From cc1791b79b492d305a3619b97e416207ecfd2887 Mon Sep 17 00:00:00 2001 From: hrbrmstr Date: Sat, 22 May 2021 08:01:03 -0400 Subject: [PATCH] tweaked hospitalizations function --- DESCRIPTION | 2 +- NEWS.md | 3 + R/hospital.r | 51 +- README.Rmd | 11 +- README.md | 682 +++++++++---------- cran-comments.md | 7 +- man/figures/README-cdc-basemaps-1.png | Bin 45045 -> 44500 bytes man/figures/README-cdc-basemaps-2.png | Bin 72719 -> 73804 bytes man/figures/README-cdc-basemaps-3.png | Bin 59152 -> 59707 bytes man/figures/README-cdc-basemaps-4.png | Bin 88716 -> 87929 bytes man/figures/README-cdc-basemaps-5.png | Bin 81145 -> 81215 bytes man/figures/README-cdc-basemaps-6.png | Bin 90248 -> 88835 bytes man/figures/README-ili-df-1.png | Bin 70293 -> 70902 bytes man/figures/README-ili-df-2.png | Bin 100730 -> 98659 bytes man/figures/README-ili-df-3.png | Bin 103092 -> 102758 bytes man/figures/README-ili-df-4.png | Bin 165181 -> 160588 bytes man/figures/README-ili-weekly-activity-1.png | Bin 30736 -> 30358 bytes man/figures/README-nat-pi-mortality-1.png | Bin 60038 -> 44149 bytes man/figures/README-surveillance-areas-1.png | Bin 66240 -> 82618 bytes man/figures/README-who-vrevss-1.png | Bin 84988 -> 84924 bytes 20 files changed, 383 insertions(+), 373 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 8698b4b..9a04c0c 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -4,7 +4,7 @@ Encoding: UTF-8 Title: Retrieve Flu Season Data from the United States Centers for Disease Control and Prevention ('CDC') 'FluView' Portal Version: 0.9.4 -Date: 2021-02-27 +Date: 2021-05-22 Authors@R: c( person("Bob", "Rudis", email = "bob@rud.is", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5670-2640")), diff --git a/NEWS.md b/NEWS.md index be4c7f4..81d6ea3 100644 --- a/NEWS.md +++ b/NEWS.md @@ -3,6 +3,9 @@ `age_group_distribution()` function endpoint. There is now a new column `incl_wkly_rates_and_strata` in the returned data frame. Fixes #28 and CRAN failures. +- fixed `age_label` in `hospitalizations()` (different calls to + the hidden API for this function return different levels depending + on the input parameters so it is no longer a factor.) # cdcfluview 0.9.2 diff --git a/R/hospital.r b/R/hospital.r index 3cb1128..16a5377 100644 --- a/R/hospital.r +++ b/R/hospital.r @@ -71,22 +71,51 @@ hospitalizations <- function(surveillance_area=c("flusurv", "eip", "ihsp"), sea_df <- setNames( hosp$meta$seasons, - c("sea_description", "sea_endweek", "sea_label", "seasonid", "sea_startweek", "color", "color_hexvalue")) + c("sea_description", "sea_endweek", "sea_label", "seasonid", "sea_startweek", "color", "color_hexvalue") + ) sea_df <- sea_df[,c("seasonid", "sea_label", "sea_description", "sea_startweek", "sea_endweek")] ser_names <- unlist(hosp$res$busdata$datafields, use.names = FALSE) - suppressWarnings(suppressMessages(mmwr_df <- dplyr::bind_rows(hosp$res$mmwr))) + suppressWarnings( + suppressMessages( + mmwr_df <- dplyr::bind_rows(hosp$res$mmwr) + ) + ) + mmwr_df <- mmwr_df[,c("mmwrid", "weekend", "weeknumber", "weekstart", "year", "yearweek", "seasonid", "weekendlabel", "weekendlabel2")] - suppressMessages(suppressWarnings( - dplyr::bind_rows(lapply(hosp$res$busdata$dataseries, function(.x) { - tdf <- dplyr::bind_rows(lapply(.x$data, function(.x) setNames(.x, ser_names))) - tdf$age <- .x$age - tdf$season <- .x$season - tdf - })) -> xdf)) + suppressMessages( + suppressWarnings( + + dplyr::bind_rows( + lapply(hosp$res$busdata$dataseries, function(.x) { + + dplyr::bind_rows( + lapply(.x$data, function(.x) setNames(.x, ser_names)) + ) -> tdf + + tdf$age <- .x$age + tdf$season <- .x$season + + tdf + + }) + ) -> xdf + + ) + ) + + if (length(unique(xdf$age)) > 9) { + data.frame( + age = 1:12, + age_label = c("0-4 yr", "5-17 yr", "18-49 yr", "50-64 yr", "65+ yr", "Overall", + "65-74 yr", "75-84 yr", "85+", "18-29 yr", "30-39 yr", "40-49 yr" + ) + ) -> age_df + age_df$age_label <- factor(age_df$age_label, levels = age_df$age_label) + } dplyr::left_join(xdf, mmwr_df, c("mmwrid", "weeknumber")) %>% dplyr::left_join(age_df, "age") %>% @@ -97,10 +126,6 @@ hospitalizations <- function(surveillance_area=c("flusurv", "eip", "ihsp"), ) %>% dplyr::left_join(mmwrid_map, "mmwrid") -> xdf - xdf$age_label <- factor(xdf$age_label, - levels=c("0-4 yr", "5-17 yr", "18-49 yr", "50-64 yr", - "65+ yr", "Overall")) - xdf <- xdf[,c("surveillance_area", "region", "year", "season", "wk_start", "wk_end", "year_wk_num", "rate", "weeklyrate", "age", "age_label", "sea_label", "sea_description", "mmwrid")] diff --git a/README.Rmd b/README.Rmd index a1a79ec..a78a659 100644 --- a/README.Rmd +++ b/README.Rmd @@ -28,7 +28,7 @@ The U.S. Centers for Disease Control (CDC) maintains a portal for accessing -state, regional and national influenza statistics as well as Mortality -Surveillance Data. The Flash interface makes it difficult and + for +accessing state, regional and national influenza statistics as well as +Mortality Surveillance Data. The Flash interface makes it difficult and time-consuming to select and retrieve influenza data. This package provides functions to access the data provided by the portal’s underlying API. @@ -53,55 +46,50 @@ underlying API. The following functions are implemented: - - `age_group_distribution`: Age Group Distribution of Influenza +- `age_group_distribution`: Age Group Distribution of Influenza Positive Tests Reported by Public Health Laboratories - - `cdc_basemap`: Retrieve CDC U.S. Basemaps - - `geographic_spread`: State and Territorial Epidemiologists Reports +- `cdc_basemap`: Retrieve CDC U.S. base maps +- `geographic_spread`: State and Territorial Epidemiologists Reports of Geographic Spread of Influenza - - `get_weekly_flu_report`: Retrieves (high-level) weekly (XML) +- `get_weekly_flu_report`: Retrieves (high-level) weekly (XML) influenza surveillance report from the CDC - - `hospitalizations`: Laboratory-Confirmed Influenza Hospitalizations - - `ilinet`: Retrieve ILINet Surveillance Data - - `ili_weekly_activity_indicators`: Retrieve weekly state-level ILI +- `hospitalizations`: Laboratory-Confirmed Influenza Hospitalizations +- `ilinet`: Retrieve ILINet Surveillance Data +- `ili_weekly_activity_indicators`: Retrieve weekly state-level ILI indicators per-state for a given season - - `pi_mortality`: Pneumonia and Influenza Mortality Surveillance - - `state_data_providers`: Retrieve metadata about