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Facilitating Understanding, Modeling and Simulation of Infectious Disease Epidemics in the Age of COVID-19.
Rubin, David M; Achari, Shamin; Carlson, Craig S; Letts, Robyn F R; Pantanowitz, Adam; Postema, Michiel; Richards, Xriz L; Wigdorowitz, Brian.
  • Rubin DM; Biomedical Engineering Research Group, School of EIE, University of the Witwatersrand, Johannesburg, South Africa.
  • Achari S; Biomedical Engineering Research Group, School of EIE, University of the Witwatersrand, Johannesburg, South Africa.
  • Carlson CS; Biomedical Engineering Research Group, School of EIE, University of the Witwatersrand, Johannesburg, South Africa.
  • Letts RFR; Biomedical Engineering Research Group, School of EIE, University of the Witwatersrand, Johannesburg, South Africa.
  • Pantanowitz A; Biomedical Engineering Research Group, School of EIE, University of the Witwatersrand, Johannesburg, South Africa.
  • Postema M; Biomedical Engineering Research Group, School of EIE, University of the Witwatersrand, Johannesburg, South Africa.
  • Richards XL; BioMediTech, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
  • Wigdorowitz B; Biomedical Engineering Research Group, School of EIE, University of the Witwatersrand, Johannesburg, South Africa.
Front Public Health ; 9: 593417, 2021.
Article in English | MEDLINE | ID: covidwho-1110365
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Computer Simulation / Communicable Diseases / Pandemics / COVID-19 / Models, Theoretical Limits: Humans Language: English Journal: Front Public Health Year: 2021 Document Type: Article Affiliation country: Fpubh.2021.593417

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Computer Simulation / Communicable Diseases / Pandemics / COVID-19 / Models, Theoretical Limits: Humans Language: English Journal: Front Public Health Year: 2021 Document Type: Article Affiliation country: Fpubh.2021.593417