The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
Efficacy of face mask in preventing respiratory virus transmission: A systematic review and meta-analysis
Open accessAbstract
Background: Conflicting recommendations exist related to whether masks have a protective effect on the spread of respiratory viruses. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement was consulted to report this systematic review. Relevant articles were retrieved from PubMed, Web of Science, ScienceDirect, Cochrane Library, and Chinese National Knowledge Infrastructure (CNKI), VIP (Chinese) database. Results: A total of 21 studies met our inclusion criteria. Meta-analyses suggest that mask use provided a significant protective effect (OR = 0.35 and 95% CI = 0.24-0.51). Use of masks by healthcare workers (HCWs) and non-healthcare workers (Non-HCWs) can reduce the risk of respiratory virus infection by 80% (OR = 0.20, 95% CI = 0.11-0.37) and 47% (OR = 0.53, 95% CI = 0.36-0.79). The protective effect of wearing masks in Asia (OR = 0.31) appeared to be higher than that of Western countries (OR = 0.45). Masks had a protective effect against influenza viruses (OR = 0.55), SARS (OR = 0.26), and SARS-CoV-2 (OR = 0.04). In the subgroups based on different study designs, protective effects of wearing mask were significant in cluster randomized trials, case-control studies and retrospective studies. Conclusions: This study adds additional evidence of the enhanced protective value of masks, we stress that the use masks serve as an adjunctive method regarding the COVID-19 outbreak.
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Bias in meta-analysis detected by a simple, graphical test
Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997) · BMJ · doi:10.1136/bmj.315.7109.629 · Cited by 56,722
Meta-analysis in clinical trials
DerSimonian, R., & Laird, N. (1986) · Controlled Clinical Trials · doi:10.1016/0197-2456(86)90046-2 · Cited by 39,552
Wang, D., Hu, B., Hu, C., Zhu, F., Liu, X., Zhang, J., Wang, B., Xiang, H., Cheng, Z., Xiong, Y., et al. (2020) · JAMA · doi:10.1001/jama.2020.1585 · Cited by 20,148
La certeza de lo impredecible: Cultura Educación y Sociedad en tiempos de COVID19
Martínez González, M. (2020) · DSPACE System - Metalibrary (University of the Coast) · Cited by 18,463
(2014) · Medical Entomology and Zoology · Cited by 17,633
Assessing the quality of reports of randomized clinical trials: Is blinding necessary?
Jadad, A. R., Moore, R. A., Carroll, D., Jenkinson, C., Reynolds, D. J. M., Gavaghan, D. J., & McQuay, H. J. (1996) · Controlled Clinical Trials · doi:10.1016/0197-2456(95)00134-4 · Cited by 17,582
Operating characteristics of a rank correlation test for publication bias
Begg, C. B., & Mazumdar, M. (1994) · Biometrics · doi:10.2307/2533446 · Cited by 16,955
Aerosol and surface stability of SARS-CoV-2 as compared with SARS-CoV-1
van Doremalen, N., Bushmaker, T., Morris, D. H., Holbrook, M. G., Gamble, A., Williamson, B. N., Tamin, A., Harcourt, J. L., Thornburg, N. J., Gerber, S. I., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2004973 · Cited by 9,951
Chan, J. F.-W., Yuan, S., Kok, K.-H., To, K. K.-W., Chu, H., Yang, J., Xing, F., Liu, J., Yip, C. C.-Y., Poon, R. W.-S., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30154-9 · Cited by 8,944
Transmission of 2019-nCoV Infection from an Asymptomatic Contact in Germany
Rothe, C., Schunk, M., Sothmann, P., Bretzel, G., Froeschl, G., Wallrauch, C., Zimmer, T., Thiel, V., Janke, C., Guggemos, W., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2001468 · Cited by 4,144
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Modeling COVID-19 scenarios for the United States
IHME COVID-19 Forecasting Team, Reiner, R. C., Barber, R. M., Collins, J. K., Zheng, P., Adolph, C., Albright, J., Antony, C. M., Aravkin, A. Y., Bachmeier, S. D., et al. (2021) · Nature Medicine · doi:10.1038/s41591-020-1132-9 · Cited by 556
Olsen, S. J., Azziz-Baumgartner, E., Budd, A. P., Brammer, L., Sullivan, S., Pineda, R. F., Cohen, C., & Fry, A. M. (2020) · MMWR. Morbidity and Mortality Weekly Report · doi:10.15585/mmwr.mm6937a6 · Cited by 579
Effective public health measures to mitigate the spread of COVID-19: a systematic review
Ayouni, I., Maatoug, J., Dhouib, W., Zammit, N., Fredj, S. B., Ghammam, R., & Ghannem, H. (2021) · BMC Public Health · doi:10.1186/s12889-021-11111-1 · Cited by 418
Olsen, S. J., Azziz-Baumgartner, E., Budd, A. P., Brammer, L., Sullivan, S., Pineda, R. F., Cohen, C., & Fry, A. M. (2020) · American Journal of Transplantation · doi:10.1111/ajt.16381 · Cited by 339
Wu, S., Dong, T., Li, Y., Sun, M., Qi, Y., Liu, J., Kuss, M. A., Chen, S., & Duan, B. (2022) · Applied Materials Today · doi:10.1016/j.apmt.2022.101473 · Cited by 250
Metadata
- Authors
- Liang, M., Gao, L., Cheng, C., Zhou, Q., Uy, J. P., Heiner, K., & Sun, C.
- Venue
- Travel Medicine and Infectious Disease
- Publisher
- Elsevier BV
- Published
- 2020-07
- Volume
- 36
- Pages
- 101751
- ISSN
- 1477-8939 (ISSN-L)
- OpenAlex
- W3030991920
- Cited by
- 470
- References
- 57
- FWCI
- 19.69
- Type
- journal article
- Language
- en
- Open access
- green
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