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Open Access

Peer-reviewed

Research Article

A systematic review of passing fit testing of the masks and respirators used during the COVID-19 pandemic: Part 1-quantitative fit test procedures

  • Anahita Fakherpour ,

    Contributed equally to this work with: Anahita Fakherpour, Mehdi Jahangiri

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review & editing

    Affiliation Student Research Committee, Department of Occupational Health and Safety Engineering, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran

    ⨯
  • Mehdi Jahangiri ,

    Contributed equally to this work with: Anahita Fakherpour, Mehdi Jahangiri

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    jahangiri_m@sums.ac.ir

    Affiliation Department of Occupational Health and Safety Engineering, Research Center for Health Sciences, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran

    ⨯
  • Janis Jansz

    Roles Conceptualization, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliation School of Mines: Minerals, Energy and Chemical Engineering, Faculty of Science and Engineering, Curtin University, Perth, Australia

    ⨯

Abstract

Background

During respiratory infection pandemics, masks and respirators are highly sought after, especially for frontline healthcare workers and patients carrying respiratory viruses. The objective of this study was to systematically review fit test pass rates and identify factors influencing the fitting characteristics.

Methods

Potentially relevant studies were identified using PubMed, Scopus, Web of Science, and Science Direct during the COVID-19 pandemic from February 5, 2020, to March 21, 2023. The search strategy using the following keywords was conducted: Quantitative Fit Test, Condensation Nuclei Counter, Controlled Negative Pressure, PortaCount, Sibata, Accufit, Fit, Seal, Mask, Respirator, Respiratory Protective Device, Respiratory Protective Equipment, Protective Device, Personal Protective Equipment, COVID-19, Coronavirus, and SARS-CoV-2. The quality of the included studies was also assessed using the Newcastle-Ottawa scale.

Results

A total of 137 articles met the eligibility criteria. Fifty articles had a quality score of less than 7 (good quality). A total of 21 studies had a fit test pass rate of less than 50%. 26 studies on disposable respirators and 11 studies on reusable respirators had an FF of less than 50 and less than 200, respectively. The most influential factors include respirator brand/model, style, gender, ethnicity, facial dimensions, facial hair, age, reuse, extensive movement, seal check, comfort and usability assessment, and training.

Conclusion

37.36% of the disposable respirator studies and 43% of the reusable respirator studies did not report fit test results. 67.86% of the disposable respirator studies had a fit test pass rate greater than 50%, and 35.84% of these studies had an FF greater than 100. Also, 85.71% of the reusable respirator studies had a fit test pass rate greater than 50%, and 52.77% of these studies had an FF greater than 1000. Overall, the fit test pass rate was relatively acceptable. Newly developed or modified respirators must undergo reliable testing to ensure the protection of HCWs. Subject and respirator characteristics should be considered when implementing fit testing protocols. An optimal fit test panel should be developed prior to respirator design, certification, procurement decisions, and selection procedures.

Citation: Fakherpour A, Jahangiri M, Jansz J (2023) A systematic review of passing fit testing of the masks and respirators used during the COVID-19 pandemic: Part 1-quantitative fit test procedures. PLoS ONE 18(10): e0293129. https://doi.org/10.1371/journal.pone.0293129

Editor: Sadia Ilyas, Hanyang University - Seoul Campus: Hanyang University, REPUBLIC OF KOREA

Received: April 4, 2023; Accepted: October 5, 2023; Published: October 26, 2023

Copyright: © 2023 Fakherpour et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This study was supported by Shiraz University of Medical Sciences (grant no. 23984). Financial Disclosure This study was supported by Shiraz University of Medical Sciences (grant no. 23984). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

According to the hierarchy of controls, respiratory protective equipment (RPE) usage is inevitably considered one of the preventive and controlling measures during the COVID-19 pandemic [1]. There has been a strong demand for N95 filtering facepiece respirators (FFRs) and surgical masks during respiratory infection pandemics, particularly for the frontline healthcare workers (HCWs) who are exposed to high-risk aerosol-generating procedures (AGPs), including incubation, bronchoscopy, manual ventilation, open suctioning, and high speed drilling in dental procedures, whether through potential contact, droplet, or airborne transmission, and for the patients seeking care who may be potentially transmitting the respiratory viruses through the air [2–5].

The optimal performance of the respirators is dependent on both filtration efficiency and fitting characteristics. Meanwhile, these two main factors warranted the users’ protection by reducing the emission and spread of viral respiratory pathogens through airborne droplets and aerosols and reducing the inhalation of airborne respiratory contaminants (viruses, chemical agents, etc.) [6, 7]. The fit testing procedures are of great importance in international regulations and standards [8–12]. Filtration efficiency determines how well proposed masks or respirators’ filter media filter particles containing viruses, bacteria, and other contaminants [13]. The respirator fitting represents the fitting of a mask or respirator into anthropometric facial dimensions such that there are no gaps or air contaminant leaks between the sealing surface area of the skin and the facepiece [13, 14]. Furthermore, a respirator with a higher filtration efficiency might provide less respiratory protection compared to a respirator with a lower filtration efficiency. In this case, air preferentially passes through the face-seal area due to its lower resistance than the filter media [15].

The respirator fit testing procedure is one of the key elements of the respiratory protection program (RPP), with the aim of selecting a well-fitting respirator with a specific make, model, style, and size. To do so, it is required to provide various sizes, styles, brands, and models to ensure the users’ utmost protection. Overall, two fit testing procedures are classified as qualitative fit testing (QLFT) and quantitative fit testing (QNFT). The QLFT is a dichotomous test based on subjective response to a challenge agent with a distinctive taste or odor. The QNFT is an objective technique (FF) that involves measuring the ratio of challenge agent concentration inside the respirator (Cin) to its concentration outside the respirator (Cout) while conducting the same set of exercises [8–12].

Overall, the investigations revealed that users were mainly concerned with the filter media used for masks and respirators’ making processes (spun bond, melt blown, nanofiber, etc.) and their expected level of filtration efficiency; therefore, less attention was paid to the mask/respirator fitting characteristics during the COVID-19 pandemic [16, 17]. Recent evidence highlights the utmost importance of fit testing adoption to assure the effectiveness of respirators, which might boost regulatory compliance and break the COVID-19 transmission chain [18].

