ModelSEIRMixing function

Susceptible Exposed Infected Removed model (SEIR) with mixing

ModelSEIRMixing(
  name,
  n,
  prevalence,
  contact_rate,
  transmission_rate,
  incubation_days,
  recovery_rate,
  contact_matrix
)

## S3 method for class 'epiworld_seirmixing'
plot(x, main = get_name(x), ...)

Arguments

• name: String. Name of the virus
• n: Number of individuals in the population.
• prevalence: Double. Initial proportion of individuals with the virus.
• contact_rate: Numeric scalar. Average number of contacts per step.
• transmission_rate: Numeric scalar between 0 and 1. Probability of transmission.
• incubation_days: Numeric scalar. Average number of days in the incubation period.
• recovery_rate: Numeric scalar between 0 and 1. Probability of recovery.
• contact_matrix: Matrix of contact rates between individuals.
• x: Object of class SIRCONN.
• main: Title of the plot
• ...: Currently ignore.

Returns

• The ModelSEIRMixingfunction returns a model of class epiworld_model .

The plot function returns a plot of the SEIRMixing model of class epiworld_model .

Details

The contact_matrix is a matrix of contact rates between entities. The matrix should be of size n x n, where n is the number of entities. This is a row-stochastic matrix, i.e., the sum of each row should be 1.

The initial_states function allows the user to set the initial state of the model. In particular, the user can specify how many of the non-infected agents have been removed at the beginning of the simulation.

Examples

# Start off creating three entities.
# Individuals will be distribured randomly between the three.
e1 <- entity("Population 1", 3e3, as_proportion = FALSE)
e2 <- entity("Population 2", 3e3, as_proportion = FALSE)
e3 <- entity("Population 3", 3e3, as_proportion = FALSE)

# Row-stochastic matrix (rowsums 1)
cmatrix <- c(
  c(0.9, 0.05, 0.05),
  c(0.1, 0.8, 0.1),
  c(0.1, 0.2, 0.7)
) |> matrix(byrow = TRUE, nrow = 3)

N <- 9e3

flu_model <- ModelSEIRMixing(
  name              = "Flu",
  n                 = N,
  prevalence        = 1 / N,
  contact_rate      = 20,
  transmission_rate = 0.1,
  recovery_rate     = 1 / 7,
  incubation_days   = 7,
  contact_matrix    = cmatrix
)

# Adding the entities to the model
flu_model |>
  add_entity(e1) |>
  add_entity(e2) |>
  add_entity(e3)

set.seed(331)
run(flu_model, ndays = 100)
summary(flu_model)
plot_incidence(flu_model)

See Also

epiworld-methods

Other Models: ModelDiffNet(), ModelSEIR(), ModelSEIRCONN(), ModelSEIRD(), ModelSEIRDCONN(), ModelSIR(), ModelSIRCONN(), ModelSIRD(), ModelSIRDCONN(), ModelSIRLogit(), ModelSIRMixing(), ModelSIS(), ModelSISD(), ModelSURV(), epiworld-data