R/ggVisualizeIcu.R

In babsim.hospital: Bartz & Bartz Simulation Hospital

#' @title  ggVisualizeIcu Visualisierung der ICU Daten
#'
#' @description Quelle: ICU Daten bundesweit
#'
#' @seealso \code{\link{icudata}}
#'
#' @param data icu data, e.g., \code{\link{icudata}}
#' @param region Region: Gemeindeschluessel, \code{int 05374} fuer OBK oder
#' |code{05315} fuer Koeln oder \code{05911} fuer Bochum.
#'
#' @importFrom padr pad
#' @importFrom stats xtabs
#' @importFrom graphics legend
#' @importFrom graphics par
#' @importFrom ggplot2 xlab
#' @importFrom ggplot2 ylab
#' @importFrom ggplot2 expand_limits
#' @importFrom ggplot2 element_text
#' @importFrom ggplot2 scale_colour_manual
#' @importFrom ggplot2 theme_dark
#' @importFrom ggplot2 annotate
#'
#' @examples
#' require("stats")
#' icu <- babsim.hospital::icudata
#' icuCov <- as.data.frame(xtabs(faelle_covid_aktuell ~ daten_stand, icu))
#' icuCov$daten_stand <- as.Date(icuCov$daten_stand)
#' icuCovBeatm <- as.data.frame(xtabs(faelle_covid_aktuell_beatmet ~ daten_stand, icu))
#' icuCovBeatm$daten_stand <- as.Date(icuCovBeatm$daten_stand)
#' dataICUBeds <- data.frame(
#'   bed = (icuCov$Freq - icuCovBeatm$Freq),
#'   intensiveBedVentilation = icuCovBeatm$Freq,
#'   Day = as.Date(icuCovBeatm$daten_stand)
#' )
#'
#' require("padr")
#' require("stats")
#' require("slider")
#'
#' icu <- babsim.hospital::icudata
#' icu <- pad(icu, interval = "day")
#' icuCov <- as.data.frame(xtabs(faelle_covid_aktuell ~ daten_stand, icu))
#' icuCovBeatm <- as.data.frame(xtabs(faelle_covid_aktuell_beatmet ~ daten_stand, icu))
#' icuCovBett <- as.data.frame(xtabs(betten_belegt ~ daten_stand, icu))
#' plot(icuCov$daten_stand, icuCov$Freq,
#'   type = "p", xlab = "Tag", ylab = "COVID ",
#'   main = "COVID-Faelle in Behandlung im KHaus"
#' )
#' plot(icuCovBeatm$daten_stand, icuCovBeatm$Freq,
#'   type = "p", xlab = "Tag",
#'   ylab = "Patienten", main = "Beatmete COVID-19-Pat. nur invasive Beatmung und ECMO"
#' )
#' plot(icuCovBett$daten_stand, icuCovBett$Freq, type = "l", xlab = "Tag", ylab = "ICU Betten belegt")
#'
#' # Nur Daten des OBK:
#' icu <- babsim.hospital::icudata
#' icu <- icu[icu$gemeindeschluessel == 05374, ]
#' @format data.frame of 9 variables
#' \describe{
#'   \item{bundesland}{ int  1 1 1 1 1 1 1 1 1 1 ...}
#'   \item{gemeindeschluessel}{ int  1001 1002 1003 1004 1051 1053 1054 1055 1056 1057 ...}
#'   \item{anzahl_meldebereiche}{ int  2 3 2 1 1 2 1 3 2 1 ...}
#'   \item{faelle_covid_aktuell}{ int  0 3 5 1 3 1 0 0 5 1 ...}
#'   \item{faelle_covid_aktuell_beatmet}{ int  0 2 5 1 1 1 0 0 4 0 ...}
#'   \item{anzahl_standorte}{ int  2 3 2 1 1 2 1 3 2 1 ...}
#'   \item{betten_frei}{ int  44 113 115 19 54 7 7 18 10 7 ...}
#'   \item{betten_belegt}{ int  38 110 108 19 26 17 3 34 27 5 ...}
#'   \item{daten_stand}{Date, format: "2020-05-01" "2020-05-01" "2020-05-01" "2020-05-01" ... "2020-08-21"}
#' }
#'
#' @return NULL
#'
#' @export