The effectiveness of masks and respirators, as well as decontamination and reprocessing strategies, have been investigated in certain systematic reviews and meta-analyses; however, the fitting characteristics have not yet undergone a thorough evaluation [19–27]. Only one meta-analysis was conducted by Chopra et al. (2021) to examine the influence of ethnicity and gender on respirator fitting [28]. In the current study, we systematically reviewed the studies performed on respirator fitting and affective factors during COVID-19. On the other side, we investigated which countries adopted or implemented respirator fit testing protocols during the COVID-19 pandemics? What were the overall passing rates? Which factors (subjects and respirator features) could significantly affect the fitting capability? Furthermore, we assessed which types of RPE and QNFT protocols were preferably used and then considered possible challenges and limitations obtained during the fit testing. Lastly, we reviewed the quality level of the included studies and summarized their strengths and weaknesses.

Accordingly, this study might serve to emphasize the significance of respirator fitting and also be useful in adopting measures for RPE design and production, revising fast and affordable fit testing protocols, and developing respiratory protection guidelines for potential future pandemics.

Methods

Ethical statement

The current study was approved by the ethics committee of Shiraz University of Medical Sciences (IR.SUMS.SCHEANUT.REC.1400.093).

Search strategy

This work was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines 2020 (http://www.prisma-statement.org/) [29]. See S1 Appendix-PRISMA 2020 Checklist. A comprehensive search for primary literature using five databases, including PubMed (https://pubmed.ncbi.nlm.nih.gov/), Scopus (https://www.scopus.com/), Web of Science (https://www2.wosgs.ir/wos/woscc/advanced-search), Science Direct (https://www.sciencedirect.com/), one scientific website named “Centers for Disease Control and Prevention” (https://www.cdc.gov/), and one scientific journal named “The International Society for Respiratory Protection” (https://www.isrp.com/) during the COVID-19 pandemic from February 5, 2020 to March 21, 2023. To take into account all references cited in the studies, the researchers manually searched the reference lists of the retrieved articles.

Also, the grey literature search was performed using the Google Scholar (https://scholar.google.com/), Google (http://google.com/) search engine, ProQuest (https://www.proquest.com/), Medrxiv (https://www.medrxiv.org/search), OpenGrey (https://onlinelibrary.london.ac.uk/resources/databases/opengrey), and Epistemonikos

(https://www.epistemonikos.org/), Morbidity and Mortality Weekly Report (MMWR)-CDC (https://www.cdc.gov/mmwr/index.html), Wiley Online Library (https://onlinelibrary.wiley.com/), Springer link (https://link.springer.com/), and Nature (https://www.nature.com/) to ensure further studies or relevant electronic documents might not to have been missed. Search terms included (Mask OR Respirator OR Personal Protective Equipment OR respiratory protective device OR Protective Device, Respiratory Protective Equipment, Respiratory Protective Device) AND (Quantitative Fit Test, Condensation Nuclei Counter, Controlled Negative Pressure, PortaCount, Sibata, Accufit, Fit, Seal), AND (COVID-19, Coronavirus, and SARS-CoV-2). Meanwhile, the Medical Subject Headings (MeSH) term, including “Respiratory Protective Device,” was applied to enhance the search and include associated synonyms in the search. The search strategy and excluded articles were provided in S2 Appendix.

Study selection and eligibility.

All documents, including original articles, letters, and reports related to the QNFT procedures and affective factors (subject characteristics and respirator features), were included in the research. We excluded book chapters, review articles, meta-analyses, and guidelines. A total of 137 full texts fulfilled the eligibility criteria.

Data extraction and study quality assessment

Two reviewers (A.F & M.J) independently screened the titles and abstracts of all studies obtained from the comprehensive search. In the next step, two reviewers (A.F & M.J) independently retrieved the full-texts of the included studies, reviewed them, and selected the final studies. Afterwards, the study data, including the first author, number of study subjects, respirator features (type, brand, model, size, and style), subject characteristics (gender: female or male, occupation: HCWs or non- HCWs), country, type of standard QNFT procedure (including, Occupational Safety and Health Administration (OSHA), American National Standards Institute (ANSI), Health and Safety Executive (HSE), International Organization for Standardization (ISO), European Standard (EN), The National Institute for Occupational Safety and Health (NIOSH), Australian/New Zealand (AS/NZS), Canadian Standards Association (CSA), etc.), respirator fit tester (PortaCount, Sibata, etc.), fit test failure or pass rate by respirator brand, model, style, and gender of subjects, and where possible, the relationships between the factors influencing the fit testing and mask or respirator fitting were noted in the study extraction tables (Tables 1–2). All studies obtained during the search strategy, screening, and selection process were imported into EndNote X9 software.

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Table 1. Quantitative fit testing of disposable masks or respirators and affective factors.

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Table 2. Quantitative fit testing of reusable masks or respirators and affective factors.

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Then, the quality assessment of included studies was performed using the Newcastle- Ottawa Scale (NOS) checklist for quality assessment of observational cross-sectional studies. To do so, the quality of studies was calculated and categorized into four groups: “Unsatisfactory” (four stars or less), “Satisfactory” (five to six stars), and “Good” (seven to eight stars), and “Very Good” (nine to ten stars) [30, 31]. The results of the study quality assessment were recorded in S3 Appendix. Considerably, any disagreements during screening, eligibility, selection, data extraction, and quality assessment of included studies were resolved by consensus-based discussion between two reviewers or by the decision of the third independent reviewer (J.J). The selection process for study articles is depicted in Fig 1.

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Fig 1. Overview of systematic review execution according to PRISMA 2020 flow diagram.

