Subject validation of reusable N95 stop-gap filtering facepiece respirators in COVID-19 pandemic

A comparative study of point-of-care protection from N95 filtering face-piece respirators in a Residential Aged Care Facility and a Tertiary Hospital-Respiratory protection challenges remain amidst long-term impacts of COVID-19

This study compared the effectiveness of N95 FFRs in providing respiratory protection for healthcare staff in a residential aged care facility (RACF) and tertiary teaching hospital (TTH) who had previously passed their occupational respiratory protection program fit test. A total of 126 healthcare workers who were regularly using N95 FFRs and who had previously passed a fit test participated in this comparative study. In this study, participants were again fit tested with the PortaCount machine, and their self-assessed tolerability of wearing an N95 FFR was assessed using a standardized questionnaire. The main outcome measures included the pass rate of the fit test and the assessment of tolerability and comfort of the N95 FFR. Across all participants, the fit test pass rate was low (27%), indicating persistent gaps in respiratory protection programs for healthcare workers during the ongoing COVID-19 pandemic. Hospital workers were 3.7 times more likely to pass the test compared to their counterparts in RACFs (p < 0.001). It was also found that workers in RACFs reported higher levels of discomfort and overall dissatisfaction with N95 FFRs compared to hospital staff. These findings highlight the need for targeted interventions and improvements in respiratory protection practices beyond annual fit testing, particularly in RACFs, to ensure the safety of healthcare workers and the vulnerable population they serve.

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

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.

Personalized 3D-printed frames to reduce leak from N95 filtering facepiece respirators: A prospective crossover trial in health care workers

Correctly fitting N95 filtering facepiece respirators (FFRs) have become increasingly important in health care throughout the COVID-19 pandemic. We evaluated the hypothesis that personalized 3D-printed frames could improve N95 FFRs quantitative fit test pass rates and test scores in health care workers (HCWs). HCWs were recruited at a tertiary hospital in Adelaide, Australia (ACTRN 12622000388718). A mobile iPhone camera + app was used to produce 3D scans of volunteers' faces, which were then imported into a software program to produce personalized virtual scaffolds suited to each user's face and their unique anatomical features. These virtual scaffolds were printed on a commercially available 3D printer, producing plastic (and then silicone-coated, biocompatible) frames that can be fitted inside existing hospital supply N95 FFR. The primary endpoint was improved pass rates on quantitative fit testing, comparing participants wearing an N95 FFR alone (control 1) with participants wearing the frame + N95 FFR (intervention 1). The secondary endpoint was the fit factor (FF) in these groups, and R-COMFI respirator comfort and tolerability survey scores. N = 66 HCWs were recruited. The use of intervention 1 increased overall fit test pass rates to 62/66 (93.8%), compared to 27/66 (40.9%) for controls. (OR for pFF pass 20.89 (95%CI: 6.77, 64.48, p < 0.001.) Average FF increased, with the use of intervention 1-179.0 (95%CI: 164.3,193.7), compared to 85.2 (95%CI: 70.4,100.0) with control 1. Pass rates and FF were improved with intervention 1 compared to control 1 for all stages of the fit-test: bending, talking, side-to-side, and up-down motion. (p < 0.001 all stages). Tolerability and comfort of the frame were evaluated with the validated R-COMFI respirator comfort score, showing improvement with the frame compared to N95 FFR alone (p = 0.006). Personalized 3D-printed face frames decrease leakage, improve fit testing pass rates and FF, and provide improved comfort compared to the N95 FFR alone. Personalized 3D-printed face frames represent a rapidly scalable new technology to decrease FFR leakage in HCW and potentially the wider population.

Personalised 3D printed respirators for healthcare workers during the COVID-19 pandemic