U.S. State CDC +- `pi_mortality`: Pneumonia and Influenza Mortality Surveillance +- `state_data_providers`: Retrieve metadata about U.S. State CDC Provider Data - - `surveillance_areas`: Retrieve a list of valid sub-regions for each +- `surveillance_areas`: Retrieve a list of valid sub-regions for each surveillance area. - - `who_nrevss`: Retrieve WHO/NREVSS Surveillance Data +- `who_nrevss`: Retrieve WHO/NREVSS Surveillance Data MMWR ID Utilities: - - `mmwrid_map`: MMWR ID to Calendar Mappings - - `mmwr_week`: Convert a Date to an MMWR day+week+year - - `mmwr_weekday`: Convert a Date to an MMWR weekday - - `mmwr_week_to_date`: Convert an MMWR year+week or year+week+day to a +- `mmwrid_map`: MMWR ID to Calendar Mappings +- `mmwr_week`: Convert a Date to an MMWR day+week+year +- `mmwr_weekday`: Convert a Date to an MMWR weekday +- `mmwr_week_to_date`: Convert an MMWR year+week or year+week+day to a Date object Deprecated functions: - - `get_flu_data`: Retrieves state, regional or national influenza +- `get_flu_data`: Retrieves state, regional or national influenza statistics from the CDC (deprecated) - - `get_hosp_data`: Retrieves influenza hospitalization statistics from +- `get_hosp_data`: Retrieves influenza hospitalization statistics from the CDC (deprecated) - - `get_state_data`: Retrieves state/territory-level influenza +- `get_state_data`: Retrieves state/territory-level influenza statistics from the CDC (deprecated) The following data sets are included: - - `hhs_regions`: HHS Region Table (a data frame with 59 rows and 4 +- `hhs_regions`: HHS Region Table (a data frame with 59 rows and 4 variables) - - `census_regions`: Census Region Table (a data frame with 51 rows and +- `census_regions`: Census Region Table (a data frame with 51 rows and 2 variables) - - `mmwrid_map`: MMWR ID to Calendar Mappings (it is exported & +- `mmwrid_map`: MMWR ID to Calendar Mappings (it is exported & available, no need to use `data()`) -## NOTE - -All development happens in branches now with only critical fixes being -back-ported to the master branch when necessary. - ## Installation ``` r @@ -122,9 +110,9 @@ library(cdcfluview) library(hrbrthemes) library(tidyverse) -# current versoon +# current version packageVersion("cdcfluview") -## [1] '0.9.2' +## [1] '0.9.4' ``` ### Age Group Distribution of Influenza Positive Tests Reported by Public Health Laboratories @@ -132,22 +120,22 @@ packageVersion("cdcfluview") ``` r glimpse(age_group_distribution(years=2015)) ## Rows: 1,872 -## Columns: 16 -## $ sea_label "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "20… -## $ age_label 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 A (Subtyping not Performed), A (Subtyping not Performed), A (Subtyping not Performed), A (S… -## $ count 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 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2… -## $ seasonid 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55,… -## $ sea_description "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "… -## $ sea_startweek 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2… -## $ sea_endweek 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2… -## $ vir_description "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "… -## $ vir_startmmwrid 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1… -## $ vir_endmmwrid 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3… -## $ wk_start 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 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 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, … +## Columns: 15 +## $ sea_label "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-… +## $ age_label 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 yr… +## $ vir_label A (Subtyping not Performed), A (Subtyping not Performed), A (Subtyping not Performed), A (Subt… +## $ count 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, 0… +## $ mmwrid 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2821… +## $ seasonid 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55… +## $ sea_description "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Sea… +## $ sea_startweek 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806, 2806… +## $ sea_endweek 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857, 2857… +## $ vir_description "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-Unk", "A-U… +## $ vir_startmmwrid 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397, 1397… +## $ vir_endmmwrid 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131, 3131… +## $ wk_start 2015-10-04, 2015-10-11, 2015-10-18, 2015-10-25, 2015-11-01, 2015-11-08, 2015-11-15, 2015-11-2… +## $ wk_end 2015-10-10, 2015-10-17, 2015-10-24, 2015-10-31, 2015-11-07, 2015-11-14, 2015-11-21, 2015-11-2… +## $ year_wk_num 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, 13,… ``` ### Retrieve CDC U.S. Coverage Map @@ -192,15 +180,15 @@ plot(cdc_basemap("surv")) ``` r glimpse(geographic_spread()) -## Rows: 30,427 +## Rows: 30,851 ## Columns: 7 -## $ statename "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Al… -## $ url "http://adph.org/influenza/", "http://adph.org/influenza/", "http://adph.org/influenza/", "… -## $ website "Influenza Surveillance", "Influenza Surveillance", "Influenza Surveillance", "Influenza Su… -## $ activity_estimate "No Activity", "No Activity", "No Activity", "Local Activity", "Sporadic", "Sporadic", "Spo… -## $ weekend 2003-10-04, 2003-10-11, 2003-10-18, 2003-10-25, 2003-11-01, 2003-11-08, 2003-11-15, 2003-1… -## $ season "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "20… -## $ weeknumber "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "1", "2… +## $ statename "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Ala… +## $ url "http://adph.org/influenza/", "http://adph.org/influenza/", "http://adph.org/influenza/", "h… +## $ website "Influenza Surveillance", "Influenza Surveillance", "Influenza Surveillance", "Influenza Sur… +## $ activity_estimate "No Activity", "No Activity", "No Activity", "Local Activity", "Sporadic", "Sporadic", "Spor… +## $ weekend 2003-10-04, 2003-10-11, 2003-10-18, 2003-10-25, 2003-11-01, 2003-11-08, 2003-11-15, 2003-11… +## $ season "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "2003-04", "200… +## $ weeknumber "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "1", "2"… ``` ### Laboratory-Confirmed