Widespread use of face masks in public may slow the spread of SARS CoV-2: an ecological study

  1. Chris Kenyon

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

The reasons for the large differences between countries in the sizes of their SARS CoV-2 epidemics is unknown. Individual level studies have found that the use of face masks was protective for the acquisition and transmission of a range of respiratory viruses including SARS CoV-1. We hypothesized that population level usage of face masks may be negatively associated SARS CoV-2 spread.

Methods

At a country level, linear regression was used to assess the association between COVID-19 diagnoses per inhabitant and the national promotion of face masks in public (coded as a binary variable), controlling for the age of the COVID-19 epidemic and testing intensity.

Results

Eight of the 49 countries with available data advocated wearing face masks in public – China, Czechia, Hong Kong, Japan, Singapore, South Korea, Thailand and Malaysia. In multivariate analysis face mask use was negatively associated with number of COVID-19 cases/inhabitant (coef. −326, 95% CI −601- −51, P=0.021). Testing intensity was positively associated with COVID-19 cases (coef. 0.07, 95% CI 0.05-0.08, P<0.001).

Conclusion

Whilst these results are susceptible to residual confounding, they do provide ecological level support to the individual level studies that found face mask usage to reduce the transmission and acquisition of respiratory viral infections.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.03.31.20048652: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    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:
    A further limitation of our study was that we were unable to quantitate the intensity of face mask use per country. This resulted in a rather crude binary classification of face mask usage per country. At this albeit early phase of the pandemic it is important to explore why the virus has spread more extensively in many European countries than China and neighboring countries where the outbreak appeared to have commenced. This is difficult in the absence of data that quantitates national competency in terms of the various components of successful national COVID-19 response plans. Narrative reviews of the features that resulted in the success of countries such as China, Hong Kong, Japan, Singapore and Taiwan have noted a number of common features. These include: rapid response, extensive testing, contact isolation and the widespread usage of face masks in public [4, 21]. There are a number of countries in Western European such as Italy that have conducted intensive screening, contact tracing, isolation, social distancing and widespread lockdowns and yet have amongst the largest COVID-19 epidemics in the world [2]. A striking omission from this response-list if we compare it to the responses in China and other Asian countries with lower COVID-19 incidence is that the widespread use of face masks in public was not promoted. The only European country to adopt this strategy was Czechia, and it did so at a relatively late stage in the epidemic [19, 20]. Early indications suggest tha...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.03.31.20048652v1 on medRxiv