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The COVID-19 pandemic has made well-fitting face masks a critical piece of protective equipment for healthcare workers and civilians. While the importance of wearing face masks has been acknowledged, there remains a lack of understanding about the role of good fit in rendering protective equipment useful. In addition, supply chain constraints have caused some organizations to abandon traditional quantitative or/and qualitative fit testing, and instead, have implemented subjective fit checking. Our study seeks to quantitatively evaluate the level of fit offered by various types of masks, and most importantly, assess the accuracy of implementing fit checks by comparing fit check results to quantitative fit testing results. Seven participants first evaluated N95 and KN95 respirators by performing a fit check. Participants then underwent quantitative fit testing wearing five N95 respirators, a KN95 respirator, a surgical mask, and fabric masks. N95 respirators offered higher degrees of protection than the other categories of masks tested; however, it should be noted that most N95 respirators failed to fit the participants adequately. Fit check responses had poor correlation with quantitative fit factor scores. KN95, surgical, and fabric masks achieved low fit factor scores, with little protective difference recorded between respiratory protection options. In addition, small facial differences were observed to have a significant impact on quantitative fit. Fit is critical to the level of protection offered by respirators. For an N95 respirator to provide the promised protection, it must fit the participant. Performing a fit check via NHS self-assessment guidelines was an unreliable way of determining fit.

This article proposes a quick connection device for transformer respirators. The schemes are studied from four aspects: device structure, fastening method, material, and shock-absorbing spring. Through experimental comparison, suitable schemes for respirators are selected and physical objects are made. Finally, the effectiveness of the quick connect device is checked to verify its practicality and effectiveness.

Objectives Due to the COVID-19 pandemic and the shortage of the National Institute for Occupational Safety & Health (NIOSH)-approved N95 respirators, the Food and Drug Administration granted an Emergency Use Authorization to allow the use of non-NIOSH approved respirators provided that these respirators must undergo tests by a protocol of TEB-APR-STP-0059, similar methods of NIOSH standard testing procedure. This initiative safeguards the quality of respirators and the effectiveness of occupational protection. The dataset of all the testing results could benefit further analysis of COVID-19 infection rates in relation to different types of N95 respirators used and identify potential correlations of various test parameters in the testing system for validation. The analysis enhances understanding of the quality, effectiveness, and performance of N95 respirators in the prevention of respiratory infectious transmission and develops improved occupational safety measures. Data description The dataset was transformed, transcribed, and compiled from the official testing data of non-NIOSH-approved N95 respirators reported in the NIOSH website under the Centers for the Disease Control and Prevention in the United States. The dataset included details of 7,413 testing results of N95 respirators (manufacturer, model, and maximum and minimum filtration efficiency) and test parameters (flow rate, initial filter resistance, and initial percent leakage). Supplementary items were added to increase the availability of data analysis and enhance the interpretability of the assessments of the quality of N95 respirators.

To ensure health and wellbeing of healthcare workers, prevention of infection is essential. Although N95 filtering facepiece respirators (N95 respirators) are potentially effective respiratory protective devices, scientific evaluation for healthcare workers, particularly for ambulance crews has been insufficient. We investigated if N95 respirator user seal checking ensures seal quality through quantitative fit testing among ambulance crews. A user seal check was performed according to the manufacturer’s instructions and based on each participant’s subjective assessment of fit. A quantitative test was then performed using a dedicated counter. In the results, although the pass rates for both the user seal check and the quantitative test exceeded 50%, the kappa coefficients between the two tests were -0.072 (95%CI: -0.38–0.23), 0.11 (95%CI: -0.11–0.33), and 0.013 (95%CI: -0.31–0.34) for three kinds of N95 respirators respectively suggesting extremely low rates of agreement similar to other reports from health providers. Therefore, we compared the patterns of distributions of the two tests. In the result, probability of agreement of the two tests was determined to be 50%, which was identical to a coin toss. It is unknown what level of protection an N95 respirator will provide when only a user seal check is performed.