Influenza Hospitalizations @@ -232,27 +220,27 @@ surveillance_areas() ## 22 ihsp Utah glimpse(fs_nat <- hospitalizations("flusurv")) -## Rows: 2,979 +## Rows: 4,368 ## Columns: 14 -## $ surveillance_area "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "… -## $ region "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network", "… -## $ year 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2018, 2018, 2… -## $ season 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 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 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 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 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 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 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 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 "2017-18", "2017-18", "2017-18", "2017-18", "2017-18", "2017-18", "2017-18", "2017-18", "20… -## $ sea_description "Season 2017-18", "Season 2017-18", "Season 2017-18", "Season 2017-18", "Season 2017-18", "… -## $ mmwrid 2910, 2911, 2912, 2913, 2914, 2915, 2916, 2917, 2918, 2919, 2920, 2921, 2922, 2923, 2924, 2… +## $ surveillance_area "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "FluSurv-NET", "F… +## $ region "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network", "E… +## $ year 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2018, 2018, 20… +## $ season 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 2017-10-01, 2017-10-08, 2017-10-15, 2017-10-22, 2017-10-29, 2017-11-05, 2017-11-12, 2017-11… +## $ wk_end 2017-10-07, 2017-10-14, 2017-10-21, 2017-10-28, 2017-11-04, 2017-11-11, 2017-11-18, 2017-11… +## $ year_wk_num 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, 1… +## $ rate 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, 1… +## $ weeklyrate 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 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 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 "2017-18", "2017-18", "2017-18", "2017-18", "2017-18", "2017-18", "2017-18", "2017-18", "201… +## $ sea_description "Season 2017-18", "Season 2017-18", "Season 2017-18", "Season 2017-18", "Season 2017-18", "S… +## $ mmwrid 2910, 2911, 2912, 2913, 2914, 2915, 2916, 2917, 2918, 2919, 2920, 2921, 2922, 2923, 2924, 29… ggplot(fs_nat, aes(wk_end, rate)) + geom_line(aes(color=age_label, group=age_label)) + facet_wrap(~sea_description, scales="free_x") + - scale_color_ipsum(name=NULL) + + scale_color_viridis_d(name=NULL) + labs(x=NULL, y="Rates per 100,000 population", title="FluSurv-NET :: Entire Network :: All Seasons :: Cumulative Rate") + theme_ipsum_rc() @@ -261,78 +249,77 @@ ggplot(fs_nat, aes(wk_end, rate)) + ``` r - glimpse(hospitalizations("eip", years=2015)) -## Rows: 270 +## Rows: 390 ## Columns: 14 -## $ surveillance_area "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", … -## $ region "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network", "… -## $ year 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 2… -## $ season 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55,… -## $ wk_start 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 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 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 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 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 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 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 "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "20… -## $ sea_description "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "… -## $ mmwrid 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2… +## $ surveillance_area "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "… +## $ region "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network", "E… +## $ year 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 20… +## $ season 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, … +## $ wk_start 2015-10-04, 2015-10-11, 2015-10-18, 2015-10-25, 2015-11-01, 2015-11-08, 2015-11-15, 2015-11… +## $ wk_end 2015-10-10, 2015-10-17, 2015-10-24, 2015-10-31, 2015-11-07, 2015-11-14, 2015-11-21, 2015-11… +## $ year_wk_num 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, 1… +## $ rate 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 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 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, 10… +## $ age_label 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 "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "201… +## $ sea_description "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "S… +## $ mmwrid 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 28… glimpse(hospitalizations("eip", "Colorado", years=2015)) -## Rows: 270 +## Rows: 390 ## Columns: 14 -## $ surveillance_area "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", … -## $ region "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colora… -## $ year 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 2… -## $ season 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55,… -## $ wk_start 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 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 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 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 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 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 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 "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "20… -## $ sea_description "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "… -## $ mmwrid 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2… +## $ surveillance_area "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "EIP", "… +## $ region "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colorado", "Colorad… +## $ year 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 20… +## $ season 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, … +## $ wk_start 2015-10-04, 2015-10-11, 2015-10-18, 2015-10-25, 2015-11-01, 2015-11-08, 2015-11-15, 2015-11… +## $ wk_end 2015-10-10, 2015-10-17, 2015-10-24, 2015-10-31, 2015-11-07, 2015-11-14, 2015-11-21, 2015-11… +## $ year_wk_num 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, 