0.9.1

4 years ago · c2b16f4911
33 changed files with 484 additions and 512 deletions
--- a/11
+++ b/11
@ -3,8 +3,8 @@ Type: Package
 Encoding: UTF-8
 Title: Retrieve Flu Season Data from the United States Centers for Disease Control 
    and Prevention ('CDC') 'FluView' Portal
-Version: 0.9.0
-Date: 2019-01-23
+Version: 0.9.1
+Date: 2020-04-01
 Authors@R: c(
    person("Bob", "Rudis", email = "bob@rud.is", role = c("aut", "cre"), 
           comment = c(ORCID = "0000-0001-5670-2640")),
@ -20,12 +20,12 @@ Authors@R: c(
  )
 Maintainer: Bob Rudis <bob@rud.is>
 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 <https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html> for
    accessing state, regional and national influenza statistics as well as
    mortality surveillance data. The web interface makes it difficult and
    time-consuming to select and retrieve influenza data. Tools are provided 
    to access the data provided by the portal's underlying 'API'.
-URL: https://gitlab.com/hrbrmstr/cdcfluview
+URL: https://git.rud.is/hrbrmstr/cdcfluview
 BugReports: https://gitlab.com/hrbrmstr/cdcfluview/issues
 License: MIT + file LICENSE
 LazyData: true
@ -39,6 +39,7 @@ Imports:
    tools,
    dplyr,
    jsonlite,
+    tibble,
    stats,
    utils,
    sf,
@ -47,4 +48,4 @@ Imports:
    readr,
    MMWRweek,
    units (>= 0.4-6)
-RoxygenNote: 6.1.1
+RoxygenNote: 7.1.0
--- a/1
+++ b/1
@ -40,6 +40,7 @@ importFrom(readr,read_csv)
 importFrom(readr,type_convert)
 importFrom(sf,st_read)
 importFrom(stats,setNames)
+importFrom(tibble,tibble)
 importFrom(tools,file_path_sans_ext)
 importFrom(utils,URLencode)
 importFrom(utils,globalVariables)
--- a/NEWS.md
+++ b/NEWS.md
@ -2,6 +2,7 @@

 - renamed `pi_mortality` columns regarding the week to `week_*` instead of `wk_*`
  for consistency with `ilinet` (#21).
+- fixed CRAN check errors

 # cdcfluview 0.9.0

--- a/R/cdcfluview-package.R
+++ b/R/cdcfluview-package.R
@ -15,6 +15,7 @@
 #' @importFrom purrr map map_df map_chr map_lgl discard keep
 #' @importFrom readr read_csv type_convert
 #' @importFrom tools file_path_sans_ext
+#' @importFrom tibble tibble
 #' @importFrom dplyr left_join bind_rows mutate filter data_frame %>% arrange
 #' @importFrom jsonlite fromJSON
 #' @importFrom stats setNames
--- a/R/get-weekly-flu-report.r
+++ b/R/get-weekly-flu-report.r
@ -44,7 +44,7 @@ get_weekly_flu_report <- function() {
    color <- xml2::xml_text(xml2::xml_find_all(kids, "color"), TRUE)
    label <- xml2::xml_text(xml2::xml_find_all(kids, "label"), TRUE)

-    dplyr::data_frame(
+    tibble::tibble(
      year = period["year"],
      week_number = period["number"],
      state = abbrev,
--- a/R/mmwr-map.r
+++ b/R/mmwr-map.r
@ -15,7 +15,7 @@
 .tmp <- lapply(1962:2050, .start_date)

 mapply(function(.x, .y) {
-  data_frame(
+  tibble::tibble(
    wk_start = seq(.tmp[[.x]], .tmp[[.y]], "1 week"),
    wk_end = wk_start + 6,
    year_wk_num = 1:length(wk_start)
--- a/README.Rmd
+++ b/README.Rmd
@ -3,13 +3,13 @@ output: rmarkdown::github_document
 editor_options: 
  chunk_output_type: console
 ---
-```{r message=FALSE, warning=FALSE, error=FALSE, include=FALSE}
-knitr::opts_chunk$set(message=FALSE, warning=FALSE, fig.retina=2)
-options(width=120)
+```{r pkg-knitr-opts, include=FALSE}
+hrbrpkghelpr::global_opts()
+```
+
+```{r badges, results='asis', echo=FALSE, cache=FALSE}
+hrbrpkghelpr::stinking_badges()
 ```
-[![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

@ -181,9 +181,9 @@ count(xdf, weekend, activity_level_label) %>%
 ```{r nat-pi-mortality}
 (nat_pi <- pi_mortality("national"))

-select(nat_pi, wk_end, percent_pni, baseline, threshold) %>% 
-  gather(measure, value, -wk_end) %>% 
-  ggplot(aes(wk_end, value)) + 
+select(nat_pi, week_end, percent_pni, baseline, threshold) %>% 
+  gather(measure, value, -week_end) %>% 
+  ggplot(aes(week_end, value)) + 
  geom_line(aes(group=measure, color=measure)) + 
  scale_y_percent() +
  scale_color_ipsum(name = NULL, labels=c("Baseline", "Percent P&I", "Threshold")) +
@ -231,4 +231,4 @@ cloc::cloc_pkg_md()

 ## 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. By participating in this project you agree to abide by its terms.
--- a/README.md
+++ b/README.md
@ -1,9 +1,22 @@

-[![CRAN\_Status\_Badge](http://www.r-pkg.org/badges/version/cdcfluview)](https://cran.r-project.org/package=cdcfluview)
-[![Travis-CI Build
+[![Project Status: Active – The project has reached a stable, usable
+state and is being actively
+developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
+[![Signed
+by](https://img.shields.io/badge/Keybase-Verified-brightgreen.svg)](https://keybase.io/hrbrmstr)
+![Signed commit
+%](https://img.shields.io/badge/Signed_Commits-14%25-lightgrey.svg)
+[![Linux 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)
+Status](https://codecov.io/gh/hrbrmstr/cdcfluview/branch/master/graph/badge.svg)](https://codecov.io/gh/hrbrmstr/cdcfluview)
+[![cran
+checks](https://cranchecks.info/badges/worst/cdcfluview)](https://cranchecks.info/pkgs/cdcfluview)
+[![CRAN
+status](https://www.r-pkg.org/badges/version/cdcfluview)](https://www.r-pkg.org/pkg/cdcfluview)
+![Minimal R
+Version](https://img.shields.io/badge/R%3E%3D-3.2.0-blue.svg)
+![License](https://img.shields.io/badge/License-MIT-blue.svg)

 # I M P O R T A N T

@ -109,25 +122,22 @@ library(tidyverse)

 # current verison
 packageVersion("cdcfluview")
+## [1] '0.9.1'
 ```

-    ## [1] '0.8.0'
-
 ### Age Group Distribution of Influenza Positive Tests Reported by Public Health Laboratories