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Results

Study characteristics

A total of 137 included studies were performed on quantitative fit testing procedures. Two of the included studies were in Korean, which were translated into English in order not to miss the data in the systematic review [32, 33]. One published online ahead of print research article could not be retrieved [34]. The number of QNFT studies and type of documents that have been published during the COVID-19 pandemic can be depicted in Fig 2. Accordingly, 26 out of 137 (18.98%) studies have been equally published as articles and as original articles, 19 (13.87%) original researches, and 16 (11.68%) research articles, respectively (Fig 2). The document type and study design of the included studies were presented in S4 Appendix.

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Fig 2. Numbers of published studies on quantitative fit testing during the COVID-19 pandemic.

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According to the results from the quality assessment of the included studies in the systematic review (Fig 3), 44.52% of the studies were classified as “Good” quality and 18.98% were categorized as “Very Good” quality. The results obtained from Fig 3 indicate that 36.50% of the studies did not meet the high-quality score due to reasons such as a lack of study design, sampling strategy, sample size calculation, and statistical analysis (S3 Appendix). Therefore, it seems that researchers need to seriously consider all the aspects and details of the study design and research methodology when developing it.

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Fig 3. Results of quality assessment of included studies in the systematic review.

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As can be depicted from Fig 4, all included studies corresponded to a total of 21 countries, including 8 studies (38.1%) performed regarding quantitative fit testing in the developing countries and 13 studies (61.9%) performed in the developed countries. The majority of the studies during the COVID-19 pandemic corresponded to the United States (36.50%) and Australia (16.06%), respectively. It draws the conclusion that fit testing protocols are regulated as one of the legal requirements in developed countries. On the other aspect, it is quite revealing that the implementation of fit testing protocols has been well-established by legal authorities and legislators, manufacturers, employers or managers, and even workplace users in these countries.

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Fig 4. Numbers of studies conducted in different countries during the COVID-19 pandemic.

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All fit test standards proposed by the included studies were noted in Fig 5. A considerable proportion of studies proposed the OSHA standard, per regulation 29 CFR 19.10.134. One study did not propose a respiratory protection standard [35]. Three studies proposed both OSHA and ANSI standards [36–38], and one study proposed OSHA and CSA standards [39]. Also, one study proposed the AS/NZS and OSHA standards [40]. It seems that the precise selection and determination of the type of the proposed fit testing standards, protocols, and acceptable FF relevant to the workplace contaminants and proper respirator being assessed (100, 200, 500, 1000, etc.) before implementing the fit testing is so vital. The most striking result to emerge from the Fig 5 is that the adoption of fit test protocols without consideration of a specific fit test standard is impermissible.

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Fig 5. Proposed fit test standards in the included studies.

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The proportions of proposed quantitative fit testing procedures during the COVID-19 outbreak are presented in Fig 6. As observed, the highest proportion of fit testing procedures corresponded to the Condensation Nuclei Counter (CNC)-based PortaCount QNFT protocol (84.21%). After that, CNC-based Sibita and -AccuFit fit testers account for 6.01% and 6.01% of the included studies, respectively.

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Fig 6. Proposed respirator fit testers by included studies during the COVID-19 pandemic.

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One study used the Sibita fit tester for measuring the leakage rate≤ 5% and PortaCount fit tester for measuring the FF≥100. Surprisingly, the findings of the PortaCount are consistent with those of the Sibita fit tester in such a way that the N95 respirators had a higher probability of providing protection than the KF94 masks [41]. Regli et al., compared the results of standard PortaCount fit tester model 8038 and modified fast PortaCount model 8048 fit testers. It is somewhat surprising that modified fast protocol led to a higher fit test passing rate than that of the standard fit testing protocol [42].

Another study by Salter et al., utilized the Accufit 9000 and PortaCount 8020 fit testers and found that cloth masks made from available materials with a filtration efficiency of 70–90% could be considered as a safe option during the shortage. Moreover, the Effective Fiber Mask Program (EFMP) was strongly suggested for the mass production of optimized fabric masks [43]. Joshi et al. noted that the TSI PortaCount Pro+ model 8038 was comparable to the Grimm Condensation Particle Counter (CPC) fit tester [44]. Fadairo et al. applied the CNC-based TSI PortaCount Pro+ model 8038 and Controlled Negative Pressure (CNP)-based (QHD) fit testers. One unanticipated finding was that a significant difference found in the results of CNC fit test protocol under ambient and controlled environmental conditions using the mannequin in contrast to the CNP protocol [36]. Xu et al. assessed the fit testing results of TSI PortaCount model 8038 compared to those QHD Quantifit tester. Surprisingly, there was a significant difference between the CNC and CNP results with respect to facing forward, bending over, shaking the head, wearing the mask again, and moving the head up and down [45]. It is evident that the CNC protocol-based TSI PortaCount fit tester is the best known and most commonly used by researchers compared to the remaining fit test protocols and fit testers.

The proportion of studies in which evaluated the fitting characteristics of masks or respirators is shown in Fig 7. As can be seen, the highest proportions of studies attributed to the 72 studies on N95 masks, 27 studies on procedure masks or surgical masks; 18 studies on half-facepiece EHRs; 17 studies on cloth or fabric masks; 14 studies on both KN95 respirators and Powered Air Purifying Respirators (PAPRs), respectively. Considerably, ten studies applied three-dimensional (3D) printing materials and rapid prototyping techniques to design and make the half-facepiece filtering and elastomer respirators [46–53]. Two studies did not report the mask and respirator characteristics being utilized [54, 55]. Furthermore, the filter level, brand, and model of the FFRs were not determined in the study by Jean-Romain et al. [56]. It would seem that different masks or respirators may provide different levels of respiratory protection with respect to the subject and the mask or respirator characteristics and the nature of the user’s workplace tasks, so it is not necessary to rely on only one type of respirator to implement fit testing protocols as an essential component of RPP.

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Fig 7. Types of masks and respirators assessed during the COVID-19 pandemic.

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Quantitative fit test studies

The comprehensive reviews of the included studies are presented in Tables 1 and 2. The results were described in more detail in S5 Appendix. A total of 79 studies were conducted regarding disposable masks and or respirators (cloth masks, fabric masks, surgical masks, N95, FFP2, FFP3, KN95, K94, etc.), 49 studies on reusable masks and or respirators (snorkel masks, half-face piece respirators, full-face piece respirators, PAPR, and SCBA), and nine studies concerning knowledge, attitude, perception, skill, and training toward fit testing.