1… +## $ rate 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 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 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, 10… +## $ age_label 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 "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "201… +## $ sea_description "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "S… +## $ mmwrid 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 28… glimpse(hospitalizations("ihsp", years=2015)) -## Rows: 270 +## Rows: 390 ## Columns: 14 -## $ surveillance_area "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IH… -## $ region "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network", "… -## $ year 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 2… -## $ season 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55,… -## $ wk_start 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 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 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 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 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 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 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 "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "20… -## $ sea_description "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "… -## $ mmwrid 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 2… - -glimpse(hospitalizations("ihsp", "Oklahoma", years=2015)) -## Rows: 270 +## $ surveillance_area "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHS… +## $ region "Entire Network", "Entire Network", "Entire Network", "Entire Network", "Entire Network", "E… +## $ year 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2015, 2016, 2016, 20… +## $ season 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, … +## $ wk_start 2015-10-04, 2015-10-11, 2015-10-18, 2015-10-25, 2015-11-01, 2015-11-08, 2015-11-15, 2015-11… +## $ wk_end 2015-10-10, 2015-10-17, 2015-10-24, 2015-10-31, 2015-11-07, 2015-11-14, 2015-11-21, 2015-11… +## $ year_wk_num 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, 1… +## $ rate 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, 1… +## $ weeklyrate 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 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, 10… +## $ age_label 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 "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "2015-16", "201… +## $ sea_description "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "Season 2015-16", "S… +## $ mmwrid 2806, 2807, 2808, 2809, 2810, 2811, 2812, 2813, 2814, 2815, 2816, 2817, 2818, 2819, 2820, 28… + +glimpse(hospitalizations("ihsp", "Oklahoma", years=2010)) +## Rows: 390 ## Columns: 14 -## $ surveillance_area "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IH… -## $ region "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklaho… -## $ year 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2011, 2011, 2… -## $ season 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,… -## $ wk_start 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 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 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 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 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 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 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 "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "20… -## $ sea_description "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11", "… -## $ mmwrid 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559, 2… +## $ surveillance_area "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHSP", "IHS… +## $ region "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahoma", "Oklahom… +## $ year 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2011, 2011, 20… +## $ season 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, … +## $ wk_start 2010-10-03, 2010-10-10, 2010-10-17, 2010-10-24, 2010-10-31, 2010-11-07, 2010-11-14, 2010-11… +## $ wk_end 2010-10-09, 2010-10-16, 2010-10-23, 2010-10-30, 2010-11-06, 2010-11-13, 2010-11-20, 2010-11… +## $ year_wk_num 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, 1… +## $ rate 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 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 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 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, 18… +## $ sea_label "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "2010-11", "201… +## $ sea_description "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11", "Season 2010-11", "S… +## $ mmwrid 2545, 2546, 2547, 2548, 2549, 2550, 2551, 2552, 2553, 2554, 2555, 2556, 2557, 2558, 2559, 25… ``` ### Retrieve ILINet Surveillance Data @@ -354,147 +341,147 @@ walk(c("national", "hhs", "census", "state"), ~{ print(gg) }) -## Rows: 1,173 +## Rows: 1,233 ## Columns: 16 -## $ region_type "National", "National", "National", "National", "National", "National", "National", "Nationa… -## $ region "National", "National", "National", "National", "National", "National", "National", "Nationa… -## $ year 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1998, 19… -## $ week 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1… -## $ weighted_ili 1.101480, 1.200070, 1.378760, 1.199200, 1.656180, 1.413260, 1.986800, 2.447490, 1.739010, 1.… -## $ unweighted_ili 1.216860, 1.280640, 1.239060, 1.144730, 1.261120, 1.282750, 1.445790, 1.647960, 1.675170, 1.