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Harnessing peak transmission around symptom onset for non-pharmaceutical intervention and containment of the COVID-19 pandemic

Author

Listed:
  • Liang Tian

    (Hong Kong Baptist University, Kowloon
    Hong Kong Baptist University, Kowloon)

  • Xuefei Li

    (Hong Kong Baptist University, Kowloon
    Shenzhen Institutes of Advanced Technology)

  • Fei Qi

    (Hong Kong Baptist University, Kowloon
    Shenzhen Institutes of Advanced Technology)

  • Qian-Yuan Tang

    (Hong Kong Baptist University, Kowloon
    University of Tokyo)

  • Viola Tang

    (Hong Kong Baptist University, Kowloon
    Hong Kong University of Science and Technology)

  • Jiang Liu

    (Hong Kong Baptist University, Kowloon)

  • Zhiyuan Li

    (Hong Kong Baptist University, Kowloon
    Peking University, Haidian)

  • Xingye Cheng

    (Hong Kong Baptist University, Kowloon
    Hong Kong Baptist University, Kowloon)

  • Xuanxuan Li

    (Hong Kong Baptist University, Kowloon
    Tsinghua University, Haidian
    Beijing Normal University, Haidian)

  • Yingchen Shi

    (Hong Kong Baptist University, Kowloon
    Tsinghua University, Haidian
    Beijing Computational Science Research Center, Haidian)

  • Haiguang Liu

    (Hong Kong Baptist University, Kowloon
    Beijing Computational Science Research Center, Haidian
    Beijing Normal University, Haidian)

  • Lei-Han Tang

    (Hong Kong Baptist University, Kowloon
    Hong Kong Baptist University, Kowloon
    Beijing Computational Science Research Center, Haidian)

Abstract

Within a short period of time, COVID-19 grew into a world-wide pandemic. Transmission by pre-symptomatic and asymptomatic viral carriers rendered intervention and containment of the disease extremely challenging. Based on reported infection case studies, we construct an epidemiological model that focuses on transmission around the symptom onset. The model is calibrated against incubation period and pairwise transmission statistics during the initial outbreaks of the pandemic outside Wuhan with minimal non-pharmaceutical interventions. Mathematical treatment of the model yields explicit expressions for the size of latent and pre-symptomatic subpopulations during the exponential growth phase, with the local epidemic growth rate as input. We then explore reduction of the basic reproduction number R0 through specific transmission control measures such as contact tracing, testing, social distancing, wearing masks and sheltering in place. When these measures are implemented in combination, their effects on R0 multiply. We also compare our model behaviour to the first wave of the COVID-19 spreading in various affected regions and highlight generic and less generic features of the pandemic development.

Suggested Citation

  • Liang Tian & Xuefei Li & Fei Qi & Qian-Yuan Tang & Viola Tang & Jiang Liu & Zhiyuan Li & Xingye Cheng & Xuanxuan Li & Yingchen Shi & Haiguang Liu & Lei-Han Tang, 2021. "Harnessing peak transmission around symptom onset for non-pharmaceutical intervention and containment of the COVID-19 pandemic," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21385-z
    DOI: 10.1038/s41467-021-21385-z
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    Cited by:

    1. Vincenzo Alfano, 2022. "Work ethics, stay-at-home measures and COVID-19 diffusion," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(5), pages 893-901, July.
    2. Li, Ruqi & Song, Yurong & Wang, Haiyan & Jiang, Guo-Ping & Xiao, Min, 2023. "Reactive–diffusion epidemic model on human mobility networks: Analysis and applications to COVID-19 in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).

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