Seed the initial infections, and other compartments, in a spatial simulation

The Moore neighbourhood around the locations given in the seed data is affected with the initial values recorded in the provided seed data. The infected and exposed compartments are cast in a Moore neighbourhood of cells about the geographical coordinates recorded locations, while other compartments are cast directly into the cell corresponding exactly to the location, not a Moore neighbourhood.

Usage

castSeedDataQueensNeighbourhood(layers, seedData, neighbourhood.order)

Arguments

layers

The SpatRaster object with layers Susceptible, Vaccinated, Exposed, Infected, Recovered, and Dead.

seedData

a dataframe like the following example; the compartment columns are the initial values.

  Location Latitude Longitude Vaccinated Exposed Infected Recovered Dead
  Beni     0.49113  29.47306  0          24      12       0         4
  Butembo  0.140692 29.335014 0          0       0        0         0
  Mabalako 0.461257 29.210687 0          0       0        0         0
  Mandima  1.35551  29.08173  0          0       0        0         0

neighbourhood.order

The order of the queen's neighbourhood over which to distribute the Exposed and Infected intial state variable; zero is no neighbourhood, and corresponds to only the same cell where the queen already is. Higher orders follow the simple formula (2 * x + 1)^2 to determine the number of cells over which to evenly disperse the exposed and infected state variables. All other state variables are placed directly in the grid cell corresponding to the health zone.

Value

the input layers SpatRaster, modified with the seeded data.

Details

The Moore neighbourhood is calculated using a simple arithmetical algorithm.

Author

Bryce Carson

Examples

subregionsSpatVector <- terra::vect(
  system.file(
    "extdata",
    ## COD: Nord-Kivu and Ituri (Democratic Republic of Congo)
    "subregionsSpatVector",
    package = "spatialEpisim.foundation",
    mustWork = TRUE
  )
)
susceptibleSpatRaster <- terra::rast(
  system.file(
    "extdata",
    "susceptibleSpatRaster.tif", # Congo population
    package = "spatialEpisim.foundation",
    mustWork = TRUE
  )
)
layers <- getSVEIRD.SpatRaster(subregionsSpatVector,
                               susceptibleSpatRaster,
                               aggregationFactor = 10)
data(initialInfections.fourCities, package = "spatialEpisim.foundation")
terra::plot(castSeedDataQueensNeighbourhood(layers, initialInfections.fourCities, 0)$Susceptible)

terra::plot(castSeedDataQueensNeighbourhood(layers, initialInfections.fourCities, 1)$Susceptible)