… -## $ age_0_4 179, 199, 228, 188, 217, 178, 294, 288, 268, 299, 346, 348, 510, 579, 639, 690, 856, 824, 88… -## $ age_25_49 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … -## $ age_25_64 157, 151, 153, 193, 162, 148, 240, 293, 206, 282, 268, 235, 404, 584, 759, 654, 679, 817, 76… -## $ age_5_24 205, 242, 266, 236, 280, 281, 328, 456, 343, 415, 388, 362, 492, 576, 810, 1121, 1440, 1600,… -## $ age_50_64 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … -## $ age_65 29, 23, 34, 36, 41, 48, 70, 63, 69, 102, 81, 59, 113, 207, 207, 148, 151, 196, 233, 146, 119… -## $ ilitotal 570, 615, 681, 653, 700, 655, 932, 1100, 886, 1098, 1083, 1004, 1519, 1946, 2415, 2613, 3126… -## $ num_of_providers 192, 191, 219, 213, 213, 195, 248, 256, 252, 253, 242, 190, 251, 250, 254, 255, 245, 245, 23… -## $ total_patients 46842, 48023, 54961, 57044, 55506, 51062, 64463, 66749, 52890, 67887, 61314, 47719, 48429, 5… -## $ week_start 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: 1,173 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 -## -## 1 National Natio… 1997 40 1.10 1.22 179 NA 157 205 NA 29 -## 2 National Natio… 1997 41 1.20 1.28 199 NA 151 242 NA 23 -## 3 National Natio… 1997 42 1.38 1.24 228 NA 153 266 NA 34 -## 4 National Natio… 1997 43 1.20 1.14 188 NA 193 236 NA 36 -## 5 National Natio… 1997 44 1.66 1.26 217 NA 162 280 NA 41 -## 6 National Natio… 1997 45 1.41 1.28 178 NA 148 281 NA 48 -## 7 National Natio… 1997 46 1.99 1.45 294 NA 240 328 NA 70 -## 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 1,163 more rows, and 4 more variables: ilitotal , num_of_providers , total_patients , +## $ region_type "National", "National", "National", "National", "National", "National", "National", "National… +## $ region "National", "National", "National", "National", "National", "National", "National", "National… +## $ year 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1998, 199… +## $ week 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12… +## $ weighted_ili 1.101480, 1.200070, 1.378760, 1.199200, 1.656180, 1.413260, 1.986800, 2.447490, 1.739010, 1.9… +## $ unweighted_ili 1.216860, 1.280640, 1.239060, 1.144730, 1.261120, 1.282750, 1.445790, 1.647960, 1.675170, 1.6… +## $ age_0_4 179, 199, 228, 188, 217, 178, 294, 288, 268, 299, 346, 348, 510, 579, 639, 690, 856, 824, 881… +## $ age_25_49 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… +## $ age_25_64 157, 151, 153, 193, 162, 148, 240, 293, 206, 282, 268, 235, 404, 584, 759, 654, 679, 817, 769… +## $ age_5_24 205, 242, 266, 236, 280, 281, 328, 456, 343, 415, 388, 362, 492, 576, 810, 1121, 1440, 1600, … +## $ age_50_64 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… +## $ age_65 29, 23, 34, 36, 41, 48, 70, 63, 69, 102, 81, 59, 113, 207, 207, 148, 151, 196, 233, 146, 119,… +## $ ilitotal 570, 615, 681, 653, 700, 655, 932, 1100, 886, 1098, 1083, 1004, 1519, 1946, 2415, 2613, 3126,… +## $ num_of_providers 192, 191, 219, 213, 213, 195, 248, 256, 252, 253, 242, 190, 251, 250, 254, 255, 245, 245, 239… +## $ total_patients 46842, 48023, 54961, 57044, 55506, 51062, 64463, 66749, 52890, 67887, 61314, 47719, 48429, 52… +## $ week_start 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: 1,233 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 +## +## 1 National National 1997 40 1.10 1.22 179 NA 157 205 NA 29 +## 2 National National 1997 41 1.20 1.28 199 NA 151 242 NA 23 +## 3 National National 1997 42 1.38 1.24 228 NA 153 266 NA 34 +## 4 National National 1997 43 1.20 1.14 188 NA 193 236 NA 36 +## 5 National National 1997 44 1.66 1.26 217 NA 162 280 NA 41 +## 6 National National 1997 45 1.41 1.28 178 NA 148 281 NA 48 +## 7 National National 1997 46 1.99 1.45 294 NA 240 328 NA 70 +## 8 National National 1997 47 2.45 1.65 288 NA 293 456 NA 63 +## 9 National National 1997 48 1.74 1.68 268 NA 206 343 NA 69 +## 10 National National 1997 49 1.94 1.62 299 NA 282 415 NA 102 +## # … with 1,223 more rows, and 4 more variables: ilitotal , num_of_providers , total_patients , ## # week_start ``` - ## Rows: 11,730 + ## Rows: 12,330 ## Columns: 16 - ## $ region_type "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "H… - ## $ region Region 1, Region 2, Region 3, Region 4, Region 5, Region 6, Region 7, Region 8, Region 9, Re… - ## $ year 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 19… - ## $ week 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 42, … - ## $ weighted_ili 0.498535, 0.374963, 1.354280, 0.400338, 1.229260, 1.018980, 0.871791, 0.516017, 1.807610, 4.… - ## $ unweighted_ili 0.623848, 0.384615, 1.341720, 0.450010, 0.901266, 0.747384, 1.152860, 0.422654, 2.258780, 4.… - ## $ age_0_4 15, 0, 6, 12, 31, 2, 0, 2, 80, 31, 14, 0, 4, 21, 36, 2, 0, 0, 103, 19, 35, 0, 3, 19, 66, 2, … - ## $ age_25_49 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … - ## $ age_25_64 7, 3, 7, 23, 24, 1, 4, 0, 76, 12, 14, 2, 19, 7, 23, 2, 0, 1, 76, 7, 15, 0, 17, 15, 29, 2, 3,… - ## $ age_5_24 22, 0, 15, 11, 30, 2, 18, 3, 74, 30, 29, 0, 16, 14, 41, 2, 13, 8, 84, 35, 35, 0, 24, 18, 75,… - ## $ age_50_64 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … - ## $ age_65 0, 0, 4, 0, 4, 0, 5, 0, 13, 3, 0, 0, 3, 2, 4, 0, 2, 0, 11, 1, 0, 1, 2, 2, 16, 0, 2, 0, 9, 2,… - ## $ ilitotal 44, 3, 32, 46, 89, 5, 27, 5, 243, 76, 57, 2, 42, 44, 104, 6, 15, 9, 274, 62, 85, 1, 46, 54, … - ## $ num_of_providers 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 7053, 780, 2385, 10222, 9875, 669, 2342, 1183, 10758, 1575, 6987, 872, 2740, 11310, 9618, 68… - ## $ week_start 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: 11,730 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 - ## - ## 1 HHS Regions Regio… 1997 40 0.499 0.624 15 NA 7 22 NA 0 - ## 2 HHS Regions Regio… 1997 40 0.375 0.385 0 NA 3 0 NA 0 - ## 3 HHS Regions Regio… 1997 40 1.35 1.34 6 NA 7 15 NA 4 - ## 4 HHS Regions Regio… 1997 40 0.400 0.450 12 NA 23 11 NA 0 - ## 5 HHS Regions Regio… 1997 40 1.23 0.901 31 NA 24 30 NA 4 - ## 6 HHS Regions Regio… 1997 40 1.02 0.747 2 NA 1 2 NA 0 - ## 7 HHS Regions Regio… 1997 40 0.872 1.15 0 NA 4 18 NA 5 - ## 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 11,720 more rows, and 4 more variables: ilitotal , num_of_providers , total_patients , + ## $ region_type "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "HHS Regions", "HH… + ## $ region Region 1, Region 2, Region 3, Region 4, Region 5, Region 6, Region 7, Region 8, Region 9, Reg… + ## $ year 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 199… + ## $ week 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 42, 4… + ## $ weighted_ili 0.498535, 0.374963, 1.354280, 0.400338, 1.229260, 1.018980, 0.871791, 0.516017, 1.807610, 4.7… + ## $ unweighted_ili 0.623848, 0.384615, 1.341720, 0.450010, 0.901266, 0.747384, 1.152860, 0.422654, 2.258780, 4.8… + ## $ age_0_4 15, 0, 6, 12, 31, 2, 0, 2, 80, 31, 14, 0, 4, 21, 36, 2, 0, 0, 103, 19, 35, 0, 3, 19, 66, 2, 0… + ## $ age_25_49 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… + ## $ age_25_64 7, 3, 7, 23, 24, 1, 4, 0, 76, 12, 14, 2, 19, 7, 23, 2, 0, 1, 76, 7, 15, 0, 17, 15, 29, 2, 3, … + ## $ age_5_24 22, 0, 15, 11, 30, 2, 18, 3, 74, 30, 29, 0, 16, 14, 41, 2, 13, 8, 