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Estimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing data

Author

Listed:
  • Zengmiao Wang

    (Beijing Normal University)

  • Peng Yang

    (Beijing Center for Disease Prevention and Control
    Beijing Research Center for Respiratory Infectious Diseases)

  • Ruixue Wang

    (Beijing Normal University)

  • Luca Ferretti

    (University of Oxford
    University of Oxford)

  • Lele Zhao

    (University of Oxford
    University of Oxford)

  • Shan Pei

    (Beijing Normal University)

  • Xiaoli Wang

    (Beijing Center for Disease Prevention and Control
    Beijing Research Center for Respiratory Infectious Diseases)

  • Lei Jia

    (Beijing Center for Disease Prevention and Control
    Beijing Research Center for Respiratory Infectious Diseases)

  • Daitao Zhang

    (Beijing Center for Disease Prevention and Control
    Beijing Research Center for Respiratory Infectious Diseases)

  • Yonghong Liu

    (Beijing Center for Disease Prevention and Control
    Beijing Research Center for Respiratory Infectious Diseases)

  • Ziyan Liu

    (Beijing Normal University)

  • Quanyi Wang

    (Beijing Center for Disease Prevention and Control
    Beijing Research Center for Respiratory Infectious Diseases)

  • Christophe Fraser

    (University of Oxford
    University of Oxford)

  • Huaiyu Tian

    (Beijing Normal University)

Abstract

While many countries employed digital contact tracing to contain the spread of SARS-CoV-2, the contribution of cospace-time interaction (i.e., individuals who shared the same space and time) to transmission and to super-spreading in the real world has seldom been systematically studied due to the lack of systematic sampling and testing of contacts. To address this issue, we utilized data from 2230 cases and 220,878 contacts with detailed epidemiological information during the Omicron outbreak in Beijing in 2022. We observed that contact number per day of tracing for individuals in dwelling, workplace, cospace-time interactions, and community settings could be described by gamma distribution with distinct parameters. Our findings revealed that 38% of traced transmissions occurred through cospace-time interactions whilst control measures were in place. However, using a mathematical model to incorporate contacts in different locations, we found that without control measures, cospace-time interactions contributed to only 11% (95%CI: 10%–12%) of transmissions and the super-spreading risk for this setting was 4% (95%CI: 3%–5%), both the lowest among all settings studied. These results suggest that public health measures should be optimized to achieve a balance between the benefits of digital contact tracing for cospace-time interactions and the challenges posed by contact tracing within the same setting.

Suggested Citation

  • Zengmiao Wang & Peng Yang & Ruixue Wang & Luca Ferretti & Lele Zhao & Shan Pei & Xiaoli Wang & Lei Jia & Daitao Zhang & Yonghong Liu & Ziyan Liu & Quanyi Wang & Christophe Fraser & Huaiyu Tian, 2024. "Estimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing data," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-50487-7
    DOI: 10.1038/s41467-024-50487-7
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    References listed on IDEAS

    as
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