A total of 49803 subjects (comprised of 92 studies) reported in all studies, of which 12391 were males and 35695 were females. Approximately 1717 gender of subjects (45.21%) was not reported. In total of 46 studies did not report the gender proportion. Among them, four studies did not report the number of study subjects in more detail [43, 53, 57, 58], and two studies did not comprehensively and clearly report the number of study subjects [55, 59]. Also, in three studies, no subject characteristics were presented [60–62].

Subjects of 60 studies were HCWs, the professional group’ HCWs were included the following: four studies: anaesthetists and predominantly anaesthetic technicians, anaesthetic consultants and trainees [5, 35, 63, 64], five studies: physicians [65–69], one study: respiratory therapist [66], twenty-one: nurses [37, 40, 41, 59, 66, 67, 69–83], one study: administration [84], four studies: allied health staff [40, 59, 80, 84], seven studies: medical or clinical staff [59, 73, 80, 82, 84–86], one study: paramedic staff [78], three studies: medical practitioner [40, 80, 83], one study: aged care or disability worker [40], two studies: medical imaging staff [40, 80], five studies: other healthcare worker [40, 59, 78–80], five studies: non-clinical role [40, 80, 81, 83, 86], one study: infection control practitioners [87], two studies: laboratory workers [45, 88], eight studies: doctors [41, 70, 71, 76, 78–80, 83], one study: health center workers [89], four studies: dental and dental hygiene students [80, 90–92], one study: emergency medical technician [71], one study: ICU staff members [93], two studies: physiotherapy lecturer [81, 94], one study: radiographer [81], and three studies: pharmacists [40, 80, 95]. The study by Thiam Goh et al. performed on children [96] and other research by Lim et al. conducted on elderly females [97]. One study was conducted on one patient [98]. The study by Xu et al. was conducted on chemical plant operators and maintenance personnel [45].

Other subjects’ studies were as follows: five studies: college or university students [75, 90–92, 99], one study: UK employees [100], two studies: industry workforce or workplace participants [101, 102], two studies: Japan University of Occupational and Environmental Health [103, 104], one study: employees of the National Institute for Occupational Health (NIOH) [105], and one study: American Society of Safety Professionals (ASSP) [54]. Notably, the HCW subjects’ occupations or professional groups were not mentioned in nineteen studies [32, 33, 42, 51, 53, 58, 88, 106–117]. The subjects’ occupations in the remaining 69 studies were not exactly determined. Six studies did not characterize the numbers of study subjects [43, 44, 57, 60–62]. Also, four studies had no human subjects; then, they were categorized as laboratory studies [44, 118–120]. Eight studies were conducted using a manikin, or mannequin, or headform [36, 49, 121–126]. Among all, five studies were performed using human subjects and one manikin [36, 121–123, 125].

The quantitative fit test studies conducted on disposable respirators or masks, including cloth, or fabric, or homemade masks, surgical, or medical, or procedure masks, FFRs (e.g., N95, N99, P100, FFP2, FFP3, KN95, and KF80), and FFs of the cloth and surgical masks compared to those of FFRs in the present systematic review are presented in Table 1.

Accordingly, in Table 1, 56 out of 87 studies reported the mean passing fit testing proportions, of which 38 studies had a fit testing passing rate higher than 50% and 24 studies had a fit testing passing rate higher than 70%. 53 out of 87 studies reported mean FFs, of which 27 studies, including three studies on Cloth masks and 24 studies on FFRs with a mean FF≥ 50, and 19 studies had a mean FF≥ 100. Among these, only 27 studies reported both mean passing fit testing proportions and mean FFs. This finding seems to have highlighted the important role of fit testing in all potentially hazardous situations, for all individuals exposed to all types of respiratory hazards, including but not limited to hazardous workplaces. In the next section, we will present the principal findings of the current investigation regarding the factors influencing the fitting characteristics.

Thirteen studies reported that there were significant differences in passing fit test rates of masks or respirators [39–41, 65, 69, 77, 94, 108, 111, 127–131]. In the study by Martelly et al., the significant level was not reported; however, due to the considerable difference between the two studied respirators, it could be considered as a statistically significant difference in terms of FF (7.0 vs. 143) [129]. Whereas, no significant differences were determined between the studied masks or respirators in the six studies [32, 48, 51, 63, 131, 132]. Due to fit test principle called “OSFA” which stands for there is no one size fits all, fit test results would be unpredictable and each subject could fit with a specific brand, model, style, and size. Also, it seems that the respirator model or brand must be considered as one of the factors influencing fitting characteristics in order to ensure optimal respiratory protection for the users. For example, in the study by Drouillard et al. [39], the average FFE of the control medical mask (55.3%) was lower than that of the fabric mask (64.97%), whereas the Bandana masks exhibited lower FFEs (39.8%-48.1%). It would appear that the material characteristics, such as fabric weight and pore size were significant factors influencing FFE. An increase in fabric weight could result in higher FFE, whereas a reduction in pore diameter could enhance the FFE.

A study found that the N95 respirators had a higher FF than the K94 ones. Also, fixing ear straps with hooks significantly improved respiratory protection rates of KF94 respirators by FF (1.1% vs. 12.8%, p<0.001) [41]. With similar filtration efficiency, particles could leak through the face-seal area; in that case, the poor KF94 respirators would endanger HCWs during AGPs. Application of a hook to fix the loops at the back of the head is considered a fitting improvement strategy. Therefore, a valid fit testing method is highly needed, and a higher-protected PAPR should be substituted if possible [41].