84, 35, 35, 0, 24, 18, 75, … + ## $ age_50_64 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… + ## $ age_65 0, 0, 4, 0, 4, 0, 5, 0, 13, 3, 0, 0, 3, 2, 4, 0, 2, 0, 11, 1, 0, 1, 2, 2, 16, 0, 2, 0, 9, 2, … + ## $ ilitotal 44, 3, 32, 46, 89, 5, 27, 5, 243, 76, 57, 2, 42, 44, 104, 6, 15, 9, 274, 62, 85, 1, 46, 54, 1… + ## $ num_of_providers 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 7053, 780, 2385, 10222, 9875, 669, 2342, 1183, 10758, 1575, 6987, 872, 2740, 11310, 9618, 684… + ## $ week_start 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: 12,330 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 + ## + ## 1 HHS Regions Region 1 1997 40 0.499 0.624 15 NA 7 22 NA 0 + ## 2 HHS Regions Region 2 1997 40 0.375 0.385 0 NA 3 0 NA 0 + ## 3 HHS Regions Region 3 1997 40 1.35 1.34 6 NA 7 15 NA 4 + ## 4 HHS Regions Region 4 1997 40 0.400 0.450 12 NA 23 11 NA 0 + ## 5 HHS Regions Region 5 1997 40 1.23 0.901 31 NA 24 30 NA 4 + ## 6 HHS Regions Region 6 1997 40 1.02 0.747 2 NA 1 2 NA 0 + ## 7 HHS Regions Region 7 1997 40 0.872 1.15 0 NA 4 18 NA 5 + ## 8 HHS Regions Region 8 1997 40 0.516 0.423 2 NA 0 3 NA 0 + ## 9 HHS Regions Region 9 1997 40 1.81 2.26 80 NA 76 74 NA 13 + ## 10 HHS Regions Region 10 1997 40 4.74 4.83 31 NA 12 30 NA 3 + ## # … with 12,320 more rows, and 4 more variables: ilitotal , num_of_providers , total_patients , ## # week_start - ## Rows: 10,557 + ## Rows: 11,097 ## Columns: 16 - ## $ region_type "Census Regions", "Census Regions", "Census Regions", "Census Regions", "Census Regions", "C… - ## $ region "New England", "Mid-Atlantic", "East North Central", "West North Central", "South Atlantic",… - ## $ year 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 19… - ## $ week 40, 40, 40, 40, 40, 40, 40, 40, 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 42, 42, 42, … - ## $ weighted_ili 0.4985350, 0.8441440, 0.7924860, 1.7640500, 0.5026620, 0.0542283, 1.0189800, 2.2587800, 2.04… - ## $ unweighted_ili 0.6238480, 1.3213800, 0.8187380, 1.2793900, 0.7233800, 0.0688705, 0.7473840, 2.2763300, 3.23… - ## $ age_0_4 15, 4, 28, 3, 14, 0, 2, 87, 26, 14, 4, 36, 0, 21, 0, 2, 93, 29, 35, 3, 65, 1, 19, 0, 2, 84, … - ## $ age_25_49 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … - ## $ age_25_64 7, 8, 20, 8, 22, 3, 1, 71, 17, 14, 13, 23, 1, 14, 1, 2, 72, 11, 15, 11, 27, 5, 21, 0, 2, 55,… - ## $ age_5_24 22, 12, 28, 20, 14, 0, 2, 71, 36, 29, 8, 39, 18, 22, 0, 2, 80, 44, 35, 16, 74, 9, 24, 2, 2, … - ## $ age_50_64 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … - ## $ age_65 0, 4, 3, 6, 0, 0, 0, 15, 1, 0, 2, 2, 4, 3, 0, 0, 10, 2, 0, 3, 12, 6, 2, 0, 0, 9, 2, 0, 1, 14… - ## $ ilitotal 44, 28, 79, 37, 50, 3, 5, 244, 80, 57, 27, 100, 23, 60, 1, 6, 255, 86, 85, 33, 178, 21, 66, … - ## $ num_of_providers 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 7053, 2119, 9649, 2892, 6912, 4356, 669, 10719, 2473, 6987, 2384, 9427, 2823, 7591, 4947, 68… - ## $ week_start 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: 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 - ## - ## 1 Census Reg… New E… 1997 40 0.499 0.624 15 NA 7 22 NA 0 - ## 2 Census Reg… Mid-A… 1997 40 0.844 1.32 4 NA 8 12 NA 4 - ## 3 Census Reg… East … 1997 40 0.792 0.819 28 NA 20 28 NA 3 - ## 4 Census Reg… West … 1997 40 1.76 1.28 3 NA 8 20 NA 6 - ## 5 Census Reg… South… 1997 40 0.503 0.723 14 NA 22 14 NA 0 - ## 6 Census Reg… East … 1997 40 0.0542 0.0689 0 NA 3 0 NA 0 - ## 7 Census Reg… West … 1997 40 1.02 0.747 2 NA 1 2 NA 0 - ## 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 10,547 more rows, and 4 more variables: ilitotal , num_of_providers , total_patients , + ## $ region_type "Census Regions", "Census Regions", "Census Regions", "Census Regions", "Census Regions", "Ce… + ## $ region "New England", "Mid-Atlantic", "East North Central", "West North Central", "South Atlantic", … + ## $ year 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 1997, 199… + ## $ week 40, 40, 40, 40, 40, 40, 40, 40, 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 42, 42, 42, 4… + ## $ weighted_ili 0.4985350, 0.8441440, 0.7924860, 1.7640500, 0.5026620, 0.0542283, 1.0189800, 2.2587800, 2.048… + ## $ unweighted_ili 0.6238480, 1.3213800, 0.8187380, 1.2793900, 0.7233800, 0.0688705, 0.7473840, 2.2763300, 3.234… + ## $ age_0_4 15, 4, 28, 3, 14, 0, 2, 87, 26, 14, 4, 36, 0, 21, 0, 2, 93, 29, 35, 3, 65, 1, 19, 0, 2, 84, 1… + ## $ age_25_49 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… + ## $ age_25_64 7, 8, 20, 8, 22, 3, 1, 71, 17, 14, 13, 23, 1, 14, 1, 2, 72, 11, 15, 11, 27, 5, 21, 0, 2, 55, … + ## $ age_5_24 22, 12, 28, 20, 14, 0, 2, 71, 36, 29, 8, 39, 18, 22, 0, 2, 80, 44, 35, 16, 74, 9, 24, 2, 2, 7… + ## $ age_50_64 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… + ## $ age_65 0, 4, 3, 6, 0, 0, 0, 15, 1, 0, 2, 2, 4, 3, 0, 0, 10, 2, 0, 3, 12, 6, 2, 0, 0, 9, 2, 0, 1, 14,… + ## $ ilitotal 44, 28, 79, 37, 50, 3, 5, 244, 80, 57, 27, 100, 23, 60, 1, 6, 255, 86, 85, 33, 178, 21, 66, 2… + ## $ num_of_providers 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 7053, 2119, 9649, 2892, 6912, 4356, 669, 10719, 2473, 6987, 2384, 9427, 2823, 7591, 4947, 684… + ## $ week_start 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: 11,097 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 + ## + ## 1 Census Regi… New Engla… 1997 40 0.499 0.624 15 NA 7 22 NA 0 + ## 2 Census Regi… Mid-Atlan… 1997 40 0.844 1.32 4 NA 8 12 NA 4 + ## 3 Census Regi… East Nort… 1997 40 0.792 0.819 28 NA 20 28 NA 3 + ## 4 Census Regi… West Nort… 1997 40 1.76 1.28 3 NA 8 20 NA 6 + ## 5 Census Regi… South Atl… 1997 40 0.503 0.723 14 NA 22 14 NA 0 + ## 6 Census Regi… East Sout… 1997 40 0.0542 0.0689 0 NA 3 0 NA 0 + ## 7 Census Regi… West Sout… 1997 40 1.02 0.747 2 NA 1 2 NA 0 + ## 8 Census Regi… Mountain 1997 40 2.26 2.28 87 NA 71 71 NA 15 + ## 9 Census Regi… Pacific 1997 40 2.05 3.23 26 NA 17 36 NA 1 + ## 10 Census Regi… New Engla… 1997 41 0.643 0.816 14 NA 14 29 NA 0 + ## # … with 11,087 more rows, and 4 more variables: ilitotal , num_of_providers , total_patients , ## # week_start - ## Rows: 26,493 + ## Rows: 29,793 ## Columns: 16 - ## $ region_type "States", "States", "States", "States", "States", "States", "States", "States", "States", "S… - ## $ region "Alabama", "Alaska", "Arizona", "Arkansas", "California", "Colorado", "Connecticut", "Delawa… - ## $ year 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 