hybridModels
An R Package for the Stochastic Simulation of Disease Spreading in Dynamic Networks
Simulates stochastic hybrid models for transmission of infectious
diseases in dynamic networks. It is a metapopulation model in which each
node in the network is a sub-population and disease spreads within nodes
and among them, combining two approaches: stochastic simulation algorithm
(
Hybrid Models
Version: 0.3.8
hybridModels is an R package to simulate customizable stochastic hybrid models for transmission of diseases in dynamic networks.
Installation
It is possible to use one of the options below to install the package:
- Using the function install.packages() for stable versions from CRAN (https://CRAN.R-project.org/package=hybridModels).
From CRAN
install.packages("hybridModels")
- Making use of the devtools package (Hadley Wickham and Winston Chang (2015). devtools: Tools to Make Developing R Packages Easier. R package version 1.13.5 or higher, http://CRAN.R-project.org/package=devtools).
Through github and devtools
library(devtools)
install_github("fernandosm/hybridModels")
Features
The current version runs:
-
Customizable hybrid model in dynamic networks in which migration is the link type between nodes. Using this link type allows user to create rules that compute the number of individuals that emigrate and the probability weight of a individual of a certain state to emigrate.
-
Customizable hybrid model in dynamic networks in which influence is the link type between nodes.
-
Find nodes of contact chains (outgoing and ingoing).
-
Calculate contact chains' size (outgoing and ingoing).
-
SI hybrid model without explicit demographics (migration link). It is assumed that the total number of individuals is constant and animals migrate between premises.
-
SI hybrid model without explicit demographics (influence link). It is assumed that the total number of individuals is constant and animals do not migrate between premises, they influence other premises.
More Information and Examples
hybridModels: An R Package for the Stochastic Simulation of Disease Spreading in Dynamic Networks
Jason Ardila Galvis (email: [email protected]) studies disease spread among animals and, as an example, he created an animation (click on the image below) based on results generated by hybridModels package. In this example he made use of fictitious data.
