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Investigating setting-specific superspreading potential and generation intervals of COVID-19 in Hong Kong

Author

Listed:
  • Dongxuan Chen

    (Hong Kong Special Administrative Region
    Hong Kong Special Administrative Region)

  • Dillon C. Adam

    (Hong Kong Special Administrative Region
    Hong Kong Special Administrative Region)

  • Yiu-Chung Lau

    (Hong Kong Special Administrative Region
    Hong Kong Special Administrative Region)

  • Dong Wang

    (Hong Kong Special Administrative Region
    Hong Kong Special Administrative Region)

  • Wey Wen Lim

    (Hong Kong Special Administrative Region
    Hong Kong Special Administrative Region)

  • Faith Ho

    (Hong Kong Special Administrative Region)

  • Tim K. Tsang

    (Hong Kong Special Administrative Region
    Hong Kong Special Administrative Region)

  • Eric H. Y. Lau

    (Hong Kong Special Administrative Region
    Hong Kong Special Administrative Region)

  • Peng Wu

    (Hong Kong Special Administrative Region
    Hong Kong Special Administrative Region)

  • Jacco Wallinga

    (National Institute for Public Health and the Environment (RIVM)
    Leiden University Medical Center)

  • Benjamin J. Cowling

    (Hong Kong Special Administrative Region
    Hong Kong Special Administrative Region)

  • Sheikh Taslim Ali

    (Hong Kong Special Administrative Region
    Hong Kong Special Administrative Region)

Abstract

Superspreading is an important feature of COVID-19 transmission dynamics, but few studies have investigated this feature stratified by transmission setting. Using detailed clustering data comprising 8647 COVID-19 cases confirmed in Hong Kong between 2020 and 2021, we estimated the mean number of new infections expected in a transmission cluster ( $${C}_{Z}$$ C Z ) and the degree of overdispersion (k) by setting. Estimates of $${C}_{Z}$$ C Z ranged within 0.4–7.1 across eight settings, with highest $${C}_{Z}$$ C Z in the close-social indoor setting that an average of seven new infections per cluster was expected. Transmission was most heterogeneous (k = 0.05) in retail setting and least heterogeneous (k = 1.1) in households, where smaller k indicates greater overdispersion and superspreading potential. Point-estimates of the mean generation interval (GI) ranged within 4.4–7.0, and settings with shorter mean realized GIs were associated with smaller cluster sizes. Here, we show that superspreading potential and generation intervals can vary across settings, strengthening the need for setting-specific interventions.

Suggested Citation

  • Dongxuan Chen & Dillon C. Adam & Yiu-Chung Lau & Dong Wang & Wey Wen Lim & Faith Ho & Tim K. Tsang & Eric H. Y. Lau & Peng Wu & Jacco Wallinga & Benjamin J. Cowling & Sheikh Taslim Ali, 2025. "Investigating setting-specific superspreading potential and generation intervals of COVID-19 in Hong Kong," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-60591-x
    DOI: 10.1038/s41467-025-60591-x
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    References listed on IDEAS

    as
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