An evidence review of face masks against COVID-19

  • Jeremy Howard
    fast.ai, San Francisco, CA 94105;
  • Austin Huang
    Warren Alpert School of Medicine, Brown University, Providence, RI 02903;
  • Zhiyuan Li
    Center for Quantitative Biology, Peking University, Beijing 100871, China;
  • Zeynep Tufekci
    School of Information, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599;
  • Vladimir Zdimal
    Institute of Chemical Process Fundamentals, Czech Academy of Sciences, CZ-165 02 Praha 6, Czech Republic;
  • Helene-Mari van der Westhuizen
    Department of Primary Health Care Sciences, University of Oxford, Oxford OX2 6GG, United Kingdom;
  • Arne von Delft
    TB Proof, Cape Town 7130, South Africa;
  • Amy Price
    Anesthesia Informatics and Media Lab, School of Medicine, Stanford University, Stanford, CA 94305;
  • Lex Fridman
    Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139;
  • Lei-Han Tang
    Department of Physics, Hong Kong Baptist University, Hong Kong SAR, China;
  • Viola Tang
    Department of Information Systems, Business Statistics and Operations Management, Hong Kong University of Science and Technology, Hong Kong SAR, China;
  • Gregory L. Watson
    Department of Biostatistics, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, CA 90095;
  • Christina E. Bax
    Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104;
  • Reshama Shaikh
    Data Umbrella, New York, NY 10031;
  • Frederik Questier
    Teacher Education Department, Vrije Universiteit Brussel, 1050 Brussels, Belgium;
  • Danny Hernandez
    OpenAI, San Francisco, CA 94110;
  • Larry F. Chu
    Anesthesia Informatics and Media Lab, School of Medicine, Stanford University, Stanford, CA 94305;
  • Christina M. Ramirez
    Department of Biostatistics, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, CA 90095;
  • Anne W. Rimoin
    Department of Epidemiology, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, CA 90095

説明

<jats:p>The science around the use of masks by the public to impede COVID-19 transmission is advancing rapidly. In this narrative review, we develop an analytical framework to examine mask usage, synthesizing the relevant literature to inform multiple areas: population impact, transmission characteristics, source control, wearer protection, sociological considerations, and implementation considerations. A primary route of transmission of COVID-19 is via respiratory particles, and it is known to be transmissible from presymptomatic, paucisymptomatic, and asymptomatic individuals. Reducing disease spread requires two things: limiting contacts of infected individuals via physical distancing and other measures and reducing the transmission probability per contact. The preponderance of evidence indicates that mask wearing reduces transmissibility per contact by reducing transmission of infected respiratory particles in both laboratory and clinical contexts. Public mask wearing is most effective at reducing spread of the virus when compliance is high. Given the current shortages of medical masks, we recommend the adoption of public cloth mask wearing, as an effective form of source control, in conjunction with existing hygiene, distancing, and contact tracing strategies. Because many respiratory particles become smaller due to evaporation, we recommend increasing focus on a previously overlooked aspect of mask usage: mask wearing by infectious people (“source control”) with benefits at the population level, rather than only mask wearing by susceptible people, such as health care workers, with focus on individual outcomes. We recommend that public officials and governments strongly encourage the use of widespread face masks in public, including the use of appropriate regulation.</jats:p>

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