i think full coverage

NAMESPACE

@@ -3,11 +3,18 @@
 export(about)
 export(age_groups)
 export(available_seasons)
+export(clinical_labs)
 export(laboratory_confirmed_hospitalizations)
 export(mmwr_week)
 export(mmwr_week_to_date)
 export(mmwr_weekday)
 export(mmwrid_map)
+export(mortality_surveillance_data)
+export(nssp_er_visits_national)
+export(nssp_er_visits_regional)
+export(provisional_death_counts)
+export(public_health_labs_national)
+export(public_health_labs_regional)
 export(surveillance_areas)
 import(MMWRweek)
 import(httr)

R/clinical-labs.R

@@ -0,0 +1,24 @@
+#' Retrieve U.S. Clinical Laboratories Reporting SARS-CoV-2 Test Results to CDC
+#'
+#' @references <https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/reporting-cov2-results.html>
+#' @return data frame
+#' @export
+clinical_labs <- function() {
+
+  pg <- xml2::read_html("https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/reporting-cov2-results.html")
+
+  clab_tbl <- rvest::html_table(pg, header = TRUE, trim = TRUE)[[1]]
+  colnames(clab_tbl) <- c("week", "num_labs", "tested", "tested_pos", "pct_pos")
+
+  clab_tbl$region <- "National"
+  clab_tbl$source <- "Clinical Labs"
+
+  clab_tbl$week <- clean_int(clab_tbl$week)
+  clab_tbl$num_labs <- clean_int(clab_tbl$num_labs)
+  clab_tbl$tested <- clean_int(clab_tbl$tested)
+  clab_tbl$tested_pos <- clean_int(clab_tbl$tested_pos)
+  clab_tbl$pct_pos <- clean_num(clab_tbl$pct_pos)/100
+
+  as_tibble(clab_tbl[!is.na(clab_tbl$week),])
+
+}

R/mortality.R

@@ -0,0 +1,47 @@
+#' Retrieve NCHS Mortality Surveillance Data
+#'
+#' @return data frame
+#' @references <https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nchs-data.html>
+#' @export
+mortality_surveillance_data <- function() {
+
+  pg <- xml2::read_html("https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nchs-data.html")
+
+  nat_tbl <- rvest::html_nodes(pg, xpath=".//table[contains(., 'Total Deaths')]")
+  nat_rows <- rvest::html_nodes(nat_tbl, "tbody > tr")
+
+  lapply(nat_rows, function(.x) {
+    nat_tds <- rvest::html_nodes(.x, "td")
+    nat_tds <- gsub(",", "", rvest::html_text(nat_tds))
+    as_tibble(as.data.frame(
+      as.list(
+        set_names(
+          nat_tds, sprintf("X%02d", 1:length(nat_tds))
+        )
+      ),
+      stringsAsFactors = FALSE
+    ))
+  }) -> nat_rows
+  nat_tbl <- do.call(rbind.data.frame, nat_rows)
+
+  cov <- set_names(nat_tbl[, 1:5], c("year", "week", "total_deaths", "deaths", "pct_deaths"))
+  cov$cause <- "COVID-19"
+
+  pnu <- set_names(nat_tbl[, c(1:3, 6:7)], c("year", "week", "total_deaths", "deaths", "pct_deaths"))
+  pnu$cause <- "Pneumonia"
+
+  flu <- set_names(nat_tbl[, c(1:3, 8:9)], c("year", "week", "total_deaths", "deaths", "pct_deaths"))
+  flu$cause <- "Influenza"
+
+  nat_tbl <- rbind(cov, pnu, flu, stringsAsFactors = FALSE)
+  nat_tbl$region <- "National"
+  nat_tbl$source <- "NCHS"
+  nat_tbl$year <- clean_int(nat_tbl$year)
+  nat_tbl$week <- clean_int(nat_tbl$week)
+  nat_tbl$total_deaths <- clean_int(nat_tbl$total_deaths)
+  nat_tbl$deaths <- clean_int(nat_tbl$deaths)
+  nat_tbl$pct_deaths <- clean_num(nat_tbl$pct_deaths)/100
+
+  as_tibble(nat_tbl[!is.na(nat_tbl$week),])
+
+}

