Literature DB >> 33643988

Facilitating Understanding, Modeling and Simulation of Infectious Disease Epidemics in the Age of COVID-19.

David M Rubin1, Shamin Achari1, Craig S Carlson1, Robyn F R Letts1, Adam Pantanowitz1, Michiel Postema1,2, Xriz L Richards1, Brian Wigdorowitz1.   

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.
Copyright © 2021 Rubin, Achari, Carlson, Letts, Pantanowitz, Postema, Richards and Wigdorowitz.

Entities:  

Keywords:  engagement with COVID-19 models; epidemic modeling; mechanistic epidemiology; system dynamics; undergraduate teaching

Year:  2021        PMID: 33643988      PMCID: PMC7907159          DOI: 10.3389/fpubh.2021.593417

Source DB:  PubMed          Journal:  Front Public Health        ISSN: 2296-2565


  16 in total

1.  Epidemic Propagation With Positive and Negative Preventive Information in Multiplex Networks.

Authors:  Zhishuang Wang; Chengyi Xia; Zengqiang Chen; Guanrong Chen
Journal:  IEEE Trans Cybern       Date:  2021-02-17       Impact factor: 11.448

2.  A major epidemic of chikungunya virus infection on Reunion Island, France, 2005-2006.

Authors:  Philippe Renault; Jean-Louis Solet; Daouda Sissoko; Elsa Balleydier; Sophie Larrieu; Laurent Filleul; Christian Lassalle; Julien Thiria; Emmanuelle Rachou; Henriette de Valk; Daniele Ilef; Martine Ledrans; Isabelle Quatresous; Philippe Quenel; Vincent Pierre
Journal:  Am J Trop Med Hyg       Date:  2007-10       Impact factor: 2.345

3.  How to make epidemiological training infectious.

Authors:  Steve E Bellan; Juliet R C Pulliam; James C Scott; Jonathan Dushoff
Journal:  PLoS Biol       Date:  2012-04-03       Impact factor: 8.029

4.  Learning infectious disease epidemiology in a modern framework.

Authors:  Andreas Handel
Journal:  PLoS Comput Biol       Date:  2017-10-19       Impact factor: 4.475

5.  An open-data-driven agent-based model to simulate infectious disease outbreaks.

Authors:  Elizabeth Hunter; Brian Mac Namee; John Kelleher
Journal:  PLoS One       Date:  2018-12-19       Impact factor: 3.240

6.  How and When to End the COVID-19 Lockdown: An Optimization Approach.

Authors:  Thomas Rawson; Tom Brewer; Dessislava Veltcheva; Chris Huntingford; Michael B Bonsall
Journal:  Front Public Health       Date:  2020-06-10

7.  A mathematical model of chikungunya dynamics and control: the major epidemic on Réunion Island.

Authors:  Laith Yakob; Archie C A Clements
Journal:  PLoS One       Date:  2013-03-06       Impact factor: 3.240

8.  COVID-19 Trend Estimation in the Elderly Italian Region of Sardinia.

Authors:  Mariangela Valentina Puci; Federica Loi; Ottavia Eleonora Ferraro; Stefano Cappai; Sandro Rolesu; Cristina Montomoli
Journal:  Front Public Health       Date:  2020-04-24

9.  Forecasting the daily and cumulative number of cases for the COVID-19 pandemic in India.

Authors:  Subhas Khajanchi; Kankan Sarkar
Journal:  Chaos       Date:  2020-07       Impact factor: 3.642

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