hybridModels: An R Package for the Stochastic Simulation of Disease Spreading in Dynamic Networks
Dublin Core
Title
hybridModels: An R Package for the Stochastic Simulation of Disease Spreading in Dynamic Networks
Subject
modeling, dynamic networks, epidemic, stochastic simulation, R
Description
Disease spreading simulations are traditionally performed using coupled differential
equations. However, in the setting of metapopulations, most of the solutions provided by
this method do not account for the dynamic topography of subpopulations. Conversely,
the alternative approach of individual-based modeling (IBM) may add computational cost
and complexity.
Hybrid models allow for the study of disease spreading because they combine both
aforementioned approaches by separating them across different scales: a local scale that
addresses subpopulation dynamics using coupled differential equations and a global scale
that addresses the contact between these subpopulations using IBM.
We present a simple way of simulating the spread of disease in dynamic networks using the high-level statistical computational language R and the hybridModels package.
We built four examples using disease spread models at the local scale in several different
networks: an animal movement network; a three-node network, whose model solution
using a stochastic simulation algorithm is compared with the ordinary differential equations approach; the commuting of individuals between patches, which we compare with
the permanent migration of individuals; and the commuting of individuals within the
metropolitan area of São Paulo
equations. However, in the setting of metapopulations, most of the solutions provided by
this method do not account for the dynamic topography of subpopulations. Conversely,
the alternative approach of individual-based modeling (IBM) may add computational cost
and complexity.
Hybrid models allow for the study of disease spreading because they combine both
aforementioned approaches by separating them across different scales: a local scale that
addresses subpopulation dynamics using coupled differential equations and a global scale
that addresses the contact between these subpopulations using IBM.
We present a simple way of simulating the spread of disease in dynamic networks using the high-level statistical computational language R and the hybridModels package.
We built four examples using disease spread models at the local scale in several different
networks: an animal movement network; a three-node network, whose model solution
using a stochastic simulation algorithm is compared with the ordinary differential equations approach; the commuting of individuals between patches, which we compare with
the permanent migration of individuals; and the commuting of individuals within the
metropolitan area of São Paulo
Creator
Fernando S. Marques
Source
https://www.jstatsoft.org/article/view/v094i06
Publisher
Universidade de São Paulo
Date
June 2020
Contributor
Fajar bagus W
Format
PDF
Language
Inggris
Type
Text
Files
Collection
Citation
Fernando S. Marques, “hybridModels: An R Package for the Stochastic Simulation of Disease Spreading in Dynamic Networks,” Repository Horizon University Indonesia, accessed May 14, 2025, https://repository.horizon.ac.id/items/show/8139.