swash (version 1.1.0)

plot_regions: Plots of Regional Infections Over Time

Description

Plots regional infection curves in \(N\) plots for \(N\) regions.

Usage

plot_regions(
  object, 
  col = "red", 
  scale = FALSE, 
  normalize_by_col = NULL, 
  normalize_factor = 1
  )

Value

Plot, only no returned value

Arguments

object

object of class sbm

col

Color of line plot

scale

Set y axis of the plots uniformly based on the maximum value across all regions? (boolean, default: FALSE)

normalize_by_col

Normalize infection numbers by stating a column in the input data frame (e.g., regional population)

normalize_factor

Multiply density/incidence with a factor (say, 100,000 inhabitants)

Author

Thomas Wieland

Details

Plots regional infection curves in \(N\) plots for \(N\) regions, with the number of columns equals 4 and the number of rows is calculated based the size of \(N\).

Examples

data(COVID19Cases_geoRegion)
# Get SWISS COVID19 cases at NUTS 3 level

COVID19Cases_geoRegion <- 
  COVID19Cases_geoRegion[!COVID19Cases_geoRegion$geoRegion %in% c("CH", "CHFL"),]
# Exclude CH = Switzerland total and CHFL = Switzerland and Liechtenstein total

COVID19Cases_geoRegion <- 
  COVID19Cases_geoRegion[COVID19Cases_geoRegion$datum <= "2020-05-31",]
# Extract first COVID-19 wave

CH_covidwave1 <- 
  swash (
    data = COVID19Cases_geoRegion, 
    col_cases = "entries", 
    col_date = "datum", 
    col_region = "geoRegion"
    )
# Swash-Backwash Model for Swiss COVID19 cases
# Spatial aggregate: NUTS 3 (cantons)

plot_regions(CH_covidwave1)
# Plot of regional infections