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Systematic Review

Evidence of Face Masks and Masking Policies for the Prevention of SARS-CoV-2 Transmission and COVID-19 in Real-World Settings: A Systematic Literature Review

1
School of Public Health, San Diego State University, San Diego, CA 92123, USA
2
Institute for Behavioral and Community Health (IBACH), San Diego, CA 92123, USA
3
Laura Rodriguez Research Institute, Family Health Centers of San Diego, San Diego, CA 92101, USA
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2025, 22(10), 1590; https://doi.org/10.3390/ijerph22101590
Submission received: 27 June 2025 / Revised: 11 October 2025 / Accepted: 13 October 2025 / Published: 20 October 2025

Abstract

Objectives: Prevention of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the disease COVID-19 is a public health priority. The efficacy of non-pharmaceutical interventions such as wearing face masks to prevent SARS-CoV-2 infection has been well established in controlled settings. However, evidence for the effectiveness of face masks in preventing SARS-CoV-2 transmission within real-world settings is limited and mixed. The present systematic review evaluated the effectiveness of face mask policies and mask wearing to prevent SARS-CoV-2 transmission and COVID-19 in real-world settings. Methods: Following PRISMA guidelines, scientific databases, and gray literature, were searched through June 2023. Inclusion criteria were as follows: (1) studies/reports written in or translated to English; (2) prospectively assessed incidence of SARS-CoV-2 or COVID-19; (3) assessed the behavior and/or policy of mask-wearing; and (4) conducted in community/public settings (i.e., not laboratory). Studies were excluded if they did not parse out data specific to the effect of mask wearing (behavior and/or policy) and subsequent SARS-CoV-2 transmission or COVID-19 disease or if they relied solely on statistical models to estimate the effects of mask wearing on transmission. A total of 2616 studies were initially identified, and 470 met inclusion and exclusion criteria for full-text review. The vote counting method was used to evaluate effectiveness, and risk of bias was assessed using JBI critical appraisal tools. Results: A total of 79 unique studies met the final inclusion criteria, and their data were abstracted and evaluated. Study settings included community/neighborhood settings (n = 34, 43%), healthcare settings (n = 30, 38%), and school/universities (n = 15, 19%). A majority of studies (n = 61, 77%) provided evidence to support the effectiveness of wearing face masks and/or face mask policies to reduce the transmission of SARS-CoV-2 and/or prevention of COVID-19. Effectiveness of mask wearing did not vary substantially by study design (67–100%), type of mask (77–100%), or setting (80–91%), while 85% of masking policies specifically reported a benefit. Conclusions: This systematic literature review supports public health recommendations and policies that encourage the public to wear face masks to reduce the risk of SARS-CoV-2 infection and COVID-19 in multiple real-world settings. Effective communication strategies are needed to encourage and support the use of face masks by the general public, particularly during peak infection cycles.

1. Introduction

Since the World Health Organization (WHO) declared COVID-19 a pandemic in March of 2020 [1], the U.S. and other countries have experienced several waves of respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, which put great strain on hospitals and the healthcare system [2]. SARS-CoV-2 is responsible for the disease COVID-19, and in 2020, COVID-19 was the third leading cause of death in the U.S. and the number one cause of death for people aged 45–84 years [3]. As of June 2023, there have been over 6.9 million reported deaths globally due to COVID-19, and minoritized/underserved populations have been disproportionately affected [3].
Public health recommendations for the prevention of SARS-CoV-2 infection include vaccination, masking, social distancing, avoiding crowds and poorly ventilated spaces, frequent washing of hands, and disinfecting high touch surfaces [4]. Nonpharmaceutical interventions (NPIs), which are actions that persons and communities can take to help slow the spread of respiratory virus infections, are often the most readily available interventions to help slow the transmission of infectious viruses in communities [5]. Wearing personal protective equipment (PPE), such as face masks, has long been used in previous pandemics (e.g., 1920 influenza), epidemics, and outbreaks as an effective strategy to protect against the spread of respiratory infectious disease [6]. Despite ample evidence for the efficacy and effectiveness of PPE to prevent the transmission of respiratory infections (e.g., seasonal influenza, tuberculosis, etc.), the adoption of these preventive measures by the general public has varied widely. The emergence of increasingly infectious variants such as Delta and Omicron renewed questions about the role of masks to prevent the spread of SARS-CoV-2 [7]. These variants contain mutations that affect transmissibility and virulence, potentially impacting the efficacy and effectiveness of vaccines, therefore increasing the need to enact NPIs to help contain viral spread, particularly during peak outbreaks [8].
Enacting policies that require people to use face masks in public to curb the spread of SARS-CoV-2 has been a politicized issue [9]. Misinformation surrounding the efficacy and effectiveness of face masks can threaten the health of the public. At the height of the COVID-19 pandemic, a subset of the U.S. population expressed strong opposition to wearing masks and mask mandates through social media channels (e.g., Twitter) [10]. Some of the most common reasons cited in opposition to wearing masks were the belief that wearing masks was not necessary for certain groups (e.g., children and healthy individuals), mask mandates infringed upon personal liberty, and that masks were uncomfortable and not effective at preventing SARS-CoV-2 infection [10]. Thus, policymakers and public health officials need better quality evidence for the effectiveness of masking policies and the use of masks to provide evidence-based guidance to the public [11].
Previous literature reviews show that masks and facial coverings are efficacious at reducing the risk of SARS-CoV-2 transmission in controlled laboratory settings [11,12,13]; however, the effectiveness of masks in real-world settings (e.g., schools, community settings, transportation, and hospitals) have not been well documented. The effectiveness of masks in real-world settings are impacted by multiple factors including the level of adherence, the mask type, and other environmental contexts [14]. Overall, findings regarding the effectiveness of mask wearing in community settings remain limited to date. Leech et al. [15] used a Bayesian hierarchical model approach across 92 regions and found that self-reported mask wearing was associated with a 25% reduction in SARS-CoV-2 transmission, although mask mandates themselves were not associated with transmission rates. In contrast, Bundgaard et al. [16] reported no significant difference in SARS-CoV-2 infection rates between participants who wore masks and those who did not. One of the earliest systematic reviews in community settings provided promising preliminary evidence for the effectiveness of mask wearing; however, the evidence was limited due to the small number of studies available at that time [17]. These mixed results highlight the need for an updated and synthesized review of the effectiveness of mask policies and wearing face masks in non-controlled, real-world settings. The purpose of this review was to evaluate the effectiveness of mask-wearing and masking policies for the prevention of SARS-CoV-2 transmission and COVID-19 in multiple real-world settings.

2. Methods

2.1. Data Sources

A systematic search of electronic databases was conducted in SCOPUS, PubMed, and CINAHL. Gray literature, such as conference abstracts, county data, and government reports, was also identified through ProQuest, MedRxiv, BioRxiv, and Google Scholar. Key terms were used to capture the relevant literature on making policies, mask wearing, and SARS-CoV-2 transmission and COVID-19. Table 1 summarizes the key terms used for this review. The study protocol was registered in the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY202460011).

2.2. Study Selection

Study eligibility criteria were as follows: (1) written in or translated to English; (2) prospectively assessed incidence of SARS-CoV-2 or COVID-19; (3) assessed the behavior and/or policy of mask wearing; and 4) conducted in community/public settings such as healthcare settings, worksites, and schools. Studies were excluded if (1) they did not parse out data specific to the effect of mask wearing (behavior and/or policy) and subsequent SARS-CoV-2 transmission or COVID-19; or (2) they relied solely on statistical models to estimate the effects of mask wearing on transmission (i.e., no primary data were collected on mask-wearing behavior or transmission). The time span for the literature search included all years available in the databases up to June 2023.
This study followed the structure and recommendations for reporting a systematic literature review as outlined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [18]. Searches were uploaded to the Rayyan platform (Cambridge, MA, USA), which was also used to manage reviewer ratings and remove duplicate studies. Database searches and gray literature searches were conducted by two independent reviewers. After identifying articles from each database, duplicates were identified and removed before screening for inclusion criteria. A total of 2616 studies were screened and evaluated first by title and abstract for meeting inclusion and exclusion criteria by a primary and secondary reviewer. Discrepancies between reviewers were resolved after a discussion following the initial screening. Articles that met criteria in phase 1 (n = 470) underwent full-text review (phase 2) by two independent reviewers. Final inclusion of articles was determined after the full-text review. The included articles were also explored for works cited by using the backward referencing technique to search for additional literature that met the inclusion criteria.

2.3. Data Extraction

For all articles that met the inclusion and exclusion criteria (n = 79), relevant data and study characteristics were extracted by the two independent reviewers following a standardized data abstraction protocol. These included author, year, country, study design, outcome measures, study sample, main finding, adherence, duration, and study limitations.

2.4. Risk of Bias Assessment and Outcome Analysis

Two independent reviewers assessed the quality of included studies using Joanna Briggs Institute (JBI) critical appraisal tools [19]. A third reviewer was consulted when discrepancies were identified. JBI critical appraisal checklists are considered suitable and the most preferred for scoring quasi-experimental, observational, and cross-sectional study designs, which were the majority of studies included in this review [20]. Checklists specific to study design were used to evaluate criteria such as description of clinical condition, validity of measurement of disease outcome, appropriateness of statistical approaches, and mitigation of confounders. Each JBI risk of bias criterion for each study was rated as either red = “no”, green = “yes”, or yellow = “unclear.” Risk of bias was ranked as high when the study was rated with ≤49% of “yes” scores, moderate when the study was rated between 50 and 79% of “yes” scores, and low when the study was rated with ≥80% of “yes” scores.
Due to the high heterogeneity of statistical methods and study designs in the included studies, a vote counting methodology was used in lieu of a meta-analysis to summarize the direction of effect for masking behavior and/or masking policies for the prevention of SARS-CoV-2 transmission and COVID-19 disease [21]. The primary objective of this approach was to compare studies indicating a ‘benefit’ (i.e., prevention of SARS-CoV-2 transmission or COVID-19) with those indicating a potential ‘harm’ (i.e., increased SARS-CoV-2 transmission or COVID-19). Two independent reviewers read through each study to identify the reported effect estimate as well as the observed direction of effect of a masking policy and/or mask wearing to develop a standardized binary metric. The number of effects demonstrating benefit was then compared to the number of effects indicating harm, allowing for a quantitative assessment of the overall effectiveness of mask-wearing behavior and/or policies. The certainty of evidence was graded by classifying SARS-CoV-2 transmission and COVID-19 results and rating the evidence for each outcome in the Gradepro GDT Standard version.

