IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v11y2020i1d10.1038_s41467-020-18836-4.html
   My bibliography  Save this article

Inference of person-to-person transmission of COVID-19 reveals hidden super-spreading events during the early outbreak phase

Author

Listed:
  • Liang Wang

    (Chinese Academy of Sciences)

  • Xavier Didelot

    (University of Warwick)

  • Jing Yang

    (Chinese Academy of Sciences)

  • Gary Wong

    (Institut Pasteur of Shanghai, Chinese Academy of Sciences
    Université Laval)

  • Yi Shi

    (Chinese Academy of Sciences)

  • Wenjun Liu

    (Chinese Academy of Sciences)

  • George F. Gao

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Yuhai Bi

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences
    Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen Third People’s Hospital)

Abstract

Coronavirus disease 2019 (COVID-19) was first identified in late 2019 in Wuhan, Hubei Province, China and spread globally in months, sparking worldwide concern. However, it is unclear whether super-spreading events occurred during the early outbreak phase, as has been observed for other emerging viruses. Here, we analyse 208 publicly available SARS-CoV-2 genome sequences collected during the early outbreak phase. We combine phylogenetic analysis with Bayesian inference under an epidemiological model to trace person-to-person transmission. The dispersion parameter of the offspring distribution in the inferred transmission chain was estimated to be 0.23 (95% CI: 0.13–0.38), indicating there are individuals who directly infected a disproportionately large number of people. Our results showed that super-spreading events played an important role in the early stage of the COVID-19 outbreak.

Suggested Citation

  • Liang Wang & Xavier Didelot & Jing Yang & Gary Wong & Yi Shi & Wenjun Liu & George F. Gao & Yuhai Bi, 2020. "Inference of person-to-person transmission of COVID-19 reveals hidden super-spreading events during the early outbreak phase," Nature Communications, Nature, vol. 11(1), pages 1-6, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18836-4
    DOI: 10.1038/s41467-020-18836-4
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-020-18836-4
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-020-18836-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Arnab K Ghosh & Sara Venkatraman & Evgeniya Reshetnyak & Mangala Rajan & Anjile An & John K Chae & Mark A Unruh & David Abramson & Charles DiMaggio & Nathaniel Hupert, 2022. "Association between city-wide lockdown and COVID-19 hospitalization rates in multigenerational households in New York City," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-13, March.
    2. Jonas Dehning & Sebastian B. Mohr & Sebastian Contreras & Philipp Dönges & Emil N. Iftekhar & Oliver Schulz & Philip Bechtle & Viola Priesemann, 2023. "Impact of the Euro 2020 championship on the spread of COVID-19," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    3. Damon J A Toth & Alexander B Beams & Lindsay T Keegan & Yue Zhang & Tom Greene & Brian Orleans & Nathan Seegert & Adam Looney & Stephen C Alder & Matthew H Samore, 2021. "High variability in transmission of SARS-CoV-2 within households and implications for control," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-21, November.
    4. Terefe, Y.A. & Njagarah, J.B.H. & Kassa, S.M., 2023. "Effect of cross-border migration on the healthcare system of a destination community: Insights from mathematical modelling of COVID-19 in a developing country," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 208(C), pages 444-479.
    5. Aleksandar Radic & Michael Lück & Amr Al-Ansi & Bee-Lia Chua & Sabrina Seeler & António Raposo & Jinkyung Jenny Kim & Heesup Han, 2021. "To Dine, or Not to Dine on a Cruise Ship in the Time of the COVID-19 Pandemic: The Tripartite Approach towards an Understanding of Behavioral Intentions among Female Passengers," Sustainability, MDPI, vol. 13(5), pages 1-17, February.
    6. Elías, L. Llamazares & Elías, S. Llamazares & del Rey, A. Martín, 2022. "An analysis of contact tracing protocol in an over-dispersed SEIQR Covid-like disease," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18836-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.