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A Mechanistic Model for Long COVID Dynamics

Author

Listed:
  • Jacob Derrick

    (Department of Mathematics, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA)

  • Ben Patterson

    (Department of Mathematics, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA)

  • Jie Bai

    (School of Mathematics and Statistics, Liaoning University, Shenyang 110036, China)

  • Jin Wang

    (Department of Mathematics, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA)

Abstract

Long COVID, a long-lasting disorder following an acute infection of COVID-19, represents a significant public health burden at present. In this paper, we propose a new mechanistic model based on differential equations to investigate the population dynamics of long COVID. By connecting long COVID with acute infection at the population level, our modeling framework emphasizes the interplay between COVID-19 transmission, vaccination, and long COVID dynamics. We conducted a detailed mathematical analysis of the model. We also validated the model using numerical simulation with real data from the US state of Tennessee and the UK.

Suggested Citation

  • Jacob Derrick & Ben Patterson & Jie Bai & Jin Wang, 2023. "A Mechanistic Model for Long COVID Dynamics," Mathematics, MDPI, vol. 11(21), pages 1-16, November.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:21:p:4541-:d:1273857
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    References listed on IDEAS

    as
    1. Michael Marshall, 2021. "The four most urgent questions about long COVID," Nature, Nature, vol. 594(7862), pages 168-170, June.
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