 ``` r
 glimpse(age_group_distribution(years=2015))
-```
-
-    ## Observations: 1,872
-    ## Variables: 16
+## Rows: 1,872
+## Columns: 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, 0-4…
 ## $ 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, 0…
 ## $ 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, 55,…
-    ## $ publishyearweekid <int> 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2976, 2…
+## $ publishyearweekid <int> 3038, 3038, 3038, 3038, 3038, 3038, 3038, 3038, 3038, 3038, 3038, 3038, 3038, 3038, 3038, 3…
 ## $ 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, 2…
 ## $ sea_endweek       <int> 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2…
@ -137,6 +147,7 @@ glimpse(age_group_distribution(years=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, 2015-1…
 ## $ 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, …
+```

 ### Retrieve CDC U.S. Coverage Map

@ -144,46 +155,44 @@ glimpse(age_group_distribution(years=2015))
 plot(cdc_basemap("national"))
 ```

-<img src="README_files/figure-gfm/cdc-basemaps-1.png" width="672" />
+<img src="man/figures/README-cdc-basemaps-1.png" width="672" />

 ``` r
 plot(cdc_basemap("hhs"))
 ```

-<img src="README_files/figure-gfm/cdc-basemaps-2.png" width="672" />
+<img src="man/figures/README-cdc-basemaps-2.png" width="672" />

 ``` r
 plot(cdc_basemap("census"))
 ```

-<img src="README_files/figure-gfm/cdc-basemaps-3.png" width="672" />
+<img src="man/figures/README-cdc-basemaps-3.png" width="672" />

 ``` r
 plot(cdc_basemap("states"))
 ```

-<img src="README_files/figure-gfm/cdc-basemaps-4.png" width="672" />
+<img src="man/figures/README-cdc-basemaps-4.png" width="672" />

 ``` r
 plot(cdc_basemap("spread"))
 ```

-<img src="README_files/figure-gfm/cdc-basemaps-5.png" width="672" />
+<img src="man/figures/README-cdc-basemaps-5.png" width="672" />

 ``` r
 plot(cdc_basemap("surv"))
 ```

-<img src="README_files/figure-gfm/cdc-basemaps-6.png" width="672" />
+<img src="man/figures/README-cdc-basemaps-6.png" width="672" />

 ### State and Territorial Epidemiologists Reports of Geographic Spread of Influenza

 ``` r
 glimpse(geographic_spread())
-```
-
-    ## Observations: 28,151
-    ## Variables: 7
+## Rows: 30,427
+## Columns: 7
 ## $ 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/", "…
 ## $ website           <chr> "Influenza Surveillance", "Influenza Surveillance", "Influenza Surveillance", "Influenza Su…
@ -191,13 +200,12 @@ glimpse(geographic_spread())
 ## $ 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", "20…
 ## $ weeknumber        <chr> "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "1", "2…
+```

 ### Laboratory-Confirmed Influenza Hospitalizations

 ``` r
 surveillance_areas()
-```
-
 ##    surveillance_area               region
 ## 1            flusurv       Entire Network
 ## 2                eip           California
@ -222,28 +230,24 @@ surveillance_areas()
 ## 21              ihsp         South Dakota
 ## 22              ihsp                 Utah

-``` r
 glimpse(fs_nat <- hospitalizations("flusurv"))
-```
-
-    ## Observations: 1,746
-    ## Variables: 14
+## Rows: 2,979
+## Columns: 14
 ## $ 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", "…
-    ## $ 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, 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, 2009-1…
-    ## $ wk_end            <date> 2009-09-05, 2009-09-12, 2009-09-19, 2009-09-26, 2009-10-03, 2009-10-10, 2009-10-17, 2009-1…
-    ## $ 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, 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, 65.1,…
-    ## $ 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, 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, 0-4…
-    ## $ 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", "…
-    ## $ mmwrid            <int> 2488, 2489, 2490, 2491, 2492, 2493, 2494, 2495, 2496, 2497, 2498, 2499, 2500, 2501, 2502, 2…
+## $ year              <int> 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2018, 2018, 2…
+## $ season            <int> 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57, 57,…
+## $ wk_start          <date> 2017-10-01, 2017-10-08, 2017-10-15, 2017-10-22, 2017-10-29, 2017-11-05, 2017-11-12, 2017-1…
+## $ wk_end            <date> 2017-10-07, 2017-10-14, 2017-10-21, 2017-10-28, 2017-11-04, 2017-11-11, 2017-11-18, 2017-1…
+## $ 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, …
+## $ rate              <dbl> 0.0, 0.1, 0.1, 0.1, 0.3, 0.4, 0.6, 0.8, 1.0, 1.3, 1.8, 2.5, 3.4, 4.2, 5.6, 6.8, 8.2, 10.3, …
+## $ weeklyrate        <dbl> 0.0, 0.0, 0.0, 0.0, 0.1, 0.1, 0.2, 0.2, 0.2, 0.3, 0.6, 0.6, 0.9, 0.8, 1.3, 1.3, 1.4, 2.1, 1…
+## $ age               <int> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3…
+## $ age_label         <fct> 5-17 yr, 5-17 yr, 5-17 yr, 5-17 yr, 5-17 yr, 5-17 yr, 5-17 yr, 5-17 yr, 5-17 yr, 5-17 yr, 5…
+## $ sea_label         <chr> "2017-18", "2017-18", "2017-18", "2017-18", "2017-18", "2017-18", "2017-18", "2017-18", "20…
+## $ sea_description   <chr> "Season 2017-18", "Season 2017-18", "Season 2017-18", "Season 2017-18", "Season 2017-18", "…
+## $ mmwrid            <int> 2910, 2911, 2912, 2913, 2914, 2915, 2916, 2917, 2918, 2919, 2920, 2921, 2922, 2923, 2924, 2…

-``` r
 ggplot(fs_nat, aes(wk_end, rate)) + 
  geom_line(aes(color=age_label, group=age_label)) +
  facet_wrap(~sea_description, scales="free_x") +
@ -253,14 +257,13 @@ ggplot(fs_nat, aes(wk_end, rate)) +
  theme_ipsum_rc()
 ```

