Facilitating understanding, modeling and simulation of infectious disease epidemics in the age of COVID-19

David M. Rubin, Shamin Achari, Craig S. Carlson, Robyn F.R. Letts, Adam Pantanowitz, Michiel Postema, Xriz L. Richards, Brian Wigdorowitz

    Research output: Contribution to journalArticleScientificpeer-review

    15 Citations (Scopus)
    15 Downloads (Pure)

    Abstract

    Interest in the mathematical modeling of infectious diseases has increased due to the COVID-19 pandemic. However, many medical students do not have the required background in coding or mathematics to engage optimally in this approach. System dynamics is a methodology for implementing mathematical models as easy-to-understand stock-flow diagrams. Remarkably, creating stock-flow diagrams is the same process as creating the equivalent differential equations. Yet, its visual nature makes the process simple and intuitive. We demonstrate the simplicity of system dynamics by applying it to epidemic models including a model of COVID-19 mutation. We then discuss the ease with which far more complex models can be produced by implementing a model comprising eight differential equations of a Chikungunya epidemic from the literature. Finally, we discuss the learning environment in which the teaching of the epidemic modeling occurs. We advocate the widespread use of system dynamics to empower those who are engaged in infectious disease epidemiology, regardless of their mathematical background.
    Original languageEnglish
    Article number593417
    JournalFrontiers in Public Health
    Volume9
    DOIs
    Publication statusPublished - 2021
    Publication typeA1 Journal article-refereed

    Keywords

    • engagement with COVID-19 models
    • epidemic modeling
    • mechanistic epidemiology
    • system dynamics
    • undergraduate teaching

    Publication forum classification

    • Publication forum level 1

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