Yiming Chen
Yuelin Wang1
Jun Yang- 1Department of Epidemiology and Health Statistics, School of Public Health, Faculty of Medicine, Hangzhou Normal University, Hangzhou, China
- 2Department of Nutrition and Toxicology, School of Public Health, Faculty of Medicine, Hangzhou Normal University, Hangzhou, China
- 3National Key Laboratory for the Diagnosis and Treatment for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
Background: Respiratory viral infections (RVIs) are a major health concern, and some previous studies have shown that wearing masks was effective in preventing RVIs, while others failed to show such effect. Therefore, a systematic review and meta-analysis was conducted to investigate the effectiveness of wearing masks.
Methods: PubMed, ScienceDirect, Web of Science, the Cochrane Library, EMBASE, MEDLINE, China National Knowledge Infrastructure (CNKI), and Chinese Scientific Journal Database (VIP database) were searched for studies evaluating the effectiveness of wearing masks. The risk ratio (RR) was used to measure the effectiveness of wearing masks in preventing RVIs for randomized controlled trials (RCTs) and cohort studies, and the odds ratio (OR) was used for case-control studies. Forest plots were used to visually assess pooled estimates and corresponding 95% CIs. The I2 test was used to examine the heterogeneity, and subgroup analysis was used to explore the possible explanations for heterogeneity or compare the results between subgroups. Sensitivity analysis was conducted to assess robustness of the synthesized results. Begg's test and Egger's test were used to assess the publications bias.
Results: Thirty-one studies (13,329 participants) were eligible for meta-analyses. Overall, the results showed that wearing masks was effective in preventing RVIs. The sensitivity analysis showed that the results of those meta-analyses were robust and reliable. There was no significant publication bias in meta-analysis of case-control studies and most subgroup analyses.
Conclusions: Wearing masks might be effective in preventing RVIs. To reduce their RVI risk, people should wear masks when they go out in public.
Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42021296092.
Introduction
In recent years, respiratory viral infections (RVIs), such as Corona Virus Disease 2019 (COVID-19), Severe Acute Respiratory Syndrome (SARS), influenza, and Middle East Respiratory Syndrome (MERS), have spread across the world and seriously threatened public health. Under such circumstances, there is an urgent need to find some effective management strategies that can help prevent RVIs. Previous studies have found that surgical masks and N95 masks were effective in preventing RVIs (1–4), as were common masks, such as cotton masks (5, 6). Thus, in the combat against COVID-19, people were required to wear masks when going out in public in many countries (7–9). However, some studies indicated that there was insufficient evidence for the effectiveness of wearing masks (10, 11), while substantial adverse physiological and psychological effects of wearing masks, including hypercapnia, shortness of breath, anxiety, depression, etc. (12), were reported. Several meta-analyses have evaluated the potential benefits of wearing masks, however, they all suffered certain weakness, for instance, some only analyzed a single disease (13–15), some focused on limited types of masks (16–20), and others only included a small number of studies (13, 21). Moreover, the conclusions of these meta-analyses were inconsistent, as some found that wearing masks were effective in preventing RVIs (13–16, 18, 21), while another study failed to show the benefits (17, 19, 20). In view of this problem, a meta-analysis was conducted to quantify the effectiveness of wearing masks in the prevention of RVIs.
Materials and Methods
A systematic review was conducted following PRISMA guidelines (22). The study protocol has been registered with PROSPERO: CRD42021296092.
Search Strategy
A comprehensive literature search was carried out in PubMed, ScienceDirect, Web of Science, the Cochrane Library, EMBASE, MEDLINE, China National Knowledge Infrastructure (CNKI), and Chinese Scientific Journal Database (VIP database) from January 1, 2000 to May 1, 2021. The literature search was conducted using the following medical subject heading terms and Boolean operators: “(“mask” OR “facemask” OR “N95” OR “respirator”) AND (“influenza virus” OR “SARS” OR “MERS” OR “COVID-19” OR “virus”).” The details of the search strategy are shown in Supplementary Table 1. Searching was restricted to articles in English and Chinese, and the references of the articles retrieved were also screened.
