SEIR-class

<p>Class to handle the SEIR <code><a rd-options="" href="/link/SimInf_model?package=SimInf&version=6.2.0" data-mini-rdoc="SimInf::SimInf_model">SimInf_model</a></code>.</p>

Provides an efficient and very flexible framework to
conduct data-driven epidemiological modeling in realistic large
scale disease spread simulations. The framework integrates
infection dynamics in subpopulations as continuous-time Markov
chains using the Gillespie stochastic simulation algorithm and
incorporates available data such as births, deaths and movements
as scheduled events at predefined time-points. Using C code for
the numerical solvers and 'OpenMP' (if available) to divide work
over multiple processors ensures high performance when simulating
a sample outcome. One of our design goals was to make the package
extendable and enable usage of the numerical solvers from other R
extension packages in order to facilitate complex epidemiological
research. The package contains template models and can be extended
with user-defined models.

Stefan Widgren

SimInf

A Framework for Data-Driven Stochastic Disease Spread
Simulations

Robin Eriksson

Stefan Engblom

Pavol Bauer

Attractive Chaos 

SEIR-class function

<p>Class to handle the SEIR <code><a rd-options='' href='SimInf_model'>SimInf_model</a></code>.</p>

SEIR-class: Definition of the ‘SEIR’ model

Description

Arguments