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Model with transmission delays for COVID‐19 control: Theory and empirical assessment

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  • Natali Hritonenko
  • Olga Yatsenko
  • Yuri Yatsenko

Abstract

The paper focuses on modeling of public health measures to control the COVID‐19 pandemic. The authors suggest a flexible integral model with distributed lags, which realistically describes COVID‐19 infectiousness period from clinical data. It contains susceptible–infectious–recovered (SIR), susceptible–exposed–infectious–recovered (SEIR), and other epidemic models as special cases. The model is used for assessing how government decisions to lockdown and reopen the economy affect epidemic spread. The authors demonstrate essential differences in transition and asymptotic dynamics of the integral model and the SIR model after lockdown. The provided simulation on real data accurately describes several waves of the COVID‐19 epidemic in the United States and is in good correspondence with government actions to curb the epidemic.

Suggested Citation

  • Natali Hritonenko & Olga Yatsenko & Yuri Yatsenko, 2022. "Model with transmission delays for COVID‐19 control: Theory and empirical assessment," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 24(5), pages 1218-1244, October.
    • Handle: RePEc:bla:jpbect:v:24:y:2022:i:5:p:1218-1244
    DOI: 10.1111/jpet.12554
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    References listed on IDEAS

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    Cited by:

    1. John Higgins & Tarun Sabarwal, 2023. "Control and spread of contagion in networks with global effects," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 25(6), pages 1149-1187, December.
    2. Natali Hritonenko & Yuri Yatsenko, 2024. "Analysis of optimal lockdown in integral economic–epidemic model," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 77(1), pages 235-259, February.
    3. Thomas Hellmann & Veikko Thiele, 2022. "A theory of voluntary testing and self‐isolation in an ongoing pandemic," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 24(5), pages 873-911, October.
    4. John Higgins & Tarun Sabarwal, 2021. "Control and Spread of Contagion in Networks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202111, University of Kansas, Department of Economics.

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