Inclusion and Exclusion Criteria
Inclusion criteria were (1) study type: case-control studies, cohort studies, and randomized controlled trials (RCTs); (2) participants: healthcare workers (HCWs, workers in a health care setting who might be exposed to patients with RVIs) and non-healthcare workers (non-HCWs); (3) intervention: all types of masks; and (4) outcome: laboratory-confirmed RVIs. Exclusion criteria were (1) studies without raw data, such as theoretical models, conference abstracts, case reports, editorials, and comments; (2) studies with incomplete or invalid data; (3) studies with unavailable full texts; (4) human or non-human experimental laboratory studies; and (5) duplicate publication or overlapped studies.
Study Selection and Data Extraction
Two reviewers independently screened the articles based on the titles, abstracts, and full texts. Then, two reviewers independently exacted the following data from the included studies: first author, publication year, country, type of RVI, type of mask, occupation of participants, sample size, and study design. Any disagreements were resolved by a panel discussion with other reviewers.
Quality Assessment
The Newcastle-Ottawa Scale (NOS) (23, 24) was used to evaluate the quality of the case-control studies and cohort studies. The scale, whose ratings ranged from zero to nine, included eight items within three domains to evaluate bias in selection, comparability, and exposure (for case-control studies)/outcome (for cohort studies). A scale of six to nine represented high quality, and scale of five or less represented low quality of the study. The Cochrane Collaboration's tool (25) was used for evaluating the quality of RCTs. The tool covers six domains of bias: selection bias, performance bias, detection bias, attrition bias, reporting bias, and other bias. Each domain was assessed as low, unclear or high risk of bias. Two reviewers completed assessments independently, and any disagreements were resolved by a panel discussion with other reviewers.
Statistical Analysis
Data analysis was performed by using the Review Manager 5.3 software and STATA 14.0 software. The risk ratio (RR) was used to measure the effectiveness of wearing masks in preventing RVIs for RCTs and cohort studies, and the odds ratio (OR) was used for case-control studies. Forest plots were used to visually assess pooled estimates and corresponding 95% CIs. The heterogeneity was examined by the I2 test. A random-effects model was used to calculate the pooled effect size when the heterogeneity was considered significant (I2 > 50%, P ≤ 0.10); otherwise, a fixed-effects model was used. Subgroup analysis was used to explore the possible explanations for heterogeneity or compare the results between subgroups. Leave-one-out sensitivity analysis was conducted to assess robustness of the synthesized results. Begg's test and Egger's test were used to assess the publication bias, and P < 0.05 was set as the level of significance.
Results
Literature Search
After searching the databases, 9,859 articles were identified, and finally 31 articles (1–6, 10, 11, 26–48) were included in the final pooled analysis based on the inclusion/exclusion criteria, and the total number of participants involved in the systematic review was 13,329. The search details of the study selection process are shown in Figure 1, and a summary of the included studies are presented in Table 1. Among them, 18 articles (2, 5, 6, 29–32, 34, 36, 38, 40–48) were case-control studies, 7 articles (1, 4, 26, 28, 33, 39, 45) were cohort studies, and 6 articles (3, 10, 11, 27, 35, 37) were RCTs. In case-control studies, 14 studies (2, 5, 6, 29–31, 34, 36, 38, 43, 44, 46–48) were of high quality (Supplementary Table 2). In cohort studies, 3 studies (1, 28, 33) were of high quality (Supplementary Table 3). In RCTs, the results of The Cochrane Collaboration's tool present an overall low risk of bias (Supplementary Figures 1, 2).
Figure 1. The study selection process.
Table 1. Characteristics of studies included in the meta-analysis.
Effectiveness of Wearing Masks in Preventing RVIs
Three meta-analyses were conducted according to the type of study design.
In the meta-analysis of case-control studies, 18 studies were included, and the total number of participants was 4,326. The I2 test indicated significant heterogeneity among the studies (I2 = 40.00%, P = 0.04), so a random-effects model was used to pool the data. The result suggested that wearing masks was effective in preventing RVIs (OR = 0.36, 95% CI: 0.26~0.48, P < 0.01; see Figure 2).
Figure 2. Forest plot of meta-analysis of case-control studies.
In the meta-analysis of cohort studies, 7 studies were included, and the total number of participants was 1,968. The I2 test indicated no significant heterogeneity among the studies (I2 = 11.00%, P = 0.34), so a fixed-effects model was used to pool the data. The result suggested that wearing masks was effective in preventing RVIs (RR = 0.31, 95% CI: 0.22~0.44, P < 0.01; see Figure 3).
