prevalence.icm.bip

This function provides all active model state sizes from
the network at the specified time step, output to a list of
vectors.

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

prevalence.icm.bip 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

Get Epidemic Output from icm Model — prevalence.icm.bip

<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>

prevalence.icm.bip: Get Epidemic Output from icm Model

Description

Usage

Value

Arguments