-<img src="README_files/figure-gfm/surveillance-areas-1.png" width="960" />
+<img src="man/figures/README-surveillance-areas-1.png" width="960" />

 ``` r
-glimpse(hospitalizations("eip", years=2015))
-```

-    ## Observations: 180
-    ## Variables: 14
+glimpse(hospitalizations("eip", years=2015))
+## Rows: 270
+## Columns: 14
 ## $ 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", "…
 ## $ year              <int> 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 2…
@ -268,20 +271,17 @@ glimpse(hospitalizations("eip", years=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, 2015-1…
 ## $ 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, …
-    ## $ 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, 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, 0-4…
+## $ rate              <dbl> 0.4, 0.7, 1.0, 1.1, 1.4, 1.6, 1.9, 2.2, 2.4, 2.8, 3.4, 4.4, 5.0, 6.5, 7.6, 8.7, 10.4, 12.5,…
+## $ weeklyrate        <dbl> 0.4, 0.3, 0.3, 0.2, 0.3, 0.3, 0.3, 0.3, 0.2, 0.4, 0.6, 0.9, 0.6, 1.5, 1.1, 1.1, 1.6, 2.1, 3…
+## $ age               <int> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 2…
+## $ age_label         <fct> 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+…
 ## $ 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", "…
 ## $ mmwrid            <int> 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2…

-``` r
 glimpse(hospitalizations("eip", "Colorado", years=2015))
-```
-
-    ## Observations: 180
-    ## Variables: 14
+## Rows: 270
+## Columns: 14
 ## $ 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", "Colora…
 ## $ year              <int> 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 2…
@ -289,20 +289,17 @@ glimpse(hospitalizations("eip", "Colorado", years=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, 2015-1…
 ## $ 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, …
-    ## $ 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, 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, 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, 0-4…
+## $ rate              <dbl> 0.0, 0.3, 0.6, 0.9, 0.9, 1.3, 1.3, 1.6, 1.6, 2.5, 2.8, 4.4, 6.3, 7.8, 9.7, 10.7, 12.5, 14.7…
+## $ weeklyrate        <dbl> 0.0, 0.3, 0.3, 0.3, 0.0, 0.3, 0.0, 0.3, 0.0, 0.9, 0.3, 1.6, 1.9, 1.6, 1.9, 0.9, 1.9, 2.2, 2…
+## $ age               <int> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 2…
+## $ age_label         <fct> 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+…
 ## $ 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", "…
 ## $ mmwrid            <int> 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2…

-``` r
 glimpse(hospitalizations("ihsp", years=2015))
-```
-
-    ## Observations: 180
-    ## Variables: 14
+## Rows: 270
+## Columns: 14
 ## $ 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", "…
 ## $ year              <int> 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 2…
@ -310,20 +307,17 @@ glimpse(hospitalizations("ihsp", years=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, 2015-1…
 ## $ 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, …
-    ## $ 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, 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, 0-4…
+## $ rate              <dbl> 0.4, 0.8, 1.0, 1.2, 1.4, 1.4, 1.4, 1.6, 1.8, 2.0, 2.5, 3.1, 3.5, 4.1, 5.1, 6.5, 8.0, 10.0, …
+## $ weeklyrate        <dbl> 0.4, 0.4, 0.2, 0.2, 0.2, 0.0, 0.0, 0.2, 0.2, 0.2, 0.4, 0.6, 0.4, 0.6, 1.0, 1.4, 1.4, 2.0, 4…
+## $ age               <int> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 2…
+## $ age_label         <fct> 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+ yr, 65+…
 ## $ 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", "…
 ## $ mmwrid            <int> 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2…

-``` r
 glimpse(hospitalizations("ihsp", "Oklahoma", years=2015))
-```
-
-    ## Observations: 180
-    ## Variables: 14
+## Rows: 270
+## Columns: 14
 ## $ surveillance_area <chr> "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IH…
 ## $ 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, 2…
@ -331,13 +325,14 @@ glimpse(hospitalizations("ihsp", "Oklahoma", years=2015))
 ## $ 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, 2010-1…
 ## $ 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, …
-    ## $ 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, 1.2, 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, 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, 0-4…
+## $ rate              <dbl> 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2, 0.2, 0.5, 0.7, 0.7, 1.4, 2.3, 2.5, 3.5, 4.6, 6.0, 7.8, 8…
+## $ 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, 1.2, 1.4, 1.8, 0…
+## $ 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, 8…
+## $ age_label         <fct> 18-49 yr, 18-49 yr, 18-49 yr, 18-49 yr, 18-49 yr, 18-49 yr, 18-49 yr, 18-49 yr, 18-49 yr, 1…
 ## $ 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", "…
 ## $ mmwrid            <int> 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559, 2…
+```

 ### Retrieve ILINet Surveillance Data

@ -358,10 +353,8 @@ walk(c("national", "hhs", "census", "state"), ~{
  print(gg)
  
 })
-```
-
-    ## Observations: 1,111
-    ## Variables: 16
+## Rows: 1,173
+## Columns: 16
 ## $ region_type      <chr> "National", "National", "National", "National", "National", "National", "National", "Nationa…
 ## $ 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, 19…
@ -378,7 +371,7 @@ walk(c("national", "hhs", "census", "state"), ~{
 ## $ 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, 5…
 ## $ 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: 1,111 x 16
+## # A tibble: 1,173 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
 ##    <chr>       <chr>  <int> <int>        <dbl>          <dbl>   <dbl>     <dbl>     <dbl>    <dbl>     <dbl>  <dbl>
 ##  1 National    Natio…  1997    40         1.10           1.22     179        NA       157      205        NA     29
@ -391,13 +384,14 @@ walk(c("national", "hhs", "census", "state"), ~{
 ##  8 National    Natio…  1997    47         2.45           1.65     288        NA       293      456        NA     63
 ##  9 National    Natio…  1997    48         1.74           1.68     268        NA       206      343        NA     69
 ## 10 National    Natio…  1997    49         1.94           1.62     299        NA       282      415        NA    102
-    ## # … with 1,101 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>,
+## # … with 1,163 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>,
 ## #   week_start <date>
+```

-<img src="README_files/figure-gfm/ili-df-1.png" width="672" />
+<img src="man/figures/README-ili-df-1.png" width="672" />

-    ## Observations: 11,110
-    ## Variables: 16
+    ## Rows: 11,730
+    ## Columns: 16
    ## $ 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, Re…
    ## $ year             <int> 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 19…
@ -414,7 +408,7 @@ walk(c("national", "hhs", "census", "state"), ~{
    ## $ 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, 68…
    ## $ 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: 11,110 x 16
+    ## # A tibble: 11,730 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
    ##    <chr>       <fct>  <int> <int>        <dbl>          <dbl>   <dbl>     <dbl>     <dbl>    <dbl>     <dbl>  <dbl>
    ##  1 HHS Regions Regio…  1997    40        0.499          0.624      15        NA         7       22        NA      0
@ -427,13 +421,13 @@ walk(c("national", "hhs", "census", "state"), ~{
    ##  8 HHS Regions Regio…  1997    40        0.516          0.423       2        NA         0        3        NA      0
    ##  9 HHS Regions Regio…  1997    40        1.81           2.26       80        NA        76       74        NA     13
    ## 10 HHS Regions Regio…  1997    40        4.74           4.83       31        NA        12       30        NA      3
-    ## # … with 11,100 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>,
+    ## # … with 11,720 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>,
    ## #   week_start <date>

-<img src="README_files/figure-gfm/ili-df-2.png" width="672" />
+<img src="man/figures/README-ili-df-2.png" width="672" />

-    ## Observations: 9,999
-    ## Variables: 16
+    ## Rows: 10,557
+    ## Columns: 16
    ## $ 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",…
    ## $ year             <int> 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 19…
@ -450,7 +444,7 @@ walk(c("national", "hhs", "census", "state"), ~{
    ## $ 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, 68…
    ## $ 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: 9,999 x 16
+    ## # A tibble: 10,557 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
    ##    <chr>       <chr>  <int> <int>        <dbl>          <dbl>   <dbl>     <dbl>     <dbl>    <dbl>     <dbl>  <dbl>
    ##  1 Census Reg… New E…  1997    40       0.499          0.624       15        NA         7       22        NA      0
@ -463,13 +457,13 @@ walk(c("national", "hhs", "census", "state"), ~{
    ##  8 Census Reg… Mount…  1997    40       2.26           2.28        87        NA        71       71        NA     15
    ##  9 Census Reg… Pacif…  1997    40       2.05           3.23        26        NA        17       36        NA      1
    ## 10 Census Reg… New E…  1997    41       0.643          0.816       14        NA        14       29        NA      0
-    ## # … with 9,989 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>,
+    ## # … with 10,547 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>,
    ## #   week_start <date>

-<img src="README_files/figure-gfm/ili-df-3.png" width="672" />
+<img src="man/figures/README-ili-df-3.png" width="672" />

-    ## Observations: 23,120
-    ## Variables: 16
+    ## Rows: 26,493
+    ## Columns: 16
    ## $ region_type      <chr> "States", "States", "States", "States", "States", "States", "States", "States", "States", "S…
    ## $ 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, 20…
@ -486,7 +480,7 @@ walk(c("national", "hhs", "census", "state"), ~{
    ## $ 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, 1252…
    ## $ 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: 23,120 x 16
+    ## # A tibble: 26,493 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
    ##    <chr>       <chr>  <int> <int>        <dbl>          <dbl>   <dbl>     <dbl>     <dbl>    <dbl>     <dbl>  <dbl>
    ##  1 States      Alaba…  2010    40           NA         2.13        NA        NA        NA       NA        NA     NA
@ -499,33 +493,30 @@ walk(c("national", "hhs", "census", "state"), ~{
    ##  8 States      Delaw…  2010    40           NA         0.100       NA        NA        NA       NA        NA     NA
    ##  9 States      Distr…  2010    40           NA         2.81        NA        NA        NA       NA        NA     NA
    ## 10 States      Flori…  2010    40           NA        NA           NA        NA        NA       NA        NA     NA
-    ## # … with 23,110 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>,
+    ## # … with 26,483 more rows, and 4 more variables: ilitotal <dbl>, num_of_providers <dbl>, total_patients <dbl>,
    ## #   week_start <date>

-<img src="README_files/figure-gfm/ili-df-4.png" width="672" />
+<img src="man/figures/README-ili-df-4.png" width="672" />

 ### Retrieve weekly state-level ILI indicators per-state for a given season

