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Estimating internationally imported cases during the early COVID-19 pandemic

Author

Listed:
  • Tigist F. Menkir

    (Harvard University)

  • Taylor Chin

    (Harvard University)

  • James A. Hay

    (Harvard University)

  • Erik D. Surface

    (Harvard University)

  • Pablo M. Salazar

    (Harvard University)

  • Caroline O. Buckee

    (Harvard University)

  • Alexander Watts

    (BlueDot)

  • Kamran Khan

    (BlueDot
    Li Ka Shing Knowledge Institute, St. Michael’s Hospital
    University of Toronto)

  • Ryan Sherbo

    (BlueDot)

  • Ada W. C. Yan

    (Imperial College London)

  • Michael J. Mina

    (Harvard University)

  • Marc Lipsitch

    (Harvard University)

  • Rene Niehus

    (Harvard University)

Abstract

Early in the COVID-19 pandemic, predictions of international outbreaks were largely based on imported cases from Wuhan, China, potentially missing imports from other cities. We provide a method, combining daily COVID-19 prevalence and flight passenger volume, to estimate importations from 18 Chinese cities to 43 international destinations, including 26 in Africa. Global case importations from China in early January came primarily from Wuhan, but the inferred source shifted to other cities in mid-February, especially for importations to African destinations. We estimate that 10.4 (6.2 – 27.1) COVID-19 cases were imported to these African destinations, which exhibited marked variation in their magnitude and main sources of importation. We estimate that 90% of imported cases arrived between 17 January and 7 February, prior to the first case detections. Our results highlight the dynamic role of source locations, which can help focus surveillance and response efforts.

Suggested Citation

  • Tigist F. Menkir & Taylor Chin & James A. Hay & Erik D. Surface & Pablo M. Salazar & Caroline O. Buckee & Alexander Watts & Kamran Khan & Ryan Sherbo & Ada W. C. Yan & Michael J. Mina & Marc Lipsitch , 2021. "Estimating internationally imported cases during the early COVID-19 pandemic," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20219-8
    DOI: 10.1038/s41467-020-20219-8
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    Cited by:

    1. Baining Zhao & Xuzhe Wang & Tianyu Zhang & Rongye Shi & Fengli Xu & Fanhang Man & Erbing Chen & Yang Li & Yong Li & Tao Sun & Xinlei Chen, 2024. "Estimating and modeling spontaneous mobility changes during the COVID-19 pandemic without stay-at-home orders," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.

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