A total of eight studies assessed the influence of respirator style on respirator fitting [33, 70, 80, 82, 95, 107, 128, 130]. In four studies, cup-shaped respirators had the highest passing fit rate [33, 70, 80, 130]. Cup-shaped, duckbill, and flat-fold respirators also had the highest fit test pass rates, respectively in two studies [33, 70]. Ng et al. found that the three-panel flat-fold had a higher passing rate than cup-shaped ones [80]. Contrary to expectations, no significant difference was observed between the respirator styles in the study by Zhang et al. (cup: 57.1% vs. flat-fold: 51.8%) [128]. This inconsistency may be related to the variety of molds that manufacturers are commonly used to produce respirators for the users with different facial dimensions and ethnicities. Besides, application of non-standard or inappropriate commercially available molds by some manufacturers during respirator production may adversely affect the fitting capability and optimal respiratory protection.

Six studies were conducted regarding the effects of extended reuse on fitting characteristics [66, 68, 70, 87, 133, 134]. Sheikh et al. showed that the trend of pass rate was downward from the first attempt to the fourth attempt and upward by the fifth attempt [66]. Fabre et al. estimated all donned N95s less than 12 times, and the probability of an N95 maintaining a good fit was >95% for up to 23 donnings [68]. One study reported that the general respirator protection factor (GRPF) tended to increase or decrease from the previous day as the number of reuses per day increased. Overall, the GRPF for all subjects was lower than the initial GRPF after donning on day 5 [133]. Jung et al. determined that the successive donning led to a reduction in fit test passing rate and thus highlighted that in high-risk situations like those involving aerosol-generating operations, N95 respirators should only be used once and for no longer than one-hour [87]. Contrary to expectations, two studies reported high fit rates after reuse of N95 respirators. It is implied that acceptable fit prior to donning the reused respirators in real healthcare setting should be ensured by implementing a valid fit testing protocol, preferably the QNFT, due to infrequent or false passes in fit testing [68, 70]. However, it would be better to adopt the reuse technique for a short period of time [70].

Ten studies were conducted on the impact of fit test exercise type on fitting characteristics [45, 60, 71, 77, 79, 104, 127, 135–137]. Amongst, three studies evaluated chest compression [71, 79, 135]. Hwang et al. demonstrated that about 73% of the HCWs failed the fit testing on at least one of the three chest compressions [71]. Similarly, Goto et al. confirmed that a high proportion (78%) of the HCWs failed at least one of the three compressions [79]. In contrast, the investigation of the fitting of PAPR during compression by Ng et al. concentrated on the fact that no significant differences were observed in passing the fit testing before, during, or after the chest compression, regardless of the HALO PAPR power mode, which could be considered an alternative to the N95 respirator. Nonetheless, other aspects, including doffing difficulty and perceived communication interference should be paid attention [135], In the Han et al. investigation, the face-nose adhesion also decreased due to the effects of gravity, and the FFs of all three groups of respirators considerably dropped during the waist-bending exercise. When caring for patients who require airborne precautions, healthcare professionals should avoid bending at the waist. This happened because the fit test exercises revealed a variation in fit [77]. The fit test was not passed by talking exercise in the research by Xu et al. [45] and Kechli et al. [60]. The fit test exercises had a greater FF than resting exercises, according to the Baba et al. study [104]. Anwari et al. deemed "Failure" three of the fit test exercises, which involved bending, talking, and side-to-side movement [136]. Likewise, another research pointed out that extensive head and body movements could disrupt the adjustment and fitting of respirator [137]. These findings seriously focused on the fact that unpredictable movements (heavy or light workload) of the subjects while performing the tasks with environmental situations and verbal communications could affect the provision of respiratory protection to the users and increase their exposure to workplace hazards; therefore, the need for proper respirator selection and donning and standard fit testing procedures are strongly suggested.

Eight studies looked at the effect of gender on fitting ability [32, 37, 66, 78, 89, 107, 111, 114, 117], with four of these highlighting that males had a higher pass rate than females [66, 89, 111, 117]. Christopher et al. highlighted the reasons for failing the fit test for females, including facial asymmetry (8%), small bones (77%), and none reported (15%), and the reasons for males, including facial hair (91%), large bones (3%), and small bones (6%) [89]. In the study by Williams et al., although males had a higher passing rate than females; however, females were fitted with the 3M 9320A more often than males (7.3% vs. 1.5%, p< 0.001) [111]. In contrast, some other studies reported that females had a higher pass rate than males [78, 107, 114]. Two studies also found no significant differences in fit test pass rates by gender [32, 37]. Overall, gender appears to be one of the factors influencing fit testing; therefore, providing a variety of respirators in terms of brand, model, style, and size is also of great importance.

Three studies examined the impact of ethnicity on fitting capability [66, 117, 134]. In the study by Sheikh et al., White males or females received a higher FF than those of whether non-White males or females, and then this study addressed that gender and ethnicity should be considered to reflect the diversity of Canadian HCWs [66]. Other studies found that male and White ethnic HCWs were significantly more likely to succeed in fitting compared to females [117, 134]. It would appear that manufacturers are required to design and produce respirators that are relevant to the facial dimensions of their population in terms of gender and age distribution.

Two studies, by Seo et al. and Winski et al., found that face size categories had no effect on fitting [78, 100]. Also, seven studies investigated the influence of facial dimensions on fitting [37, 41, 66, 78, 100, 128, 134]. In the study by De-Yñigo‐Mojado et al., there were significant variations in face length, breadth, and depth between males and females. As a result of the lager face length, depth, and width dimensions in males, as well as the presence of facial hair, the males had lower FFs [37]. In the Seo et al. research, the facial dimensions of the Korean people compared to the NIOSH bivariate panel were significant. However, due to the insignificant difference in passing rates among the face-size groups, it is required to develop a unique fit test panel for the Korean users [78]. Furthermore, in the research of Winski et al., only significant differences were observed between face width and jaw width with FF, and they concluded that increasing the ratio of face width to jaw width (10%) could significantly increase FF [100]. The research of Zhang et al. also showed that bitragion submandibular arc had an inverse relationship and face length had a direct relationship with FF [128]. There was also a slight difference between the fit test results and facial dimensions (e.g., facial length, nasal length and protrusion, alar and biocular width) reported by Sheikh et al. [66]. Park et al. determined that face length, age, department of current work, and career were associated with an adequate protection rate [41]. It seems that taking facial dimensions into account when designing respirators has resulted in optimal production.