 ``` r
 ili_weekly_activity_indicators(2017)
-```
-
 ## # A tibble: 2,805 x 8
-    ##    statename    url                         website        activity_level activity_level_l… weekend    season weeknumber
+##    statename      url                website   activity_level activity_level_label weekend    season  weeknumber
 ##  * <chr>          <chr>              <chr>              <dbl> <chr>                <date>     <chr>        <dbl>
-    ##  1 Alabama      http://adph.org/influenza/  Influenza Sur…              2 Minimal           2017-10-07 2017-…         40
-    ##  2 Alaska       "http://dhss.alaska.gov/dp… Influenza Sur…              1 Minimal           2017-10-07 2017-…         40
-    ##  3 Arizona      http://www.azdhs.gov/phs/o… Influenza & R…              2 Minimal           2017-10-07 2017-…         40
-    ##  4 Arkansas     http://www.healthy.arkansa… Communicable …              1 Minimal           2017-10-07 2017-…         40
-    ##  5 California   https://www.cdph.ca.gov/Pr… Influenza (Fl…              2 Minimal           2017-10-07 2017-…         40
-    ##  6 Colorado     https://www.colorado.gov/p… Influenza Sur…              1 Minimal           2017-10-07 2017-…         40
-    ##  7 Connecticut  http://www.portal.ct.gov/D… Flu Statistics              1 Minimal           2017-10-07 2017-…         40
-    ##  8 Delaware     http://dhss.delaware.gov/d… Weekly Influe…              1 Minimal           2017-10-07 2017-…         40
-    ##  9 District of… http://doh.dc.gov/page/inf… Influenza Inf…              2 Minimal           2017-10-07 2017-…         40
-    ## 10 Florida      "http://www.floridahealth.… Weekly Influe…              1 Minimal           2017-10-07 2017-…         40
+##  1 Virgin Islands http://doh.vi.gov/ Influenza              0 Insufficient Data    2017-10-07 2017-18         40
+##  2 Virgin Islands http://doh.vi.gov/ Influenza              0 Insufficient Data    2017-10-14 2017-18         41
+##  3 Virgin Islands http://doh.vi.gov/ Influenza              0 Insufficient Data    2017-10-21 2017-18         42
+##  4 Virgin Islands http://doh.vi.gov/ Influenza              0 Insufficient Data    2017-10-28 2017-18         43
+##  5 Virgin Islands http://doh.vi.gov/ Influenza              0 Insufficient Data    2017-11-04 2017-18         44
+##  6 Virgin Islands http://doh.vi.gov/ Influenza              0 Insufficient Data    2017-11-11 2017-18         45
+##  7 Virgin Islands http://doh.vi.gov/ Influenza              0 Insufficient Data    2017-12-02 2017-18         48
+##  8 Virgin Islands http://doh.vi.gov/ Influenza              0 Insufficient Data    2017-12-09 2017-18         49
+##  9 Virgin Islands http://doh.vi.gov/ Influenza              0 Insufficient Data    2017-12-23 2017-18         51
+## 10 Virgin Islands http://doh.vi.gov/ Influenza              0 Insufficient Data    2017-12-30 2017-18         52
 ## # … with 2,795 more rows

-``` r
 xdf <- map_df(2008:2017, ili_weekly_activity_indicators)

 count(xdf, weekend, activity_level_label) %>% 
@ -540,35 +531,32 @@ count(xdf, weekend, activity_level_label) %>%
  theme(legend.position="bottom")
 ```

-<img src="README_files/figure-gfm/ili-weekly-activity-1.png" width="960" />
+<img src="man/figures/README-ili-weekly-activity-1.png" width="960" />

 ### Pneumonia and Influenza Mortality Surveillance

