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Modeling local coronavirus outbreaks

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  • Chang, Joseph T.
  • Kaplan, Edward H.

Abstract

This article presents an overview of methods developed for the modeling and control of local coronavirus outbreaks. The article reviews early transmission dynamics featuring exponential growth in infections, and links this to a renewal epidemic model where the current incidence of infection depends upon the expected value of incidence randomly lagged into the past. This leads directly to simple formulas for the fraction of the population infected in an unmitigated outbreak, and reveals herd immunity as the solution to an optimization problem. The model also leads to direct and easy-to-understand formulas for aligning observable epidemic indicators such as cases, hospitalizations and deaths with the unobservable incidence of infection, and as a byproduct leads to a simple first-order approach for estimating the effective reproduction number Rt. The model also leads naturally to direct assessments of the effectiveness of isolation in preventing the spread of infection. This is illustrated with application to repeat asymptomatic screening programs of the sort utilized by universities, sports teams and businesses to prevent the spread of infection.

Suggested Citation

  • Chang, Joseph T. & Kaplan, Edward H., 2023. "Modeling local coronavirus outbreaks," European Journal of Operational Research, Elsevier, vol. 304(1), pages 57-68.
    • Handle: RePEc:eee:ejores:v:304:y:2023:i:1:p:57-68
    DOI: 10.1016/j.ejor.2021.07.049
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    References listed on IDEAS

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    1. J. A. P. Heesterbeek & K. Dietz, 1996. "The concept of Ro in epidemic theory," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 50(1), pages 89-110, March.
    2. Katelyn M Gostic & Lauren McGough & Edward B Baskerville & Sam Abbott & Keya Joshi & Christine Tedijanto & Rebecca Kahn & Rene Niehus & James A Hay & Pablo M De Salazar & Joel Hellewell & Sophie Meaki, 2020. "Practical considerations for measuring the effective reproductive number, Rt," PLOS Computational Biology, Public Library of Science, vol. 16(12), pages 1-21, December.
    3. Edward H. Kaplan, 2020. "OM Forum—COVID-19 Scratch Models to Support Local Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 22(4), pages 645-655, July.
    4. Edward H. Kaplan, 2020. "Containing 2019-nCoV (Wuhan) coronavirus," Health Care Management Science, Springer, vol. 23(3), pages 311-314, September.
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    Cited by:

    1. Das, Saikat & Bose, Indranil & Sarkar, Uttam Kumar, 2023. "Predicting the outbreak of epidemics using a network-based approach," European Journal of Operational Research, Elsevier, vol. 309(2), pages 819-831.
    2. Fan, Yufei & Meng, Xueyu & Liu, Jun & Ma, Jun-Chao & Cai, Zhiqiang & Si, Shubin, 2025. "Hamiltonian optimal control of quarantine against epidemic spreading on complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 194(C).

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