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Cited by 1,529

The DOI matches its Crossref record; 121 of the 121 references it cites were found in a registry or an index.

An evidence review of face masks against COVID-19

Open access
Howard, Jeremy, Huang, Austin, Li, Zhiyuan, Tufekci, Zeynep, Zdimal, Vladimir, van der Westhuizen, Helene-Mari, von Delft, Arne, Price, Amy, Fridman, Lex, Tang, Lei-Han, Tang, Viola, Watson, Gregory L., Bax, Christina E., Shaikh, Reshama, Questier, Frederik, Hernandez, Danny, Chu, Larry F., Ramirez, Christina M., Rimoin, Anne W.·2021·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.2014564118

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Abstract

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.

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Citations

Cites

Show all 121 references

Research works printed but not linked: 16

  1. Q. Wang, C. Yu, Letter to editor: Role of masks/respirator protection against 2019-novel coronavirus (COVID-19). Infect. Contr. Hosp. Epidemiol. 1, 1–7 (2020).
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  3. World Health Organization, Handbook for Guideline Development (World Health Organization, 2010).
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  11. 10.3141/2393-05 · doi:10.3141/2393-05
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  14. P. Illingworth, W. E. Parmet, Solidarity and health: A public goods justification. Diametros 43, 65–71 (2015).
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Metadata

Authors
Howard, J., Huang, A., Li, Z., Tufekci, Z., Zdimal, V., van der Westhuizen, H.-M., von Delft, A., Price, A., Fridman, L., Tang, L.-H., Tang, V., Watson, G. L., Bax, C. E., Shaikh, R., Questier, F., Hernandez, D., Chu, L. F., Ramirez, C. M., & Rimoin, A. W.
Venue
Proceedings of the National Academy of Sciences
Publisher
Proceedings of the National Academy of Sciences
Published
2021-01-11
Volume
118
Issue
4
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.2014564118
OpenAlex
W3118643387
Cited by
1,529
References
121
FWCI
174.89
Type
journal article
Language
en
Update notices
correction (2024-04-25)
Open access
bronze
Licence
www.pnas.org/site/aboutpnas/licenses.xhtml (vor, 181 d)

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CoChat. (2026). Citation check: An evidence review of face masks against COVID-19. https://app.cochat.ai/papers/10.1073/pnas.2014564118
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Howard, J., Huang, A., Li, Z., Tufekci, Z., Zdimal, V., van der Westhuizen, H.-M., von Delft, A., Price, A., Fridman, L., Tang, L.-H., Tang, V., Watson, G. L., Bax, C. E., Shaikh, R., Questier, F., Hernandez, D., Chu, L. F., Ramirez, C. M., & Rimoin, A. W. (2021). An evidence review of face masks against COVID-19. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.2014564118

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.