3. Results

Results of the article screening process are presented in the PRISMA flow diagram (Figure 1). A total of 2616 articles and gray literature were identified, and 79 met the final criteria for inclusion and data abstraction. Table 2 summarizes key characteristics for each study included in this review. A greater proportion of studies (47%) were from the United States [22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58], followed by China (10%) [59,60,61,62,63,64,65,66], Germany (8%) [67,68,69,70,71,72], Japan (4%) [73,74,75], Spain (3%) [76,77], and other countries that had two or less studies (29%) [16,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99]. SARS-CoV-2 infection was primarily identified through lab-verified test results such as polymerase chain reaction rapid (PCR) antigen tests (n = 56) or serological tests (n = 4), followed by self-report (n = 6) and aggregate community-level data reports of COVID-19 cases (n = 13).

3.1. Study Design and Vote Counting Results

Of the 79 studies, 34% (n = 27) were prospective or retrospective cohort studies, 29% (n = 23) were cross-sectional studies, 13% (n = 10) were case–control studies, 14% (n = 11) were case reports, 6% (n = 5) were quasi-experimental studies, and 4% (n = 3) were randomized controlled studies (RCTs). Overall, 77% (n = 61) of studies reported a beneficial association or effect of mask wearing or policy on SARS-CoV-2 transmission or COVID-19 disease (Table 3). Among the cross-sectional studies, 87% (n = 20) reported a beneficial association of mask wearing or policy on SARS-CoV-2 transmission or COVID-19. Ninety percent (n = 9) of case–control studies reported a beneficial effect of mask wearing or policy. Of the prospective cohort studies, 93% (n = 14) reported a benefit from mask wearing or policy, and of the retrospective cohort studies, 67% (n = 8) reported a benefit to mask wearing or policy. Lastly, all the quasi-experimental and RCT studies reported a benefit to mask wearing and preventing the spread of SARS-CoV-2 transmission or COVID-19 disease (n = 8). Most of the case report studies did not report sufficient information to determine whether mask wearing or policy provided any benefits or harm (82%, n = 9).

3.2. Type of Mask

There was high variability in the types of masks used in the studies that were evaluated (e.g., surgical, cloth, N-95, FFP2, and KF94 respirator). Of the total 79 included studies, 82% (n = 65) assessed various combinations of types of masks (e.g., two or more types). Among these studies, 77% (n = 50) found masks to be beneficial in preventing SARS-CoV-2 transmission or COVID-19 disease, 6% (n = 4) found no benefit, and 17% (n = 11) did not report sufficient data to determine the effect (Table 3). The remaining 18% (n = 14) of studies assessed either surgical masks (n = 10), N-95s (n = 3), or FFP2s (n = 1). Of the 10 studies that assessed surgical masks, 80% (n = 8) found this type of mask to be beneficial, one found no benefit, and one did not provide sufficient data to determine the effect (Table 3). All studies assessing N-95 masks (n = 3) and the single study on FFP2 masks reported them to be beneficial in reducing SARS-CoV-2 transmission.

3.3. Settings

3.3.1. Community

A greater proportion of the studies occurred in community settings (n = 34, 43%) (Table 2). Community settings included studies conducted in neighborhood settings (n = 23), aircraft (n = 3), work offices/businesses (n = 2), nightclubs/music festivals (n = 2), sports facilities (n = 1), hair salons (n = 1), community markets (n = 1), or camps (n = 1). Among the 34 community studies, 91% (n = 31) found face masks to be beneficial in preventing SARS-CoV-2 transmission, 6% (n = 2) found no benefit, and 3% (n = 1) did not report sufficient data to determine an association. Of these studies, 28 (82%) examined various types of masks or did not specify the mask type; within this group, 25 (89%) found that mask use reduced transmission. Six studies (18%) specifically assessed surgical, N-95, FFP2, or two-layer cloth masks, and five (83%) demonstrated effectiveness in preventing transmission.
Four different outcome measures were used to assess SARS-CoV-2 infection and COVID-19 in community and neighborhood settings. Symptomatic laboratory-confirmed COVID-19 was the most common method used in 23 (68%) studies, with masks shown to be effective in 21 (91%) of them. Aggregate community transmission was assessed in seven studies (20%), in which five (71%) found masks to be protective. Two studies (6%) relied on participants’ self-reported laboratory-confirmed infection, and all reported a protective effect of mask use. Finally, SARS-CoV-2 seroconversion was evaluated in two studies (6%), with both showing benefit.

3.3.2. Healthcare

A total of 30 studies (38%) took place in a healthcare setting (Table 2). Healthcare settings included public hospitals (n = 23), healthcare networks (n = 2), dental settings (n = 1), residential aged-care facilities (i.e., nursing home) (n = 1), tertiary care medical centers (n = 1), public health centers (n = 1), and Veteran’s Affairs (VA) healthcare centers (n = 1). Among these studies, 70% (n = 21) found facemasks or mask policies to be beneficial in preventing SARS-CoV-2 transmission or COVID-19 disease, whereas one found there to be no benefit. Additionally, 27% (n = 8) of studies did not report sufficient data to determine the association between face mask wearing and COVID-19. Of these studies, 16 (53%) assessed masks that included surgical, N-95, FFP2, FFP2, disposable, and KF94 respirators, and 10 (63%) of these studies reported the masks to prevent the transmission of SARS-CoV-2. Fourteen studies examined various masks or did not specify what kinds of masks were assessed. Twelve (86%) of the various or not specified masks in a community setting helped reduce the transmission of SARS-CoV-2.
Three outcome measures were used to assess SARS-CoV-2 infection and COVID-19 in healthcare settings. The most common was symptomatic laboratory-confirmed COVID-19, reported in 26 studies (74%), with masks shown to be effective in 17 (65%) of them. Two studies (7%) relied on participants’ self-reported laboratory-confirmed infection, and all reported a protective effect of mask use. Finally, SARS-CoV-2 seroconversion was evaluated in two studies (7%), with both showing benefit.

3.3.3. Schools/Universities

Few studies took place in school settings (n = 15; 19%) (Table 2), which included K-12 schools (n = 12), classrooms (n = 1), universities (n = 1), and childcare programs (n = 1). Among these studies, 80% (n = 12) found facemasks to be beneficial in preventing SARS-CoV-2 transmission or COVID-19, 13% (n = 2) found no benefit, and 7% (n = 1) did not report sufficient data to determine an association. Of these studies, 14 (93%) examined various types of masks or did not specify the mask type; within this group, 10 (71%) found that masks reduced transmission. One study (7%) specifically assessed FFP2 masks and found that they demonstrated effectiveness in preventing transmission.
Three different outcome measures were used to assess SARS-CoV-2 and COVID-19 in school and university settings. Symptomatic laboratory-confirmed COVID-19 was used in seven (47%) studies, with masks shown to be effective in four (57%) of them. The second outcome measure was aggregate community transmission, which was used in six studies (40%), of which all found masks to be protective. Finally, two studies (13%) relied on participants’ self-reported laboratory-confirmed infection, and both reported a protective effect of mask use.

3.3.4. Mask Mandates and Policies

Thirteen studies [25,28,29,30,31,32,34,37,42,49,55,70,94] specifically assessed the effectiveness of mask mandates and policies on COVID-19 outcomes (e.g., transmission rates, hospitalizations, and deaths) across statewide, county-level, and school settings. Overall, 85% (11 of 13) of studies demonstrated a beneficial effect in the prevention of COVID-19. Approximately 100 days after implementation, U.S. statewide mask mandates were reported to be associated with a 1.1% decrease in county-level COVID-19 cases [34]. In Kansas, counties that implemented mask mandates observed a decrease (mean decrease = 0.08 cases per 100,000 per day) in COVID-19 incidence, while those without mask mandates observed an increase (mean increase = 0.11 cases per 100,000 per day) [55]. Multiple studies in the U.S. and Germany found that mask mandates implemented in K-12 schools were associated with lower COVID-19 infection and transmission rates [31,37,49,70]. One observation study conducted across 61 U.S. school districts found that those with optional masking policies had a 3.6 times higher rate of secondary COVID-19 transmission [28]. However, one study did not find an association between the Texas Statewide Mandate (GA-29) and reductions in COVID-19 hospitalization rates or incidence [25]. Another study analyzed COVID-19 data across 35 European countries and found that countries that complied more with mask mandates did not have lower COVID-19 incidence rates [85].

3.4. Risk of Bias Assessment and Quality of Evidence

Table 4, Table 5, Table 6, Table 7, Table 8 and Table 9 show the risk of bias assessment across all studies included. Six separate JBI checklists were used to assess bias based on study design. Risk of bias was classified as high in 3 studies (3.8%), moderate in 31 studies (39.2%), and low in 45 studies (57%). Of the 11 case reports, 55% were classified as low risk of bias, while 45% were classified as moderate risk of bias due to insufficient description of adverse events (Table 4). Most (88%) of the quasi-experimental and RCT studies were classified as moderate or high bias due to unclear allocation procedures, lack of blinding, and the inadequate description of follow-up procedures to minimize dropout (Table 5 and Table 9). Of the case–control studies, 70% were rated as low risk of bias (Table 6). Fifty-six percent of cohort studies were classified as low risk of bias, and most were reliable in the measurement of outcomes, as they were laboratory-confirmed results (Table 7). Thirteen out of twenty-three (57%) cross-sectional studies were rated as low risk of bias (Table 8).
Table 10 summarizes the quality of evidence for four types of COVID-19 outcomes: (1) symptomatic laboratory-confirmed COVID-19, (2) self-reported laboratory-confirmed COVID-19, (3) SARS-CoV-2 seroconversion, and (4) aggregate community-level incidence (rt-qPCR). For all outcomes, the level of certainty for the evidence was low due to a high number of non-randomized studies and the number of studies with moderate to high risk of bias.