Widespread issues in respirator availability and fit have been rendered acutely apparent by the COVID-19 pandemic. This study sought to determine whether personalized 3D printed respirators provide adequate filtration and function for healthcare workers through a Randomized Controlled Trial (RCT). Fifty healthcare workers recruited within NHS Lothian, Scotland, underwent 3D facial scanning or 3D photographic reconstruction to produce 3D printed personalized respirators. The primary outcome measure was quantitative fit-testing to FFP3 standard. Secondary measures included respirator comfort, wearing experience, and function instrument (R-COMFI) for tolerability, Modified Rhyme Test (MRT) for intelligibility, and viral decontamination on respirator material. Of the 50 participants, 44 passed the fit test with the customized respirator, not significantly different from the 38 with the control (p = 0.21). The customized respirator had significantly improved comfort over the control respirator in both simulated clinical conditions (p < 0.0001) and during longer wear (p < 0.0001). For speech intelligibility, both respirators performed equally. Standard NHS decontamination agents were able to eradicate 99.9% of viral infectivity from the 3D printed plastics tested. Personalized 3D printed respirators performed to the same level as control disposable FFP3 respirators, with clear communication and with increased comfort, wearing experience, and function. The materials used were easily decontaminated of viral infectivity and would be applicable for sustainable and reusable respirators.

Quantitative Fit Test of a 3D Printed Frame Fitted Over a Surgical Mask: An Alternative Option to N95 Respirator

Background

COVID-19 has spread worldwide and caused severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to numerous dead cases. However, with the new COVID-19 outbreaks, there is a shortage of personal protective equipment (PPE) especially N95 masks worldwide including Thailand. This issue had placed the health professional in great need of an alternative mask.

Aim

This study aimed to measure the fit factor of 3D printed frames by quantitative fit testing (QNFT) to find an alternative facemask by using a mask fitter together with 2 different kinds of the American Society for Testing and Materials (ASTM) level 1 surgical mask.

Materials and Methods

Two commonly used surgical masks (Sultan Com-Fit Super Sensitive Ear Loop Mask or “White Mask Group,” not water-resistant, and Sultan Blue Com-Fit Super High Filtration Ear Loop Mask or “Blue Mask Group,” water-resistant) with and without 3D printed frame covering. The fit performance was measured by a quantitative fit test (QNFT) device (PortaCount, model 8048, TSI Incorporated, Minnesota, USA) accepted by the Occupational Safety and Health Administration (OSHA). The PortaCount device, which is based on a miniature continuous flow condensation nucleus counter (CNC), assesses the respiratory fit by comparing the concentration of ambient dust particles outside the surgical mask to the concentration that has leaked into the surgical mask. The ratio of these two concentrations (C_out/C_in) is called the fit factor. A fit factor of a 3D printed frame of at least 100 is required and considered as a pass level.

Results

We found that the mask fitter improves the overall performance of surgical masks significantly. The improved performance is comparable to that of N95.

Conclusion

The mask fitter improves the performance of surgical masks. The authors suggested that further study on frame material, shape, and expanded sample size would be beneficial to society.

Development, manufacturing, and preliminary validation of a reusable half-face respirator during the COVID-19 pandemic

Introduction

The COVID-19 pandemic has led to widespread shortages of N95 respirators and other personal protective equipment (PPE). An effective, reusable, locally-manufactured respirator can mitigate this problem. We describe the development, manufacture, and preliminary testing of an open-hardware-licensed device, the “simple silicone mask” (SSM).

Methods

A multidisciplinary team developed a reusable silicone half facepiece respirator over 9 prototype iterations. The manufacturing process consisted of 3D printing and silicone casting. Prototypes were assessed for comfort and breathability. Filtration was assessed by user seal checks and quantitative fit-testing according to CSA Z94.4–18.

Results

The respirator originally included a cartridge for holding filter material; this was modified to connect to standard heat-moisture exchange (HME) filters (N95 or greater) after the cartridge showed poor filtration performance due to flow acceleration around the filter edges, which was exacerbated by high filter resistance. All 8 HME-based iterations provided an adequate seal by user seal checks and achieved a pass rate of 87.5% (N = 8) on quantitative testing, with all failures occurring in the first iteration. The overall median fit-factor was 1662 (100 = pass). Estimated unit cost for a production run of 1000 using distributed manufacturing techniques is CAD $15 in materials and 20 minutes of labor.

Conclusion

Small-scale manufacturing of an effective, reusable N95 respirator during a pandemic is feasible and cost-effective. Required quantities of reusables are more predictable and less vulnerable to supply chain disruption than disposables. With further evaluation, such devices may be an alternative to disposable respirators during public health emergencies. The respirator described above is an investigational device and requires further evaluation and regulatory requirements before clinical deployment. The authors and affiliates do not endorse the use of this device at present.