Figure 3. Forest plot of meta-analysis of cohort studies.
In the meta-analysis of RCTs, 6 studies were included, and the total number of participants was 7,035. The I2 test indicated no significant heterogeneity among the studies (I2 = 13.00%, P = 0.33), so a fixed-effects model was used to pool the data. The result suggested that wearing masks was effective in preventing RVIs (RR = 0.66, 95% CI: 0.50~0.88, P = 0.01; see Figure 4).
Figure 4. Forest plot of meta-analysis of RCTs.
Subgroup Analyses
Three subgroup analyses based on type of RVI, type of mask, and occupation of participants were conducted respectively for every meta-analysis (Table 2).
Table 2. The results of meta-analyses.
Subgroup Analyses of Case-Control Studies
In the subgroup analysis based on type of RVI, the I2 test indicated no significant heterogeneity in every subgroup. The result showed that masks were effective in preventing SARS (OR = 0.28, 95% CI: 0.20~0.41) and COVID-19 (OR = 0.53, 95% CI: 0.37~0.77), while there was no significant effectiveness of wearing masks in preventing MERS (OR = 0.08, 95% CI: 0.004~1.41) and H1N1 (OR = 0.87, 95% CI: 0.32~2.36).
In the subgroup analysis based on type of mask, the I2 test indicated significant heterogeneity in the subgroup of common masks (I2 = 55.50%, P = 0.13) and masks not defined (I2 = 40.10%, P = 0.07). The result showed that N95 masks (OR = 0.27, 95% CI: 0.14~0.54) and common masks (OR = 0.20, 95% CI: 0.06~0.62) were both effective in preventing RVIs, while surgical masks (OR = 0.45, 95% CI: 0.20~1.05) failed to show the significant effectiveness.
In the subgroup analysis based on occupation of participants, the I2 test indicated no significant heterogeneity in each subgroup. The result showed significant effectiveness of wearing masks in preventing RVIs for both HCWs (OR = 0.29, 95% CI: 0.20~0.42) and non-HCWs (OR = 0.56, 95% CI: 0.40~0.78).
Subgroup Analyses of Cohort Studies
In the subgroup analysis based on type of RVI, the I2 test indicated significant heterogeneity in the subgroup of COVID-19 (I2 = 70.40%, P = 0.07). The result showed that masks were effective in preventing SARS (RR = 0.34, 95% CI: 0.22~0.53), MERS (RR = 0.44, 95% CI: 0.22~0.89), H1N1 (RR = 0.08, 95% CI: 0.01~0.61), and COVID-19 (RR = 0.27, 95% CI: 0.13~0.53).
In the subgroup analysis based on type of mask, the I2 test indicated significant heterogeneity in the subgroup of N95 masks (I2 = 69.30%, P = 0.07). The result showed that N95 masks (RR = 0.30, 95% CI: 0.16~0.58) and surgical masks (RR = 0.05, 95% CI: 0.00~0.97) were all effective in preventing RVIs.
In the subgroup analysis based on occupation of participants, the I2 test indicated no significant heterogeneity in each subgroup. The result showed significant effectiveness of wearing masks in preventing RVIs for both HCWs (RR = 0.30, 95% CI: 0.20~0.45) and non-HCWs (RR = 0.33, 95% CI: 0.16~0.65).
Subgroup Analyses of RCTs
In the subgroup analysis based on type of RVI, the I2 test indicated no significant heterogeneity in the subgroup of influenza not defined (I2 = 34.70%, P = 0.22). The result showed that masks were effective in preventing influenza (RR = 0.67, 95% CI: 0.49~0.93), while there was no significant effectiveness showed in other subgroups.
In the subgroup analysis based on type of mask, the I2 test indicated no significant heterogeneity in the subgroup of surgical masks (I2 = 31.80%, P = 0.21). The result showed that surgical masks (RR = 0.65, 95% CI: 0.48~0.89) were effective in preventing RVIs.
In the subgroup analysis based on occupation of participants, the I2 test indicated no significant heterogeneity in the subgroup of non-HCWs (I2 = 32.30%, P = 0.21). The result showed significant effectiveness of wearing masks in preventing RVIs for non-HCWs (RR = 0.62, 95% CI: 0.45~0.85).