20… - ## $ week 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, … - ## $ weighted_ili NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … - ## $ unweighted_ili 2.1347700, 0.8751460, 0.6747210, 0.6960560, 1.9541200, 0.6606840, 0.0783085, 0.1001250, 2.80… - ## $ age_0_4 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … - ## $ age_25_49 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … - ## $ age_25_64 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … - ## $ age_5_24 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … - ## $ age_50_64 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … - ## $ age_65 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, … - ## $ ilitotal 249, 15, 172, 18, 632, 134, 3, 4, 73, NA, 647, 20, 19, 505, 65, 10, 39, 19, 391, 22, 117, 16… - ## $ num_of_providers 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 11664, 1714, 25492, 2586, 32342, 20282, 3831, 3995, 2599, NA, 40314, 1943, 4579, 39390, 1252… - ## $ week_start 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: 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 - ## - ## 1 States Alaba… 2010 40 NA 2.13 NA NA NA NA NA NA - ## 2 States Alaska 2010 40 NA 0.875 NA NA NA NA NA NA - ## 3 States Arizo… 2010 40 NA 0.675 NA NA NA NA NA NA - ## 4 States Arkan… 2010 40 NA 0.696 NA NA NA NA NA NA - ## 5 States Calif… 2010 40 NA 1.95 NA NA NA NA NA NA - ## 6 States Color… 2010 40 NA 0.661 NA NA NA NA NA NA - ## 7 States Conne… 2010 40 NA 0.0783 NA NA NA NA NA NA - ## 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 26,483 more rows, and 4 more variables: ilitotal , num_of_providers , total_patients , + ## $ region_type "States", "States", "States", "States", "States", "States", "States", "States", "States", "St… + ## $ region "Alabama", "Alaska", "Arizona", "Arkansas", "California", "Colorado", "Connecticut", "Delawar… + ## $ year 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 2010, 201… + ## $ week 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 40, 4… + ## $ weighted_ili NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… + ## $ unweighted_ili 2.1347700, 0.8751460, 0.6747210, 0.6960560, 1.9541200, 0.6606840, 0.0783085, 0.1001250, 2.808… + ## $ age_0_4 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… + ## $ age_25_49 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… + ## $ age_25_64 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… + ## $ age_5_24 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… + ## $ age_50_64 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… + ## $ age_65 NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N… + ## $ ilitotal 249, 15, 172, 18, 632, 134, 3, 4, 73, NA, 647, 20, 19, 505, 65, 10, 39, 19, 391, 22, 117, 168… + ## $ num_of_providers 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 11664, 1714, 25492, 2586, 32342, 20282, 3831, 3995, 2599, NA, 40314, 1943, 4579, 39390, 12525… + ## $ week_start 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: 29,793 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 + ## + ## 1 States Alabama 2010 40 NA 2.13 NA NA NA NA NA NA + ## 2 States Alaska 2010 40 NA 0.875 NA NA NA NA NA NA + ## 3 States Arizona 2010 40 NA 0.675 NA NA NA NA NA NA + ## 4 States Arkansas 2010 40 NA 0.696 NA NA NA NA NA NA + ## 5 States California 2010 40 NA 1.95 NA NA NA NA NA NA + ## 6 States Colorado 2010 40 NA 0.661 NA NA NA NA NA NA + ## 7 States Connecticut 2010 40 NA 0.0783 NA NA NA NA NA NA + ## 8 States Delaware 2010 40 NA 0.100 NA NA NA NA NA NA + ## 9 States District o… 2010 40 NA 2.81 NA NA NA NA NA NA + ## 10 States Florida 2010 40 NA NA NA NA NA NA NA NA + ## # … with 29,783 more rows, and 4 more variables: ilitotal , num_of_providers , total_patients , ## # week_start @@ -504,18 +491,18 @@ walk(c("national", "hhs", "census", "state"), ~{ ``` r ili_weekly_activity_indicators(2017) ## # A tibble: 2,805 x 8 -## statename url website activity_level activity_level_label weekend season weeknumber -## * -## 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 +## statename url website activity_level activity_level_… weekend season weeknumber +## * +## 1 Alabama "http://adph.org/influenza/" Influenza Sur… 2 Minimal 2017-10-07 2017-… 40 +## 2 Alaska "http://dhss.alaska.gov/dph… 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 "https://portal.ct.gov/DPH/… 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… "https://dchealth.dc.gov/no… Influenza Inf… 2 Minimal 2017-10-07 2017-… 40 +## 10 Florida "http://www.floridahealth.g… Weekly Influe… 1 Minimal 2017-10-07 2017-… 40 ## # … with 2,795 more rows xdf <- map_df(2008:2017, ili_weekly_activity_indicators) @@ -538,20 +525,20 @@ count(xdf, weekend, activity_level_label) %>% ``` r (nat_pi <- pi_mortality("national")) -## # A tibble: 337 x 19 +## # A tibble: 398 x 19 ## seasonid baseline threshold percent_pni percent_complete number_influenza number_pneumonia all_deaths total_pni ## -## 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 , geo_description , age_label , +## 1 60 0.053 0.0560 0.081 1 8 4825 59682 4833 +## 2 60 0.054 0.057 0.084 1 12 5173 61641 5185 +## 3 60 0.055 0.0580 0.086 1 16 5208 60467 5224 +## 4 60 0.0560 0.059 0.091 1 15 5642 62047 5657 +## 5 60 0.057 0.06 0.0970 1 21 6142 63280 6163 +## 6 60 0.0580 0.061 0.105 1 21 7075 67380 7096 +## 7 60 0.059 0.062 0.117 1 20 8040 68644 8060 +## 8 60 0.06 0.063 0.132 1 30 9400 71440 9430 +## 9 60 0.061 0.064 0.143 1 27 10440 73066 10467 +## 10 60 0.062 0.065 0.157 1 35 12048 77136 12083 +## # … with 388 more rows, and 10 more variables: weeknumber , geo_description , age_label , ## # week_start , week_end , year_week_num , mmwrid , coverage_area , region_name , ## # callout @@ -570,7 +557,6 @@ select(nat_pi, week_end, percent_pni, baseline, threshold) %>% ``` r - (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 @@ -593,16 +579,16 @@ select(nat_pi, week_end, percent_pni, baseline, threshold) %>% ## # A tibble: 520 x 19 ## seasonid baseline threshold percent_pni percent_complete number_influenza number_pneumonia all_deaths total_pni ## -## 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 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 +## 1 55 0.064 0.071 0.07 1 0 178 2525 178 +## 2 55 0.065 0.072 0.064 1 0 160 2512 160 +## 3 55 0.066 0.073 0.0580 1 1 141 2457 142 +## 4 55 0.067 0.074 0.07 0.989 0 171 2426 171 +## 5 55 0.068 0.075 0.065 1 