4. Discussion

Results of this systematic review demonstrate consistent evidence (77% of all studies), supporting that wearing a facemask and masking policies are effective at prevention and reducing the risk of SARS-CoV-2 transmission or COVID-19 disease across various real-world settings. Mask wearing was reported to reduce SARS-CoV-2 transmission across multiple community spaces (e.g., markets, workplaces, and salons), healthcare environments, and schools. These findings provide evidence that masking is an important and practical strategy to reduce transmission outside of controlled laboratory conditions. The results of this review are consistent with previous systematic reviews and meta-analyses [17,100,101,102]. One previous meta-analysis demonstrated a pooled relative risk of 0.12 (i.e., risk reduction of 88%), and another study reported an odds ratio of 0.38 for risk of SARS-CoV-2 infection when masking policies were in place [101,102]. Another review conducted only in cohort and case–control studies found that wearing a cloth mask decreased the odds of COVID-19 regardless of mask type [103]. The results of the present systematic review builds on these previous studies [17] and provides additional evidence for the benefits of face masks and masking policies to reduce SARS-CoV-2 transmission and COVID-19 disease specifically in real-world settings. This is particularly important given that the public’s adherence to wearing masks and the enforcement of mask wearing can vary widely, which would lower the expected effect of the policy. Yet, the results from this review show that 85% (11 of 13) of studies that focused on mask policies demonstrated a beneficial effect in preventing SARS-CoV-2 and COVID-19 disease. Thus, these findings support the external validity and generalizability of previous laboratory-based studies for the benefits of mask wearing to prevent SARS-CoV-2 infection and COVID-19 [100]. These results can be used to develop and support future public health messaging campaigns to address respiratory disease outbreaks, epidemics, and pandemics. Public health messaging that emphasizes positive framing for mask wearing such as promoting community togetherness and community unity resonate better with the general public compared to messages focused on fear or policies that may be perceived as overly intrusive [104].
This systematic review included studies of various designs, types of masks, and community settings to evaluate the evidence of effectiveness of mask wearing and masking policies. The proportion of studies demonstrating a benefit for mask wearing did not vary greatly by study design (67–100%), type of mask (77–100%), or setting (80–91%), while 85% of masking policies specifically reported a benefit. This level of consistent and protective effects of mask wearing and masking policies across study characteristics provides strong empirical evidence for the real-world effectiveness of masking recommendations to reduce the spread of SARS-CoV-2 and COVID-19 disease outside controlled settings. Importantly, the risk of bias ratings were classified as low for 57% of included studies. This suggests that the evidence from this systematic review can be interpreted as mostly reliable with moderate to high validity.
It is important to note that not all studies demonstrate a clear benefit of wearing face masks for the prevention of SARS-CoV-2 infection in community settings. In this systematic literature review, five studies (6%) did not demonstrate a clear protective effect. There are several potential explanations for these results. Sasser et al. [46] found no statistically significant association between COVID-19 incidence and face mask use among high school sports participants. This may be partially explained by a relatively low COVID-19 community prevalence during the time of the study. Likewise, April et al. [25] did not find that a mask mandate reduced SARS-CoV-2 transmission. It is also possible that mobility-restricting policies (i.e., stay-at-home orders) may have had a larger effect on reducing transmission than wearing masks in community settings. In these studies, data on self-reported mask wearing were not available, which may have limited the ability to evaluate the true effect of masking compared to other mitigation measures. Key study limitations included missing data and variable adherence to mask wearing, which can reduce the ability to detect an intervention effect. Notably, a previous Cochrane review concluded that N95 masks had little impact on the prevention of viral respiratory illness [105]. However, the studies included in the review demonstrated high variability in methodology and data quality, which can increase the risk of bias towards null findings [105]. These factors limit the ability to produce reliable estimates of effectiveness in community contexts. In summary, key methodological limitations among studies with null results may partially explain the non-significant findings for the effectiveness of mask wearing on the prevention of SARS-CoV-2 transmission and COVID-19 in community settings. Future research should address these methodological limitations to provide more accurate and reliable estimates of effectiveness.

Strengths and Limitations

This review followed a rigorous and systematic approach using PRISMA guidelines to identify and evaluate relevant studies. Two independent reviewers followed a strict protocol for assessing inclusion/exclusion criteria and subsequently abstracting study data. The Rayyan study management platform and the JBI risk of bias appraisal tools provided standardized methods to manage and evaluate studies. However, a meta-analysis was not conducted due to the high heterogeneity of settings, types of masks, study designs, statistical methods, and outcome measures used (e.g., infection, symptomology) across studies. Meta-analyses are not recommended when there is this level of heterogeneity. Instead, the vote counting method is recommended as an alternative to meta-analysis, which allows for the identification of patterns (direction of results) across different studies. Several studies included in this review lacked information on the community’s adherence to wearing face masks, the specific the type of masks used, and there were inconsistencies in the type of incidence measure (SARS-CoV-2 vs. COVID-19 disease). These limitations make it difficult to more precisely evaluate the effectiveness of masking policies and mask wearing. Furthermore, only three randomized controlled study trials were identified. Although randomized controlled studies can provide stronger evidence of effectiveness and external validity, these study designs can also raise ethical concerns in the context of a new and deadly respiratory disease, such as COVID-19, where randomizing people or communities to not wear face masks may be considered unethical. Lastly, studies written or translated to a language other than English were not included. This may potentially bias results if the excluded studies reported different or contrary results to those studies that were included in this review.

5. Conclusions

Evidence from this systematic literature review supports that masking policies and mask wearing are beneficial to prevent and reduce the risk of SARS-CoV-2 infections and COVID-19 disease in various real-world settings. Importantly, relative to other recommendations (such as limiting travel, limiting group gatherings), wearing a face mask remains one of the most feasible, accessible, and effective non-pharmacologic public health interventions to prevent the spread of SARS-CoV-2. Given the varying adherence to masking from the public, there is a need to improve public health messaging to address misinformation and barriers to wearing masks. Reducing barriers to wearing masks can include providing high quality masks to those who otherwise do not have access to them or would not actively seek to obtain one on their own and by creating positive and supportive social environments that support mask wearing (i.e., depoliticizing and de-stigmatizing mask use).

Author Contributions

N.C.C. conceptualized the current study and made substantial contributions to data acquisition, writing, and revision of the work. S.S. assisted with acquisition of data, risk of bias assessment, and revision of paper drafts. K.K. assisted with acquisition of data, risk of bias assessment, and revision of paper drafts. J.M.F. led the acquisition of data, interpretation, and drafting of the manuscript. P.D. assisted with acquisition of data, risk of bias assessment, and revision of paper drafts. E.T.H. and C.M.-D. interpreted study findings and contributed to revisions of paper drafts. J.G.G., C.B.R. and J.P.E. all interpreted study findings and substantively revised initial and final drafts of the paper. All authors have read and agreed to the published version of the manuscript.