Sensitivity Analysis and Publication Bias
The sensitivity analysis showed that the results of meta-analyses including case-control studies (Supplementary Figure 3), cohort studies (Supplementary Figure 4), and RCTs (Supplementary Figure 5) were all robust and reliable.
There was no significant publication bias in the meta-analysis of case-control studies, while the meta-analyses of cohort studies and RCTs were of significant publication biases. However, most subgroup analyses showed no significant publication bias (Table 2).
Discussion
In this meta-analysis, the associations between wearing masks and the risk of RVIs were analyzed, and the results showed that wearing masks can reduce the risk of RVIs overall.
In previous meta-analyses, Liang et al. (21) and Offeddu et al. (16) investigated the effectiveness of wearing masks in the prevention of RVIs, and both results showed that wearing masks could significantly reduce the risk of RVIs. The results of this study were consistent with these results. For specific type of RVIs, Li et al. (14), Chu et al. (13), and Tabatabaeizadeh et al. (15) found that mask use provided a significant effectiveness in preventing COVID-19, while Sharma et al. (17) failed to find the effectiveness.
The major transmission routes of respiratory viruses are inhalation of aerosol (≤5 μm)/droplet (>5 μm) and person-to-person contact. Aerosol/droplets with respiratory viruses can transmit to susceptible individuals when patients with RVIs are speaking, coughing, or sneezing (49–51). Masks that can filtrate aerosol/droplets provide susceptible individuals with physical protection against respiratory viruses, thus reducing the risk of RVIs. A study examining the filtration efficiency of masks for polystyrene latex microspheres sized from 0.03~2.5 μm showed that the filtration efficiency of surgical masks was 76~92%, that of N95 masks was 76~92%, and that of cloth masks with an exhaust valve was 39~65% (52). Whiley et al. (53) found that the filtration efficiency of surgical masks, N95 masks, and three-layered cotton masks was 99.3, 98.5, and 65.8%, respectively, when the size of microspheres was 2.6 μm; and that the filtration efficiency became 99.9, 99.6, and 54.4%, respectively, when the size of the microspheres was 6 μm. Patra et al. (54) examined the efficiency of some commonly used face masks in filtrating microspheres sized from 0.3~10 μm, and found out that the filtration efficiency of N95 masks, which proved to be the most effective, was 91.8%; the filtration efficiency of surgical masks was 77.8%, and the filtration efficiency of one-layered T-shirt fabric masks was 64.8% and the least effective. Nonetheless, these studies showed that masks can filtrate aerosol/droplets.
For the subgroup analyses based on type of RVI, the result showed no significant effectiveness of masks in preventing H1N1 and MERS in case-control studies, while the subgroup analysis of cohort studies showed opposite results. Moreover, the result of the subgroup analysis of RCTs showed no significant effectiveness of masks in preventing H5N1. Given that the total number of studies investigating H1N1, MERS, or H5N1 was inadequate, more studies should be conducted to make the evidence stronger. For the subgroup analyses based on type of mask, the result showed no significant effectiveness of surgical masks in case-control studies, the reason also might be that the total number of studies in the subgroup was inadequate. In contrast, there were 5 RCTs investigating the effectiveness of surgical masks, and the result showed significant effectiveness when the data of these 5 RCTs were pooled (The publication bias was not significant). Thus, it could be considered that surgical masks were effective in preventing RVIs. Based on the results of the subgroup analyses for participants occupation, it could be considered that masks were effective for both HCWs and non-HCWs.
Study Limitations
The study has some limitations. First, besides wearing masks, some participants might take other measures to prevent RVIs, such as hand hygiene, and wearing gloves/goggles/full face shields. But this information was few available. Thus, the potential impacts of these factors on the outcome could not be considered. Also, the possible influence of location and contact distance was not be analyzed. Second, in different region, the epidemic types and strength of RVIs, as well as people's living environments and habits, might be different. Unfortunately, no studies from Africa, South America, or Oceania were included in this meta-analysis, so the effectiveness of wearing masks in these areas was unknown. Moreover, the total number of studies was inadequate in some subgroups, more studies should to be conducted to make the evidence stronger. Finally, there was significant publication biases in the meta-analyses of cohort studies and RCTs. The reason might be that the number of high-quality studies was relatively inadequate.