2 166 2565 168 +## 6 55 0.069 0.077 0.067 0.985 1 162 2415 163 +## 7 55 0.071 0.078 0.079 1 0 198 2491 198 +## 8 55 0.072 0.079 0.072 1 1 176 2468 177 +## 9 55 0.073 0.081 0.067 0.96 3 154 2353 157 +## 10 55 0.075 0.0820 0.062 0.996 0 151 2441 151 ## # … with 510 more rows, and 10 more variables: weeknumber , geo_description , age_label , ## # week_start , week_end , year_week_num , mmwrid , coverage_area , region_name , ## # callout @@ -623,7 +609,7 @@ state_data_providers() ## 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 +## 9 District of … District of Columbia Depart… "https://dchealth.dc.gov/node/114… 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 ``` @@ -633,7 +619,7 @@ state_data_providers() ``` r glimpse(xdat <- who_nrevss("national")) ## List of 3 -## $ combined_prior_to_2015_16: tibble [940 × 14] (S3: tbl_df/tbl/data.frame) +## $ combined_prior_to_2015_16: tibble[,14] [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 ... @@ -648,32 +634,32 @@ 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 : 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" ... +## $ public_health_labs : tibble[,13] [293 × 13] (S3: tbl_df/tbl/data.frame) +## ..$ region_type : chr [1:293] "National" "National" "National" "National" ... +## ..$ region : chr [1:293] "National" "National" "National" "National" ... +## ..$ year : int [1:293] 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 ... +## ..$ week : int [1:293] 40 41 42 43 44 45 46 47 48 49 ... +## ..$ total_specimens : int [1:293] 1139 1152 1198 1244 1465 1393 1458 1157 1550 1518 ... +## ..$ a_2009_h1n1 : int [1:293] 4 5 10 9 4 11 17 17 27 38 ... +## ..$ a_h3 : int [1:293] 65 41 50 31 23 34 42 24 36 37 ... +## ..$ a_subtyping_not_performed: int [1:293] 2 2 1 4 4 1 1 0 3 3 ... +## ..$ b : int [1:293] 10 7 8 9 9 10 4 4 9 11 ... +## ..$ bvic : int [1:293] 0 3 3 1 1 4 0 3 3 2 ... +## ..$ byam : int [1:293] 1 0 2 4 4 2 4 9 12 11 ... +## ..$ h3n2v : int [1:293] 0 0 0 0 0 0 0 0 0 0 ... +## ..$ wk_date : Date[1:293], format: "2015-10-04" "2015-10-11" "2015-10-18" "2015-10-25" ... +## $ clinical_labs : tibble[,11] [293 × 11] (S3: tbl_df/tbl/data.frame) +## ..$ region_type : chr [1:293] "National" "National" "National" "National" ... +## ..$ region : chr [1:293] "National" "National" "National" "National" ... +## ..$ year : int [1:293] 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 ... +## ..$ week : int [1:293] 40 41 42 43 44 45 46 47 48 49 ... +## ..$ total_specimens : int [1:293] 12029 13111 13441 13537 14687 15048 15250 15234 16201 16673 ... +## ..$ total_a : int [1:293] 84 116 97 98 97 122 84 119 145 140 ... +## ..$ total_b : int [1:293] 43 54 52 52 68 86 98 92 81 106 ... +## ..$ percent_positive: num [1:293] 1.06 1.3 1.11 1.11 1.12 ... +## ..$ percent_a : num [1:293] 0.698 0.885 0.722 0.724 0.66 ... +## ..$ percent_b : num [1:293] 0.357 0.412 0.387 0.384 0.463 ... +## ..$ wk_date : Date[1:293], format: "2015-10-04" "2015-10-11" "2015-10-18" "2015-10-25" ... mutate(xdat$combined_prior_to_2015_16, percent_positive = percent_positive / 100) %>% @@ -687,7 +673,6 @@ mutate(xdat$combined_prior_to_2015_16, ``` r - who_nrevss("hhs", years=2016) ## $public_health_labs ## # A tibble: 520 x 13 @@ -757,18 +742,18 @@ who_nrevss("census", years=2016) 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 -## -## 1 States Alaba… Season 2016-17 570 3 227 1 2 15 14 0 -## 2 States Alaska Season 2016-17 5222 14 905 3 252 2 11 0 -## 3 States Arizo… Season 2016-17 2975 63 1630 0 5 227 578 0 -## 4 States Arkan… Season 2016-17 121 0 51 0 0 4 0 0 -## 5 States Calif… Season 2016-17 14074 184 4696 120 116 28 152 0 -## 6 States Color… Season 2016-17 714 3 267 2 4 31 219 0 -## 7 States Conne… Season 2016-17 1348 19 968 0 0 62 263 0 -## 8 States Delaw… Season 2016-17 3090 5 659 4 11 27 127 1 -## 9 States Distr… Season 2016-17 73 1 34 0 3 0 4 0 -## 10 States Flori… Season 2016-17 +## region_type region season_descripti… total_specimens a_2009_h1n1 a_h3 a_subtyping_not_p… b bvic byam h3n2v +## +## 1 States Alabama Season 2016-17 570 3 227 1 2 15 14 0 +## 2 States Alaska Season 2016-17 5222 14 905 3 252 2 11 0 +## 3 States Arizona Season 2016-17 2975 63 1630 0 5 227 578 0 +## 4 States Arkansas Season 2016-17 121 0 51 0 0 4 0 0 +## 5 States California Season 2016-17 14074 184 4696 120 116 28 152 0 +## 6 States Colorado Season 2016-17 714 3 267 2 4 31 219 0 +## 7 States Connectic… Season 2016-17 1348 19 968 0 0 62 263 0 +## 8 States Delaware Season 2016-17 3090 5 659 4 11 27 127 1 +## 9 States District … Season 2016-17 73 1 34 0 3 0 4 0 +## 10 States Florida Season 2016-17 ## # … with 44 more rows, and 1 more variable: wk_date ## ## $clinical_labs @@ -791,10 +776,13 @@ who_nrevss("state", years=2016) ## cdcfluview Metrics | Lang | \# Files | (%) | LoC | (%) | Blank lines | (%) | \# Lines | (%) | -| :--- | -------: | ---: | --: | ---: | ----------: | ---: | -------: | ---: | -| 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 | +|:-----|---------:|-----:|----:|-----:|------------:|-----:|---------:|-----:| +| R | 21 | 0.46 | 865 | 0.44 | 311 | 0.40 | 512 | 0.43 | +| Rmd | 1 | 0.02 | 81 | 0.04 | 64 | 0.08 | 82 | 0.07 | +| make | 1 | 0.02 | 32 | 0.02 | 11 | 0.01 | 1 | 0.00 | +| SUM | 23 | 0.50 | 978 | 0.50 | 386 | 0.50 | 595 | 0.50 | + +clock Package Metrics for cdcfluview ## Code of Conduct diff --git a/cran-comments.md b/cran-comments.md index 7da41e0..d77cff6 100644 --- a/cran-comments.md +++ b/cran-comments.md @@ -1,11 +1,10 @@ ## Test environments -* local R installation, R 4.0.4 -* ubuntu 16.04 (on travis-ci), R 4.0.4 +* local R installation, R 4.1.0 +* ubuntu 20.04, R 4.1.0 * win-builder (devel) ## R CMD check results 0 errors | 0 warnings | 1 note -* Fixed one failing test -* Fixed one API URL +* Fixed one failing test noted in CRAN email diff --git a/man/figures/README-cdc-basemaps-1.png b/man/figures/README-cdc-basemaps-1.png index 2c6e3110290c5290581a36b72cd9f34232e2877a..6e093a1965de4730a7a4be19f88e1d448f619117 100644 GIT binary patch literal 44500 zcmZsBWn5gn6E3briWZ8yQ`{FQu8X@AcPkEy7H@GYx(gJy;x0vsvlMrVE>c_y1I12S zO&S5AE)o0D0`;|w=&7af5us+1;^0*hK|@tXu4GZ?`S}?c85tE7)wZuV9x{fAi1_mI z0*mW^mA|;S*xufT!{IkKH-v;lCnqOQPfw(zq_niOJv}|Gt*uyCSdNa4ot>R^KkIyb zeFFmnBO@c3nVENYcX4oVE-x>q|4bhq9u^lDOG`_Kg@uicjcxwj+}PMyTwKh}%{@Ci zdw6(AO-(H;E92qev9hun92~T@wJn;{;^yX7RaGr2Dq>(@SXo&S6BA2LP8JpxMnOlc 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