control.dcm: Control Settings for Deterministic Compartmental Models

In EpiModel: Mathematical Modeling of Infectious Disease Dynamics

Control Settings for Deterministic Compartmental Models

Description

Sets the controls for deterministic compartmental models simulated with dcm().

Usage

control.dcm(
  type,
  nsteps,
  dt = 1,
  odemethod = "lsoda",
  dede = FALSE,
  new.mod = NULL,
  sens.param = TRUE,
  print.mod = FALSE,
  verbose = FALSE,
  ode.args = NULL,
  solver = NULL,
  ...
)

Arguments

type	Disease type to be modeled, with the choice of "SI" for Susceptible-Infected diseases, "SIR" for Susceptible-Infected-Recovered diseases, and "SIS" for Susceptible-Infected-Susceptible diseases.
nsteps	Number of time steps to solve the model over or vector of times to solve the model over. If the number of time steps, then this must be a positive integer of length 1.
dt	Time unit for model solutions, with the default of 1. Model solutions for fractional time steps may be obtained by setting this to a number between 0 and 1.
odemethod	Ordinary differential equation (ODE) integration method, with the default of "lsoda" (see deSolve::ode for other options).
dede	If TRUE, use the delayed differential equation solver, which allows for time-lagged variables.
new.mod	If not running a base model type, a function with a new model to be simulated (see details).
sens.param	If TRUE, evaluate arguments in parameters or initial conditions with length greater than 1 as sensitivity analyses, with one model run per value. If FALSE, one model will be run with parameters and initial conditions of arbitrary length (the model may error unless the model function is designed to accommodate vectors).
print.mod	If TRUE, print the model form to the console.
verbose	If TRUE, print model progress to the console.
ode.args	A named list of further arguments passed to deSolve::ode (or deSolve::dede with dede = TRUE), such as the tolerances rtol and atol or the maximum step hmax.
solver	An optional function that solves the model in place of deSolve::ode, called as solver(y, times, func, parms, control) (see details).
...	additional control settings passed to model.

Details

control.dcm sets the required control settings for any deterministic compartmental models solved with the dcm() function. Controls are required for both base model types and original models. For all base models, the type argument is a necessary parameter and it has no default.

Value

An EpiModel object of class control.dcm.

ODE Solver

As of EpiModel 2.5.5, the default ODE solver was changed from "rk4" (fixed-step Runge-Kutta 4) to "lsoda" (adaptive step-size). The "lsoda" method automatically adjusts its internal step size, providing numerical stability across a wide range of parameter values. The fixed-step "rk4" solver could produce numerical instability (negative compartment sizes, NaN values) for models with high transmission rates or stiff dynamics. Users who require the previous behavior can set odemethod = "rk4" explicitly.

New Model Functions

The form of the model function for base models may be displayed with the print.mod argument set to TRUE. In this case, the model will not be run. These model forms may be used as templates to write original model functions.

These new models may be input and solved with dcm() using the new.mod argument, which requires as input a model function.

Custom Solvers

By default, dcm() solves the model with one call to deSolve::ode over all time steps, passing odemethod and any ode.args. A model whose rates change abruptly (an intervention that starts on a given day, for example) is solved more accurately by restarting the solver at each change. The solver argument allows this, or any other solver, for base and new models alike. It is called with the initial state y, the solution times times, the model function func, the parameters parms, and the control settings control, and must return a matrix or data frame with time in the first column and one named column per state variable, as ode does. Any further columns it returns, such as derived outputs, are kept as model outputs. Columns whose names contain .flow are converted from cumulative counts to counts per time step after the solver returns, as for the default solver.

See Also

Use param.dcm() to specify model parameters and init.dcm() to specify the initial conditions. Run the parameterized model with dcm().

EpiModel documentation built on Oct. 16, 2026, 5:07 p.m.