Two studies comprehensively evaluated the applicability of the NIOSH bivariate fit test panel to the Korean and American Sheikh populations, [66, 78]. In addition, five studies concluded that the NIOSH bivariate fit test panel may not be representative of the proposed population; thereby, these studies outlined the need to develop the optimal fit test panel representing the facial dimensions is necessary [66, 78, 100, 127, 130]. Additionally, if the fit test results are indistinguishable between the NIOSH cells [78, 100], adjustments must be made. To optimize the NIOSH bivariate panel for the proposed population, facial dimensions relevant to the respirator fitting must be measured, not just face length and width, which are proper predictions of respirator fitting based on the ISO 16976–2 standard [138].

Four studies concluded the negative effects of facial hair on fitting capability [38, 89, 115, 139]. Another point is that the influence of facial hair on the fitting capability of surgical masks was less than that of the FFP3 respirators. The lower FFs for the HCWs without facial hair while wearing surgical masks could be attributed to their cranial shape and facial anatomy [38]. Two factors, including small bone structure for females and facial hair for males, are considered to be the main challenges for fit test failure [89]. Subjects must be clean-shaven prior to fit testing and while donning a tight-fitting respirator; otherwise, positive pressure respirators (such as PAPR, etc.) should be worn [37]. For example, Sandaradura et al. found that the odds of failing the fit test were 1.35 for light stubble, 2.22 for moderate to heavy stubble, and 25 times higher for a full beard than for no facial hair [115]. In the Prince et al. research, the influence of beard length on respirator fitting showed that the rapid inhalation and facial movements associated with speech are likely to cause a loose-fitting mask or respirator to pull toward the face, as opposed to the sealing challenge of a rigid respirator to obtain a tight fit [139]. It appears that facial hair could get stuck under the straps while adjusting the respirator on the face, then it might play as an interfering factor. In that case, subjects feel a false sense of protection whilst inhaling respiratory contaminants through creating a gap between the users’ face and respirator’s facepiece.

Two studies evaluated the effect of age group on fit test results [41, 107]. Park et al. found that age could increase the likelihood of passing the fit test [41]. In contrast, the pass rate for subjects aged 18–29 years was significantly higher than for those aged 30–59 years. Consequently, older age groups and male groups were associated with significantly higher fit test failure rates [107]. In light of the above, it is noteworthy that the age of the subjects is taken into account in the fit test survey.

Ten studies evaluated the impact of user seal checks (USCs) on passing the fit test [52, 59, 63, 64, 68, 71, 88, 102, 140, 141]. There were no similarities between the results of the USCs and fit tests in eight studies [63, 64, 68, 71, 88, 102, 140, 141]. It may seem that the USCs could only detect the gross leakage around the sealing surface area and considered as a proper adjusting the respirator into face; however, users should not fully rely on the USCs; instead, they need to concentrate on the fit test protocols to ensure respiratory protection.

Seven studies evaluated the subjective indices (comfort, usability, activity, speech intelligibility, etc.) regarding the respirators tested [52, 66, 75, 80, 90, 91, 96]. In the research by Ng et al., among four respirator styles, overall comfort and overall assessment values were highest for the three-panel flat-fold respirator and lowest for the semi-rigid cup respirator. To ensure respiratory protection for HCWs, procurement procedures should take into account comfort and usability values, fit testing results, and performance evaluation [80]. According to the Cloet et al. study, the design of a high-performance respirator must take into account activity (breathability and stability) and usability (subjective discomfort, wear efficiency, and speech intelligibility) factors. It is obvious that in addition to the protective factors, ergonomic parameters should be considered during the selection or replacement of a new brand, model, style, or size of respirator [91].

The results of fit testing of reusable masks and respirators are shown in Table 2. A total of 50 studies performed on EHRs were reviewed. A total of 21 studies reported the mean fit test pass rate, of which 18 studies reported a relatively high pass rate (≥50%) and 17 studies reported a high pass rate (≥70%). In addition, 36 studies reported mean FFs, including 25 studies with mean FF≥ 200, 21 studies with mean FF≥ 500, and 19 studies with mean FF≥ 1000. Of these, only 11 studies reported both mean fit test pass rates and mean FFs.

In five studies of reusable respirators, optimal fit was not achieved [46, 53, 141–143]. Despite the fact that all of the 3D-printed prototypes in the Ballard et al. study were built of flexible materials, three of them failed to offer an acceptable fit into the facial dimensions of four individuals. Importantly, fit testing procedures must be conducted on a sufficient sample of consumers in order to make adjustments to the prototypes that have been put to the test feasible [142]. In another study by Ballard et al., 3D-printed prototypes equipped with only HEPA filters could pass the fit test. This finding concentrated on the fact that the type of filter used for fit testing of EHRs is of great value, because improper filters lead to the leakage and provide a false sense of protection [53]. Duda et al. noted that the studied 3D-printed face masks could not be used in clinical settings. The main causes of this are leakages associated with the connection of the masks with the filter material, particularly unwanted leakages brought on by the simplified filter box construction, as well as the low flexibility of the material and the thin sealing line, which prevent the necessary sealing performance on the face [46]. It is undeniable that the respirators with 3D-printed designs are made of subtle, heavy, and complicated components with different materials, and components’ connections. In this regard, it is masterwork and hard challenging to achieve an acceptable fit.

In the study by Martelly et al., molding a reusable respirator could serve as another strategy to improve fitting and be utilized as a safe substitution during the shortage of N95 respirators. Accordingly, one key factor in obtaining proper respirator fitting is the strap tension and orientation. Keeping the top strap from sliding to the back of the head caused problems for the subjects with short and smooth hair, which in turn influenced the fitting during fit testing. Other subjects with long or short, textured hair keep the strap from sliding by either using a ponytail or friction [129]. It is evident that the subjects’ hairstyle acted as an interference factor, causing the head straps to slip and loosen, thereby disrupting the proper fit.