 ``` r
 (nat_pi <- pi_mortality("national"))
-```
-
-    ## # A tibble: 483 x 19
+## # A tibble: 337 x 19
 ##    seasonid baseline threshold percent_pni percent_complete number_influenza number_pneumonia all_deaths total_pni
 ##    <chr>       <dbl>     <dbl>       <dbl>            <dbl>            <dbl>            <dbl>      <dbl>     <dbl>
-    ##  1 58         0.055     0.0580      0.0560                1               10             2880      51416      2890
-    ##  2 58         0.0560    0.059       0.055                 1               12             2765      50411      2777
-    ##  3 58         0.0560    0.06        0.0560                1               18             2802      50742      2820
-    ##  4 58         0.057     0.061       0.057                 1               22             2895      51425      2917
-    ##  5 58         0.0580    0.062       0.0560                1               23             2819      51136      2842
-    ##  6 58         0.059     0.063       0.0560                1               28             2819      50945      2847
-    ##  7 58         0.06      0.064       0.0580                1               25             2953      51618      2978
-    ##  8 58         0.061     0.065       0.057                 1               31             2905      51109      2936
-    ##  9 58         0.062     0.066       0.059                 1               34             2923      49720      2957
-    ## 10 58         0.064     0.067       0.06                  1               48             2857      48381      2905
-    ## # … 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>,
+##  1 59         0.053     0.057       0.052                 1               16             2702      52444      2718
+##  2 59         0.054     0.057       0.053                 1               16             2769      52858      2785
+##  3 59         0.055     0.0580      0.055                 1               18             2976      54120      2994
+##  4 59         0.0560    0.059       0.0560                1               30             2984      53906      3014
+##  5 59         0.057     0.06        0.054                 1               31             2906      53971      2937
+##  6 59         0.0580    0.062       0.0560                1               31             3061      55460      3092
+##  7 59         0.059     0.063       0.0560                1               39             3092      55679      3131
+##  8 59         0.06      0.064       0.054                 1               50             2992      55976      3042
+##  9 59         0.062     0.065       0.055                 1               65             2971      55225      3036
+## 10 59         0.063     0.066       0.06                  1               99             3305      56974      3404
+## # … with 327 more rows, and 10 more variables: weeknumber <chr>, geo_description <chr>, age_label <chr>,
+## #   week_start <date>, week_end <date>, year_week_num <int>, mmwrid <chr>, coverage_area <chr>, region_name <chr>,
 ## #   callout <chr>

-``` r
-select(nat_pi, wk_end, percent_pni, baseline, threshold) %>% 
-  gather(measure, value, -wk_end) %>% 
-  ggplot(aes(wk_end, value)) + 
+select(nat_pi, week_end, percent_pni, baseline, threshold) %>% 
+  gather(measure, value, -week_end) %>% 
+  ggplot(aes(week_end, value)) + 
  geom_line(aes(group=measure, color=measure)) + 
  scale_y_percent() +
  scale_color_ipsum(name = NULL, labels=c("Baseline", "Percent P&I", "Threshold")) +
@ -578,79 +566,73 @@ select(nat_pi, wk_end, percent_pni, baseline, threshold) %>%
  theme(legend.position="bottom")
 ```

-<img src="README_files/figure-gfm/nat-pi-mortality-1.png" width="672" />
+<img src="man/figures/README-nat-pi-mortality-1.png" width="672" />

 ``` r
-(st_pi <- pi_mortality("state", years=2015))
-```

+(st_pi <- pi_mortality("state", years=2015))
 ## # A tibble: 2,704 x 19
 ##    seasonid baseline threshold percent_pni percent_complete number_influenza number_pneumonia all_deaths total_pni
 ##    <chr>       <dbl>     <dbl>       <dbl>            <dbl>            <dbl>            <dbl>      <dbl>     <dbl>
-    ##  1 55             NA        NA      0.047             1                    0               46        979        46
-    ##  2 55             NA        NA      0.038             0.963                0               34        889        34
-    ##  3 55             NA        NA      0.053             1                    0               52        978        52
-    ##  4 55             NA        NA      0.07              1                    0               68        968        68
-    ##  5 55             NA        NA      0.053             0.981                0               48        906        48
-    ##  6 55             NA        NA      0.0580            1                    0               56        968        56
-    ##  7 55             NA        NA      0.051             1                    0               53       1041        53
-    ##  8 55             NA        NA      0.062             1                    1               63       1031        64
-    ##  9 55             NA        NA      0.0560            1                    0               55        976        55
-    ## 10 55             NA        NA      0.054             1                    0               56       1045        56
+##  1 55             NA        NA      0.046             0.962                0               43        935        43
+##  2 55             NA        NA      0.036             0.835                0               29        811        29
+##  3 55             NA        NA      0.054             0.833                0               44        809        44
+##  4 55             NA        NA      0.07              0.947                0               64        920        64
+##  5 55             NA        NA      0.053             0.926                0               48        900        48
+##  6 55             NA        NA      0.057             0.987                0               55        959        55
+##  7 55             NA        NA      0.052             1                    0               53       1023        53
+##  8 55             NA        NA      0.063             1                    1               62       1002        63
+##  9 55             NA        NA      0.0560            0.95                 0               52        923        52
+## 10 55             NA        NA      0.054             0.954                0               50        927        50
 ## # … 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>,
+## #   week_start <date>, week_end <date>, year_week_num <int>, mmwrid <chr>, coverage_area <chr>, region_name <chr>,
 ## #   callout <chr>

-``` r
 (reg_pi <- pi_mortality("region", years=2015))
-```
-
 ## # A tibble: 520 x 19
 ##    seasonid baseline threshold percent_pni percent_complete number_influenza number_pneumonia all_deaths total_pni
 ##    <chr>       <dbl>     <dbl>       <dbl>            <dbl>            <dbl>            <dbl>      <dbl>     <dbl>
-    ##  1 55          0.065    0.072       0.07                  1                0              178       2525       178
+##  1 55          0.064    0.072       0.07              1                    0              178       2525       178
 ##  2 55          0.065    0.073       0.064             1                    0              160       2512       160
 ##  3 55          0.066    0.074       0.0580            1                    1              141       2457       142
-    ##  4 55          0.067    0.075       0.07                  1                0              171       2426       171
-    ##  5 55          0.068    0.076       0.065                 1                2              166       2565       168
-    ##  6 55          0.069    0.077       0.067                 1                1              162       2415       163
-    ##  7 55          0.071    0.078       0.079                 1                0              198       2491       198
-    ##  8 55          0.072    0.08        0.072                 1                1              176       2469       177
-    ##  9 55          0.073    0.081       0.067                 1                3              154       2353       157
-    ## 10 55          0.075    0.0820      0.062                 1                0              151       2441       151
+##  4 55          0.067    0.075       0.07              0.989                0              171       2426       171
+##  5 55          0.068    0.077       0.065             1                    2              166       2565       168
+##  6 55          0.07     0.078       0.067             0.984                1              162       2415       163
+##  7 55          0.071    0.079       0.079             1                    0              198       2491       198
+##  8 55          0.073    0.081       0.072             1                    1              176       2468       177
+##  9 55          0.074    0.0820      0.067             0.959                3              154       2353       157
+## 10 55          0.076    0.084       0.062             0.995                0              151       2441       151
 ## # … 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>,
+## #   week_start <date>, week_end <date>, year_week_num <int>, mmwrid <chr>, coverage_area <chr>, region_name <chr>,
 ## #   callout <chr>
+```