R/nss-cd-reg.R

@@ -0,0 +1,57 @@
+#' Retrieve Regional Syndromic Surveillance Program (NSSP): Emergency Department Visits Percentage of Visits for COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI)
+#'
+#' @return data frame
+#' @references <https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nssp-regions.html>
+#' @export
+nssp_er_visits_regional <- function() {
+
+  xml2::read_html(
+    "https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nssp-regions.html"
+  ) -> pg
+
+  regions <- sprintf("Region %d", 1:10)
+
+  lapply(regions, function(region){
+
+    reg_tbl <- rvest::html_nodes(pg, xpath=".//table[contains(., 'National')]")
+    nat_rows <- rvest::html_nodes(reg_tbl, "tbody > tr")
+    lapply(nat_rows, function(.x) {
+      nat_tds <- rvest::html_nodes(.x, "td")
+      nat_tds <- gsub(",", "", rvest::html_text(nat_tds))
+      as_tibble(as.data.frame(
+        as.list(
+          set_names(
+            nat_tds, sprintf("X%02d", 1:length(nat_tds))
+          )
+        ),
+        stringsAsFactors = FALSE
+      ))
+    }) -> nat_rows
+    reg_tbl <- do.call(rbind.data.frame, nat_rows)
+
+    cli <- set_names(reg_tbl[, 1:5], c("week", "num_fac", "total_ed_visits", "visits", "pct_visits"))
+    cli$visit_type <- "cli"
+
+    ili <- set_names(reg_tbl[, c(1:3, 6:7)], c("week", "num_fac", "total_ed_visits", "visits", "pct_visits"))
+    ili$visit_type <- "ili"
+
+    reg_tbl <- rbind(ili, cli, stringsAsFactors = FALSE)
+    reg_tbl$region <- region
+    reg_tbl$source <- "Emergency Departments"
+    reg_tbl$week <- as.character(clean_int(reg_tbl$week))
+    reg_tbl$year <- clean_int(substr(reg_tbl$week, 1, 4))
+    reg_tbl$week <- clean_int(substr(reg_tbl$week, 5, 6))
+    reg_tbl$num_fac <- clean_int(reg_tbl$num_fac)
+    reg_tbl$visits <- clean_int(reg_tbl$visits)
+    reg_tbl$pct_visits <- clean_num(reg_tbl$pct_visits)/100
+
+    reg_tbl[!is.na(reg_tbl$week),]
+
+
+  }) -> regs
+
+  out <- do.call(rbind.data.frame, regs)
+
+  as_tibble(out)
+
+}

R/nssp-cd.R

@@ -0,0 +1,43 @@
+#' Retrieve National Syndromic Surveillance Program (NSSP): Emergency Department Visits Percentage of Visits for COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI)
+#'
+#' @references <https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nssp-regions.html>
+#' @return data frame
+#' @export
+nssp_er_visits_national <- function() {
+
+  pg <- xml2::read_html("https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nssp-regions.html")
+
+  nat_tbl <- rvest::html_nodes(pg, xpath=".//table[contains(., 'National')]")
+  nat_rows <- rvest::html_nodes(nat_tbl, "tbody > tr")
+  lapply(nat_rows, function(.x) {
+    nat_tds <- rvest::html_nodes(.x, "td")
+    nat_tds <- gsub(",", "", rvest::html_text(nat_tds))
+    as_tibble(as.data.frame(
+      as.list(
+        set_names(
+          nat_tds, sprintf("X%02d", 1:length(nat_tds))
+        )
+      ),
+      stringsAsFactors = FALSE
+    ))
+  }) -> nat_rows
+  nat_tbl <- do.call(rbind.data.frame, nat_rows)
+
+  cli <- set_names(nat_tbl[, 1:5], c("week", "num_fac", "total_ed_visits", "visits", "pct_visits"))
+  cli$visit_type <- "cli"
+
+  ili <- set_names(nat_tbl[, c(1:3, 6:7)], c("week", "num_fac", "total_ed_visits", "visits", "pct_visits"))
+  ili$visit_type <- "ili"
+
+  nat_tbl <- rbind(ili, cli, stringsAsFactors = FALSE)
+  nat_tbl$region <- "National"
+  nat_tbl$source <- "Emergency Departments"
+  nat_tbl$year <- clean_int(substr(nat_tbl$week, 1, 4))
+  nat_tbl$week <- clean_int(substr(nat_tbl$week, 5, 6))
+  nat_tbl$num_fac <- clean_int(nat_tbl$num_fac)
+  nat_tbl$visits <- clean_int(nat_tbl$visits)
+  nat_tbl$pct_visits <- clean_num(nat_tbl$pct_visits)/100
+
+  as_tibble(nat_tbl[!is.na(nat_tbl$week),])
+
+}

