## $ yearweek <int> 201040, 201041, 201042, 201043, 201044, 201045, 201046, 201047, 201048, 201049, 201050, 2...
  202. ## $ seasonid <int> 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 5...
  203. ## $ weekendlabel <chr> "Oct 09, 2010", "Oct 16, 2010", "Oct 23, 2010", "Oct 30, 2010", "Nov 06, 2010", "Nov 13, ...
  204. ## $ weekendlabel2 <chr> "Oct-09-2010", "Oct-16-2010", "Oct-23-2010", "Oct-30-2010", "Nov-06-2010", "Nov-13-2010",...
  205. ## $ age_label <chr> "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-4...
  206. ## $ sea_label <chr> "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "...
  207. ## $ sea_description <chr> "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11",...
  208. ## $ sea_startweek <int> 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545,...
  209. ## $ sea_endweek <int> 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596,...
  210. ## $ surveillance_area <chr> "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP"...
  211. ## $ region <chr> "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colo...
  212. ``` r
  213. glimpse(hospitalizations("ihsp"))
  214. ```
  215. ## Observations: 1,476
  216. ## Variables: 20
  217. ## $ mmwrid <int> 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559,...
  218. ## $ weeknumber <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...
  219. ## $ rate <dbl> 0.0, 0.0, 0.1, 0.2, 0.2, 0.3, 0.3, 0.4, 0.6, 0.9, 1.1, 1.9, 2.8, 3.9, 4.9, 6.8, 7.6, 9.0,...
  220. ## $ weeklyrate <dbl> 0.0, 0.0, 0.0, 0.1, 0.0, 0.0, 0.0, 0.1, 0.2, 0.4, 0.2, 0.8, 0.9, 1.1, 1.0, 2.0, 0.8, 1.4,...
  221. ## $ age <int> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,...
  222. ## $ 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...
  223. ## $ weekend <chr> "2010-10-09", "2010-10-16", "2010-10-23", "2010-10-30", "2010-11-06", "2010-11-13", "2010...
  224. ## $ weekstart <chr> "2010-10-03", "2010-10-10", "2010-10-17", "2010-10-24", "2010-10-31", "2010-11-07", "2010...
  225. ## $ year <int> 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2011, 2011,...
  226. ## $ yearweek <int> 201040, 201041, 201042, 201043, 201044, 201045, 201046, 201047, 201048, 201049, 201050, 2...
  227. ## $ seasonid <int> 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 5...
  228. ## $ weekendlabel <chr> "Oct 09, 2010", "Oct 16, 2010", "Oct 23, 2010", "Oct 30, 2010", "Nov 06, 2010", "Nov 13, ...
  229. ## $ weekendlabel2 <chr> "Oct-09-2010", "Oct-16-2010", "Oct-23-2010", "Oct-30-2010", "Nov-06-2010", "Nov-13-2010",...
  230. ## $ age_label <chr> "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-4...
  231. ## $ sea_label <chr> "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "...
  232. ## $ sea_description <chr> "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11",...
  233. ## $ sea_startweek <int> 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545,...
  234. ## $ sea_endweek <int> 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596,...
  235. ## $ surveillance_area <chr> "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "...
  236. ## $ region <chr> "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network",...
  237. ``` r
  238. glimpse(hospitalizations("ihsp", "Oklahoma"))
  239. ```
  240. ## Observations: 390
  241. ## Variables: 20
  242. ## $ mmwrid <int> 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559,...
  243. ## $ weeknumber <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...
  244. ## $ rate <dbl> 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2, 0.2, 0.4, 0.7, 0.7, 1.3, 2.2, 2.5, 3.4, 4.5, 5.8, 7.6,...
  245. ## $ weeklyrate <dbl> 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2, 0.0, 0.2, 0.2, 0.0, 0.7, 0.9, 0.2, 0.9, 1.1, 1.3, 1.8,...
  246. ## $ age <int> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,...
  247. ## $ 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...
  248. ## $ weekend <chr> "2010-10-09", "2010-10-16", "2010-10-23", "2010-10-30", "2010-11-06", "2010-11-13", "2010...
  249. ## $ weekstart <chr> "2010-10-03", "2010-10-10", "2010-10-17", "2010-10-24", "2010-10-31", "2010-11-07", "2010...
  250. ## $ year <int> 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2011, 2011,...
  251. ## $ yearweek <int> 201040, 201041, 201042, 201043, 201044, 201045, 201046, 201047, 201048, 201049, 201050, 2...
  252. ## $ seasonid <int> 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 5...
