EpiModel (version 2.5.0)

comp_plot: Plot Compartment Diagram for Epidemic Models

Description

Plots a compartment flow diagram for deterministic compartmental models, stochastic individual contact models, and stochastic network models.

Usage

comp_plot(x, at, digits, ...)
# S3 method for netsim
comp_plot(x, at = 1, digits = 3, ...)
# S3 method for icm
comp_plot(x, at = 1, digits = 3, ...)
# S3 method for dcm
comp_plot(x, at = 1, digits = 3, run = 1, ...)

Arguments

x

An EpiModel object of class dcm, icm, or netsim.

at

Time step for model statistics.

digits

Number of significant digits to print.

...

Additional arguments passed to plot (not currently used).

run

Model run number, for dcm class models with multiple runs (sensitivity analyses).

Details

The comp_plot function provides a visual summary of an epidemic model at a specific time step. The information contained in comp_plot is the same as in the summary functions for a model, but presented graphically as a compartment flow diagram.

For dcm class plots, specify the model run number if the model contains multiple runs, as in a sensitivity analysis. For icm and netsim class plots, the run argument is not used; the plots show the means and standard deviations across simulations at the specified time step.

These plots are currently limited to one-group models for each of the three model classes. That functionality may be expanded in future software releases.

Examples

## Example 1: DCM SIR model with varying act.rate
param <- param.dcm(inf.prob = 0.2, act.rate = 5:7,
                   rec.rate = 1/3, a.rate = 1/90, ds.rate = 1/100,
                   di.rate = 1/35, dr.rate = 1/100)
init <- init.dcm(s.num = 1000, i.num = 1, r.num = 0)
control <- control.dcm(type = "SIR", nsteps = 25, verbose = FALSE)
mod1 <- dcm(param, init, control)
comp_plot(mod1, at = 25, run = 3)

## Example 2: ICM SIR model with 3 simulations
param <- param.icm(inf.prob = 0.2, act.rate = 3, rec.rate = 1/50,
                   a.rate = 1/100, ds.rate = 1/100,
                   di.rate = 1/90, dr.rate = 1/100)
init <- init.icm(s.num = 500, i.num = 1, r.num = 0)
control <- control.icm(type = "SIR", nsteps = 25,
                       nsims = 3, verbose = FALSE)
mod2 <- icm(param, init, control)
comp_plot(mod2, at = 25, digits = 1)