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Cited by 608

The DOI matches its OpenAlex record; 5 of the 5 references it cites were found in a registry or an index.

Face masks for the public during the covid-19 crisis

Open access
Trisha Greenhalgh, Manuel Schmid, Thomas Czypionka, Dirk Bassler, Laurence D. Gruer·2020·Zurich Open Repository and Archive (University of Zurich)

Abstract

The precautionary principle is, according to Wikipedia, “a strategy for approaching issues of potential harm when extensive scientific knowledge on the matter is lacking.” The evidence base on the efficacy and acceptability of the different types of face mask in preventing respiratory infections during epidemics is sparse and contested (1,2). But covid-19 is a serious illness that currently has no known treatment or vaccine and is spreading in an immune naive population. Deaths are rising steeply, and health systems are under strain. This raises an ethical question: should policy makers apply the precautionary principle now and encourage people to wear face masks on the grounds that we have little to lose and potentially something to gain from this measure? (3) We believe they should.

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OpenAlex · 10.5167/uzh-187180

Cites

5 of 5 references verified0 citation errors · 0 not checkable

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Metadata

Authors
Greenhalgh, T., Schmid, M., Czypionka, T., Bassler, D., & Gruer, L. D.
Venue
Zurich Open Repository and Archive (University of Zurich)
Publisher
BMJ Publishing Group
Published
2020-04-09
OpenAlex
W3017966133
Cited by
608
References
5
FWCI
70.56
Type
journal article
Language
en
Open access
green

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This page
CoChat. (2026). Citation check: Face masks for the public during the covid-19 crisis. https://app.cochat.ai/papers/10.5167/uzh-187180
The paper
Greenhalgh, T., Schmid, M., Czypionka, T., Bassler, D., & Gruer, L. D. (2020). Face masks for the public during the covid-19 crisis. Zurich Open Repository and Archive (University of Zurich). https://doi.org/10.5167/uzh-187180

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.