Funding

Dr. Crespo received support from Family Health Centers of San Diego’s Scientist in Residence Program sponsored by The Conrad Prebys Foundation. Administrative and (or) IT support was provided by the SDSU HealthLINK Endowment (S21 MD010690).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data from the current study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. PRISMA diagram.
Figure 1. PRISMA diagram.
Ijerph 22 01590 g001
Table 1. List of key search terms.
Table 1. List of key search terms.
“SARS-CoV-2”[MeSH Terms] OR “SARS-CoV-2”[All Fields] OR “COVID”[All Fields] OR “COVID-19”[MeSH Terms] OR “COVID-19”[All Fields]) AND (“masks”[MeSH Terms] OR “masks”[All Fields] OR “mask”[All Fields]) AND (“transmissibility”[All Fields] OR “transmissible”[All Fields] OR “transmissibilities”[All Fields] OR “transmissibility”[All Fields] OR “transmissible”[All Fields] OR “transmissibles”[All Fields] OR “transmission”[MeSH Subheading] OR “transmission”[All Fields] OR “transmissions”[All Fields]
Table 2. Included studies.
Table 2. Included studies.
Author (Year)Study DesignCountryStudy PurposeStudy SampleSettingMask TypeMeasurement of COVID-19Duration
Abaluck et al. (2022) [78]Randomized Controlled TrialBangladeshTo conduct a cluster-randomized trial that handed out masks and conducted a range of mask-wearing promotional activitiesRural Bangladesh residents Mosques, markets, the main entrance roads to villages, and tea stallsVariousSeroprevalence; blood sampleNovember 2020–April 2021
Adawee et al. (2021) [22]Cross SectionalUnited StatesTo survey commonalities among HCW who tested positive for COVID-19 and to evaluate the effectiveness of the organizational intervention to require HCW to wear masks throughout their shiftHCW who tested positive for COVID-19 from the first positive test, which occurred 18 March 2020, to the last known positive test at the time of analysis, which occurred 6 May 2020 (n = 40), were includedHospitalNot specifiedPositive COVID-19 test; lab testMarch–May 2020
Sertcelik (2023) [79] Case–ControlTurkeyTo evaluate the risk factors for COVID-19 in HCWs and the effectiveness of the measures taken for protectionHCWs; cases had a positive test, and each case matched with 3 controls who worked in the same unit at the time of the RT-PCR test of the case, had no symptoms, and tested negative2 hospital buildings of the University in Ankara, TurkeyVariousPositive SARS-CoV-2 test; naso-oropharyngeal sampleMarch 2020–May 2020
Ambrosch et al. (2020) [67]Quasi-ExperimentalGermanyTo investigate the extent to which the introduction of a strict hygiene bundle including a general mask requirement has an impact on the SARS-CoV-2 nosocomial rate in the pandemic environmentAll inpatients from a maximum care hospital in Regensburg (Bavaria)HospitalSurgicalSARS-CoV-2 infection; lab testMarch 2020–June 2020
Andrejko et al. (2021) [24]Case–ControlUnited StatesTo address predictors of SARS-CoV-2 infection among participants who reported high-risk exposures, defined as social contact with an individual known or suspected to have been infected with SARS-CoV-2, within 2 weeks preceding participants’ SARS-CoV-2 testsCalifornia residentsNAVarious Positive and negative SARS-CoV-2 test; exposures assessed by interviewsFebruary 2021–November 2021
Andrejko et al. (2022) [23]Case–ControlUnited StatesFace mask or respirator use was assessed among individuals who self-reported being in indoor public settings during the 2 weeks preceding testing and who reported no known contact with anyone with confirmed or suspected SARS-CoV-2 infection during this timePersons who received a positive (case participants) or negative (control participants) SARS-CoV-2 test resultPublic settingsVariousPositive (case participants) or negative (control participants) SARS-CoV-2 test result18 February–1 December 2021
April et al. (2022) [25]Retrospective Cohort in the Context of a Natural ExperimentUnited StatesTo compare COVID-19 case load, hospital bed use, and deaths before and after implementation of Texas Executive Order GA-29 mask orderResidents of TexasTexasVariousCOVID-19 incidence cases Pre-order period was from 19 June to 2 July 2020; post-order period was 17 July to 17 September 2020
Badri et al. (2021) [26]Cross SectionalUnited StatesTo identify behaviors and evaluate trends in COVID-19-mitigating practices in a predominantly Black and Hispanic population and to identify differences in practices by self-reported ethnicityRandom sample of adults who underwent SARS-CoV-2 testing at a safety-net healthcare system Chicago, ILVariousLaboratory confirmed SARS-CoV-2 April 2020–May 2020
Baker et al. (2022) [27]Retrospective CohortUnited StatesTo investigate the effectiveness of prevention strategies in household settings, CDC partnered with four U.S. jurisdictions to describe Omicron household transmission during November 2021–February 2022Persons with sequence-confirmed Omicron infection and their household contactsChicago IL, Milwaukee WI, Utah, ConnecticutVarious COVID-19 positive test; interview November 2021–February 2022
Baumkötter et al. (2022) [68]Prospective CohortGermany Protective behavior and SARS-CoV-2 infection risk in the population—results from the Gutenberg COVID-19 studyRandom individuals drawn by the regional registration officesGermany Various RT-qPCR and two antibody immunoassays; self-reported COVID-19 test results were additionally considered January 2020–June 2021
Boutzoukas et al. (2022) [28]Prospective Cohort in the Context of a Natural ExperimentUnited StatesTo evaluate school masking policies and secondary SARS-CoV-2 transmissionStudents and staff United States Schools Various Data were provided as aggregate counts at the school level and were analyzed at an aggregate district level; therefore, details on cases including students versus staff were not available July 2021–December 2021
Brandt et al. (2021) [69]Case ReportGermanyPresent data on the effectiveness of preventive measures against SARS-CoV-2 during an acute viral spread amongst healthcare professionals and aimed to retrace the dissemination of SARS-CoV-2Prospectively recorded data of all employees in our department with symptoms of possible SARS-CoV-2 infectionHospitalSurgical, FFP2SARS-CoV-2 infection; rt-qPCRMarch 2020–April 2020
Bruckhaus et al. (2022) [29]Cross SectionalUnited StatesTo discover the implications of government-enforced health policies for reopening public businesses amidst the pandemic and its effect on county-level infection ratesEighty-three US counties (n = 83) that reported at least 20 000 cases Public businesses VariousLaboratory confirmed SARS-CoV-2 November 2020
Budzyn et al. (2021) [30]Cross SectionalUnited StatesTo assess the impact of masking in schools on COVID-19 incidence among K–12 students across the United States520 US CountiesSchoolsVariousCOVID-19 cases; CDC COVID-19 Data TrackerJuly 2021–September 2021
Bundgaard et al. (2021) [16]RCTDenmarkTo assess whether recommending surgical mask use outside the home reduces wearers’ risk for SARS-CoV-2 infection in a setting where masks were uncommon and not among recommended public health measuresAdults spending more than 3 h per day outside the home without occupational mask useCommunity-basedSurgicalSARS-CoV-2 infection; positive testApril 2020–June 2020
Chano et al. (2022) [73]Cross SectionalJapan To evaluate the correlation between seroprevalence of SARS-CoV-2 antibodies among HCWs and the implementation of PPE and IPCHCWsNine public hospitals designated for COVID-19 in Shiga PrefectureN-95Serological surveillance of SARS-CoV-2 antibodies and self-answered questionnaireFebruary 2021–November 2021
Chen et al. (2020) [59]Case ReportChinaTo evaluate the seroprevalence of SARS-CoV-2 in a cohort of 105 HCWs exposed to COVID-19 patients using both EIA and microneutralization assay105 HCWs exposed to four patients who were laboratory confirmed with COVID-19HospitalDisposable non-surgical face mask, surgical mask, or N-95 respiratory if wearing face maskCOVID-19 infection; RT-qPCRJanuary 2020–February 2020
Cheng et al. (2020) [60]Cross SectionalChinaTo assess the effect of community-wide mask usage to control COVID-19 in HKSARHKSAR of China Community-basedVariousCOVID-19 positivity; lab testDecember 2019 to April 8 2020
Collatuzzo et al. (2022) [80]Cross SectionalItaly Effectiveness of prevention of SARS-CoV-2 transmission among unvaccinated Italian healthcare workersHCWsHospitalsVariousRhino-pharyngeal swabs to detect SARS-CoV-2 RNA by RT-PCR in a reference laboratory, and databases were established to monitor and follow subjects; SARS-CoV-2 RNA was studied by a molecular test, AptimaTM SARS-CoV-2 Assay with the PantherTM Fusion SystemMarch 2020–September 2020
Coma et al. (2022) [81]Retrospective CohortSpain Unraveling the role of the mandatory use of face
covering masks for the control of SARS-CoV-2 in
schools: a quasi-experimental study nested in a
population-based cohort in Catalonia (Spain)
Children aged 3–11 years
attending preschool (3–5 years, without FCM mandate) and primary education (6–11 years, with FCM mandate)
Schools in Catalonia (Spain)Various Incidence of SARS-CoV-2,
SARs, and effective R*
September 2021–December 2021
Donovan et al. (2022) [31]Prospective CohortUnited StatesSARS-CoV-2 incidence in K–12 school districts with mask-required versus mask-optional policies—Arkansas, August–October 2021Students and staff within school districts School districts Various Self-reportAugust 2021–October 2021
Dorr et al. (2022) [82]Prospective CohortSwitzerlandAnalyzed the SARS-CoV-2 risk for HCWs depending on cumulative exposure to patients with COVID-19 and assessed whether this risk can be modulated by the use of respirators compared with surgical masks2919 volunteer HCWs7 healthcare networks in Northern and Eastern SwitzerlandVarious SARS-CoV-2-self-reported positive nasopharyngeal swab and/or antinucleocapsid seroconversion from baseline; self-reported mask type when come in contact 12 months later September 2020–2021
Doung-Ngern et al. (2020) [83]Case–ControlThailandTo evaluate the effectiveness of mask wearing, handwashing, social distancing, and other personal protective measures against SARS-CoV-2 infection in public in ThailandRandomized individuals throughout Thailand through contact tracingNight clubs, boxing stadiums, and a state enterprise office in ThailandVariousSARS-CoV-2 infection; RT-PCRMarch–May 2020
Fischer et al. (2021) [32]Cross SectionalUnited StatesTo examine mask wearing policy and adherence in association with COVID-19 case ratesAll 50 states and D.C.All 50 states and D.C.AllMask wearing and physical distance policies, mask adherence, COVID-19 cases, and demographicsApril–September 2020
Gettings et al. (2021) [33]Prospective Cohort in the Context of a Natural ExperimentUnited StatesTo assess the impact of school-level prevention strategies on incidence of COVID-19 among students and staff before the availability of COVID-19 vaccines169 K–5 schools SchoolsNot specifiedLaboratory-confirmed reverse transcription–polymerase chain reaction or rapid antigen-positive test results self-reported to the schoolNovember 2020–December 2020
Gras-Valentí et al. (2021) [76]Prospective Cohort in the Context of a Natural ExperimentSpainTo evaluate the effectiveness of a program of control and prevention of COVID-19 in an academic general hospital in SpainPatients with confirmed diagnosis of COVID-19 Alicante University General Hospital (AUGH)Surgical maskNumber of COVID-19 cases and the type of contact that occurred in hospitalized patients and HCWMarch 2020–April 2020
Guo et al. (2020) [61]Case–ControlChinaAimed to study orthopedic surgeons, a particular group of HCWs not working on the front lines, as an indication of the overall infection situation of healthcare workersOrthopedic surgeons and trainees who were infected with COVID-19 from 31 December 2019 to 24 February 2020 in the urban area of Wuhan24 hospitals in the urban area of WuhanN-95 respirator and other masksSurvey to identify the orthopedic surgeons who were infected with COVID-19 in Wuhan; outcome: possible risk factors for COVID-19December 2019–February 2020
Guy et al. (2021) [34]Cross SectionalUnited StatesTo examine the association of state-issued mask mandates and allowing on-premises restaurant dining with COVID-19 cases and deaths during March 1–December 31, 2020Starting in April, 38 states and the District of Columbia (DC) issued mask mandates in 202038 states and DCVariousCase growth rates; county-level data on state government websitesMarch 2020–December 2020
Hast et al. (2022) [35]Cross SectionalUnited StatesDescribes the prevalence of COVID-19 risk behaviors in an exposed population of students and school staff in the pre-vaccine era and identifies associations between these behaviors and testing positive for SARS-CoV-2School staff and students12 public school districts in Atlanta, GAVariousCOVID-19 test and risk behavior surveyDecember 2020–January 2021
Heinsohn et al. (2022) [70]Retrospective CohortGermany Infection and transmission risks of COVID-19 in schools and their contribution to population infections in Germany: a retrospective observational study using nationwide and regional health and education agency notification dataSchool staff and students Schools Various SARS-CoV-2 school infections and transmissionMarch 2020–April 2022
Hendrix et al. (2020) [36]Case ReportUnited StatesTo assess the role of source control in preventing COVID-19 transmission139 clients exposed to two symptomatic hair stylists with confirmed COVID-19 while both the stylists and the clients wore face masksHair salonSurgical and N-95COVID-19 diagnosis; lab-confirmed COVID-19May 2020
Hong et al. (2020) [62]Retrospective CohortChinaTo describe the epidemiological trajectory and clinical features of these patients, and a cluster of 21 sequential local COVID-19 patients originated from a couple back from Wuhan among 57 close-contact individuals was detailed127 patients, 71 male and 56 female confirmed to be infected with SARS-CoV-2HospitalNot specifiedCOVID-19 diagnosis; lab-confirmed COVID-19January 2020–March 2020
Jarnig et al. (2022) [84]Retrospective cohortAustriaTest the effectiveness of mask wearing in a classroom setting School students ClassroomFFP2 SARS-CoV-2 detected by PCR tests September 2021–April 2022