R/provisional-deaths.R

@@ -0,0 +1,62 @@
+#' Retrieve Provisional Death Counts for Coronavirus Disease (COVID-19)
+#'
+#' @note Please see the indicated reference for all the caveats and precise meanings for each field. Also,
+#'       this function used the JSON API (<https://data.cdc.gov/resource/hc4f-j6nb.json>)
+#' @return a list with 4 named elements: `by_week`, `by_age`, `by_state`, `by_sex`
+#' @references <https://data.cdc.gov/api/views/hc4f-j6nb/rows.csv?accessType=DOWNLOAD&bom=true&format=true>
+#' @export
+provisional_death_counts <- function() {
+
+  res <- jsonlite::fromJSON("https://data.cdc.gov/resource/hc4f-j6nb.json")
+  res <- as_tibble(res)
+
+  res$covid_deaths <- clean_int(res$covid_deaths)
+  res$total_deaths <- clean_int(res$total_deaths)
+  res$pneumonia_deaths <- clean_int(res$pneumonia_deaths)
+  res$pneumonia_and_covid_deaths <- clean_int(res$pneumonia_and_covid_deaths)
+  res$all_influenza_deaths_j09_j11 <- clean_int(res$all_influenza_deaths_j09_j11)
+  res$percent_expected_deaths <- clean_num(res$percent_expected_deaths)
+
+  by_week <- res[res$group == "By week",]
+  by_age <- res[res$group == "By age",]
+  by_state <- res[res$group == "By state",]
+  by_sex <- res[res$group == "By sex",]
+
+  by_week <- by_week[!grepl("total", tolower(by_week$indicator)),]
+  by_week$group <- NULL
+  by_week$indicator <- as.Date(by_week$indicator, "%m/%d/%Y")
+  colnames(by_week) <- c(
+    "week", "covid_deaths", "total_deaths", "percent_expected_deaths",
+    "pneumonia_deaths", "pneumonia_and_covid_deaths", "all_influenza_deaths_j09_j11"
+  )
+
+  by_age$group <- NULL
+  colnames(by_age) <- c(
+    "age_group", "covid_deaths", "total_deaths", "percent_expected_deaths",
+    "pneumonia_deaths", "pneumonia_and_covid_deaths", "all_influenza_deaths_j09_j11"
+  )
+  by_age$age_group <- sub("&ndash;", "-", by_age$age_group, fixed=TRUE)
+  by_age$age_group <- sub("yea.*", "yr", by_age$age_group)
+
+  by_state$group <- NULL
+  colnames(by_state) <- c(
+    "state", "covid_deaths", "total_deaths", "percent_expected_deaths",
+    "pneumonia_deaths", "pneumonia_and_covid_deaths", "all_influenza_deaths_j09_j11"
+  )
+  by_state <- by_state[by_state$state != "Total US",]
+
+  by_sex$group <- NULL
+  colnames(by_sex) <- c(
+    "sex", "covid_deaths", "total_deaths", "percent_expected_deaths",
+    "pneumonia_deaths", "pneumonia_and_covid_deaths", "all_influenza_deaths_j09_j11"
+  )
+  by_sex <- by_sex[!grepl("Total", by_sex$sex),]
+
+  list(
+    by_week = as_tibble(by_week),
+    by_age = as_tibble(by_age),
+    by_state = as_tibble(by_state),
+    by_sex = as_tibble(by_sex)
+  )
+
+}