  253. ## $ weekendlabel <chr> "Oct 09, 2010", "Oct 16, 2010", "Oct 23, 2010", "Oct 30, 2010", "Nov 06, 2010", "Nov 13, ...
  254. ## $ weekendlabel2 <chr> "Oct-09-2010", "Oct-16-2010", "Oct-23-2010", "Oct-30-2010", "Nov-06-2010", "Nov-13-2010",...
  255. ## $ age_label <chr> "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-49 yr", "18-4...
  256. ## $ sea_label <chr> "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "...
  257. ## $ sea_description <chr> "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11",...
  258. ## $ sea_startweek <int> 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545, 2545,...
  259. ## $ sea_endweek <int> 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596, 2596,...
  260. ## $ surveillance_area <chr> "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "...
  261. ## $ region <chr> "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Okla...
  262. ### Retrieve ILINet Surveillance Data
  263. ``` r
  264. ilinet("national")
  265. ```
  266. ## # A tibble: 1,048 x 15
  267. ## 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
  268. ## <chr> <chr> <int> <int> <dbl> <dbl> <int> <chr> <chr> <int> <chr> <int>
  269. ## 1 National <NA> 1997 40 1.10148 1.21686 179 <NA> 157 205 <NA> 29
  270. ## 2 National <NA> 1997 41 1.20007 1.28064 199 <NA> 151 242 <NA> 23
  271. ## 3 National <NA> 1997 42 1.37876 1.23906 228 <NA> 153 266 <NA> 34
  272. ## 4 National <NA> 1997 43 1.19920 1.14473 188 <NA> 193 236 <NA> 36
  273. ## 5 National <NA> 1997 44 1.65618 1.26112 217 <NA> 162 280 <NA> 41
  274. ## 6 National <NA> 1997 45 1.41326 1.28275 178 <NA> 148 281 <NA> 48
  275. ## 7 National <NA> 1997 46 1.98680 1.44579 294 <NA> 240 328 <NA> 70
  276. ## 8 National <NA> 1997 47 2.44749 1.64796 288 <NA> 293 456 <NA> 63
  277. ## 9 National <NA> 1997 48 1.73901 1.67517 268 <NA> 206 343 <NA> 69
  278. ## 10 National <NA> 1997 49 1.93919 1.61739 299 <NA> 282 415 <NA> 102
  279. ## # ... with 1,038 more rows, and 3 more variables: ilitotal <int>, num_of_providers <int>, total_patients <int>
  280. ``` r
  281. ilinet("hhs")
  282. ```
  283. ## # A tibble: 10,480 x 15
  284. ## 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
  285. ## <chr> <chr> <int> <int> <dbl> <dbl> <int> <int> <int> <int> <int> <int>
  286. ## 1 HHS Regions Region 1 1997 40 0.498535 0.623848 15 NA 7 22 NA 0
  287. ## 2 HHS Regions Region 2 1997 40 0.374963 0.384615 0 NA 3 0 NA 0
  288. ## 3 HHS Regions Region 3 1997 40 1.354280 1.341720 6 NA 7 15 NA 4
  289. ## 4 HHS Regions Region 4 1997 40 0.400338 0.450010 12 NA 23 11 NA 0
  290. ## 5 HHS Regions Region 5 1997 40 1.229260 0.901266 31 NA 24 30 NA 4
  291. ## 6 HHS Regions Region 6 1997 40 1.018980 0.747384 2 NA 1 2 NA 0
  292. ## 7 HHS Regions Region 7 1997 40 0.871791 1.152860 0 NA 4 18 NA 5
  293. ## 8 HHS Regions Region 8 1997 40 0.516017 0.422654 2 NA 0 3 NA 0
  294. ## 9 HHS Regions Region 9 1997 40 1.807610 2.258780 80 NA 76 74 NA 13
  295. ## 10 HHS Regions Region 10 1997 40 4.743520 4.825400 31 NA 12 30 NA 3
  296. ## # ... with 10,470 more rows, and 3 more variables: ilitotal <int>, num_of_providers <int>, total_patients <int>
  297. ``` r
  298. ilinet("census")
  299. ```
  300. ## # A tibble: 9,432 x 15
  301. ## region_type region year week weighted_ili unweighted_ili age_0_4 age_25_49 age_25_64 age_5_24