Conclusions
Overall, wearing masks was effective in preventing RVIs, especially SARS, influenza, and COVID-19. Besides, N95 masks, surgical masks, and common masks were all effective for RVIs prevention. This suggests that people should be encouraged to wear masks when they are in a large group of people to reduce the risk of RVIs. And such Infection Prevention and Control (IPC) strategies are recommended to be implemented to mitigate the RVIs rates.
Data Availability Statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors.
Author Contributions
YWu and JY designed the study and revised the manuscript critically for important intellectual content. YWa, NQ, and YC conducted the systematic literature search and data extraction. YC conducted the statistical analyses and wrote the manuscript. All authors contributed to the article and approved the submitted version.
Funding
This work was supported by National Natural Science Foundation of China [31971138]; Natural Science Foundation of Zhejiang Province [LZ19H260001]; and Health Commission of Zhejiang Province [2022506699].
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's Note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary Material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2022.874693/full#supplementary-material
References
1. Loeb M, McGeer A, Henry B, Ofner M, Rose D, Hlywka T, et al. SARS among critical care nurses, Toronto. Emerg Infect Dis. (2004) 10:251–5. doi: 10.3201/eid1002.030838
2. Ki HK, Han SK, Son JS, Park SO. Risk of transmission via medical employees and importance of routine infection-prevention policy in a nosocomial outbreak of Middle East respiratory syndrome (MERS): a descriptive analysis from a tertiary care hospital in South Korea. BMC Pulm Med. (2019) 19:190. doi: 10.1186/s12890-019-0940-5
3. Suess T, Remschmidt C, Schink SB, Schweiger B, Nitsche A, Schroeder K, et al. The role of facemasks and hand hygiene in the prevention of influenza transmission in households: results from a cluster randomised trial; Berlin, Germany, 2009-2011. BMC Infect Dis. (2012) 12:26. doi: 10.1186/1471-2334-12-26
4. Wang X, Pan Z, Cheng Z. Association between 2019-nCoV transmission and N95 respirator use. J Hosp Infect. (2020) 105:104–5. doi: 10.1016/j.jhin.2020.02.021
5. Pei LY, Gao ZC, Yang Z, Wei DG, Wang SX, Ji JM, et al. Investigation of the influencing factors on severe acute respiratory syndrome among health care workers. Beijing Da Xue Xue Bao Yi Xue Ban. (2006) 38:271–5. doi: 10.19723/j.issn.1671-167x.2006.03.039
6. Yin WW, Gao LD, Lin WS, Gao LD, Lin WS, Du L, et al. Effectiveness of personal protective measures in prevention of nosocomial transmission of severe acute respiratory syndrome. Zhonghua Liu Xing Bing Xue Za Zhi. (2004) 25:18–22. doi: 10.3760/j.issn:0254-6450.2004.01.007
7. Scheid JL, Lupien SP, Ford GS, West SL. Commentary: physiological and psychological impact of face mask usage during the COVID-19 pandemic. Int J Environ Res Public Health. (2020) 17:6655. doi: 10.3390/ijerph17186655
8. Matuschek C, Moll F, Fangerau H, Fischer JC, Zänker K, van Griensven M, et al. Face masks: benefits and risks during the COVID-19 crisis. Eur J Med Res. (2020) 25:32. doi: 10.1186/s40001-020-00430-5
9. Li T, Liu Y, Li M, Qian X, Dai SY. Mask or no mask for COVID-19: A public health and market study. PLoS ONE. (2020) 15:e0237691. doi: 10.1371/journal.pone.0237691
