u0_SISe3 {SimInf} | R Documentation

## Example data to initialize the ‘SISe3’ model

### Description

Example data to initialize a population of 1600 nodes and demonstrate the `SISe3` model.

### Usage

    data(u0_SISe3)

### Format

A `data.frame`

### Details

A `data.frame` with the number of individuals in the ‘S_1’, ‘S_2’, ‘S_3’, ‘I_1’, ‘I_2’ and ‘I_3’ compartments in 1600 nodes. Note that the ‘I_1’, ‘I_2’ and ‘I_3’ compartments are zero.

### Examples

    ## Create an 'SISe3' model with 1600 nodes and initialize it to
    ## run over 4*365 days and record data at weekly time-points.

    ## Load the initial population and add ten infected individuals to
    ## I_1 in the first node.
    u0 <- u0_SISe3
    u0$I_1[1] <- 10

    ## Define 'tspan' to run the simulation over 4*365 and record the
    ## state of the system at weekly time-points.
    tspan <- seq(from = 1, to = 4*365, by = 7)

    ## Load scheduled events for the population of nodes with births,
    ## deaths and between-node movements of individuals.
    events <- events_SISe3

    ## Create a 'SISe3' model
    model <- SISe3(u0 = u0, tspan = tspan, events = events,
                   phi = rep(0, nrow(u0)), upsilon_1 = 1.8e-2,
                   upsilon_2 = 1.8e-2, upsilon_3 = 1.8e-2,
                   gamma_1 = 0.1, gamma_2 = 0.1, gamma_3 = 0.1,
                   alpha = 1, beta_t1 = 1.0e-1, beta_t2 = 1.0e-1,
                   beta_t3 = 1.25e-1, beta_t4 = 1.25e-1, end_t1 = 91,
                   end_t2 = 182, end_t3 = 273, end_t4 = 365, epsilon = 0)

    ## Run the model to generate a single stochastic trajectory.
    result <- run(model, threads = 1)

    ## Summarize trajectory
    summary(result)

    ## Plot the proportion of nodes with at least one infected
    ## individual.
    plot(prevalence(result, I_1 + I_2 + I_3 ~ ., "nop"), type = "l")

[Package SimInf version 6.3.0 Index]