  302. ## <chr> <chr> <int> <int> <dbl> <dbl> <int> <chr> <chr> <int>
  303. ## 1 Census Regions New England 1997 40 0.4985350 0.6238480 15 <NA> 7 22
  304. ## 2 Census Regions Mid-Atlantic 1997 40 0.8441440 1.3213800 4 <NA> 8 12
  305. ## 3 Census Regions East North Central 1997 40 0.7924860 0.8187380 28 <NA> 20 28
  306. ## 4 Census Regions West North Central 1997 40 1.7640500 1.2793900 3 <NA> 8 20
  307. ## 5 Census Regions South Atlantic 1997 40 0.5026620 0.7233800 14 <NA> 22 14
  308. ## 6 Census Regions East South Central 1997 40 0.0542283 0.0688705 0 <NA> 3 0
  309. ## 7 Census Regions West South Central 1997 40 1.0189800 0.7473840 2 <NA> 1 2
  310. ## 8 Census Regions Mountain 1997 40 2.2587800 2.2763300 87 <NA> 71 71
  311. ## 9 Census Regions Pacific 1997 40 2.0488300 3.2349400 26 <NA> 17 36
  312. ## 10 Census Regions New England 1997 41 0.6426690 0.8158010 14 <NA> 14 29
  313. ## # ... with 9,422 more rows, and 5 more variables: age_50_64 <chr>, age_65 <int>, ilitotal <int>,
  314. ## # num_of_providers <int>, total_patients <int>
  315. ``` r
  316. ilinet("state")
  317. ```
  318. ## # A tibble: 19,718 x 15
  319. ## region_type region year week weighted_ili unweighted_ili age_0_4 age_25_49 age_25_64 age_5_24
  320. ## <chr> <chr> <int> <int> <chr> <chr> <chr> <chr> <chr> <chr>
  321. ## 1 States Alabama 2010 40 <NA> 2.13477 <NA> <NA> <NA> <NA>
  322. ## 2 States Alaska 2010 40 <NA> 0.875146 <NA> <NA> <NA> <NA>
  323. ## 3 States Arizona 2010 40 <NA> 0.674721 <NA> <NA> <NA> <NA>
  324. ## 4 States Arkansas 2010 40 <NA> 0.696056 <NA> <NA> <NA> <NA>
  325. ## 5 States California 2010 40 <NA> 1.95412 <NA> <NA> <NA> <NA>
  326. ## 6 States Colorado 2010 40 <NA> 0.660684 <NA> <NA> <NA> <NA>
  327. ## 7 States Connecticut 2010 40 <NA> 0.0783085 <NA> <NA> <NA> <NA>
  328. ## 8 States Delaware 2010 40 <NA> 0.100125 <NA> <NA> <NA> <NA>
  329. ## 9 States District of Columbia 2010 40 <NA> 2.80877 <NA> <NA> <NA> <NA>
  330. ## 10 States Florida 2010 40 <NA> <NA> <NA> <NA> <NA> <NA>
  331. ## # ... with 19,708 more rows, and 5 more variables: age_50_64 <chr>, age_65 <chr>, ilitotal <chr>,
  332. ## # num_of_providers <chr>, total_patients <chr>
  333. ### Retrieve weekly state-level ILI indicators per-state for a given season
  334. ``` r
  335. ili_weekly_activity_indicators(2017)
  336. ```
  337. ## # A tibble: 216 x 9
  338. ## statename ili_activity_label ili_activity_group statefips stateabbr weekend weeknumber year seasonid
  339. ## <chr> <fctr> <chr> <chr> <chr> <date> <int> <int> <int>
  340. ## 1 Alabama Level 2 Minimal 01 AL 2017-10-07 40 2017 57
  341. ## 2 Alabama Level 2 Minimal 01 AL 2017-10-14 41 2017 57
  342. ## 3 Alabama Level 2 Minimal 01 AL 2017-10-21 42 2017 57
  343. ## 4 Alabama Level 3 Minimal 01 AL 2017-10-28 43 2017 57
  344. ## 5 Alaska Level 1 Minimal 02 AK 2017-10-07 40 2017 57
  345. ## 6 Alaska Level 2 Minimal 02 AK 2017-10-14 41 2017 57
  346. ## 7 Alaska Level 4 Low 02 AK 2017-10-21 42 2017 57
  347. ## 8 Alaska Level 3 Minimal 02 AK 2017-10-28 43 2017 57
  348. ## 9 Arizona Level 2 Minimal 04 AZ 2017-10-07 40 2017 57
  349. ## 10 Arizona Level 3 Minimal 04 AZ 2017-10-14 41 2017 57
  350. ## # ... with 206 more rows
  351. ``` r
  352. ili_weekly_activity_indicators(2015)
  353. ```
  354. ## # A tibble: 2,807 x 9