10. Cowling BJ, Fung RO, Cheng CK, Fang VJ, Chan KH, Seto WH, et al. Preliminary findings of a randomized trial of non-pharmaceutical interventions to prevent influenza transmission in households. PLoS ONE. (2008) 3:e2101. doi: 10.1371/journal.pone.0002101
11. Aiello AE, Perez V, Coulborn RM, Davis BM, Uddin M, Monto AS. Facemasks, hand hygiene, and influenza among young adults: a randomized intervention trial. PLoS ONE. (2012) 7:e29744. doi: 10.1371/journal.pone.0029744
12. Vainshelboim B. Retracted: Facemasks in the COVID-19 era: a health hypothesis. Med Hypotheses. (2021) 146:110411. doi: 10.1016/j.mehy.2020.110411
13. Chu DK, Akl EA, Duda S, Solo K, Yaacoub S, Schünemann HJ. Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis. Lancet. (2020) 395:1973–87. doi: 10.1016/S0140-6736(20)31142-9
14. Li Y, Liang M, Gao L, Ayaz Ahmed M, Uy JP, Cheng C, et al. Face masks to prevent transmission of COVID-19: a systematic review and meta-analysis. Am J Infect Control. (2021) 49:900–6. doi: 10.1016/j.ajic.2020.12.007
15. Tabatabaeizadeh SA. Airborne transmission of COVID-19 and the role of face mask to prevent it: a systematic review and meta-analysis. Eur J Med Res. (2021) 26:1. doi: 10.1186/s40001-020-00475-6
16. Offeddu V, Yung CF, Low MSF, Tam CC. Effectiveness of masks and respirators against respiratory infections in healthcare workers: a systematic review and meta-analysis. Clin Infect Dis. (2017) 65:1934–42. doi: 10.1093/cid/cix681
17. Sharma SK, Mishra M, Mudgal SK. Efficacy of cloth face mask in prevention of novel coronavirus infection transmission: a systematic review and meta-analysis. J Educ Health Promot. (2020) 9:192. doi: 10.4103/jehp.jehp_533_20
18. Smith JD, MacDougall CC, Johnstone J, Copes RA, Schwartz B, Garber GE. Effectiveness of N95 respirators versus surgical masks in protecting health care workers from acute respiratory infection: a systematic review and meta-analysis. CMAJ. (2016) 188:567–74. doi: 10.1503/cmaj.150835
19. Bartoszko JJ, Farooqi MAM, Alhazzani W, Loeb M. Medical masks vs N95 respirators for preventing COVID-19 in healthcare workers: a systematic review and meta-analysis of randomized trials. Influenza Other Respir Viruses. (2020) 14:365–73. doi: 10.1111/irv.12745
20. Long Y, Hu T, Liu L, Chen R, Guo Q, Yang L, et al. Effectiveness of N95 respirators versus surgical masks against influenza: a systematic review and meta-analysis. J Evid Based Med. (2020) 13:93–101. doi: 10.1111/jebm.12381
21. Liang M, Gao L, Cheng C, Zhou Q, Uy JP, Heiner K, et al. Efficacy of face mask in preventing respiratory virus transmission: a systematic review and meta-analysis. Travel Med Infect Dis. (2020) 36:101751. doi: 10.1016/j.tmaid.2020.101751
22. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Bmj. (2021) 372:n71. doi: 10.1136/bmj.n71
23. Lichtenstein MJ, Mulrow CD, Elwood PC. Guidelines for reading case-control studies. J Chronic Dis. (1987) 40:893–903. doi: 10.1016/0021-9681(87)90190-1
24. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. (2010) 25:603–5. doi: 10.1007/s10654-010-9491-z
25. Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The cochrane collaboration's tool for assessing risk of bias in randomised trials. BMJ. (2011) 343:d5928. doi: 10.1136/bmj.d5928
26. Alraddadi BM, Al-Salmi HS, Jacobs-Slifka K, Slayton RB, Estivariz CF, Geller AI, et al. Risk factors for middle east respiratory syndrome coronavirus infection among healthcare personnel. Emerg Infect Dis. (2016) 22:1915–20. doi: 10.3201/eid2211.160920
