SimInf (version 11.1.0)

events_SIS: Example event data for the SIS model with cattle herds

Description

Dataset containing 466,692 scheduled events for a population of 1,600 cattle herds over 1,460 days (4 years). Demonstrates how demographic and movement events affect SIS dynamics in a cattle disease context.

Usage

events_SIS()

Value

A data.frame with columns:

event

Event type: "exit", "enter", or "extTrans".

time

Day when event occurs (1-1460).

node

Affected herd identifier (1-1600).

dest

Destination herd for external transfer events.

n

Number of cattle affected.

proportion

0. Not used in this example.

select

Model compartment to affect (see SimInf_events).

shift

0. Not used in this example.

Details

The event data contains three types of scheduled events that affect cattle herds (nodes):

Exit

Deaths or removal of cattle from a herd (n = 182,535). These events decrease the population in both susceptible and infected compartments.

Enter

Births or introduction of cattle to a herd (n = 182,685). These events add susceptible cattle to herds.

External transfer

Movement of cattle between herds (n = 101,472). These events transfer cattle from one herd to another, potentially spreading disease across the herd network. Either susceptible or infected animals may be transferred.

The select column in the returned data frame is mapped to the columns of the internal select matrix:

• select = 1 corresponds to Enter events, targeting the Susceptible (S) compartment.

• select = 2 corresponds to Exit and External Transfer events, targeting all compartments (S and I).

Events are distributed across all 1,600 herds over the 4-year period. These are synthetic data generated to illustrate how to incorporate scheduled events (such as births, deaths, and movements) into a compartment model in the SimInf framework.

See Also

u0_SIS for the corresponding initial cattle population, SIS for creating SIS models with these events, and SimInf_events for event structure details

Examples

## For reproducibility, call the set.seed() function and specify the
## number of threads to use. To use all available threads, remove the
## set_num_threads() call.
set.seed(123)
set_num_threads(1)

## Create an 'SIS' model with 1600 cattle herds (nodes) and initialize
## it to run over 4*365 days. Add one infected animal to the first
## herd to seed the outbreak. Define 'tspan' to record the state of
## the system at daily time-points. Load scheduled events for the
## population of nodes with births, deaths and between-node movements
## of individuals.
u0 <- u0_SIS()
u0$I[1] <- 1
model <- SIS(
    u0     = u0,
    tspan  = seq(from = 1, to = 4*365, by = 1),
    events = events_SIS(),
    beta   = 0.16,
    gamma  = 0.01
)

## Display the number of cattle affected by each event type per day.
plot(events(model))

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

## Plot the median and interquartile range of the number of
## susceptible and infected individuals.
plot(result)

## Plot the trajectory for the first herd.
plot(result, index = 1)

## Summarize the trajectory. The summary includes the number of events
## by event type.
summary(result)