  355. ## statename ili_activity_label ili_activity_group statefips stateabbr weekend weeknumber year seasonid
  356. ## <chr> <fctr> <chr> <chr> <chr> <date> <int> <int> <int>
  357. ## 1 Alabama Level 1 Minimal 01 AL 2015-10-10 40 2015 55
  358. ## 2 Alabama Level 1 Minimal 01 AL 2015-10-17 41 2015 55
  359. ## 3 Alabama Level 1 Minimal 01 AL 2015-10-24 42 2015 55
  360. ## 4 Alabama Level 1 Minimal 01 AL 2015-10-31 43 2015 55
  361. ## 5 Alabama Level 1 Minimal 01 AL 2015-11-07 44 2015 55
  362. ## 6 Alabama Level 1 Minimal 01 AL 2015-11-14 45 2015 55
  363. ## 7 Alabama Level 1 Minimal 01 AL 2015-11-21 46 2015 55
  364. ## 8 Alabama Level 3 Minimal 01 AL 2015-11-28 47 2015 55
  365. ## 9 Alabama Level 1 Minimal 01 AL 2015-12-05 48 2015 55
  366. ## 10 Alabama Level 1 Minimal 01 AL 2015-12-12 49 2015 55
  367. ## # ... with 2,797 more rows
  368. ### Pneumonia and Influenza Mortality Surveillance
  369. ``` r
  370. pi_mortality("national")
  371. ```
  372. ## # A tibble: 419 x 19
  373. ## seasonid baseline threshold percent_pni percent_complete number_influenza number_pneumonia all_deaths total_pni
  374. ## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
  375. ## 1 57 5.8 6.1 0.054 0.763 10 1962 36283 1972
  376. ## 2 57 5.8 6.2 0.056 0.675 10 1795 32107 1805
  377. ## 3 56 5.9 6.3 0.059 1.000 18 3022 51404 3040
  378. ## 4 56 6.0 6.3 0.061 1.000 11 3193 52130 3204
  379. ## 5 56 6.1 6.4 0.062 1.000 7 3178 51443 3185
  380. ## 6 56 6.2 6.5 0.061 1.000 17 3129 51865 3146
  381. ## 7 56 6.3 6.6 0.060 1.000 16 3099 51753 3115
  382. ## 8 56 6.4 6.7 0.061 1.000 19 3208 52541 3227
  383. ## 9 56 6.5 6.8 0.060 1.000 7 3192 53460 3199
  384. ## 10 56 6.6 6.9 0.062 1.000 22 3257 53163 3279
  385. ## # ... with 409 more rows, and 10 more variables: weeknumber <chr>, geo_description <chr>, age_label <chr>,
  386. ## # weekend <date>, weekstart <date>, year <int>, yearweek <int>, coverage_area <chr>, region_name <chr>, callout <chr>
  387. ``` r
  388. pi_mortality("state")
  389. ```
  390. ## # A tibble: 21,788 x 19
  391. ## seasonid baseline threshold percent_pni percent_complete number_influenza number_pneumonia all_deaths total_pni
  392. ## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
  393. ## 1 57 NA NA 0.065 0.836 0 50 772 50
  394. ## 2 57 NA NA 0.064 0.767 0 45 708 45
  395. ## 3 57 NA NA 0.063 0.666 1 2 48 3
  396. ## 4 57 NA NA 0.105 0.527 0 4 38 4
  397. ## 5 57 NA NA 0.053 0.412 0 20 374 20
  398. ## 6 57 NA NA 0.059 0.393 0 21 356 21
  399. ## 7 57 NA NA 0.060 0.751 0 25 420 25
  400. ## 8 57 NA NA 0.050 0.604 0 17 338 17
  401. ## 9 57 NA NA 0.065 0.774 1 228 3510 229
  402. ## 10 57 NA NA 0.059 0.758 2 201 3438 203
  403. ## # ... with 21,778 more rows, and 10 more variables: weeknumber <chr>, geo_description <chr>, age_label <chr>,
  404. ## # weekend <date>, weekstart <date>, year <int>, yearweek <int>, coverage_area <chr>, region_name <chr>, callout <chr>
  405. ``` r
  406. pi_mortality("region")
  407. ```
  408. ## # A tibble: 4,190 x 19
  409. ## seasonid baseline threshold percent_pni percent_complete number_influenza number_pneumonia all_deaths total_pni
  410. ## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
  411. ## 1 57 6.0 6.7 0.051 0.735 0 85 1683 85
  412. ## 2 57 6.1 6.8 0.060 0.701 0 96 1605 96
  413. ## 3 57 6.0 6.5 0.061 0.608 1 154 2524 155
  414. ## 4 57 6.0 6.6 0.063 0.602 1 157 2497 158