Jehn et al. (2021) [37]Cross SectionalUnited StatesTo evaluate the association between school mask policies and school-associated COVID-19 outbreaks in K–12 public non-charter schools open for in-person learning in Maricopa and Pima counties K–12 public non-charter schools open for in-person learning in Maricopa and Pima counties SchoolsNot specifiedSchool-associated outbreak; 2 or more lab-confirmed COVID-19 casesJuly 2021–August 2021
Kim et al. (2021) [85]Case ReportSouth KoreaTo report exposure of HCWs during dental procedures on a mild symptomatic COVID-19 patientA total of 48 persons were identified as exposed, including 15 HCWs at a dental clinic at Konkuk University Medical CenterDental settingSurgical, KF94 respiratorSARS-CoV-2 infection; rRT-PCR testing May 2020
Klompas et al. (2021) [38]Case ReportUnited StatesTo describe 3 cases of SARS-CoV-2 transmission with homologous whole-genome sequencing that
occurred despite the use of medical masks and eye protection
All patients and employees newly diagnosed with SARS-CoV-2 at Brigham and Women’s Hospital in BostonHospitalNot specifiedSARS-CoV-2 infection; lab testNovember 2020–January 2021
Lio et al. (2021) [63]Case–ControlChinaTo clarify the efficacy of these measures, and the results may provide valuable guidance to policymakers to educate the general public about how to reduce the individual-level risk of COVID-19 infectionPatients from Centro Hospitalar Conde de São Januário (C.H.C.S.J.)Hospital and high-risk countriesNot specifiedLaboratory-confirmed COVID-19 March–April 2020
Liu et al. (2021) [39]Prospective CohortUnited StatesTo better understand the risk of SARS-CoV-2 transmission from a pediatric primary index case to household contacts living in Los Angeles CountyHouseholds met eligibility criteria if the index case was less than 18 years of age, reported a positive SARS-CoV-2 test, was the first member of their household with known lab-confirmed COVID-19 infection in the last 14 days, and resided in Los Angeles CountyHouseholdsNot specifiedSARS-CoV-2 pediatric index cases; lab-confirmed SARS-CoV-2December 2020–February 2021
Malik (2020) [86]Case ReportPakistanTo understand the efficacy and benefits of different types of respiratory protective equipment used by HCWs during the management of patients infected with the coronavirus55-year-old woman with a history of diabetes mellitus who was positive for SARS-CoV-2Intensive care unit—hospitalN-95 and surgicalCOVID-19 infection; PCRMarch 2020
Martin-Sanchez et al. (2021) [64]Cross SectionalChinaTo assess the settings where COVID-19 transmission occurred and determine the fraction of transmission events that occurred in settings where masks are not usually wornHong Kong Department of Health on local COVID-19 cases diagnosed up to 30 September 2020Hong KongVariousCOVID-19 transmission; lab testJanuary 2020–September 2020
Meylan et al. (2021) [87]Cross SectionalSwitzerlandTo assess the SARS-CoV-2 transmission in HCWs using seroprevalence as a surrogate marker of infection in our tertiary care center according to exposure1874 participants at the tertiary care university center in Lausanne, SwitzerlandHospitalSurgicalCOVID-19 infection; PCRMay 2020–June 2020
Moorthy et al. (2022) [40]Quasi-Experimental (two interventions, no comparison group)United StatesMasking adherence in K–12 schools and SARS-CoV-2 secondary transmission2 K-12 schools districts including students and staff (2400 students in district 1; 20,000 students in district 2)SchoolsVarious Monitoring mask adherence and transmission rates April 2021–May 2021
Murray et al. (2022) [41]Prospective CohortUnited StatesTo assess the association between masking children 2 years and older and subsequent childcare closure because of COVID-196654 childcare professionalsUnited States and United States Territories’ childcare programsVarious Self-reported child masking22 May to 8 June 2020 (baseline) and 26 May–23 June 2021 (follow-up)
Nir-Paz et al. (2020) [88]Case reportIsraelTo assess risk of transmission of SARS-CoV-2 during flights11 citizens from the Diamond Princesses cruise ship in JapanCommercial aircraftFFP2 and surgicalCOVID-19 positivity; RT-PCR2 weeks (flight + isolation)
Pan et al. (2021) [65]Retrospective CohortChinaTo describe the use of masks among HCW exposed to index cases of COVID-19 and to evaluate any association with infection rateHealthcare workers at Zhongnan Hospital of Wuhan UniversityHospitalSurgicalSelf-reported use of surgical masks and gloves and were tested for severe acute respiratory syndrome coronavirus 2December 2019–February 2020
Pauser et al. (2021) [71]Case Report (data analyzed cross sectionally)GermanyTo analyze SARS-CoV-2 transmission during a professional sports event (2nd division professional basketball in Germany)69 players, coaches, and other persons present at the sporting event in GermanyIndoor sports facilityVariousCOVID-19 transmission; PCR testNovember 2020
Ranjan et al. (2020) [89]Cross SectionalIndiaTo determine whether the non-compliance with specific preventive practices was associated with the acquisition of the infection or not384 patients of an outpatient COVID-19 clinic at a tertiary care hospital in New Delhi, IndiaHospitalN-95COVID-19 positivity; self-report preventative practicesJune-July 2020
Rebeiro et al. (2021) [42]Quasi-experimentalUnited StatesTo assess the impact of state mask-wearing requirement on COVID-19 cases, hospitalizations, and deaths in the United StatesUS residentsUnited States Various COVID-19 cases daily from 1 January 2020 to 31 October 2020 January 2020–October 2020
Rebmann et al. (2021) [43]Cross SectionalUnited StatesTo assess the impact of a modified quarantine protocol that considered mask use when determining which close contacts required quarantine265 SLU students who received a positive SARS-CoV-2 test resultSt. Louis University (SLU) Not specifiedPositive SARS-CoV-2 test; mask useJanuary 2021–May 2021
Reyné et al. (2021) [90]Retrospective CohortFranceThe goal of this study was to investigate the efficiency of IPC measures implemented in the Hérault department (Occitanie region, France) in reducing the spread of SARS-CoV-2 in ACFs when a patient tested positiveResidents of the ACFs12 public and private ACFsVarious RT–PCR testing via nasopharyngeal swabs on a weekly basis; a full week without any residents testing positive for SARS-CoV-2 indicated the end of the outbreakMarch 2020–May 2020
Riley et al. (2022) [44]Prospective CohortUnited StatesTo examine how effective masks are at reducing transmission of SARS-CoV-2Residents of Johnson County, Iowa who tested positive for COVID-19Community2-layer cloth masks, disposable surgical masks, double-layer gaiters, and KN-95 masksTransmission of SARS-Co-2; lab-confirmed case of COVID-19October 2020- February 2021
Russell et al. (2022) [91]Quasi-Experimental **Brazil To estimate the individual effects of seven nonpharmaceutical interventions on COVID-19 cases and deaths to help policymakers choose the most effective interventions to mitigate the pandemic and reduce disease burdenCOVID-19 cases and deaths who lived in BrazilStates of BrazilVarious Case confirmation by PCR testMarch 2020–December 2020
Sarti et al. (2021) [45]Case ReportUnited StatesTo describe a COVID-19 cluster among workers in an office in ItalyOffice workers Office Various Nasopharyngeal swab results, symptoms onset, type of symptoms, and number and status of family members in respect to COVID-19 November 2020–December 2020
Sasser et al. (2022) [46]Cross SectionalUnited StatesTo describe the incidence of COVID-19 in Wisconsin high school athletes and investigate the relationship of COVID-19 incidence with sport and face mask useAthletic directors representing 30,074 high school athletes with or without SARS-CoV2High schoolsNot specifiedCOVID-19 rates among athletes September 2020
Seidelman et al. (2020) [47]Prospective CohortUnited StatesTo measure the effect of universal masking on COVID-19 acquisition within the healthcare settingFrom 15 March 2020 to 6 June 2020, all HCWs who tested positive for SARS-CoV-2 at Duke HealthHospitalNot specifiedCOVID-19 incidence; negative binomial regressionMarch-June 2020
Shah et al. (2021) [48]Retrospective CohortUnited StatesAimed to identify factors related to lapses in PPE use that may influence transmission of SARS-CoV-2 from patients to HCW345 HCW who sustained a significant occupational exposure to a patient with COVID-19 from 13 May 2020 through 30 November 2020Tertiary-care medical center in MinnesotaSurgical maskCOVID-19 evaluated by RT-PCRMay 2020–November 2020
Shah et al. (2022) [49]Retrospective CohortUnited StatesData was collected from Texas school districts comparing COVID-19 positivity rates for districts where masks were mandated or optionalStudents and staff from 30 school districts in Texas SchoolsVarious Positive COVID-19 test; lab testAugust 2021–November 2021
Sharif et al. (2021) [92]Cross SectionalBangladeshThis study was conducted to investigate the association of the preventive measures with the reduction in transmission of COVID-19 in Bangladesh1690 participants from 54 districts in BangladeshEight divisional cities covering 54 districts in BangladeshVariousInterviews over phone calls and by using digital questionnaires January 2020–May 2021
Shaweno et al. (2021) [93]Cross SectionalEthiopiaTo determine the seroprevalence of SARS-CoV-2 antibody among individuals aged above 15 years and residing in the congregate settings of Dire Dawa city administration, EthiopiaIndividuals aged above 15 years and residing in randomly selected households from purposefully selected 11 enumeration areas in overcrowded neighborhoods in Dire DawaOvercrowded neighborhoodsVariousSeroprevalence, interview, and blood sample collectionJune-July 2020
Spira (2022) [94]Cross SectionalEuropean CountriesThis analysis aimed to verify whether mask usage was correlated with COVID-19 morbidity and mortalityIndividuals living in European countriesWestern and Eastern European countries with a population of more than 1 million peopleVariousData on morbidity, mortality, and mask usage were retrieved from the IHME; vaccination obtained from Our World in DataOctober 2020–March 2021
Sugimura et al. (2021) [74]Cross SectionalJapanTo investigate the relationship between mask wearing and COVID-19 among close contacts of COVID-19 patients 820 patients at public health centers in the Hiroshima Prefecture, JapanJapanese public health centersVariousDiagnosed COVID-19; PCR testMarch–May 2020
Suh et al. (2021) [50]Cross SectionalUnited StatesTo estimate the prevalence of COVID-19 cases among
campers and staff and its relation to individual and
multiple NPIs instituted at these camps
US campers and staffUS ACA affiliated camps VariousSurveys Summer 2020
Sun et al. (2022) [95]Prospective CohortCosta RicaTo better estimate the secondary attack rates and understand the behavioral determinants of SARS-CoV-2 household transmission, a household serologic study nested within a larger prospective population-based study of the SARS-CoV-2 immunologic response in Costa Rica was conducted719 household contacts of 304 household index cases Costa Rican householdsVariousBlood specimens collected within 30–60 days of index case diagnosis, and serum was tested for presence of spike and nucleocapsid SARS-CoV-2 IgG antibodiesNovember 2020–July 2021
Suñer et al. (2022) [77]Cross SectionalSpainThe primary objective was to compare the incidence of COVID-19 within the 3 to 10 days following the event between attendees and a population-based control groupAttendees at a music festivalTwo outdoor music festivals held in CataloniaVariousAg-RDT screening of nasopharyngeal swab for SARS-CoV-2 and survey-based assessment of risk behaviors during the event3 July 2021 and 8–10 July 2021
Thakkar et al. (2022) [51]Prospective CohortUnited StatesCharacterize school-associated secondary transmission and COVID-19 incidence among population of a single PreK-12 school during a period of high-community SARS-CoV-2 incidenceStudents, faculty, and staff at a private school Mecklenburg County, NCVariousSelf-report symptoms, community SARS-CoV-2 exposures, and any results of recent SARS-CoV-2 testing; cases defined by positive SARS-CoV-2 RT-PCR or antigen test resultAugust 2020–January 2021
Thompson et al. (2021) [52]Retrospective CohortUnited StatesTo assess extent of a healthcare-associated outbreak of SARS-CoV-2 and to evaluate the effectiveness of infection control measures, including universal maskingIndex patient and 250 exposed patients and staffIntegrated VA healthcare system with 2 facilities and 330 bedsVariousCOVID-19 cases and transmission; point-prevalence survey 4 weeks
Tjaden et al. (2022) [53]Case–ControlUnited StatesTo assess the association between self-reported mask wearing behavior during non-household interactions and COVID-19 infection during 3 pandemic periods using conditional logistic regression models of risk of infection that were adjusted for demographics, vaccination status, and recent known exposure to COVID-19Sample of adults enrolled at 6 North Carolina healthcare systemsNorth Carolina healthcare systemsVarious Mask use, recent exposure, and positive SARS-CoV-2 test; self-reportApril 2020–June 2021
Tjaden et al. (2023) [54]Case–ControlUnited StatesTo assess the association between COVID-19 and consistent mask wearing during contact with others outside the household—a nested case–control analysis, November 2020–October 2021Participants who were associated with 10 different healthcare systemsSouthern United StatesVarious Symptomatic SARS-CoV-2 infection (COVID-19) November 2020–October 2021
Toyokawa et al. (2021) [75]Prospective CohortJapan Transmission of SARS-CoV-2 during a 2 h domestic flight to Okinawa, Japan, March 2020146 aircraft passengers, excluding the pilotsAircraft Various Measuring transmission of SARS-CoV-2 by nasopharyngeal swabs, PCR tests, and mask-wearing outcomes23 March 2020
Van Dyke et al. (2020) [55]Cross Sectional in the Context of a Natural ExperimentUnited StatesTo analyze trends in county-level COVID-19 incidence before (1 June–2 July) and after (3 July–23 August) the governor’s executive order among counties that ultimately had a mask mandate in place and those that did notMandated mask counties and nonmandated mask counties in Kansas CommunityVariousCOVID-19 incidence; data from Kansas Health Institute June 2020–August 2020