R/public-health-labs-national.R

@@ -0,0 +1,57 @@
+#' Retrieve National Surveillance of U.S. State and Local Public Health Laboratories Reporting to CDC
+#'
+#' @return data frame
+#' @references <https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/labs-regions.html>
+#' @export
+public_health_labs_national <- function() {
+
+  xml2::read_html(
+    "https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/labs-regions.html"
+  ) -> pg
+
+  nat_tbl <- rvest::html_nodes(pg, xpath=".//table[contains(., 'National')]")
+  nat_rows <- rvest::html_nodes(nat_tbl, "tbody > tr")
+  lapply(nat_rows, function(.x) {
+    nat_tds <- rvest::html_nodes(.x, "td")
+    nat_tds <- gsub(",", "", rvest::html_text(nat_tds))
+    as_tibble(as.data.frame(
+      as.list(
+        set_names(
+          nat_tds, sprintf("X%02d", 1:length(nat_tds))
+        )
+      ),
+      stringsAsFactors = FALSE
+    ))
+  }) -> nat_rows
+  nat_tbl <- do.call(rbind.data.frame, nat_rows)
+
+  total <- set_names(nat_tbl[, 1:5], c("week", "num_labs", "tested", "tested_pos", "pct_pos"))
+  total$age_group <- "Overall"
+
+  a1 <- set_names(nat_tbl[, c(1:2, 6:8)], c("week", "num_labs", "tested", "tested_pos", "pct_pos"))
+  a1$age_group <- "0-4 yr"
+
+  a2 <- set_names(nat_tbl[, c(1:2, 9:11)], c("week", "num_labs", "tested", "tested_pos", "pct_pos"))
+  a2$age_group <- "5-17 yr"
+
+  a3 <- set_names(nat_tbl[, c(1:2, 12:14)], c("week", "num_labs", "tested", "tested_pos", "pct_pos"))
+  a3$age_group <- "18-49 yr"
+
+  a4 <- set_names(nat_tbl[, c(1:2, 15:17)], c("week", "num_labs", "tested", "tested_pos", "pct_pos"))
+  a4$age_group <- "50-64 yr"
+
+  a5 <- set_names(nat_tbl[, c(1:2, 18:20)], c("week", "num_labs", "tested", "tested_pos", "pct_pos"))
+  a5$age_group <- "65+ yr"
+
+  nat_tbl <- rbind(total, a1, a2, a3, a4, a5, stringsAsFactors = FALSE)
+  nat_tbl$region <- "National"
+  nat_tbl$source <- "Public Health Labs"
+  nat_tbl$week <- clean_int(nat_tbl$week)
+  nat_tbl$num_labs <- clean_int(nat_tbl$num_labs)
+  nat_tbl$tested <- clean_int(nat_tbl$tested)
+  nat_tbl$tested_pos <- clean_int(nat_tbl$tested_pos)
+  nat_tbl$pct_pos <- clean_num(nat_tbl$pct_pos)/100
+
+  nat_tbl[!is.na(nat_tbl$week),]
+
+}

R/public-health-labs-regional.R

@@ -0,0 +1,42 @@
+#' Retrieve Regional Surveillance of U.S. State and Local Public Health Laboratories Reporting to CDC
+#'
+#' @return data frame
+#' @references <https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/labs-regions.html>
+#' @export
+public_health_labs_regional <- function() {
+
+  xml2::read_html(
+    "https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/labs-regions.html"
+  ) -> pg
+
+  regions <- sprintf("Region %d", 1:10)
+
+  lapply(regions, function(region){
+
+    rvest::html_node(
+      pg,
+      xpath=sprintf(".//table[contains(., '%s (')]", region)
+    ) -> reg_tbl
+
+    reg_tbl <- rvest::html_table(reg_tbl, header = TRUE, trim = TRUE)
+
+    colnames(reg_tbl) <- c("week", "num_labs", "tested", "tested_pos", "pct_pos")
+
+    reg_tbl$region <- region
+    reg_tbl$source <- "Public Health Labs"
+
+    reg_tbl$week <- clean_int(reg_tbl$week)
+    reg_tbl$num_labs <- clean_int(reg_tbl$num_labs)
+    reg_tbl$tested <- clean_int(reg_tbl$tested)
+    reg_tbl$tested_pos <- clean_int(reg_tbl$tested_pos)
+    reg_tbl$pct_pos <- clean_num(reg_tbl$pct_pos)/100
+
+    as_tibble(reg_tbl[!is.na(reg_tbl$week),])
+
+  }) -> regs
+
+  out <- do.call(rbind.data.frame, regs)
+
+  as_tibble(out)
+
+}

R/utils.R

@@ -1,3 +1,11 @@
+clean_int <- function(x) {
+  suppressWarnings(as.integer(gsub(",", "", x)))
+}
+
+clean_num <- function(x) {
+  suppressWarnings(as.numeric(gsub(",", "", x)))
+}
+
 set_names <- function(object = nm, nm) { names(object) <- nm ; object }
 
 as_tibble <- function(x) {
@@ -9,7 +17,7 @@ tibble <- function(...) {
   as_tibble(data.frame(..., stringsAsFactors = FALSE))
 }
 
-#' Tests whether a raw httr response or character vector has a byte order mark (BOM)
+# Tests whether a raw httr response or character vector has a byte order mark (BOM)
 has_bom <- function(resp, encoding="UTF-8") {
   if (inherits(resp, "response")) {
     F <- resp$content[1:4]
@@ -32,7 +40,7 @@ has_bom <- function(resp, encoding="UTF-8") {
   }
 }
 