  415. ## 5 57 5.3 5.8 0.045 0.511 1 115 2575 116
  416. ## 6 57 5.4 5.9 0.045 0.440 1 98 2215 99
  417. ## 7 57 5.6 6.0 0.051 0.744 3 394 7753 397
  418. ## 8 57 5.7 6.1 0.052 0.651 1 354 6778 355
  419. ## 9 57 5.5 5.9 0.052 0.914 1 403 7701 404
  420. ## 10 57 5.6 6.0 0.054 0.799 4 358 6733 362
  421. ## # ... with 4,180 more rows, and 10 more variables: weeknumber <chr>, geo_description <chr>, age_label <chr>,
  422. ## # weekend <date>, weekstart <date>, year <int>, yearweek <int>, coverage_area <chr>, region_name <chr>, callout <chr>
  423. ### Retrieve metadata about U.S. State CDC Provider Data
  424. ``` r
  425. state_data_providers()
  426. ```
  427. ## # A tibble: 59 x 5
  428. ## statename statehealthdeptname
  429. ## * <chr> <chr>
  430. ## 1 Alabama Alabama Department of Public Health
  431. ## 2 Alaska State of Alaska Health and Social Services
  432. ## 3 Arizona Arizona Department of Health Services
  433. ## 4 Arkansas Arkansas Department of Health
  434. ## 5 California California Department of Public Health
  435. ## 6 Colorado Colorado Department of Public Health and Environment
  436. ## 7 Connecticut Connecticut Department of Public Health
  437. ## 8 Delaware Delaware Health and Social Services
  438. ## 9 District of Columbia District of Columbia Department of Health
  439. ## 10 Florida Florida Department of Health
  440. ## # ... with 49 more rows, and 3 more variables: url <chr>, statewebsitename <chr>, statefluphonenum <chr>
  441. ### Retrieve WHO/NREVSS Surveillance Data
  442. ``` r
  443. who_nrevss("national")
  444. ```
  445. ## $combined_prior_to_2015_16
  446. ## # A tibble: 940 x 13
  447. ## region_type region year week total_specimens percent_positive a_2009_h1n1 a_h1 a_h3 a_subtyping_not_performed
  448. ## <chr> <chr> <int> <int> <int> <dbl> <int> <int> <int> <int>
  449. ## 1 National <NA> 1997 40 1291 0.000000 0 0 0 0
  450. ## 2 National <NA> 1997 41 1513 0.727032 0 0 0 11
  451. ## 3 National <NA> 1997 42 1552 1.095360 0 0 3 13
  452. ## 4 National <NA> 1997 43 1669 0.419413 0 0 0 7
  453. ## 5 National <NA> 1997 44 1897 0.527148 0 0 9 1
  454. ## 6 National <NA> 1997 45 2106 0.284900 0 0 0 6
  455. ## 7 National <NA> 1997 46 2204 0.362976 0 0 3 4
  456. ## 8 National <NA> 1997 47 2533 0.908014 0 0 5 17
  457. ## 9 National <NA> 1997 48 2242 1.650310 0 0 14 22
  458. ## 10 National <NA> 1997 49 2607 1.534330 0 0 11 28
  459. ## # ... with 930 more rows, and 3 more variables: a_unable_to_subtype <int>, b <int>, h3n2v <int>
  460. ##
  461. ## $public_health_labs
  462. ## # A tibble: 108 x 12
  463. ## region_type region year week total_specimens a_2009_h1n1 a_h3 a_subtyping_not_performed b bvic byam h3n2v
  464. ## <chr> <chr> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
  465. ## 1 National <NA> 2015 40 1139 4 65 2 10 0 1 0
  466. ## 2 National <NA> 2015 41 1152 5 41 2 7 3 0 0
  467. ## 3 National <NA> 2015 42 1198 10 50 1 8 3 2 0
  468. ## 4 National <NA> 2015 43 1244 9 31 4 9 1 4 0
  469. ## 5 National <NA> 2015 44 1465 4 23 4 9 1 4 0
  470. ## 6 National <NA> 2015 45 1393 11 34 1 10 4 2 0
  471. ## 7 National <NA> 2015 46 1458 17 42 1 4 0 4 0
  472. ## 8 National <NA> 2015 47 1157 17 24 0 4 3 9 0
  473. ## 9 National <NA> 2015 48 1550 27 36 3 9 3 12 0
  474. ## 10 National <NA> 2015 49 1518 38 37 3 11 2 11 0