Varela (2022) [96]RCTColombiaAimed to determine the effectiveness of closed face shields with surgical face masks to prevent SARS-CoV-2 transmission in working adults during the COVID-19 pandemic in Bogotá, ColombiaCoVIDA project participants who had a negative RT-PCR test for SARS-CoV-2 in the previous 2 monthsParticipants living in geographic areas with active COVID-19 transmission and in areas with medium, medium-high, and high vulnerability indexSurgical maskSARS-CoV-2 tested; lab testJanuary 2021–March 2021
Walker et al. (2020) [56]Quasi-experimental in the Context of a Natural ExperimentUnited StatesTo describe the impact of universal masking and universal testing on admission for high-risk exposures to SARS-CoV-2 for HCWsHCWs at a tertiary referral center in the Southeastern United StatesHospitalN-95Universal masking; self-report of exposures to COVID-19April 2020–May 2020
Wang et al. (2020) [66]Retrospective CohortChinaTo study the use of NPIs, such as face masks, social distancing, and disinfection in the household setting335 people in 124 families with at least one laboratory-confirmed COVID-19 case in BeijingHouseholdsN-95 mask, disposable surgical mask, or cloth maskSecondary transmission of SARS-CoV-2 within the familyFebruary 2020–March 2020
Wang et al. (2020) [57]Prospective CohortUnited StatesTo describe SARS-CoV-2 PCR test positivity among HCWs before, during, and after implementation of a policy requiring universal masking of all HCWs and patients in a large healthcare system in Massachusetts9850 tested HCWs at Mass General BrighamHospitalSurgicalSARS-CoV-2 infection; rRT-PCR testing March–April 2020
Wendt et al. (2020) [72]Case ReportGermanyTo investigate potential transmissions of a symptomatic SARS-CoV-2-positive physician in a tertiary care hospital who worked for 15 cumulative hours without wearing a face maskPatients/187 nurses and doctors/technical and medical assistants and other healthcare staffHospitalNot specifiedLaboratory-confirmed COVID-19March 2020
Williams et al. (2021) [58]Prospective CohortUnited StatesTo assess the risk of SARS-CoV-2 transmission from universally masked HCWs to patients or residentsHCWs and patients Hospitals Various Laboratory-confirmed COVID-19October 2020–April 2021
Williamson et al. (2021) [97]Case–ControlAustralia Transmission of SARS-CoV-2 Delta variant from an infected aircrew member on a short-haul domestic flight, Australia 2021Flight passengers and crew members aboard the aircraftAircraft Various A survey for contact tracing and PCR tests was conducted on individuals aboard the flight June 2021
Wilson et al. (2022) [98]Case–Control *FranceTo investigate socio-demographic factors and professional practice associated with the risk of COVID-19 among HCWs in health establishments 2058 respondents, respectively, 1363 (66.2%) and 695 (33.8%), in medical and medico-social establishments, including HCWs with and without contact with patientsMedical establishments and medico-social establishments in FranceSurgical maskSARS-CoV2 PCR or antigenic testMarch 2021–June 2021
Xinias et al. (2021) [99]Case ReportGreeceTo report experience regarding a pediatric patient-case who had a COVID-19 infection, which was initially considered a common viral infection and was managed accordingly for the first 36 h while being hospitalizedHippokration Hospital pediatric ward staffHospitalSurgical maskCOVID-19 transmission; PCR test7–10 after exposure to infected patient
* Also cross sectional; ** intervention was a natural experiment. Note: HCW = healthcare workers; RT-PCR = Reverse Transcription Polymerase Chain Reaction; COVID-19 = Coronavirus Disease 2019; SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2; CDC = Centers for Disease Control and Prevention; RT-qPCR = Reverse Transcription Quantitative Polymerase Chain Reaction; FFP2 = Filtering Facepiece Part 2; RCT = randomized controlled trial; PPE = personal protective equipment; IPC = Infection Prevention and Control; EIA = Enzyme Immunoassay; HKSAR = Hong Kong Special Administrative Region; RNA = Ribonucleic Acid; FCM = Face Covering Mask; SAR = Secondary Attack Rate; R* = Reproductive Number; AUGH = Alicante University General Hospital; SLU = St. Louis University; D.C. = District of Columbia; rRT-PCR = Real-time Reverse Transcription Polymerase Chain Reaction; ACF = aged-care facilities; NPI = Nonpharmaceutical Intervention; ACA = American Camp Association; IgG = Immunoglobulin G Antibodies; Ag-RDT = Antigen Rapid Diagnostic Test; VA = United States Department of Veterans Affairs; NA = Not Applicable; and IHME = Institute of Health Metrics and Evaluation.
Table 3. Vote counting method results.
Table 3. Vote counting method results.
Author (Year)Measure of Effect DescriptionEffect
Abaluck et al. (2022) [78]Prevalence ratios1
Adawee et al. (2021) [22]NoneUnable to determine *
Ahmet Sertcelik (2023) [79]Odds ratios1
Ambrosch et al. (2020) [67]Unadjusted incidence density ratio1
Andrejko et al. (2021) [24]Odds ratios1
Andrejko et al. (2022) [23]Odds ratios from multivariable logistic regression1
April et al. (2022) [25]Cohen’s d0
Badri et al. (2021) [26]Odds ratios from multivariable logistic regression1
Baker et al. (2022) [27]Attack rates1
Baumkötter et al. (2022) [68]Prevalence ratios1
Boutzoukas et al. (2022) [28]Incidence rate ratio1
Brandt et al. (2021) [69]NoneUnable to determine *
Bruckhaus et al. (2022) [29]Incidence rate comparison using multiple linear regression1
Budzyn et al. (2021) [30]Multiple linear regression 1
Bundgaard et al. (2021) [16]Odds ratio from logistic regression1
Chano et al. (2022) [73]Odds ratios1
Chen et al. (2020) [59]Odds ratios from multivariable logistic regression1
Cheng et al. (2020) [60]Incidence rate comparison using exact Poisson test1
Collatuzzo et al. (2022) [80]Odds ratios from multivariable logistic regression1
Coma et al. (2022) [81]Risk ratios0
Donovan et al. (2022) [31]Incidence rate ratios1
Dorr et al. (2022) [82]Odds ratios1
Doung-Ngern et al. (2020) [83]Odds ratios from multivariable logistic regression1
Fischer et al. (2021) [32]Odds ratios from multivariable logistic regression1
Gettings et al. (2021) [33]Rate ratios from adjusted -1 binomial regression models1
Gras-Valentí et al. (2021) [76]Unadjusted relative risk ratios1
Guo et al. (2020) [61]Odds ratios from multivariable logistic regression1
Guy et al. (2021) [34]Weighted least-squares regression for COVID-19 case counts 1
Hast et al. (2022) [35]Odds ratios1
Heinsohn et al. (2022) [70]Incidence rates1
Hendrix et al. (2020) [36]None; transmission did not occur among 67 close contactsUnable to determine *
Hong et al. (2020) [62]Comparison of incidence proportions1
Jarnig et al. (2022) [84]Odds ratio from logistic regression1
Jehn et al. (2021) [37]Odds ratios from multivariable logistic regression1
Kim et al. (2021) [85]NoneUnable to determine *
Klompas et al. (2021) [38]NoneUnable to determine *
Lio et al. (2021) [63]Odds ratios from multivariable logistic regression1
Liu et al. (2021) [39]Household secondary attack rates1
Malik (2020) [86]NoneUnable to determine *
Martin-Sanchez et al. (2021) [64]Odds ratios from multivariable logistic regression1
Meylan et al. (2021) [87]Odds ratios from multivariable logistic regression1
Moorthy et al. (2022) [40]Secondary transmission rates over time1
Murray et al. (2022) [41]Risk ratios1
Nir-Paz et al. (2020) [88]NoneUnable to determine *
Pan et al. (2021) [65]Descriptive comparison (t-test)1
Pauser et al. (2021) [71]Fisher’s exact test1
Ranjan et al. (2020) [89]Odds ratios from multivariable logistic regression1
Rebeiro et al. (2021) [42]Incidence rate slopes1
Rebmann et al. (2021) [43]Odds ratios from multivariable logistic regression1
Reyné et al. (2021) [90]Odds ratio from generalized linear mixed model1
Riley et al. (2022) [44]Odds ratios from multivariable logistic regression1
Russell et al. (2022) [91]Daily percent positivity growth rate1
Sarti et al. (2021) [45]NoneUnable to determine *
Sasser et al. (2022) [46]Incidence rate ratios from -1 binomial regression0
Seidelman et al. (2020) [47]Incidence rate comparison from -1 binomial regression1
Shah et al. (2021) [48]Student’s t test0
Shah et al. (2022) [49]Student’s t test comparing percent positivity1
Sharif et al. (2021) [92]Odds ratios1
Shaweno et al. (2021) [93]Odds ratios from multivariable logistic regression1
Spira (2022) [94]Correlation coefficient0
Sugimura et al. (2021) [74]Relative risk ratios from adjusted Poisson regression models1
Suh et al. (2021) [50]Risk ratios1
Sun et al. (2022) [95]Odds ratios1
Suner et al. (2022) [77]Odds ratios1
Thakkar et al. (2022) [51]NoneUnable to determine *
Thompson et al. (2021) [52]NoneUnable to determine *
Tjaden et al. (2022) [53]Odds ratios1
Tjaden et al. (2023) [54]Odds ratios from multivariable logistic regression1
Toyokawa et al. (2021) [75]Odds ratios from multivariable logistic regression1
Van Dyke et al. (2020) [55]Generalized estimating equation regression 1
Varela (2022) [96]Risk difference1
Walker et al. (2020) [56]Rate ratios from unadjusted -1 binomial regression model1
Wang et al. (2020) [66]Odds ratios from multivariable logistic regression1
Wang et al. (2020) [57]Weighted non-linear regression of positivity rates1
Wendt et al. (2020) [72]NoneUnable to determine *
Williams et al. (2021) [58]Relative risk ratios1
Williamson et al. (2021) [97]NoneUnable to determine *
Wilson et al. (2022) [98]Odds ratios1
Xinias et al. (2021) [99]NoneUnable to determine *
Note: 1 = benefit; 0 = no association; 1 = harm; and * study did not report sufficient data to determine if mask wearing or policy had an association with SARS-CoV-2 infection or COVID-19.
Table 4. JBI risk of bias quality assessment—case reports.
Table 4. JBI risk of bias quality assessment—case reports.
StudyA1A2A3A4A5A6A7A8Yes (%)Risk *
Wendt et al. (2020) [72]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Nir-Paz et al. (2020) [88]Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00275Moderate
Malik (2020) [86]Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i00175Moderate
Kim et al. (2021) [85]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Xinias et al. (2021) [99]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i00162.5Moderate
Brandt et al. (2021) [69]Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00187.5Low
Klompas et al. (2021) [38]Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i00162.5Moderate
Hendrix et al. (2020) [36]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i00187.5Low
Chen et al. (2020) [59]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Sarti et al. (2021) [45]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i00162.5Moderate
Pauser et al. (2021) [71]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00175Low
Criteria Met: Ijerph 22 01590 i001 = yes; Ijerph 22 01590 i003 = unclear; and Ijerph 22 01590 i002 = no; A1 Were patients’ demographic characteristics clearly described?; A2 Was the patient’s history clearly described and presented as a timeline?; A3 Was the current clinical condition of the patient on presentation clearly described?; A4 Were diagnostic tests or assessment methods and the results clearly described?; A5 Was the intervention(s) or treatment procedure(s) clearly described?; A6 Was the post-intervention clinical condition clearly described?; A7 Were adverse events (harms) or unanticipated events identified and described?; A8 Does the case report provide takeaway lessons?; * Risk of bias was ranked as high when the study was rated with ≤49% of “yes” scores, moderate when the study was rated between 50 and 79% of “yes” scores, and low when the study was rated with ≥80% of “yes” scores.
Table 5. JBI risk of bias quality assessment—quasi-experimental trial.
Table 5. JBI risk of bias quality assessment—quasi-experimental trial.
StudyB1B2B3B4B5B6B7B8B9Yes (%)Risk *
Walker et al. (2020) [56]Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00166.7Moderate
Rebeiro, Aronoff, and Smith (2021) [42]Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i00155.6Moderate
Moorthy et al. (2022) [40]Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i00155.6Moderate
Ambrosch et al. (2020) [67]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00188.9Low
Russell et al. (2022) [91]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00166.7Moderate
Criteria Met: Ijerph 22 01590 i001 = yes; Ijerph 22 01590 i003 = unclear; and Ijerph 22 01590 i002 = no; A1 Were patients’ demographic characteristics clearly described?; A2 Was the patient’s history clearly described and presented as a timeline?; A3 Was the current clinical condition of the patient on presentation clearly described?; A4 Were diagnostic tests or assessment methods and the results clearly described?; A5 Was the intervention(s) or treatment procedure(s) clearly described?; A6 Was the post-intervention clinical condition clearly described?; A7 Were adverse events (harms) or unanticipated events identified and described?; A8 Does the case report provide takeaway lessons?; * Risk of bias was ranked as high when the study was rated with ≤49% of “yes” scores, moderate when the study was rated between 50 and 79% of “yes” scores, and low when the study was rated with ≥80% of “yes” scores.
Table 6. JBI risk of bias quality assessment—case–control studies.
Table 6. JBI risk of bias quality assessment—case–control studies.
StudyC1C2C3C4C5C6C7C8C9C10Yes (%)Risk *
Lio et al. (2021) [63]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00190Low
Guo et al. (2020) [61]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Doung-Ngern et al. (2020) [83]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Ahmet et al. (2023) [79]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00190Low
Tjaden et al. (2022) [53]Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00160Moderate
Andrejko et al. (2022) [23]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Andrejko et al. (2021) [24]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Tjaden et al. (2023) [54]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Wilson et al. (2022) [98]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00170Moderate