-#' Remove byte order mark (BOM) from \code{httr::response} object or character vector
+# Remove byte order mark (BOM) from \code{httr::response} object or character vector
 sans_bom <- function(resp) {
 
   if (inherits(resp, "response")) {

README.Rmd

@@ -39,13 +39,15 @@ packageVersion("cdccovidview")
 
 ```
 
-```{r ex-01, fig.width = 10, fig.height = 7}
+```{r ex-01, fig.width = 10, fig.height = 7, cache=TRUE}
 library(cdccovidview)
 library(hrbrthemes)
 library(tidyverse)
 
 hosp <- laboratory_confirmed_hospitalizations()
 
+hosp
+
 c(
   "0-4 yr", "5-17 yr", "18-49 yr", "50-64 yr", "65+ yr", "65-74 yr", "75-84 yr", "85+"
 ) -> age_f
@@ -73,6 +75,46 @@ mutate(hosp, start = mmwr_week_to_date(mmwr_year, mmwr_week)) %>%
 
 ```
 
+### Clinical Labs
+
+```{r ex-02}
+head(clinical_labs())
+```
+
+### Public Health Labs
+
+```{r ex-03}
+head(public_health_labs_national())
+
+head(public_health_labs_regional())
+```
+
+### Emergency Department Visits
+
+```{r ex-04}
+head(nssp_er_visits_national())
+
+head(nssp_er_visits_regional())
+```
+
+### Mortality
+
+```{r ex-05}
+head(mortality_surveillance_data())
+```
+
+```{r ex-06}
+pd <- provisional_death_counts()
+
+head(pd$by_week)
+
+head(pd$by_age)
+
+head(pd$by_state)
+
+head(pd$by_sex)
+```
+
 ## cdccovidview Metrics
 
 ```{r cloc, echo=FALSE}

README.md

@@ -32,8 +32,8 @@ The following functions are implemented:
   - `about`: Display information about the data source
   - `age_groups`: Return age groups used in the surveillance
   - `available_seasons`: Show available seasons
-  - `has_bom`: Tests whether a raw httr response or character vector has
-    a byte order mark (BOM)
+  - `clinical_labs`: Retrieve U.S. Clinical Laboratories Reporting
+    SARS-CoV-2 Test Results to CDC
   - `laboratory_confirmed_hospitalizations`: Retrieve
     Laboratory-Confirmed COVID-19-Associated Hospitalizations
   - `mmwr_week_to_date`: Convert an MMWR year+week or year+week+day to a
@@ -41,8 +41,20 @@ The following functions are implemented:
   - `mmwr_week`: Convert a Date to an MMWR day+week+year
   - `mmwr_weekday`: Convert a Date to an MMWR weekday
   - `mmwrid_map`: MMWR ID to Calendar Mappings
-  - `sans_bom`: Remove byte order mark (BOM) from httr::response object
-    or character vector
+  - `mortality_surveillance_data`: Retrieve NCHS Mortality Surveillance
+    Data
+  - `nssp_er_visits_national`: Retrieve National Syndromic Surveillance
+    Program (NSSP): Emergency Department Visits Percentage of Visits for
+    COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI)
+  - `nssp_er_visits_regional`: Retrieve Regional Syndromic Surveillance
+    Program (NSSP): Emergency Department Visits Percentage of Visits for
+    COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI)
+  - `provisional_death_counts`: Retrieve Provisional Death Counts for
+    Coronavirus Disease (COVID-19)
+  - `public_health_labs_national`: Retrieve National Surveillance of
+    U.S. State and Local Public Health Laboratories Reporting to CDC
+  - `public_health_labs_regional`: Retrieve Regional Surveillance of
+    U.S. State and Local Public Health Laboratories Reporting to CDC
   - `surveillance_areas`: Show network & network catchments
 
 ## Installation
@@ -55,6 +67,8 @@ remotes::install_git("https://git.sr.ht/~hrbrmstr/cdccovidview")
 remotes::install_gitlab("hrbrmstr/cdccovidview")
 # or
 remotes::install_bitbucket("hrbrmstr/cdccovidview")
+# or
+remotes::install_github("hrbrmstr/cdccovidview")
 ```
 
 NOTE: To use the ‘remotes’ install options you will need to have the
@@ -77,6 +91,22 @@ library(tidyverse)
 
 hosp <- laboratory_confirmed_hospitalizations()
 