Fifteen studies were performed regarding the reusable respirators compared to the FFRs [48, 51, 53, 58, 61, 63, 67, 69, 93, 94, 99, 112, 127, 137, 142]. All those studies reported that reusable respirators achieved a higher passing fit test rate than those of FFRs. The novel Duo mask, consisting of two inhalation valves, one exhalation valve, and two filters, reduced inspiratory resistance and dead space while prolonging the service life of filter [127]. Ballard et al. remarked that the 3D-prototype respirator is a desirable alternative to the N95 respirator when achieving the optimal fitting is impossible [142].

The Stick-on mask Lekad improved FF by 40, 35, and 30 times compared to surgical, double, and N95 masks. The Duo mask showed a higher FF than N95, suggesting disposable respirators could replace reusable masks in terms of bidirectional protection requirements and cost-benefit analysis [94]. It is strongly suggested to compare the fitting characteristics of novel reusable respirators to those of traditional EHRs or FFRs to undergo various fit testing procedures (CNC vs. CNP) in order to learn and understand about the variations, restrictions, and FFs offered to users with various anatomical features. For example, in the Nicholson et al. study, a full-face respirator was compared with three different types of Snorkel masks, with comparable results [144]. It would seem that a series of prototype designs using various molds and multi-system sizes may overcome the technical difficulties and create respirators that could serve the intended market. Nonetheless, it is strongly recommended that modified commercial respirators due to unstable protection be required to undergo rigorous testing to ensure that the HCWs remain protected.

Additionally, it is preferred that respirators be evaluated when employees are doing duties in actual workplaces or simulating work processes as part of a fit test exercise for SWPF or WPF evaluation to ensure the optimum protection. Besides, not only is the performance evaluation of commercial, modified, or newly developed respirators critical to meeting the standard criteria, but comfort, usability, and activity evaluations are also highly recommended. Since disposable respirators were lighter, they were more comfortable than reusable respirators for a short period of time; however, some limitations, such as a lower level of protection and variability of protection rate due to structural damage or prolonged use or reuse, possible contamination of the outside of the respirator, a lower filtration level and unacceptable fit, and the inability to be worn by individuals with asthmatic, cardiovascular, and hypertensive diseases, etc., could occur.

A total of twelve studies, including eleven studies on disposable respirators (Table 1) and one study on reusable respirators (Table 2) were assessed the influence of fit testing procedure on attitude, knowledge, perception, or training in fit testing. A total of were conducted. Three studies were conducted on knowledge [55, 72, 92], three studies on attitude [55, 59, 72], two studies on perception [54, 92], one study on skills [59], and six studies assessing the influence of training on fit testing [33, 81, 83, 84, 140, 145]. Accordingly, in two studies, knowledge [55, 59], in one study, attitude [55], in two studies, perception [54, 92], in one study, skills [59], and in six studies, training [33, 81, 83, 84, 140, 145] regarding the fit testing improved. Training plans (online or visual inspection of respirator fit and verbal suggestions for adjustment) could improve knowledge, attitude, perception, skill level in properly donning the respirator, and the importance of performing fit tests, resulting in reliable fit test results and passing the fit test.

Discussion

The present study aimed to evaluate the fitting capability of all kinds of masks and respirators and explore the relationship between mask or respirator fitting and affective factors during the COVID-19 pandemic. Some key findings obtained from this study are presented below.

According to the risk of bias assessment, although 50 (36.50%) out of 137 studies, except for one, possessed an acceptable quality score. However, those studies have some considerable weaknesses in terms of study design and methodology. To do so, this investigation informs specialists and researchers that before developing a study on respiratory protection, all aspects and research process steps must be deeply considered. Some important values that were neglected and need to be improved in the studies are as follows: acceptable sample size (calculation, justification), type of study (experimental, cross-sectional, observational, etc.), study design (blinding, randomization, control group), subject characteristics (number, gender, occupation, age, BMI, facial dimensions, etc.), respirator features (filtration level, brand, style, size), and exact and full reports of study findings.

In this review, 31 out of 87 studies (35.63%) and 34 out of 87 studies (39.08%) conducted on disposable masks or respirators did not report the mean fit test pass rate and mean FF, respectively. Similarly, 29 out of 50 studies (58%) and 14 out of 50 studies (28%) on reusable respirators did not report the mean fit test pass rate and mean FF, respectively. This issue was a major concern among the studies, so it is highly necessary that researchers report the results more clearly and comprehensively to enhance the importance and value of the study and make those results more useful and convincing to the relevant readers or users.

Among the reported studies on disposable masks, 18 out of 56 studies had a pass rate lower than 50%, 26 out of 53 studies had an FF lower than 50, and 31 out of 50 studies had an FF lower than 100, respectively. It concluded that the fit test failure rate in these studies was relatively high. Providing multiple brands, styles, or sizes could benefit respirator users achieve an optimal FF. Also, among the reported studies on reusable masks, 3 out of 21 and 4 out of 21 studies had pass rates lower than 50% and 70%, respectively. 11 out of 36 studies had an FF lower than 200, and 17 out of 36 studies had an FF lower than 1000. It can be found that most of the studies had an acceptable fit test pass rate (≥50%) and FF (≥200). Because there are a considerable number of non-reported studies, the final decision on the results of all studies would be challenging.

One possible reason for the low passing rate among these studies could be due to the limited supply of standard masks and respirators, such as N95 types, in order to provide optimal fitting for the users with high-risk duties (e.g., AGPs); in particular, for the HCWs exposed to suspected or confirmed COVID-19 patients. Moreover, it might be that only one size or one style of masks or respirators underwent fit testing procedures. To overcome this issue, according to the principle “there is no OSFA respirator”, every user could not be fitted into a respirator of a specific brand, model, style, and size; therefore, managers and employers are required to provide a variety of respirators with combinations of brands, models, styles, and sizes to ensure the satisfactory protection for the workers [172]. Another reason could be that those studies rely on only the filtration efficiency; the respirator fitting into anthropometric dimensions as one of the affective factors on respiratory protection has been neglected [7, 16].