Williamson et al. (2021) [97]Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00170Moderate
Criteria Met: Ijerph 22 01590 i001 = yes; Ijerph 22 01590 i003 = unclear; and Ijerph 22 01590 i002 = no; A1 Were patients’ demographic characteristics clearly described?; A2 Was the patient’s history clearly described and presented as a timeline?; A3 Was the current clinical condition of the patient on presentation clearly described?; A4 Were diagnostic tests or assessment methods and the results clearly described?; A5 Was the intervention(s) or treatment procedure(s) clearly described?; A6 Was the post-intervention clinical condition clearly described?; A7 Were adverse events (harms) or unanticipated events identified and described?; A8 Does the case report provide takeaway lessons?; * Risk of bias was ranked as high when the study was rated with ≤49% of “yes” scores, moderate when the study was rated between 50 and 79% of “yes” scores, and low when the study was rated with ≥80% of “yes” scores.
Table 7. JBI risk of bias quality assessment—cohort studies.
Table 7. JBI risk of bias quality assessment—cohort studies.
StudyD1D2D3D4D5D6D7D8D9D10D11Yes (%)Risk *
Wang et al. (2020) [66]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i00182Low
Wang et al. (2020) [57]Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00164Moderate
Liu et al. (2021) [39]Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i00164Moderate
Hong et al. (2020) [62]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i003Ijerph 22 01590 i00182Low
Riley et al. (2022) [44]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Coma et al. (2022) [81]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i003Ijerph 22 01590 i00173Moderate
Baumkötter et al. (2022) [68]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i00191Low
Boutzoukas et al. (2022) [28]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Donovan et al. (2022) [31]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00182Low
Toyokawa et al. (2021) [75]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
April et al. (2022) [25]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i00173Moderate
Dörr et al. (2022) [82]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00182Low
Murray et al. (2022) [41]Ijerph 22 01590 i003Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i00245High
Seidelman et al. (2020) [47]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00173Moderate
Thakkar et al. (2022) [51]Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i00145High
Williams et al. (2021) [58]Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i00254.5Moderate
Baker et al. (2022) [27]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Gras-Valentí et al. (2021) [76]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i003Ijerph 22 01590 i00163Moderate
Heinsohn et al. (2022) [70]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100 Low
Gettings et al. (2021) [33]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i00173Moderate
Jarnig et al. (2022) [84]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Pan et al. (2021) [65]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100 Low
Reyné et al. (2021) [90]Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i00154.5Moderate
Shah et al. (2021) [48]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Shah et al. (2022) [49]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i00173Moderate
Sun et al. (2022) [95]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00191Low
Thompson et al. (2021) [52]Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00182Low
Criteria Met: Ijerph 22 01590 i001 = yes; Ijerph 22 01590 i003 = unclear; and Ijerph 22 01590 i002 = no; A1 Were patients’ demographic characteristics clearly described?; A2 Was the patient’s history clearly described and presented as a timeline?; A3 Was the current clinical condition of the patient on presentation clearly described?; A4 Were diagnostic tests or assessment methods and the results clearly described?; A5 Was the intervention(s) or treatment procedure(s) clearly described?; A6 Was the post-intervention clinical condition clearly described?; A7 Were adverse events (harms) or unanticipated events identified and described?; A8 Does the case report provide takeaway lessons?; * Risk of bias was ranked as high when the study was rated with ≤49% of “yes” scores, moderate when the study was rated between 50 and 79% of “yes” scores, and low when the study was rated with ≥80% of “yes” scores.
Table 8. JBI risk of bias quality assessment—cross-sectional studies.
Table 8. JBI risk of bias quality assessment—cross-sectional studies.
StudyE1E2E3E4E5E6E7E8Yes (%)Risk *
Sugimura et al. (2021) [74]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Ranjan et al. (2020) [89]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i00175Moderate
Meylan et al. (2021) [87]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Guy et al. (2021) [34]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00187.5Low
Fischer et al. (2021) [32]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00187.5Low
Cheng et al. (2020) [60]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i00162.5Moderate
Bruckhaus et al. (2022) [29]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00187.5Low
Badri et al. (2021) [26]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00187.5Low
Adawee et al. (2021) [22]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Sasser et al. (2022) [46]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i00175Moderate
Shaweno et al. (2021) [93]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00187.5Low
Martin-Sanchez et al. (2021) [64]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00187.5Low
Sharif et al. (2021) [92]Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i00137.5High
Spira (2022) [94]Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i00175Moderate
Hast et al. (2022) [35]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i00187.5Low
Collatuzzo et al. (2022) [80]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Chano et al. (2022) [73]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i00262.5Moderate
Budzyn et al. (2021) [30]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i00175Moderate
Jehn et al. (2021) [37]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Rebmann et al. (2021) [43]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001100Low
Suh et al. (2021) [50]Ijerph 22 01590 i002Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i00125High
Suñer et al. (2022) [77]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i00175Moderate
Van Dyke et al. (2020) [55]Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i00175Moderate
Criteria Met: Ijerph 22 01590 i001 = yes; Ijerph 22 01590 i003 = unclear; and Ijerph 22 01590 i002 = no; A1 Were patients’ demographic characteristics clearly described?; A2 Was the patient’s history clearly described and presented as a timeline?; A3 Was the current clinical condition of the patient on presentation clearly described?; A4 Were diagnostic tests or assessment methods and the results clearly described?; A5 Was the intervention(s) or treatment procedure(s) clearly described?; A6 Was the post-intervention clinical condition clearly described?; A7 Were adverse events (harms) or unanticipated events identified and described?; A8 Does the case report provide takeaway lessons?; * Risk of bias was ranked as high when the study was rated with ≤49% of “yes” scores, moderate when the study was rated between 50 and 79% of “yes” scores, and low when the study was rated with ≥80% of “yes” scores.
Table 9. JBI risk of bias quality assessment—randomized controlled trial.
Table 9. JBI risk of bias quality assessment—randomized controlled trial.
StudyF1F2F3F4F5F6F7F8F9F10F11F12F13Yes (%)Risk *
Bundgaard et al. (2021) [16]Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00161.5Moderate
Varela et al. (2022) [96]Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00361.5Moderate
Abaluck et al. (2022) [78]Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i001Ijerph 22 01590 i003Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i002Ijerph 22 01590 i001Ijerph 22 01590 i001Ijerph 22 01590 i00353.8High
Criteria Met: Ijerph 22 01590 i001 = yes; Ijerph 22 01590 i003 = unclear; and Ijerph 22 01590 i002 = no; A1 Were patients’ demographic characteristics clearly described?; A2 Was the patient’s history clearly described and presented as a timeline?; A3 Was the current clinical condition of the patient on presentation clearly described?; A4 Were diagnostic tests or assessment methods and the results clearly described?; A5 Was the intervention(s) or treatment procedure(s) clearly described?; A6 Was the post-intervention clinical condition clearly described?; A7 Were adverse events (harms) or unanticipated events identified and described?; A8 Does the case report provide takeaway lessons?; * Risk of bias was ranked as high when the study was rated with ≤49% of “yes” scores, moderate when the study was rated between 50 and 79% of “yes” scores, and low when the study was rated with ≥80% of “yes” scores.
Table 10. Summary of findings—face masks and masking policies for preventing SARS-CoV-2 transmission and COVID-19 disease.
Table 10. Summary of findings—face masks and masking policies for preventing SARS-CoV-2 transmission and COVID-19 disease.
Certainty AssessmentDescription of EffectCertaintyImportance
№ of StudiesStudy DesignRisk of BiasInconsistencyIndirectnessImprecisionOther ConsiderationsMasking Strategies and Policies
Symptomatic laboratory-confirmed COVID-19 (assessed with diagnostic lab test (rt-qPCR))
56non-randomized studiesserious aserious bnot serious bnot seriousstrong association,
all plausible residual confounding would reduce the demonstrated effect
Overall results: Based on vote counting table, 39 out of the 56 (70%) included studies demonstrated a favorable effect of mask wearing in prevention of SARS-CoV-2 infection or COVID-19 disease.
Results by study design: All 8 included case–control studies demonstrated a favorable association between mask wearing and COVID-19. However, 8 out of 11 case report studies did not report the effect between mask wearing and COVID-19. Fourteen cross-sectional studies were included, of which the majority (86%) reported a positive effect. Nineteen cohort studies were included, of which 14 reported a favorable effect between mask wearing and COVID-19. Four interventions (2 RCTs and 2 quasi-experimental) were included; all four studies reported a favorable effect between mask wearing and COVID-19 infection.
⨁⨁◯◯
Low a, b
IMPORTANT
Self-reported laboratory-confirmed COVID-19
6non-randomized studiesserious cnot seriousnot seriousnot seriousall plausible residual confounding would reduce the demonstrated effectOverall results: Based on vote counting table, all 6 studies (100%) demonstrated a favorable effect of mask wearing in prevention of SARS-CoV-2 infection or COVID-19 disease.
Results by study design: Of the six included studies, 2 cohort studies and 2 cross-sectional studies reported a favorable effect of mask wearing on COVID-19 infection. The 2 other studies included (case report and quasi-experimental) also demonstrated a favorable effect.
⨁⨁◯◯
Low c
IMPORTANT
SARS-CoV-2 seroconversion
4non-randomized studiesserious dnot seriousnot seriousnot seriousall plausible residual confounding would reduce the demonstrated effectResults by study design: All four of the included studies (100%; 2 cross-sectional, a cohort, and a case–control study) demonstrated a favorable effect of mask wearing in prevention of SARS-CoV-2 infection or COVID-19 disease.⨁⨁◯◯
Low d
IMPORTANT
Aggregate community-level incidence (rt-qPCR)
13non-randomized studiesserious enot seriousnot seriousnot seriousall plausible residual confounding would reduce the demonstrated effectOverall results: Eleven out of thirteen studies (85%) reported a favorable effect between mask wearing in prevention of SARS-CoV-2 infection or COVID-19 disease.
Results by study design: All studies except 2 (1 cross-sectional and 1 retrospective cohort) demonstrated a favorable effect of mask wearing in prevention of SARS-CoV-2 infection or COVID-19 disease.
⨁⨁◯◯
Low e
IMPORTANT
GRADE Working Group grades of evidence: Level of certainty is indicated by ⨁ selected; High certainty: It is highly improbable that additional research will alter confidence in the effect estimate. Moderate certainty: Additional research is likely to significantly influence confidence in the effect estimate and may lead to a change in the estimate. Low certainty: Additional research is highly likely to significantly affect confidence in the effect estimate and is expected to result in a change to the estimate. Very low certainty: There is a high degree of uncertainty regarding the estimate. Explanations: a. We downgraded the quality of evidence for this outcome by 1 level, as several included studies had an overall moderate or high risk of bias (see JBI figures for risk of bias ratings). b. Thirteen studies did not report an effect between mask wearing and COVID-19. Three studies reported no association between mask wearing and COVID-19. As we were not able to interpret these study findings and observed an inconsistent result in 3 studies, we decided to downgrade the evidence by one level. c. Of the 6 included studies, 5 were rated as having moderate or high risk of bias (see JBI figures for risk of bias ratings). d. Of the 4 included studies, 2 were rated as having moderate risk of bias (see JBI figures for risk of bias ratings). e. Several studies were rated as having moderate risk of bias (see JBI figures for risk of bias ratings).
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Crespo, N.C.; Shifflett, S.; Kosta, K.; Fornasier, J.M.; Dionicio, P.; Hyde, E.T.; Godino, J.G.; Ramers, C.B.; Elder, J.P.; McDaniels-Davidson, C. Evidence of Face Masks and Masking Policies for the Prevention of SARS-CoV-2 Transmission and COVID-19 in Real-World Settings: A Systematic Literature Review. Int. J. Environ. Res. Public Health 2025, 22, 1590. https://doi.org/10.3390/ijerph22101590