  475. ## # ... with 98 more rows
  476. ##
  477. ## $clinical_labs
  478. ## # A tibble: 108 x 10
  479. ## region_type region year week total_specimens total_a total_b percent_positive percent_a percent_b
  480. ## <chr> <chr> <int> <int> <int> <int> <int> <dbl> <dbl> <dbl>
  481. ## 1 National <NA> 2015 40 12029 84 43 1.05578 0.698312 0.357469
  482. ## 2 National <NA> 2015 41 13111 116 54 1.29662 0.884753 0.411868
  483. ## 3 National <NA> 2015 42 13441 97 52 1.10855 0.721672 0.386876
  484. ## 4 National <NA> 2015 43 13537 98 52 1.10807 0.723942 0.384132
  485. ## 5 National <NA> 2015 44 14687 97 68 1.12344 0.660448 0.462994
  486. ## 6 National <NA> 2015 45 15048 122 86 1.38224 0.810739 0.571505
  487. ## 7 National <NA> 2015 46 15250 84 98 1.19344 0.550820 0.642623
  488. ## 8 National <NA> 2015 47 15234 119 92 1.38506 0.781147 0.603912
  489. ## 9 National <NA> 2015 48 16201 145 81 1.39498 0.895006 0.499969
  490. ## 10 National <NA> 2015 49 16673 140 106 1.47544 0.839681 0.635758
  491. ## # ... with 98 more rows
  492. ``` r
  493. who_nrevss("hhs")
  494. ```
  495. ## $combined_prior_to_2015_16
  496. ## # A tibble: 9,400 x 13
  497. ## region_type region year week total_specimens percent_positive a_2009_h1n1 a_h1 a_h3 a_subtyping_not_performed
  498. ## <chr> <chr> <int> <int> <int> <dbl> <int> <int> <int> <int>
  499. ## 1 HHS Regions Region 1 1997 40 51 0 0 0 0 0
  500. ## 2 HHS Regions Region 2 1997 40 152 0 0 0 0 0
  501. ## 3 HHS Regions Region 3 1997 40 143 0 0 0 0 0
  502. ## 4 HHS Regions Region 4 1997 40 98 0 0 0 0 0
  503. ## 5 HHS Regions Region 5 1997 40 147 0 0 0 0 0
  504. ## 6 HHS Regions Region 6 1997 40 343 0 0 0 0 0
  505. ## 7 HHS Regions Region 7 1997 40 133 0 0 0 0 0
  506. ## 8 HHS Regions Region 8 1997 40 78 0 0 0 0 0
  507. ## 9 HHS Regions Region 9 1997 40 98 0 0 0 0 0
  508. ## 10 HHS Regions Region 10 1997 40 48 0 0 0 0 0
  509. ## # ... with 9,390 more rows, and 3 more variables: a_unable_to_subtype <int>, b <int>, h3n2v <int>
  510. ##
  511. ## $public_health_labs
  512. ## # A tibble: 1,080 x 12
  513. ## region_type region year week total_specimens a_2009_h1n1 a_h3 a_subtyping_not_performed b bvic byam
  514. ## <chr> <chr> <int> <chr> <int> <int> <int> <int> <int> <int> <int>
  515. ## 1 HHS Regions Region 1 2015 XX 39 0 5 0 0 0 0
  516. ## 2 HHS Regions Region 2 2015 XX 56 1 4 0 1 0 0
  517. ## 3 HHS Regions Region 3 2015 XX 132 1 3 0 0 0 0
  518. ## 4 HHS Regions Region 4 2015 XX 83 0 5 0 1 0 0
  519. ## 5 HHS Regions Region 5 2015 XX 218 2 7 0 0 0 1
  520. ## 6 HHS Regions Region 6 2015 XX 97 0 2 0 0 0 0
  521. ## 7 HHS Regions Region 7 2015 XX 36 0 2 0 0 0 0
  522. ## 8 HHS Regions Region 8 2015 XX 71 0 2 0 0 0 0
  523. ## 9 HHS Regions Region 9 2015 XX 273 0 22 2 8 0 0
  524. ## 10 HHS Regions Region 10 2015 XX 134 0 13 0 0 0 0
  525. ## # ... with 1,070 more rows, and 1 more variables: h3n2v <int>
  526. ##
  527. ## $clinical_labs
  528. ## # A tibble: 1,080 x 10
  529. ## region_type region year week total_specimens total_a total_b percent_positive percent_a percent_b
  530. ## <chr> <chr> <int> <int> <int> <int> <int> <dbl> <dbl> <dbl>
  531. ## 1 HHS Regions Region 1 2015 40 693 2 3 0.721501 0.288600 0.432900
  532. ## 2 HHS Regions Region 2 2015 40 1220 5 0 0.409836 0.409836 0.000000
  533. ## 3 HHS Regions Region 3 2015 40 896 0 1 0.111607 0.000000 0.111607
