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Enhancing Covid-19 virus spread modeling using an activity travel model

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  • Nguyen, Tri K.
  • Hoang, Nam H.
  • Currie, Graham
  • Vu, Hai L.

Abstract

Coronavirus 2019 (COVID-19) and its variants are still spreading rapidly with deadly consequences and profound impacts on the global health and world economy. Without a suitable vaccine, mobility restriction has been the most effective method so far to prevent its spreading and avoid overwhelming the heath system of the affected country. The compartmental model SIR (or Susceptible, Infected, and Recovered) is the most popular mathematical model used to predict the course of the COVID-19 pandemic in order to plan the control actions and mobility restrictions against its spreading. A major limitation of this model in relation to modeling the spreading of COVID-19, and the mobility limitation strategy, is that the SIR model does not include mobility or take into account changes in mobility within its structure. This paper develops and tests a new hybrid SIR model; SIR-M which is integrated with an urban activity travel model to explore how it might improve the prediction of pandemic course and the testing of mobility limitation strategies in managing virus spread. The paper describes the enhanced methodology and tests a range of mobility limitation strategies on virus spread outcomes. Implications for policy and research futures are suggested.

Suggested Citation

  • Nguyen, Tri K. & Hoang, Nam H. & Currie, Graham & Vu, Hai L., 2022. "Enhancing Covid-19 virus spread modeling using an activity travel model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 161(C), pages 186-199.
    • Handle: RePEc:eee:transa:v:161:y:2022:i:c:p:186-199
    DOI: 10.1016/j.tra.2022.05.002
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    References listed on IDEAS

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    1. Serina Chang & Emma Pierson & Pang Wei Koh & Jaline Gerardin & Beth Redbird & David Grusky & Jure Leskovec, 2021. "Mobility network models of COVID-19 explain inequities and inform reopening," Nature, Nature, vol. 589(7840), pages 82-87, January.
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    3. Sheryl L. Chang & Nathan Harding & Cameron Zachreson & Oliver M. Cliff & Mikhail Prokopenko, 2020. "Modelling transmission and control of the COVID-19 pandemic in Australia," Nature Communications, Nature, vol. 11(1), pages 1-13, December.
    4. Roorda, Matthew J. & Miller, Eric J. & Habib, Khandker M.N., 2008. "Validation of TASHA: A 24-h activity scheduling microsimulation model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(2), pages 360-375, February.
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