Respirator type and brand were reported to have a significant effect on respirator fit. Overall, all disposable and reusable respirators had a specific structure and design that could affect their fitting characteristics, e.g., material characteristics, including rigid or soft materials, fabric or filter weight, pore size, and number of layers; and design factors, such as head straps, nose clips, and ear fixation; and inspiratory and expiratory valves, are affective factors on optimum fitting. Unexpected leakage from component connections or installations (inflexible or heavy molds, valves, and straps) was considered a notable concern [46]. Clogging and disinfection are other challenges that increase backpressure, ultimately resulting in a decrease in FFs [137].

In the study by Ballard et al., a well-fitting EHR equipped with HEPA filters (high filtration level) could be comparable to the commercial N95 respirator [53]. Roche et al. demonstrated that a 3D-printed respirator would be comparable to the FFP3 without compromising verbal communication [51]. Germonpre et al. outlined that a modified snorkel mask with 3D-printed adaptors could outperform the N95 fit and be superior to temporary adaptations [58]. Another study found that the N95 respirator and snorkel mask with high-efficiency filters could provide inconsistent protection compared to the snorkel mask with PAPR. Therefore, robust testing is needed to assure the protection of the HCWs [69]. One of the disadvantages is that although the PAPR could obtain a consistent and adequate level of respiratory protection during compression, it could create doffing difficulty and communication performance interference [135]. Another study stated that a 3D-printed respirator could be utilized when subjects do not pass the fit testing of a commercial N95 respirator due to style, size, or variations in face morphology. Particularly, it could be an appropriate alternative to disposable respirators due to continuous failure of the fit test following the adoption of reuse and disinfection procedures [142].

Another finding was that the cup-shaped respirators fitted more than all styles. Likewise, the cup-shaped activated carbon was considered the best option for filtering anticancer drugs in a clinical setting [95]. Since each user has a specific face shape (anatomical structure, hollow, protrusion, etc.) with regards to BMI, ethnicity, age, etc., it is necessary to provide a variety of respirators for fit testing to identify the best fit option in terms of protective and ergonomic aspects. As the number of models, sizes, or styles increases, the likelihood of subjects succeeding in fit testing increases. Ciotti et al. stated the cup-shaped respirators were more suitable for HCWs with large faces [173]. However, the three-panel flat-fold style was more fitted into the anthropometric dimensions of the Australian HCWs with the highest comfort and usability scores [130]. It is recommended that manufacturers design and make masks or respirators following approaches towards multiple-size-systems (3-, 4-, and 5-size) [174] instead of single-size system (OSFA) and various styles [173] (cup-shaped, flat-fold, and duckbill) to fit the proposed users, including HCWs, industrial workers, etc.

Extensive reuse was reported as another factor influencing respirator fit. Given that continuous and repeated donning of the respirator over several days will impede the quality of fitting due to possible contamination or deterioration of the respirator’s components. Nevertheless, fit testing of reused respirators prior to entry into hazardous workplaces is essential. Subjects with high-risk occupations should be cautious about excessive movement. Notably, a properly fitted respirator would not provide protection for the HCWs, thereby impairing the protective performance of the respirator, because chest compression during CPR requires significantly rapid, intense, and dynamic upper body movements that are more dynamic than QNFT exercise [71]. To ensure the provision of respirators in real situations (e.g., emergencies), it is strongly suggested that investigators adopt fit test protocols in a simulated scenario such as chest compressions. If it is necessary, the respirators will be changed or effective control strategies will be implemented in the workplace.

Differences in anthropometrical dimensions between females and males could considerably affect the results of respirator fit testing [117]. Given that the design and production of RPE are mostly based on males’ dimensions. Proper selection and certification of RPE is so hard-working. Due to the specific effect of gender on respirator fit, careful attention must be paid to the design and selection of respirators that are appropriate for their facial dimensions.

The facial dimension is another affective factor. An optimal and unique respirator fit test panel (RFTP) based on the facial dimensions of the proposed population should be developed before respirator design, certification, and selection [175–179]. This issue could assess the procurement decision-making procedures for respirator stocking, preventing poor respirator supply and the scarcity of correctly sized respirators [117].

Comfort, usability, and activity indices are three paramount factors in determining the respirator fitting. Moreover, as part of a comprehensive RPP, four classifications of RPE characteristics are taken into account, including "safe and effective; compatible with work activities; comfortable and tolerable for the duration of wear; and compliant with relevant standards, guidelines, and policies", which benefit from proper respirator evaluation and selection [180]. The necessity of implementing fit testing and performance evaluation of HCWs when making procurement decisions was emphasized by Ng et al. In the interim, wearer compliance, respirator fitting, and purchasing decisions are influenced by the fit test passing rate, usability, and comfort evaluations [80]. Training on proper selection, donning and doffing, and the importance of fit testing protocols could improve the subjects’ knowledge, perception, attitude, skill, and experience toward respirator fit testing compared to the pre-fit test steps [59, 76, 83, 161].

Limitations

The included studies lack the appropriate or proper study design, sampling strategy, sample size calculation, statistical analysis, and study procedure (e.g., fit testing of respirators with various brands, models, styles, and sizes). Another limitation is that some studies did not report the features of the respirators (brand, style, size, filtration level, etc.) or subjects (gender, age, occupation; high/low physical workload, etc.) being fit tested. Furthermore, small sample sizes are another weakness. In this study, a comprehensive systematic review was conducted to evaluate the fitting capability of all kinds of masks and respirators and to explore the relationship between respirator fitting and affective factors during the COVID-19 pandemic.

Conclusion

37.36% of the disposable respirator studies and 43% of the reusable respirator studies did not report fit test results. 67.86% of the disposable respirator studies had a fit test pass rate greater than 50%, and 35.84% of these studies had an FF greater than 100. Also, 85.71% of the reusable respirator studies had a fit test pass rate greater than 50%, and 52.77% of these studies had an FF greater than 1000. Overall, the fit test pass rate was relatively acceptable. Newly developed or modified respirators must undergo reliable testing to ensure the protection of HCWs. Subject and respirator characteristics should be considered when implementing fit testing protocols. An optimal fit test panel should be developed prior to respirator design, certification, procurement decisions, and selection procedures.

Acknowledgments

The authors gratefully acknowledge those researchers who provide assistance in improving this research.

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