AMA Style

Crespo NC, Shifflett S, Kosta K, Fornasier JM, Dionicio P, Hyde ET, Godino JG, Ramers CB, Elder JP, McDaniels-Davidson C. Evidence of Face Masks and Masking Policies for the Prevention of SARS-CoV-2 Transmission and COVID-19 in Real-World Settings: A Systematic Literature Review. International Journal of Environmental Research and Public Health. 2025; 22(10):1590. https://doi.org/10.3390/ijerph22101590

Chicago/Turabian Style

Crespo, Noe C., Savannah Shifflett, Kayla Kosta, Joelle M. Fornasier, Patricia Dionicio, Eric T. Hyde, Job G. Godino, Christian B. Ramers, John P. Elder, and Corinne McDaniels-Davidson. 2025. "Evidence of Face Masks and Masking Policies for the Prevention of SARS-CoV-2 Transmission and COVID-19 in Real-World Settings: A Systematic Literature Review" International Journal of Environmental Research and Public Health 22, no. 10: 1590. https://doi.org/10.3390/ijerph22101590

APA Style

Crespo, N. C., Shifflett, S., Kosta, K., Fornasier, J. M., Dionicio, P., Hyde, E. T., Godino, J. G., Ramers, C. B., Elder, J. P., & McDaniels-Davidson, C. (2025). Evidence of Face Masks and Masking Policies for the Prevention of SARS-CoV-2 Transmission and COVID-19 in Real-World Settings: A Systematic Literature Review. International Journal of Environmental Research and Public Health, 22(10), 1590. https://doi.org/10.3390/ijerph22101590

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