Association of social distancing and face mask use with risk of COVID-19

  1. Sohee Kwon
  2. Amit D. Joshi
  3. Chun-Han Lo
  4. David A. Drew
  5. Long H. Nguyen
  6. Chuan-Guo Guo
  7. Wenjie Ma
  8. Raaj S. Mehta
  9. Fatma Mohamed Shebl
  10. Erica T. Warner
  11. Christina M. Astley
  12. Jordi Merino
  13. Benjamin Murray
  14. Jonathan Wolf
  15. Sebastien Ourselin
  16. Claire J. Steves
  17. Tim D. Spector
  18. Jaime E. Hart
  19. Mingyang Song
  20. Trang VoPham
  21. Andrew T. Chan

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Abstract

Given the continued burden of COVID-19 worldwide, there is a high unmet need for data on the effect of social distancing and face mask use to mitigate the risk of COVID-19. We examined the association of community-level social distancing measures and individual face mask use with risk of predicted COVID-19 in a large prospective U.S. cohort study of 198,077 participants. Individuals living in communities with the greatest social distancing had a 31% lower risk of predicted COVID-19 compared with those living in communities with poor social distancing. Self-reported ‘always’ use of face mask was associated with a 62% reduced risk of predicted COVID-19 even among individuals living in a community with poor social distancing. These findings provide support for the efficacy of mask-wearing even in settings of poor social distancing in reducing COVID-19 transmission. Despite mass vaccination campaigns in many parts of the world, continued efforts at social distancing and face mask use remain critically important in reducing the spread of COVID-19.

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  1. Version published to 10.1038/s41467-021-24115-7
  2. ScreenIT

    SciScore for 10.1101/2020.11.11.20229500: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: At enrollment, participants provided informed consent to the use of aggregated information for research purposes and agreed to applicable privacy policies and terms of use.
    IRB: This research study was approved by the Partners Human Research Committee (Institutional Review Board Protocol 2020P000909).
    RandomizationTo build a prediction model, the UK participants were randomly divided into a training set and a test set (ratio: 80:20).
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableBased on the training set, a logistic model generated to predict symptomatic COVID-19 was: Log odds (Predicted COVID-19) = −1.32 - (0.01 x age) + (0.44 x male sex) + (1.75 x loss of smell or taste) + (0.31 x severe or significant persistent cough)

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Noticeably, the inverse association between living in a community with greater social distancing and risk of predicted COVID-19 was most consistently observed among younger individuals without significant health problems or limitations in mobility. We observed that the disease burden of COVID-19 at the start of the social distancing measurement did not influence the association of social distancing and personal use of a face mask with risk of predicted COVID-19. We also observed that protective effect of social distancing on predicted COVID-19 was present both in areas where the epidemic was slowing or maintained (Rt ≤1.0) as well as in areas where COVID-19 was actively spreading (Rt>1.0). We similarly observed that the benefit of personal use of a face mask was observed in regions and time periods in which there was epidemic slowing/maintenance or growth. These findings imply that baseline risk did not impact the relative benefits of social distancing policies and/or face mask use, although it is remains possible that the absolute reduction in risk is greater in areas with higher burden of COVID-19. In our study, we used predicted COVID-19 as a proxy for a positive COVID-19 test due to the small number of COVID-19 test positive app users during the study period. The small fraction of positive COVID-19 tests among all participants (0.17%) may be largely influenced by the limited availability of COVID-19 testing during the study period. A recent study demonstrated that more th...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04331509RecruitingCOVID-19 Symptom Tracker

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2020.11.11.20229500v1 on medRxiv