+hosp
+## # A tibble: 4,590 x 8
+##    catchment      network   year  mmwr_year mmwr_week age_category cumulative_rate weekly_rate
+##    <chr>          <chr>     <chr> <chr>     <chr>     <chr>                  <dbl>       <dbl>
+##  1 Entire Network COVID-NET 2020  2020      10        0-4 yr                   0           0  
+##  2 Entire Network COVID-NET 2020  2020      11        0-4 yr                   0           0  
+##  3 Entire Network COVID-NET 2020  2020      12        0-4 yr                   0           0  
+##  4 Entire Network COVID-NET 2020  2020      13        0-4 yr                   0.3         0.3
+##  5 Entire Network COVID-NET 2020  2020      14        0-4 yr                   0.6         0.3
+##  6 Entire Network COVID-NET 2020  2020      15        0-4 yr                  NA          NA  
+##  7 Entire Network COVID-NET 2020  2020      16        0-4 yr                  NA          NA  
+##  8 Entire Network COVID-NET 2020  2020      17        0-4 yr                  NA          NA  
+##  9 Entire Network COVID-NET 2020  2020      18        0-4 yr                  NA          NA  
+## 10 Entire Network COVID-NET 2020  2020      19        0-4 yr                  NA          NA  
+## # … with 4,580 more rows
+
 c(
   "0-4 yr", "5-17 yr", "18-49 yr", "50-64 yr", "65+ yr", "65-74 yr", "75-84 yr", "85+"
 ) -> age_f
@@ -105,12 +135,142 @@ mutate(hosp, start = mmwr_week_to_date(mmwr_year, mmwr_week)) %>%
 
 <img src="man/figures/README-ex-01-1.png" width="960" />
 
+### Clinical Labs
+
+``` r
+head(clinical_labs())
+##     week num_labs tested tested_pos pct_pos   region        source
+## 1 202011       26   2785        182   0.065 National Clinical Labs
+## 2 202012       41  18494       1149   0.062 National Clinical Labs
+## 3 202013       50  37390       2966   0.079 National Clinical Labs
+## 4 202014       37  36468       2798   0.077 National Clinical Labs
+```
+
+### Public Health Labs
+
+``` r
+head(public_health_labs_national())
+##     week num_labs tested tested_pos pct_pos age_group   region             source
+## 1 202010       73   8049        945   0.117   Overall National Public Health Labs
+## 2 202011       79  32072       3292   0.103   Overall National Public Health Labs
+## 3 202012       80  63369       6494   0.103   Overall National Public Health Labs
+## 4 202013       79  56443       9529   0.169   Overall National Public Health Labs
+## 5 202014       75  65917      12177   0.185   Overall National Public Health Labs
+## 6 202010       73    212          9   0.043    0-4 yr National Public Health Labs
+
+head(public_health_labs_regional())
+##     week num_labs tested tested_pos pct_pos   region             source
+## 1 202010        8    619         46   0.074 Region 1 Public Health Labs
+## 2 202011       17   3208        194   0.061 Region 1 Public Health Labs
+## 3 202012       18   9608        732   0.076 Region 1 Public Health Labs
+## 4 202013       16   4625        700   0.151 Region 1 Public Health Labs
+## 5 202014       15   6123       1611   0.263 Region 1 Public Health Labs
+## 6 202010        5   1381        193   0.140 Region 2 Public Health Labs
+```
+
+### Emergency Department Visits
+
+``` r
+head(nssp_er_visits_national())
+##   week num_fac total_ed_visits visits pct_visits visit_type   region                source year
+## 1   40    3255         2146776  19503      0.009        ili National Emergency Departments 2019
+## 2   41    3249         2106999  20457      0.010        ili National Emergency Departments 2019
+## 3   42    3256         2101358  22515      0.011        ili National Emergency Departments 2019
+## 4   43    3254         2122427  23776      0.011        ili National Emergency Departments 2019
+## 5   44    3295         2087335  25466      0.012        ili National Emergency Departments 2019
+## 6   45    3315         2137854  29948      0.014        ili National Emergency Departments 2019
+
+head(nssp_er_visits_regional())
+##   week num_fac total_ed_visits visits pct_visits visit_type   region                source year
+## 1   40    3255         2146776  19503      0.009        ili Region 1 Emergency Departments 2019
+## 2   41    3249         2106999  20457      0.010        ili Region 1 Emergency Departments 2019
+## 3   42    3256         2101358  22515      0.011        ili Region 1 Emergency Departments 2019
+## 4   43    3254         2122427  23776      0.011        ili Region 1 Emergency Departments 2019
+## 5   44    3295         2087335  25466      0.012        ili Region 1 Emergency Departments 2019