  534. ## 4 HHS Regions Region 4 2015 40 2486 24 16 1.609010 0.965406 0.643604
  535. ## 5 HHS Regions Region 5 2015 40 2138 14 3 0.795136 0.654818 0.140318
  536. ## 6 HHS Regions Region 6 2015 40 1774 8 16 1.352870 0.450958 0.901917
  537. ## 7 HHS Regions Region 7 2015 40 621 2 1 0.483092 0.322061 0.161031
  538. ## 8 HHS Regions Region 8 2015 40 824 1 1 0.242718 0.121359 0.121359
  539. ## 9 HHS Regions Region 9 2015 40 980 25 2 2.755100 2.551020 0.204082
  540. ## 10 HHS Regions Region 10 2015 40 397 3 0 0.755668 0.755668 0.000000
  541. ## # ... with 1,070 more rows
  542. ``` r
  543. who_nrevss("census")
  544. ```
  545. ## $combined_prior_to_2015_16
  546. ## # A tibble: 8,460 x 13
  547. ## region_type region year week total_specimens percent_positive a_2009_h1n1 a_h1 a_h3
  548. ## <chr> <chr> <int> <int> <int> <dbl> <int> <int> <int>
  549. ## 1 Census Regions New England 1997 40 51 0 0 0 0
  550. ## 2 Census Regions Mid-Atlantic 1997 40 155 0 0 0 0
  551. ## 3 Census Regions East North Central 1997 40 127 0 0 0 0
  552. ## 4 Census Regions West North Central 1997 40 183 0 0 0 0
  553. ## 5 Census Regions South Atlantic 1997 40 204 0 0 0 0
  554. ## 6 Census Regions East South Central 1997 40 34 0 0 0 0
  555. ## 7 Census Regions West South Central 1997 40 339 0 0 0 0
  556. ## 8 Census Regions Mountain 1997 40 85 0 0 0 0
  557. ## 9 Census Regions Pacific 1997 40 113 0 0 0 0
  558. ## 10 Census Regions New England 1997 41 54 0 0 0 0
  559. ## # ... with 8,450 more rows, and 4 more variables: a_subtyping_not_performed <int>, a_unable_to_subtype <int>, b <int>,
  560. ## # h3n2v <int>
  561. ##
  562. ## $public_health_labs
  563. ## # A tibble: 972 x 12
  564. ## region_type region year week total_specimens a_2009_h1n1 a_h3 a_subtyping_not_performed b
  565. ## <chr> <chr> <int> <chr> <int> <int> <int> <int> <int>
  566. ## 1 Census Regions New England 2015 XX 39 0 5 0 0
  567. ## 2 Census Regions Mid-Atlantic 2015 XX 63 1 5 0 1
  568. ## 3 Census Regions East North Central 2015 XX 91 2 5 0 0
  569. ## 4 Census Regions West North Central 2015 XX 169 0 4 0 0
  570. ## 5 Census Regions South Atlantic 2015 XX 187 1 7 0 0
  571. ## 6 Census Regions East South Central 2015 XX 21 0 0 0 1
  572. ## 7 Census Regions West South Central 2015 XX 72 0 2 0 0
  573. ## 8 Census Regions Mountain 2015 XX 111 0 6 0 0
  574. ## 9 Census Regions Pacific 2015 XX 386 0 31 2 8
  575. ## 10 Census Regions New England 2015 XX 39 2 3 0 0
  576. ## # ... with 962 more rows, and 3 more variables: bvic <int>, byam <int>, h3n2v <int>
  577. ##
  578. ## $clinical_labs
  579. ## # A tibble: 972 x 10
  580. ## region_type region year week total_specimens total_a total_b percent_positive percent_a percent_b
  581. ## <chr> <chr> <int> <int> <int> <int> <int> <dbl> <dbl> <dbl>
  582. ## 1 Census Regions New England 2015 40 693 2 3 0.721501 0.288600 0.4329000
  583. ## 2 Census Regions Mid-Atlantic 2015 40 1584 5 1 0.378788 0.315657 0.0631313
  584. ## 3 Census Regions East North Central 2015 40 1918 13 3 0.834202 0.677789 0.1564130
  585. ## 4 Census Regions West North Central 2015 40 978 3 1 0.408998 0.306748 0.1022490
  586. ## 5 Census Regions South Atlantic 2015 40 2403 20 12 1.331670 0.832293 0.4993760
  587. ## 6 Census Regions East South Central 2015 40 615 4 4 1.300810 0.650407 0.6504070