 ### Retrieve metadata about U.S. State CDC Provider Data

 ``` r
 state_data_providers()
-```
-
 ## # A tibble: 59 x 5
 ##    statename     statehealthdeptname          url                                statewebsitename       statefluphonenum
 ##  * <chr>         <chr>                        <chr>                              <chr>                  <chr>           
-    ##  1 Alabama       Alabama Department of Publi… http://adph.org/influenza/        Influenza Surveillance  334-206-5300    
-    ##  2 Alaska        State of Alaska Health and … "http://dhss.alaska.gov/dph/Epi/… Influenza Surveillance… 907-269-8000    
-    ##  3 Arizona       Arizona Department of Healt… http://www.azdhs.gov/phs/oids/ep… Influenza & RSV Survei… 602-542-1025    
-    ##  4 Arkansas      Arkansas Department of Heal… http://www.healthy.arkansas.gov/… Communicable Disease a… 501-661-2000    
-    ##  5 California    California Department of Pu… https://www.cdph.ca.gov/Programs… Influenza (Flu)         916-558-1784    
-    ##  6 Colorado      Colorado Department of Publ… https://www.colorado.gov/pacific… Influenza Surveillance  303-692-2000    
-    ##  7 Connecticut   Connecticut Department of P… http://www.portal.ct.gov/DPH/Inf… Flu Statistics          860-509-8000    
-    ##  8 Delaware      Delaware Health and Social … http://dhss.delaware.gov/dhss/dp… Weekly Influenza Surve… 302-744-4700    
-    ##  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://www.floridahealth.gov/di… Weekly Influenza Surve… 850-245-4300    
+##  1 Alabama       Alabama Department of Publi… "http://adph.org/influenza/"       Influenza Surveillance 334-206-5300    
+##  2 Alaska        State of Alaska Health and … "http://dhss.alaska.gov/dph/Epi/i… Influenza Surveillanc… 907-269-8000    
+##  3 Arizona       Arizona Department of Healt… "http://www.azdhs.gov/phs/oids/ep… Influenza & RSV Surve… 602-542-1025    
+##  4 Arkansas      Arkansas Department of Heal… "http://www.healthy.arkansas.gov/… Communicable Disease … 501-661-2000    
+##  5 California    California Department of Pu… "https://www.cdph.ca.gov/Programs… Influenza (Flu)        916-558-1784    
+##  6 Colorado      Colorado Department of Publ… "https://www.colorado.gov/pacific… Influenza Surveillance 303-692-2000    
+##  7 Connecticut   Connecticut Department of P… "https://portal.ct.gov/DPH/Epidem… Flu Statistics         860-509-8000    
+##  8 Delaware      Delaware Health and Social … "http://dhss.delaware.gov/dhss/dp… Weekly Influenza Surv… 302-744-4700    
+##  9 District of … District of Columbia Depart… "https://dchealth.dc.gov/flu "     Influenza Information  202-442-5955    
+## 10 Florida       Florida Department of Health "http://www.floridahealth.gov/dis… Weekly Influenza Surv… 850-245-4300    
 ## # … with 49 more rows
+```

 ### Retrieve WHO/NREVSS Surveillance Data

 ``` r
 glimpse(xdat <- who_nrevss("national"))
-```
-
 ## List of 3
-    ##  $ combined_prior_to_2015_16:Classes 'tbl_df', 'tbl' and 'data.frame':   940 obs. of  14 variables:
+##  $ combined_prior_to_2015_16: tibble [940 × 14] (S3: tbl_df/tbl/data.frame)
 ##   ..$ region_type              : chr [1:940] "National" "National" "National" "National" ...
 ##   ..$ region                   : chr [1:940] "National" "National" "National" "National" ...
 ##   ..$ year                     : int [1:940] 1997 1997 1997 1997 1997 1997 1997 1997 1997 1997 ...
@ -665,34 +647,33 @@ glimpse(xdat <- who_nrevss("national"))
 ##   ..$ 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 ...
 ##   ..$ 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':   171 obs. of  13 variables:
-    ##   ..$ region_type              : chr [1:171] "National" "National" "National" "National" ...
-    ##   ..$ region                   : chr [1:171] "National" "National" "National" "National" ...
-    ##   ..$ year                     : int [1:171] 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 ...
-    ##   ..$ week                     : int [1:171] 40 41 42 43 44 45 46 47 48 49 ...
-    ##   ..$ total_specimens          : int [1:171] 1139 1152 1198 1244 1465 1393 1458 1157 1550 1518 ...
-    ##   ..$ a_2009_h1n1              : int [1:171] 4 5 10 9 4 11 17 17 27 38 ...
-    ##   ..$ a_h3                     : int [1:171] 65 41 50 31 23 34 42 24 36 37 ...
-    ##   ..$ a_subtyping_not_performed: int [1:171] 2 2 1 4 4 1 1 0 3 3 ...
-    ##   ..$ b                        : int [1:171] 10 7 8 9 9 10 4 4 9 11 ...
-    ##   ..$ bvic                     : int [1:171] 0 3 3 1 1 4 0 3 3 2 ...
-    ##   ..$ byam                     : int [1:171] 1 0 2 4 4 2 4 9 12 11 ...
-    ##   ..$ h3n2v                    : int [1:171] 0 0 0 0 0 0 0 0 0 0 ...
-    ##   ..$ 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':   171 obs. of  11 variables:
-    ##   ..$ region_type     : chr [1:171] "National" "National" "National" "National" ...
-    ##   ..$ region          : chr [1:171] "National" "National" "National" "National" ...
-    ##   ..$ year            : int [1:171] 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 ...
-    ##   ..$ week            : int [1:171] 40 41 42 43 44 45 46 47 48 49 ...
-    ##   ..$ total_specimens : int [1:171] 12029 13111 13441 13537 14687 15048 15250 15234 16201 16673 ...
-    ##   ..$ total_a         : int [1:171] 84 116 97 98 97 122 84 119 145 140 ...
-    ##   ..$ total_b         : int [1:171] 43 54 52 52 68 86 98 92 81 106 ...
-    ##   ..$ percent_positive: num [1:171] 1.06 1.3 1.11 1.11 1.12 ...
-    ##   ..$ percent_a       : num [1:171] 0.698 0.885 0.722 0.724 0.66 ...
-    ##   ..$ percent_b       : num [1:171] 0.357 0.412 0.387 0.384 0.463 ...
-    ##   ..$ wk_date         : Date[1:171], format: "2015-10-04" "2015-10-11" "2015-10-18" "2015-10-25" ...
+##  $ public_health_labs       : tibble [233 × 13] (S3: tbl_df/tbl/data.frame)
+##   ..$ region_type              : chr [1:233] "National" "National" "National" "National" ...
+##   ..$ region                   : chr [1:233] "National" "National" "National" "National" ...
+##   ..$ year                     : int [1:233] 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 ...
+##   ..$ week                     : int [1:233] 40 41 42 43 44 45 46 47 48 49 ...
+##   ..$ total_specimens          : int [1:233] 1139 1152 1198 1244 1465 1393 1458 1157 1550 1518 ...
+##   ..$ a_2009_h1n1              : int [1:233] 4 5 10 9 4 11 17 17 27 38 ...
+##   ..$ a_h3                     : int [1:233] 65 41 50 31 23 34 42 24 36 37 ...
+##   ..$ a_subtyping_not_performed: int [1:233] 2 2 1 4 4 1 1 0 3 3 ...
+##   ..$ b                        : int [1:233] 10 7 8 9 9 10 4 4 9 11 ...
+##   ..$ bvic                     : int [1:233] 0 3 3 1 1 4 0 3 3 2 ...
+##   ..$ byam                     : int [1:233] 1 0 2 4 4 2 4 9 12 11 ...
+##   ..$ h3n2v                    : int [1:233] 0 0 0 0 0 0 0 0 0 0 ...
+##   ..$ wk_date                  : Date[1:233], format: "2015-10-04" "2015-10-11" "2015-10-18" "2015-10-25" ...
+##  $ clinical_labs            : tibble [233 × 11] (S3: tbl_df/tbl/data.frame)
+##   ..$ region_type     : chr [1:233] "National" "National" "National" "National" ...
+##   ..$ region          : chr [1:233] "National" "National" "National" "National" ...
+##   ..$ year            : int [1:233] 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 ...
+##   ..$ week            : int [1:233] 40 41 42 43 44 45 46 47 48 49 ...
+##   ..$ total_specimens : int [1:233] 12029 13111 13441 13537 14687 15048 15250 15234 16201 16673 ...
+##   ..$ total_a         : int [1:233] 84 116 97 98 97 122 84 119 145 140 ...
+##   ..$ total_b         : int [1:233] 43 54 52 52 68 86 98 92 81 106 ...
+##   ..$ percent_positive: num [1:233] 1.06 1.3 1.11 1.11 1.12 ...
+##   ..$ percent_a       : num [1:233] 0.698 0.885 0.722 0.724 0.66 ...
+##   ..$ percent_b       : num [1:233] 0.357 0.412 0.387 0.384 0.463 ...
+##   ..$ wk_date         : Date[1:233], format: "2015-10-04" "2015-10-11" "2015-10-18" "2015-10-25" ...