+## 6   45    3315         2137854  29948      0.014        ili Region 1 Emergency Departments 2019
+```
+
+### Mortality
+
+``` r
+head(mortality_surveillance_data())
+##   year week total_deaths deaths pct_deaths    cause   region source
+## 1 2019   40        52452      0          0 COVID-19 National   NCHS
+## 2 2019   41        52860      0          0 COVID-19 National   NCHS
+## 3 2019   42        54129      0          0 COVID-19 National   NCHS
+## 4 2019   43        53914      0          0 COVID-19 National   NCHS
+## 5 2019   44        53980      0          0 COVID-19 National   NCHS
+## 6 2019   45        55468      0          0 COVID-19 National   NCHS
+```
+
+``` r
+pd <- provisional_death_counts()
+
+head(pd$by_week)
+##         week covid_deaths total_deaths percent_expected_deaths pneumonia_deaths pneumonia_and_covid_deaths
+## 2 2020-02-01            0        56402                    0.95             3618                          0
+## 3 2020-02-08            0        56737                    0.95             3601                          0
+## 4 2020-02-15            0        55273                    0.94             3580                          0
+## 5 2020-02-22            0        54859                    0.94             3427                          0
+## 6 2020-02-29            5        54513                    0.95             3464                          3
+## 7 2020-03-07           18        53801                    0.93             3552                         11
+##   all_influenza_deaths_j09_j11
+## 2                          452
+## 3                          483
+## 4                          489
+## 5                          502
+## 6                          573
+## 7                          555
+
+head(pd$by_age)
+##     age_group covid_deaths total_deaths percent_expected_deaths pneumonia_deaths pneumonia_and_covid_deaths
+## 12   All ages         4984       511424                    0.89            36423                       2341
+## 13 Under 1 yr            0         2727                    0.65               19                          0
+## 14     1-4 yr            1          552                    0.76               27                          1
+## 15    5-14 yr            1          809                    0.73               26                          0
+## 16   15-24 yr            6         4638                    0.81               87                          2
+## 17   25-34 yr           46         9624                    0.86              257                         21
+##    all_influenza_deaths_j09_j11
+## 12                         4541
+## 13                            9
+## 14                           26
+## 15                           34
+## 16                           35
+## 17                          106
+
+head(pd$by_state)
+##         state covid_deaths total_deaths percent_expected_deaths pneumonia_deaths pneumonia_and_covid_deaths
+## 25    Alabama           14         9220                    0.87              539                          4
+## 26     Alaska            1          627                    0.75               31                          1
+## 27    Arizona           26        11862                    0.97              748                         13
+## 28   Arkansas            3         5938                    0.92              372                          2
+## 29 California          175        52505                    0.94             4170                         96
+## 30   Colorado           62         7787                    0.98              493                         33
+##    all_influenza_deaths_j09_j11
+## 25                           75
+## 26                            3
+## 27                           95
+## 28                           62
+## 29                          511
+## 30                           77
+
+head(pd$by_sex)
+##        sex covid_deaths total_deaths percent_expected_deaths pneumonia_deaths pneumonia_and_covid_deaths
+## 79    Male         2993       262727                    0.90            19129                       1374
+## 80  Female         1991       248679                    0.89            17294                        967
+## 81 Unknown            0           18                    0.82                0                          0
+##    all_influenza_deaths_j09_j11
+## 79                         2262
+## 80                         2279
+## 81                            0
+```
+
 ## cdccovidview Metrics
 
