recovery.icm

This function simulates recovery from the infected state
either to a distinct recovered state (SIR model type) or back
to a susceptible state (SIS model type), for use in
<code>icm</code>.

internal

Tools for simulating mathematical models of infectious disease dynamics.
Epidemic model classes include deterministic compartmental models, stochastic
individual-contact models, and stochastic network models. Network models use the
robust statistical methods of exponential-family random graph models (ERGMs)
from the Statnet suite of software packages in R. Standard templates for epidemic
modeling include SI, SIR, and SIS disease types. EpiModel features an API for
extending these templates to address novel scientific research aims. Full
methods for EpiModel are detailed in Jenness et al. (2018, <doi:10.18637/jss.v084.i08>).

Samuel Jenness

EpiModel

Mathematical Modeling of Infectious Disease Dynamics

Steven M. Goodreau

Martina Morris

Adrien Le Guillou

Chad Klumb

Skye Bender-deMoll

recovery.icm function

<dl><dt>dat</dt>
<dd>Main <code>icm_dat</code> class data object passed through <code>icm</code>
simulations.</dd>
<dt>at</dt>
<dd>Current time step.</dd></dl>

Arguments

Recovery: icm Module — recovery.icm

<dl>

<dt>dat</dt>
<dd>Main <code>icm_dat</code> class data object passed through <code>icm</code>
simulations.</dd>


<dt>at</dt>
<dd>Current time step.</dd>

</dl>

recovery.icm: Recovery: icm Module

Description

Usage

Value

Arguments