27. Bundgaard H, Bundgaard JS, Raaschou-Pedersen DET, von Buchwald C, Todsen T, Norsk JB, et al. Effectiveness of adding a mask recommendation to other public health measures to prevent SARS-CoV-2 infection in danish mask wearers: a randomized controlled trial. Ann Intern Med. (2021) 174:335–43. doi: 10.7326/M20-6817
28. Cheng VCC, Tai JWM, Wong LMW, Chan JFW, Li IWS, To KKW, et al. Prevention of nosocomial transmission of swine-origin pandemic influenza virus A/H1N1 by infection control bundle. J Hosp Infect. (2010) 74:271–7. doi: 10.1016/j.jhin.2009.09.009
29. Chokephaibulkit K, Assanasen S, Apisarnthanarak A, Rongrungruang Y, Kachintorn K, Tuntiwattanapibul Y, et al. Seroprevalence of 2009 H1N1 virus infection and self-reported infection control practices among healthcare professionals following the first outbreak in Bangkok, Thailand. Influenza Other Respir Viruses. (2013) 7:359–63. doi: 10.1111/irv.12016
30. Doung-Ngern P, Suphanchaimat R, Panjangampatthana A, Janekrongtham C, Ruampoom D, Daochaeng N, et al. Case-Control study of use of personal protective measures and risk for SARS-CoV 2 infection, Thailand. Emerg Infect Dis. (2020) 26:2607–16. doi: 10.3201/eid2611.203003
31. Guo X, Wang J, Hu D, Wu L, Gu L, Wang Y, et al. Survey of COVID-19 disease among orthopaedic surgeons in Wuhan, People's Republic of China. J Bone Joint Surg Am. (2020) 102:847–54. doi: 10.2106/JBJS.20.00417
32. Heinzerling A, Stuckey MJ, Scheuer T, Xu K, Perkins KM, Resseger H, et al. Transmission of COVID-19 to health care personnel during exposures to a hospitalized patient - Solano County, California, February 2020. MMWR Morb Mortal Wkly Rep. (2020) 69:472–6. doi: 10.15585/mmwr.mm6915e5
33. Jaeger JL, Patel M, Dharan N, Hancock K, Meites E, Mattson C, et al. Transmission of 2009 pandemic influenza A (H1N1) virus among healthcare personnel-Southern California, 2009. Infect Control Hosp Epidemiol. (2011) 32:1149–57. doi: 10.1086/662709
34. Khalil MM, Alam MM, Arefin MK, Chowdhury MR, Huq MR, Chowdhury JA, et al. Role of personal protective measures in prevention of COVID-19 spread among physicians in Bangladesh: a multicenter cross-sectional comparative study. SN Compr Clin Med. (2020) 2:1733–39. doi: 10.1007/s42399-020-00471-1
35. Larson EL, Ferng YH, Wong-McLoughlin J, Wang S, Haber M, Morse SS. Impact of non-pharmaceutical interventions on URIs and influenza in crowded, urban households. Public Health Rep. (2010) 125:178–91. doi: 10.1177/003335491012500206
36. Ma HJ, Wang HW, Fang LQ, Jiang JF, Wei MT, Liu W, et al. A case-control study on the risk factors of severe acute respiratory syndromes among health care workers. Zhonghua Liu Xing Bing Xue Za Zhi. (2004) 25:741–4. doi: 10.3760/j.issn:0254-6450.2004.09.002
37. MacIntyre CR, Seale H, Dung TC, Hien NT, Nga PT, Chughtai AA, et al. A cluster randomised trial of cloth masks compared with medical masks in healthcare workers. BMJ Open. (2015) 5:e006577. doi: 10.1136/bmjopen-2014-006577
38. Nishiura H, Kuratsuji T, Quy T, Phi NC, Van Ban V, Ha LE, et al. Rapid awareness and transmission of severe acute respiratory syndrome in Hanoi French Hospital, Vietnam. Am J Trop Med Hyg. (2005) 73:17–25. doi: 10.4269/ajtmh.2005.73.17
39. Nishiyama A, Wakasugi N, Kirikae T, Quy T, Ha le D, Ban VV, et al. Risk factors for SARS infection within hospitals in Hanoi, Vietnam. Jpn J Infect Dis. (2008) 61:388–90.