-| Lang | \# Files |  (%) | LoC |  (%) | Blank lines |  (%) | \# Lines |  (%) |
-| :--- | -------: | ---: | --: | ---: | ----------: | ---: | -------: | ---: |
-| R    |       11 | 0.92 | 200 | 0.85 |          75 | 0.79 |      136 | 0.82 |
-| Rmd  |        1 | 0.08 |  35 | 0.15 |          20 | 0.21 |       30 | 0.18 |
+| Lang | \# Files |  (%) | LoC | (%) | Blank lines | (%) | \# Lines | (%) |
+| :--- | -------: | ---: | --: | --: | ----------: | --: | -------: | --: |
+| R    |       18 | 0.95 | 433 | 0.9 |         145 | 0.8 |      173 | 0.8 |
+| Rmd  |        1 | 0.05 |  47 | 0.1 |          36 | 0.2 |       44 | 0.2 |
 
 ## Code of Conduct
 

man/clinical_labs.Rd

@@ -0,0 +1,17 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/clinical-labs.R
+\name{clinical_labs}
+\alias{clinical_labs}
+\title{Retrieve U.S. Clinical Laboratories Reporting SARS-CoV-2 Test Results to CDC}
+\usage{
+clinical_labs()
+}
+\value{
+data frame
+}
+\description{
+Retrieve U.S. Clinical Laboratories Reporting SARS-CoV-2 Test Results to CDC
+}
+\references{
+\url{https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/reporting-cov2-results.html}
+}

man/has_bom.Rd

@@ -1,11 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/utils.R
-\name{has_bom}
-\alias{has_bom}
-\title{Tests whether a raw httr response or character vector has a byte order mark (BOM)}
-\usage{
-has_bom(resp, encoding = "UTF-8")
-}
-\description{
-Tests whether a raw httr response or character vector has a byte order mark (BOM)
-}

man/mortality_surveillance_data.Rd

@@ -0,0 +1,17 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/mortality.R
+\name{mortality_surveillance_data}
+\alias{mortality_surveillance_data}
+\title{Retrieve NCHS Mortality Surveillance Data}
+\usage{
+mortality_surveillance_data()
+}
+\value{
+data frame
+}
+\description{
+Retrieve NCHS Mortality Surveillance Data
+}
+\references{
+\url{https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nchs-data.html}
+}

man/nssp_er_visits_national.Rd

@@ -0,0 +1,17 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/nssp-cd.R
+\name{nssp_er_visits_national}
+\alias{nssp_er_visits_national}
+\title{Retrieve National Syndromic Surveillance Program (NSSP): Emergency Department Visits Percentage of Visits for COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI)}
+\usage{
+nssp_er_visits_national()
+}
+\value{
+data frame
+}
+\description{
+Retrieve National Syndromic Surveillance Program (NSSP): Emergency Department Visits Percentage of Visits for COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI)
+}
+\references{
+\url{https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nssp-regions.html}
+}

man/nssp_er_visits_regional.Rd

@@ -0,0 +1,17 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/nss-cd-reg.R
+\name{nssp_er_visits_regional}
+\alias{nssp_er_visits_regional}
+\title{Retrieve Regional Syndromic Surveillance Program (NSSP): Emergency Department Visits Percentage of Visits for COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI)}
+\usage{
+nssp_er_visits_regional()
+}
+\value{
+data frame
+}
+\description{
+Retrieve Regional Syndromic Surveillance Program (NSSP): Emergency Department Visits Percentage of Visits for COVID-19-Like Illness (CLI) or Influenza-like Illness (ILI)
+}
+\references{
+\url{https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/nssp-regions.html}
+}

man/provisional_death_counts.Rd

@@ -0,0 +1,21 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/provisional-deaths.R
+\name{provisional_death_counts}
+\alias{provisional_death_counts}
+\title{Retrieve Provisional Death Counts for Coronavirus Disease (COVID-19)}
+\usage{
+provisional_death_counts()
+}
+\value{
+a list with 4 named elements: \code{by_week}, \code{by_age}, \code{by_state}, \code{by_sex}
+}
+\description{
+Retrieve Provisional Death Counts for Coronavirus Disease (COVID-19)
+}
+\note{
+Please see the indicated reference for all the caveats and precise meanings for each field. Also,
+this function used the JSON API (\url{https://data.cdc.gov/resource/hc4f-j6nb.json})
+}
+\references{
+\url{https://data.cdc.gov/api/views/hc4f-j6nb/rows.csv?accessType=DOWNLOAD&bom=true&format=true}
+}

man/public_health_labs_national.Rd

@@ -0,0 +1,17 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/public-health-labs-national.R
+\name{public_health_labs_national}
+\alias{public_health_labs_national}
+\title{Retrieve National Surveillance of U.S. State and Local Public Health Laboratories Reporting to CDC}
+\usage{
+public_health_labs_national()
+}
+\value{
+data frame
+}
+\description{
+Retrieve National Surveillance of U.S. State and Local Public Health Laboratories Reporting to CDC
+}
+\references{
+\url{https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/labs-regions.html}
+}

man/public_health_labs_regional.Rd

@@ -0,0 +1,17 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/public-health-labs-regional.R
+\name{public_health_labs_regional}
+\alias{public_health_labs_regional}
+\title{Retrieve Regional Surveillance of U.S. State and Local Public Health Laboratories Reporting to CDC}
+\usage{
+public_health_labs_regional()
+}
+\value{
+data frame
+}
+\description{
+Retrieve Regional Surveillance of U.S. State and Local Public Health Laboratories Reporting to CDC
+}
+\references{
+\url{https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/04102020/labs-regions.html}
+}

man/sans_bom.Rd

@@ -1,11 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/utils.R
-\name{sans_bom}
-\alias{sans_bom}
-\title{Remove byte order mark (BOM) from \code{httr::response} object or character vector}
-\usage{
-sans_bom(resp)
-}
-\description{
-Remove byte order mark (BOM) from \code{httr::response} object or character vector
-}