-``` r
 mutate(xdat$combined_prior_to_2015_16, 
       percent_positive = percent_positive / 100) %>% 
  ggplot(aes(wk_date, percent_positive)) +
@ -702,12 +683,11 @@ mutate(xdat$combined_prior_to_2015_16,
  theme_ipsum_rc(grid="XY")
 ```

-<img src="README_files/figure-gfm/who-vrevss-1.png" width="672" />
+<img src="man/figures/README-who-vrevss-1.png" width="672" />

 ``` r
-who_nrevss("hhs", years=2016)
-```

+who_nrevss("hhs", years=2016)
 ## $public_health_labs
 ## # 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   
@ -740,10 +720,7 @@ who_nrevss("hhs", years=2016)
 ## 10 HHS Regions Region 10  2016    40             590      14       0            2.37      2.37      0     2016-10-02
 ## # … with 510 more rows

-``` r
 who_nrevss("census", years=2016)
-```
-
 ## $public_health_labs
 ## # 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   
@ -776,10 +753,7 @@ who_nrevss("census", years=2016)
 ## 10 Census Regio… New England  2016    41             810       5       1            0.741     0.617    0.123  2016-10-09
 ## # … with 458 more rows

-``` r
 who_nrevss("state", years=2016)
-```
-
 ## $public_health_labs
 ## # A tibble: 54 x 12
 ##    region_type region season_descript… total_specimens a_2009_h1n1 a_h3  a_subtyping_not… b     bvic  byam  h3n2v
@ -811,17 +785,18 @@ who_nrevss("state", years=2016)
 ##  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
 ## # … 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 |
+| R    |       21 | 0.91 | 847 | 0.88 |         303 | 0.79 |      512 | 0.85 |
+| Rmd  |        1 | 0.04 |  80 | 0.08 |          68 | 0.18 |       86 | 0.14 |
 | make |        1 | 0.04 |  32 | 0.03 |          11 | 0.03 |        1 | 0.00 |

 ## 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. By participating in this project you agree to abide by its
+terms.
--- a/cran-comments.md
+++ b/cran-comments.md
@ -1,30 +1,10 @@
 ## Test environments
-
-* local OS X install, R 3.5.2
-* local Ubuntu 16.04 R 3.5.2
-* ubuntu 16.04 (on travis-ci), R current/devel
+* local OS X install, R 3.6.3
+* ubuntu 14.04 (on travis-ci), R 3.6.3
 * win-builder (devel and release)

