SimInf (version 11.1.0)

events_SEIR: Example event data for the SEIR 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 SEIR dynamics in a cattle disease context.

Usage

events_SEIR()

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 and affect all disease compartments proportionally.

Enter

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

External transfer

Movement of cattle between herds (n = 101,472). These events transfer cattle from one herd to another, potentially facilitating between-herd disease transmission.

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.

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_SEIR for the corresponding initial cattle population, SEIR for creating SEIR 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 a 'SEIR' model with 1600 cattle herds (nodes) and initialize
## it to run over 4*365 days. Add ten exposed animals to the first
## herd. Define 'tspan' to record the state of the system at weekly
## time-points. Load scheduled events for the population of nodes with
## births, deaths and between-node movements of individuals.
u0 <- u0_SEIR()
u0$E[1] <- 10
model <- SEIR(
    u0      = u0,
    tspan   = seq(from = 1, to = 4*365, by = 7),
    events  = events_SEIR(),
    beta    = 0.16,
    epsilon = 0.25,
    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, exposed, infected and recovered 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)