ggVisualizeIcu <- function(data = babsim.hospital::icudata,
                           region = 05315) {
  Freq <- daten_stand <- weekly <- NULL
  ## Landkreis
  if (region > 0 & region > 100) {
    data <- data[data$gemeindeschluessel == region, ]
  }
  ## Bundesland
  if (region > 0 & region < 100) {
    data <- data[data$bundesland == region, ]
  }
  data <- pad(data, interval = "day")
  ## faelle_covid_aktuell include faelle_covid_aktuell_beatmet, so
  ## we substract faelle_covid_aktuell_beatmet
  data$faelle_covid_aktuell <- data$faelle_covid_aktuell - data$faelle_covid_aktuell_beatmet
  dataCov <-
    as.data.frame(xtabs(faelle_covid_aktuell ~ daten_stand, data))
  dataCov$daten_stand <- as.Date(dataCov$daten_stand)
  dataCovBeatm <-
    as.data.frame(xtabs(faelle_covid_aktuell_beatmet ~ daten_stand, data))
  dataCovBeatm$daten_stand <- as.Date(dataCovBeatm$daten_stand)
  dataCovBett <-
    as.data.frame(xtabs(betten_belegt ~ daten_stand, data))
  dataCovBett$daten_stand <- as.Date(dataCovBett$daten_stand)
  meanDateX <- mean.Date(as.Date(dataCov$daten_stand))
  maxCaseNumberpVent <- max(dataCovBeatm$Freq)
  maxCaseNumberpIcu <- max(dataCov$Freq)
  if (maxCaseNumberpIcu < maxCaseNumberpVent) {
    maxCaseNumber <- maxCaseNumberpVent
  } else {
    maxCaseNumber <- maxCaseNumberpIcu
  }

  translator <- golem::get_golem_options("translator")
  if (!is.null(translator)) {
    xlabT <- translator$t("Datum")
    labICU <- translator$t("label2")
    labVent <- translator$t("label3")
    plotLegendTitle <- translator$t("Legende")
    legDaily <- translator$t("legDaily")
    legWeek <- translator$t("legWeek")
  } else {
    xlabT <- "Datum"
    labICU <- "Nicht beatmet"
    labVent <- "Invasiv beatmet"
    plotLegendTitle <- "Legende"
    legDaily <- "Tagesmeldung"
    legWeek <- "7-Tage Durchschnitt"
  }

  dataCov$weekly <-
    slide_dbl(dataCov$Freq, ~ mean(.x), .before = (7 - 1))
  pIcu <- ggplot() +
    geom_point(aes(x = daten_stand, y = Freq, col = legDaily), data = dataCov, size = 0.8) + # , color = "black") +
    geom_line(aes(x = daten_stand, y = weekly, col = legWeek), data = dataCov) + # color ="blue") +
    scale_colour_manual(values = c("blue", "black")) +
    ggplot2::labs(color = plotLegendTitle, title = "DIVI-Intensivregister") +
    xlab(xlabT) +
    ylab(labICU) +
    expand_limits(y = c(0, maxCaseNumber)) +
    theme(plot.title = element_text(hjust = 0.5)) # +

  dataCovBeatm$weekly <-
    slide_dbl(dataCovBeatm$Freq, ~ mean(.x), .before = (7 - 1))
  pVent <- ggplot() +
    geom_point(aes(x = daten_stand, y = Freq, col = legDaily), data = dataCovBeatm, size = 0.8) + # , color ="black") +
    geom_line(aes(x = daten_stand, y = weekly, col = legWeek), data = dataCovBeatm) + # ,color= "green") +
    scale_colour_manual(values = c("green", "black")) +
    xlab(xlabT) +
    ylab(labVent) +
    expand_limits(y = c(0, maxCaseNumber)) +
    theme(plot.title = element_text(hjust = 0.5)) +
    ggplot2::labs(color = plotLegendTitle)

  pl <- list(pIcu, pVent)
}