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i think full coverage

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boB Rudis 7 months ago
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20 changed files with 683 additions and 33 deletions
  1. +7
    -0
      NAMESPACE
  2. +24
    -0
      R/clinical-labs.R
  3. +47
    -0
      R/mortality.R
  4. +57
    -0
      R/nss-cd-reg.R
  5. +43
    -0
      R/nssp-cd.R
  6. +62
    -0
      R/provisional-deaths.R
  7. +57
    -0
      R/public-health-labs-national.R
  8. +42
    -0
      R/public-health-labs-regional.R
  9. +10
    -2
      R/utils.R
  10. +43
    -1
      README.Rmd
  11. +168
    -8
      README.md
  12. +17
    -0
      man/clinical_labs.Rd
  13. +0
    -11
      man/has_bom.Rd
  14. +17
    -0
      man/mortality_surveillance_data.Rd
  15. +17
    -0
      man/nssp_er_visits_national.Rd
  16. +17
    -0
      man/nssp_er_visits_regional.Rd
  17. +21
    -0
      man/provisional_death_counts.Rd
  18. +17
    -0
      man/public_health_labs_national.Rd
  19. +17
    -0
      man/public_health_labs_regional.Rd
  20. +0
    -11
      man/sans_bom.Rd

+ 7
- 0
NAMESPACE View File

@@ -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)


+ 24
- 0
R/clinical-labs.R View File

@@ -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),])

}

+ 47
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R/mortality.R View File

@@ -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),])

}

+ 57
- 0
R/nss-cd-reg.R View File

@@ -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)

}

+ 43
- 0
R/nssp-cd.R View File

@@ -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),])

}

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R/provisional-deaths.R View File

@@ -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)
)

}

+ 57
- 0
R/public-health-labs-national.R View File

@@ -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),]

}

+ 42
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R/public-health-labs-regional.R View File

@@ -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)

}

+ 10
- 2
R/utils.R View File

@@ -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")) {


+ 43
- 1
README.Rmd View File

@@ -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}


+ 168
- 8
README.md View File

@@ -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



+ 17
- 0
man/clinical_labs.Rd View File

@@ -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}
}

+ 0
- 11
man/has_bom.Rd View File

@@ -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)
}

+ 17
- 0
man/mortality_surveillance_data.Rd View File

@@ -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}
}

+ 17
- 0
man/nssp_er_visits_national.Rd View File

@@ -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}
}

+ 17
- 0
man/nssp_er_visits_regional.Rd View File

@@ -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}
}

+ 21
- 0
man/provisional_death_counts.Rd View File

@@ -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}
}

+ 17
- 0
man/public_health_labs_national.Rd View File

@@ -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}
}

+ 17
- 0
man/public_health_labs_regional.Rd View File

@@ -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}
}

+ 0
- 11
man/sans_bom.Rd View File

@@ -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
}

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