Variance in system dynamics and agent based modelling using the SIR model of infectious diseases

Classical deterministic simulations of epidemiological processes, such as those based on System Dynamics, produce a single result based on a fixed set of input parameters with no variance between simulations. Input parameters are subsequently modified on these simulations using Monte-Carlo methods,...

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Main Authors: Ahmed, Aslam, Greensmith, Julie, Aickelin, Uwe
Format: Conference or Workshop Item
Published: 2012
Online Access:https://eprints.nottingham.ac.uk/2070/
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author Ahmed, Aslam
Greensmith, Julie
Aickelin, Uwe
author_facet Ahmed, Aslam
Greensmith, Julie
Aickelin, Uwe
author_sort Ahmed, Aslam
building Nottingham Research Data Repository
collection Online Access
description Classical deterministic simulations of epidemiological processes, such as those based on System Dynamics, produce a single result based on a fixed set of input parameters with no variance between simulations. Input parameters are subsequently modified on these simulations using Monte-Carlo methods, to understand how changes in the input parameters affect the spread of results for the simulation. Agent Based simulations are able to produce different output results on each run based on knowledge of the local interactions of the underlying agents and without making any changes to the input parameters. In this paper we compare the influence and effect of variation within these two distinct simulation paradigms and show that the Agent Based simulation of the epidemiological SIR (Susceptible, Infectious, and Recovered) model is more effective at capturing the natural variation within SIR compared to an equivalent model using System Dynamics with Monte-Carlo simulation. To demonstrate this effect, the SIR model is implemented using both System Dynamics (with Monte-Carlo simulation) and Agent Based Modelling based on previously published empirical data.
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format Conference or Workshop Item
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institution University of Nottingham Malaysia Campus
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publishDate 2012
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spelling nottingham-20702020-05-04T16:33:11Z https://eprints.nottingham.ac.uk/2070/ Variance in system dynamics and agent based modelling using the SIR model of infectious diseases Ahmed, Aslam Greensmith, Julie Aickelin, Uwe Classical deterministic simulations of epidemiological processes, such as those based on System Dynamics, produce a single result based on a fixed set of input parameters with no variance between simulations. Input parameters are subsequently modified on these simulations using Monte-Carlo methods, to understand how changes in the input parameters affect the spread of results for the simulation. Agent Based simulations are able to produce different output results on each run based on knowledge of the local interactions of the underlying agents and without making any changes to the input parameters. In this paper we compare the influence and effect of variation within these two distinct simulation paradigms and show that the Agent Based simulation of the epidemiological SIR (Susceptible, Infectious, and Recovered) model is more effective at capturing the natural variation within SIR compared to an equivalent model using System Dynamics with Monte-Carlo simulation. To demonstrate this effect, the SIR model is implemented using both System Dynamics (with Monte-Carlo simulation) and Agent Based Modelling based on previously published empirical data. 2012-05-29 Conference or Workshop Item PeerReviewed Ahmed, Aslam, Greensmith, Julie and Aickelin, Uwe (2012) Variance in system dynamics and agent based modelling using the SIR model of infectious diseases. In: Proceedings of the 26th European Conference on Modelling and Simulation (ECMS), 29 May - 1 June 2012, Koblenz, Germany.
spellingShingle Ahmed, Aslam
Greensmith, Julie
Aickelin, Uwe
Variance in system dynamics and agent based modelling using the SIR model of infectious diseases
title Variance in system dynamics and agent based modelling using the SIR model of infectious diseases
title_full Variance in system dynamics and agent based modelling using the SIR model of infectious diseases
title_fullStr Variance in system dynamics and agent based modelling using the SIR model of infectious diseases
title_full_unstemmed Variance in system dynamics and agent based modelling using the SIR model of infectious diseases
title_short Variance in system dynamics and agent based modelling using the SIR model of infectious diseases
title_sort variance in system dynamics and agent based modelling using the sir model of infectious diseases
url https://eprints.nottingham.ac.uk/2070/