Get UK daily cases by NHS region

Get UK regional cases.

get_uk_nhs_region_cases()

Value

A dataframe of case counts in English NHS regions

Examples

get_uk_nhs_region_cases
#> function () 
#> {
#>     warning("The soource data for this function is no longer updated. Try get_uk_regional_cases for similar data")
#>     path <- "https://raw.githubusercontent.com/emmadoughty/Daily_COVID-19/8a0ea87f40edf746519afdb4d1e7ed95c816df1e/Data/COVID19_cum.csv"
#>     cases <- readr::read_csv(file = path)
#>     locations <- c("London", "South East", "South West", "East of England", 
#>         "Midlands", "North East and Yorkshire", "North West", 
#>         "Ayrshire and Arran", "Borders", "Dumfries and Galloway", 
#>         "Fife", "Forth Valley", "Grampian", "Greater Glasgow and Clyde", 
#>         "Highland", "Lanarkshire", "Lothian", "Shetland", "Tayside", 
#>         "Wales", "Northern Ireland", "Orkney", "Western Isles")
#>     cases_nhs <- cases %>% dplyr::mutate(date = stringr::str_replace_all(Date, 
#>         pattern = "\\.", replacement = "/")) %>% dplyr::select(-Date) %>% 
#>         tidyr::gather("UTLA", "confirm", -date) %>% tidyr::drop_na(date, 
#>         confirm) %>% dplyr::mutate(UTLA = stringr::str_replace_all(UTLA, 
#>         "_", " "), confirm = confirm %>% stringr::str_squish() %>% 
#>         as.numeric) %>% dplyr::filter(UTLA %in% c("London", "South East", 
#>         "South West", "East of England", "Midlands", "North East and Yorkshire", 
#>         "North West", "Ayrshire and Arran", "Borders", "Dumfries and Gallow", 
#>         "Fife", "Forth Valley", "Grampian", "Greater Glasgow and Clyde", 
#>         "Highlands", "Lanarkshire", "Lothian", "Shetland", "Tayside", 
#>         "Wales", "Northern Ireland")) %>% dplyr::mutate(UTLA = dplyr::recode(UTLA, 
#>         `Dumfries and Gallow` = "Dumfries and Galloway", Highlands = "Highland"), 
#>         date = lubridate::dmy(date)) %>% tidyr::complete(UTLA = locations, 
#>         date = seq(min(date), max(date), by = "day")) %>% dplyr::mutate(confirm = tidyr::replace_na(confirm, 
#>         0))
#>     cases_nhs <- cases_nhs %>% dplyr::select(region = UTLA, total_cases = confirm, 
#>         date) %>% dplyr::arrange(date) %>% dplyr::group_by(region) %>% 
#>         dplyr::mutate(index = 1:dplyr::n(), cases = total_cases - 
#>             ifelse(index == 1, 0, dplyr::lag(total_cases))) %>% 
#>         dplyr::ungroup() %>% dplyr::select(-index, -total_cases) %>% 
#>         dplyr::mutate(cases = ifelse(cases < 0, 0, cases))
#>     return(cases_nhs)
#> }
#> <bytecode: 0x7ff8ebcb9240>
#> <environment: namespace:NCoVUtils>

if (FALSE) {
uk_shp <- readRDS("uk_shp.rds")
cases <- NCoVUtils::get_uk_regional_cases()
cases <- cases[1:23,]
uk_shp %>%
dplyr::full_join(cases, by = "region") %>%
 ggplot2::ggplot(ggplot2::aes(fill = cases)) + ggplot2::geom_sf()
}