 ## R CMD check results

 0 errors | 0 warnings | 1 note

-* This is a maintenance update.
-
-## Reverse dependencies
-
-None
-
---
-
-The CDC removed 2 old API endpoints so those functions have been removed.
-
-There was a bug in the computation of "start week" that resulted in 
-the "ISO" day being used vs the MMWR/"epi" day being used. This 
-has also been fixed.
-
-Only some examples run on CRAN due to their time consuming nature and the need
-to make external network API calls. Monthly tests are performed on Travis-CI 
-<https://travis-ci.org/hrbrmstr/cdcfluview> and the package itself has 88%
-code coverage during tests <https://codecov.io/github/hrbrmstr/cdcfluview?branch=master>.
-All package functions are also evaluated on each new generation of the README.
+This an update to fix tibble CRAN check warnings.
--- a/man/cdc_basemap.Rd
+++ b/man/cdc_basemap.Rd
@ -4,8 +4,9 @@
 \alias{cdc_basemap}
 \title{Retrieve CDC U.S. Basemaps}
 \usage{
-cdc_basemap(basemap = c("national", "hhs", "census", "states", "spread",
-  "surv"))
+cdc_basemap(
+  basemap = c("national", "hhs", "census", "states", "spread", "surv")
+)
 }
 \arguments{
 \item{basemap}{select the CDC basemap. One of:
--- a/man/cdcfluview.Rd
+++ b/man/cdcfluview.Rd
@ -3,7 +3,6 @@
 \docType{package}
 \name{cdcfluview}
 \alias{cdcfluview}
-\alias{cdcfluview-package}
 \title{Retrieve Flu Season Data from the United States Centers for Disease Control and Prevention ('CDC') 'FluView' Portal}
 \description{
 The U.S. Centers for Disease Control (CDC) maintains a portal
--- a/man/census_regions.Rd
+++ b/man/census_regions.Rd
@ -4,7 +4,9 @@
 \name{census_regions}
 \alias{census_regions}
 \title{Census Region Table}
-\format{A data frame with 51 rows and 2 variables}
+\format{
+A data frame with 51 rows and 2 variables
+}
 \usage{
 data(census_regions)
 }
--- a/man/figures/README-cdc-basemaps-1.png
+++ b/man/figures/README-cdc-basemaps-1.png
--- a/man/figures/README-cdc-basemaps-2.png
+++ b/man/figures/README-cdc-basemaps-2.png
--- a/man/figures/README-cdc-basemaps-3.png
+++ b/man/figures/README-cdc-basemaps-3.png
--- a/man/figures/README-cdc-basemaps-4.png
+++ b/man/figures/README-cdc-basemaps-4.png
--- a/man/figures/README-cdc-basemaps-5.png
+++ b/man/figures/README-cdc-basemaps-5.png
--- a/man/figures/README-cdc-basemaps-6.png
+++ b/man/figures/README-cdc-basemaps-6.png
--- a/man/figures/README-ili-df-1.png
+++ b/man/figures/README-ili-df-1.png
--- a/man/figures/README-ili-df-2.png
+++ b/man/figures/README-ili-df-2.png
--- a/man/figures/README-ili-df-3.png
+++ b/man/figures/README-ili-df-3.png
--- a/man/figures/README-ili-df-4.png
+++ b/man/figures/README-ili-df-4.png
--- a/man/figures/README-ili-weekly-activity-1.png
+++ b/man/figures/README-ili-weekly-activity-1.png
--- a/man/figures/README-nat-pi-mortality-1.png
+++ b/man/figures/README-nat-pi-mortality-1.png
--- a/man/figures/README-surveillance-areas-1.png
+++ b/man/figures/README-surveillance-areas-1.png
--- a/man/figures/README-who-vrevss-1.png
+++ b/man/figures/README-who-vrevss-1.png
--- a/man/get_flu_data.Rd
+++ b/man/get_flu_data.Rd
@ -4,9 +4,12 @@
 \alias{get_flu_data}
 \title{Retrieves state, regional or national influenza statistics from the CDC (deprecated)}
 \usage{
-get_flu_data(region = "hhs", sub_region = 1:10,
-  data_source = "ilinet", years = as.numeric(format(Sys.Date(),
-  "\%Y")))
+get_flu_data(
+  region = "hhs",
+  sub_region = 1:10,
+  data_source = "ilinet",
+  years = as.numeric(format(Sys.Date(), "\%Y"))
+)
 }
 \arguments{
 \item{region}{one of "\code{hhs}", "\code{census}", "\code{national}",
--- a/man/get_hosp_data.Rd
+++ b/man/get_hosp_data.Rd
@ -4,8 +4,11 @@
 \alias{get_hosp_data}
 \title{Retrieves influenza hospitalization statistics from the CDC (deprecated)}
 \usage{
-get_hosp_data(area = "flusurvnet", age_group = "overall",
-  years = as.numeric(format(Sys.Date(), "\%Y")) - 1)
+get_hosp_data(
+  area = "flusurvnet",
+  age_group = "overall",
+  years = as.numeric(format(Sys.Date(), "\%Y")) - 1
+)
 }
 \arguments{
 \item{area}{one of "\code{flusurvnet}", "\code{eip}", "\code{ihsp}", or two
--- a/man/hhs_regions.Rd
+++ b/man/hhs_regions.Rd
@ -4,7 +4,9 @@
 \name{hhs_regions}
 \alias{hhs_regions}
 \title{HHS Region Table}
-\format{A data frame with 59 rows and 4 variables}
+\format{
+A data frame with 59 rows and 4 variables
+}
 \usage{
 data(hhs_regions)
 }
--- a/man/hospitalizations.Rd
+++ b/man/hospitalizations.Rd
@ -4,8 +4,11 @@
 \alias{hospitalizations}
 \title{Laboratory-Confirmed Influenza Hospitalizations}
 \usage{
-hospitalizations(surveillance_area = c("flusurv", "eip", "ihsp"),
-  region = "all", years = NULL)
+hospitalizations(
+  surveillance_area = c("flusurv", "eip", "ihsp"),
+  region = "all",
+  years = NULL
+)
 }
 \arguments{
 \item{surveillance_area}{one of "\code{flusurv}", "\code{eip}", or "\code{ihsp}"}
--- a/man/mmwrid_map.Rd
+++ b/man/mmwrid_map.Rd
@ -4,7 +4,9 @@
 \name{mmwrid_map}
 \alias{mmwrid_map}
 \title{MMWR ID to Calendar Mappings}
-\format{A data frame with 4,592 rows and 4 columns}
+\format{
+A data frame with 4,592 rows and 4 columns
+}
 \description{
 The CDC uses a unique "Morbidity and Mortality Weekly Report" identifier
 for each week that starts at 1 (Ref: < https://www.cdc.gov/mmwr/preview/mmwrhtml/su6004a9.htm>).
--- a/man/pi_mortality.Rd
+++ b/man/pi_mortality.Rd
@ -4,8 +4,7 @@
 \alias{pi_mortality}
 \title{Pneumonia and Influenza Mortality Surveillance}
 \usage{
-pi_mortality(coverage_area = c("national", "state", "region"),
-  years = NULL)
+pi_mortality(coverage_area = c("national", "state", "region"), years = NULL)
 }
 \arguments{
 \item{coverage_area}{coverage area for data (national, state or region)}
@ -29,7 +28,7 @@ NCHS Mortality Surveillance System data are presented by the week the death occu
 at the national, state, and HHS Region levels. Data on the percentage of deaths due
 to P&I on a national level are released two weeks after the week of death to allow
 for collection of enough data to produce a stable percentage.  States and HHS regions
-with less than 20% of the expected total deaths (average number of total deaths
+with less than 20\% of the expected total deaths (average number of total deaths
 reported by week during 2008-2012) will be marked as insufficient data. Collection
 of complete data is not expected at the time of initial report, and a reliable
 percentage of deaths due to P&I is not anticipated at the U.S. Department of Health
--- a/man/who_nrevss.Rd
+++ b/man/who_nrevss.Rd
@ -4,8 +4,7 @@
 \alias{who_nrevss}
 \title{Retrieve WHO/NREVSS Surveillance Data}
 \usage{
-who_nrevss(region = c("national", "hhs", "census", "state"),
-  years = NULL)
+who_nrevss(region = c("national", "hhs", "census", "state"), years = NULL)
 }
 \arguments{
 \item{region}{one of "\code{national}", "\code{hhs}", "\code{census}", or "\code{state}"}