  588. ## 7 Census Regions West South Central 2015 40 1592 8 16 1.507540 0.502513 1.0050300
  589. ## 8 Census Regions Mountain 2015 40 943 1 1 0.212089 0.106045 0.1060450
  590. ## 9 Census Regions Pacific 2015 40 1303 28 2 2.302380 2.148890 0.1534920
  591. ## 10 Census Regions New England 2015 41 752 11 4 1.994680 1.462770 0.5319150
  592. ## # ... with 962 more rows
  593. ``` r
  594. who_nrevss("state")
  595. ```
  596. ## $combined_prior_to_2015_16
  597. ## # A tibble: 14,094 x 13
  598. ## region_type region year week total_specimens percent_positive a_2009_h1n1 a_h1 a_h3
  599. ## <chr> <chr> <int> <int> <chr> <chr> <chr> <chr> <chr>
  600. ## 1 States Alabama 2010 40 54 0 0 0 0
  601. ## 2 States Alaska 2010 40 40 0 0 0 0
  602. ## 3 States Arizona 2010 40 40 2.5 0 0 1
  603. ## 4 States Arkansas 2010 40 15 0 0 0 0
  604. ## 5 States California 2010 40 183 3.28 2 0 3
  605. ## 6 States Colorado 2010 40 126 0.79 0 0 1
  606. ## 7 States Connecticut 2010 40 54 0 0 0 0
  607. ## 8 States Delaware 2010 40 75 4 0 0 3
  608. ## 9 States District of Columbia 2010 40 14 0 0 0 0
  609. ## 10 States Florida 2010 40 <NA> <NA> <NA> <NA> <NA>
  610. ## # ... with 14,084 more rows, and 4 more variables: a_subtyping_not_performed <chr>, a_unable_to_subtype <chr>, b <chr>,
  611. ## # h3n2v <chr>
  612. ##
  613. ## $public_health_labs
  614. ## # A tibble: 162 x 11
  615. ## region_type region season_description total_specimens a_2009_h1n1 a_h3 a_subtyping_not_performed
  616. ## <chr> <chr> <chr> <chr> <chr> <chr> <chr>
  617. ## 1 States Alabama Season 2015-16 256 59 16 1
  618. ## 2 States Alaska Season 2015-16 4691 607 98 0
  619. ## 3 States Arizona Season 2015-16 2110 762 580 0
  620. ## 4 States Arkansas Season 2015-16 128 20 8 0
  621. ## 5 States California Season 2015-16 12241 1394 825 28
  622. ## 6 States Colorado Season 2015-16 1625 912 243 3
  623. ## 7 States Connecticut Season 2015-16 1581 662 52 0
  624. ## 8 States Delaware Season 2015-16 2754 414 20 12
  625. ## 9 States District of Columbia Season 2015-16 172 68 3 0
  626. ## 10 States Florida Season 2015-16 <NA> <NA> <NA> <NA>
  627. ## # ... with 152 more rows, and 4 more variables: b <chr>, bvic <chr>, byam <chr>, h3n2v <chr>
  628. ##
  629. ## $clinical_labs
  630. ## # A tibble: 5,832 x 10
  631. ## region_type region year week total_specimens total_a total_b percent_positive percent_a percent_b
  632. ## <chr> <chr> <int> <int> <chr> <chr> <chr> <chr> <chr> <chr>
  633. ## 1 States Alabama 2015 40 167 2 3 2.99 1.2 1.8
  634. ## 2 States Alaska 2015 40 <NA> <NA> <NA> <NA> <NA> <NA>
  635. ## 3 States Arizona 2015 40 55 0 0 0 0 0
  636. ## 4 States Arkansas 2015 40 26 0 1 3.85 0 3.85
  637. ## 5 States California 2015 40 679 2 0 0.29 0.29 0
  638. ## 6 States Colorado 2015 40 255 0 1 0.39 0 0.39
  639. ## 7 States Connecticut 2015 40 304 1 0 0.33 0.33 0
  640. ## 8 States Delaware 2015 40 22 0 0 0 0 0
  641. ## 9 States District of Columbia 2015 40 <NA> <NA> <NA> <NA> <NA> <NA>
  642. ## 10 States Florida 2015 40 <NA> <NA> <NA> <NA> <NA> <NA>
  643. ## # ... with 5,822 more rows
  644. Code of Conduct
  645. ---------------
  646. Please note that this project is released with a [Contributor Code of
  647. Conduct](CONDUCT.md). By participating in this project you agree to
  648. abide by its terms.