40. Reynolds MG, Anh BH, Thu VH, Montgomery JM, Bausch DG, Shah JJ, et al. Factors associated with nosocomial SARS-CoV transmission among healthcare workers in Hanoi, Vietnam, 2003. BMC Public Health. (2006) 6:207. doi: 10.1186/1471-2458-6-207
41. Scales DC, Green K, Chan AK, Poutanen SM, Foster D, Nowak K, et al. Illness in intensive care staff after brief exposure to severe acute respiratory syndrome. Emerg Infect Dis. (2003) 9:1205–10. doi: 10.3201/eid0910.030525
42. Seto WH, Tsang D, Yung RW, Ching TY, Ng TK, Ho M, et al. Effectiveness of precautions against droplets and contact in prevention of nosocomial transmission of severe acute respiratory syndrome (SARS). Lancet. (2003) 361:1519–20. doi: 10.1016/S0140-6736(03)13168-6
43. Teleman MD, Boudville IC, Heng BH, Zhu D, Leo YS. Factors associated with transmission of severe acute respiratory syndrome among health-care workers in Singapore. Epidemiol Infect. (2004) 132:797–803. doi: 10.1017/S0950268804002766
44. Tuan PA, Horby P, Dinh PN, Mai LT, Zambon M, Shah J, et al. SARS transmission in Vietnam outside of the health-care setting. Epidemiol Infect. (2007) 135:392–401. doi: 10.1017/S0950268806006996
45. Wang Y, Tian H, Zhang L, Zhang M, Guo D, Wu W, et al. Reduction of secondary transmission of SARS-CoV-2 in households by face mask use, disinfection and social distancing: a cohort study in Beijing, China. BMJ Glob Health. (2020) 5:e002794. doi: 10.1136/bmjgh-2020-002794
46. Wu J, Xu F, Zhou W, Feikin DR, Lin CY, He X, et al. Risk factors for SARS among persons without known contact with SARS patients, Beijing, China. Emerg Infect Dis. (2004) 10:210–6. doi: 10.3201/eid1002.030730
47. Zhang HX, Liu F, Xiao S, Feng YB, Liu YR, Fu ZW, et al. A 1:1 ratio case-control study on coronavirus disease 2019. J Hainan Med Univ. (2021) 27:721–8. doi: 10.12659/MSM.929701
48. Zhang Y, Seale H, Yang P, MacIntyre CR, Blackwell B, Tang S, et al. Factors associated with the transmission of pandemic (H1N1) 2009 among hospital healthcare workers in Beijing, China. Influenza Other Respir Viruses. (2013) 7:466–71. doi: 10.1111/irv.12025
49. Kutter JS, Spronken MI, Fraaij PL, Fouchier RA, Herfst S. Transmission routes of respiratory viruses among humans. Curr Opin Virol. (2018) 28:142–51. doi: 10.1016/j.coviro.2018.01.001
50. Clase CM, Fu EL, Joseph M, Beale RCL, Dolovich MB, Jardine M, et al. Cloth masks may prevent transmission of COVID-19: an evidence-based, risk-based approach. Ann Intern Med. (2020) 173:489–91. doi: 10.7326/M20-2567
51. Otter JA, Donskey C, Yezli S, Douthwaite S, Goldenberg SD, Weber DJ. Transmission of SARS and MERS coronaviruses and influenza virus in healthcare settings: the possible role of dry surface contamination. J Hosp Infect. (2016) 92:235–50. doi: 10.1016/j.jhin.2015.08.027
52. Shakya KM, Noyes A, Kallin R, Peltier RE. Evaluating the efficacy of cloth facemasks in reducing particulate matter exposure. J Expo Sci Environ Epidemiol. (2017) 27:352–7. doi: 10.1038/jes.2016.42
53. Whiley H, Keerthirathne TP, Nisar MA, White MAF, Ross KE. Viral filtration efficiency of fabric masks compared with surgical and N95 masks. Pathogens. (2020) 9:762. doi: 10.3390/pathogens9090762
Keywords: masks, effectiveness, respiratory viral infections, meta-analysis, systematic review
Citation: Chen Y, Wang Y, Quan N, Yang J and Wu Y (2022) Associations Between Wearing Masks and Respiratory Viral Infections: A Meta-Analysis and Systematic Review. Front. Public Health 10:874693. doi: 10.3389/fpubh.2022.874693
Received: 12 February 2022; Accepted: 30 March 2022;
Published: 27 April 2022.
Edited by:
Bijaya Kumar Padhi, Post Graduate Institute of Medical Education and Research (PGIMER), IndiaReviewed by:
Zhanzhan Li, Central South University, ChinaYongjun Chen, Shangdong University of Traditional Chinese Medicine, China
Shaonan Liu, Guangdong Provincial Hospital of Chinese Medicine, China
Copyright © 2022 Chen, Wang, Quan, Yang and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Yinyin Wu, 48037663@qq.com; Jun Yang, gastate@zju.edu.cn