Background Respiratory protective devices are critical in protecting against infection in healthcare workers at high risk of novel 2019 coronavirus disease (COVID‐19); however, recommendations are conflicting and epidemiological data on their relative effectiveness against COVID‐19 are limited. Purpose To compare medical masks to N95 respirators in preventing laboratory‐confirmed viral infection and respiratory illness including coronavirus specifically in healthcare workers. Data Sources MEDLINE, Embase, and CENTRAL from January 1, 2014, to March 9, 2020. Update of published search conducted from January 1, 1990, to December 9, 2014. Study Selection Randomized controlled trials (RCTs) comparing the protective effect of medical masks to N95 respirators in healthcare workers. Data Extraction Reviewer pair independently screened, extracted data, and assessed risk of bias and the certainty of the evidence. Data Synthesis Four RCTs were meta‐analyzed adjusting for clustering. Compared with N95 respirators; the use of medical masks did not increase laboratory‐confirmed viral (including coronaviruses) respiratory infection (OR 1.06; 95% CI 0.90‐1.25; I2 = 0%; low certainty in the evidence) or clinical respiratory illness (OR 1.49; 95% CI: 0.98‐2.28; I2 = 78%; very low certainty in the evidence). Only one trial evaluated coronaviruses separately and found no difference between the two groups (P = .49). Limitations Indirectness and imprecision of available evidence. Conclusions Low certainty evidence suggests that medical masks and N95 respirators offer similar protection against viral respiratory infection including coronavirus in healthcare workers during non–aerosol‐generating care. Preservation of N95 respirators for high‐risk, aerosol‐generating procedures in this pandemic should be considered when in short supply.

This systematic review and meta-analysis quantified the protective effect of facemasks and respirators against respiratory infections among healthcare workers. Relevant articles were retrieved from Pubmed, EMBASE, and Web of Science. Meta-analyses were conducted to calculate pooled estimates. Meta-analysis of randomized controlled trials (RCTs) indicated a protective effect of masks and respirators against clinical respiratory illness (CRI) (risk ratio [RR] = 0.59; 95% confidence interval [CI]:0.46–0.77) and influenza-like illness (ILI) (RR = 0.34; 95% CI:0.14–0.82). Compared to masks, N95 respirators conferred superior protection against CRI (RR = 0.47; 95% CI: 0.36–0.62) and laboratory-confirmed bacterial (RR = 0.46; 95% CI: 0.34–0.62), but not viral infections or ILI. Meta-analysis of observational studies provided evidence of a protective effect of masks (OR = 0.13; 95% CI: 0.03–0.62) and respirators (OR = 0.12; 95% CI: 0.06–0.26) against severe acute respiratory syndrome (SARS). This systematic review and meta-analysis supports the use of respiratory protection. However, the existing evidence is sparse and findings are inconsistent within and across studies. Multicentre RCTs with standardized protocols conducted outside epidemic periods would help to clarify the circumstances under which the use of masks or respirators is most warranted.

Any strategy to cope with an influenza pandemic must be based on the knowledge and tools that are available at the time an epidemic may occur. In the near term, when we lack an adequate supply of vaccine and antiviral medication, strategies that rely on social distancing and physical barriers will be relatively more prominent as means to prevent spread of disease. The use of respirators and facemasks is one key part of a larger strategy to establish barriers and increase distance between infected and uninfected individuals. Respirators and facemasks may have a role in both clinical care and community settings. Reusability of Facemasks During an Influenza Pandemic: Facing the Flu answers a specific question about the role of respirators and facemasks to reduce the spread of flu: Can respirators and facemasks that are designed to be disposable be reused safely and effectively? The committee-assisted by outstanding staff-worked intensively to review the pertinent literature; consult with manufacturers, researchers, and medical specialists; and apply their expert judgment. This report offers findings and recommendations based on the evidence, pointing to actions that are appropriate now and to lines of research that can better inform future decisions.

This randomized crossover trial examines the effects of wearing a cloth mask or N95 respirator vs no mask at peak exercise among healthy, active adults.

Face masks are an important tool for preventing the spread of COVID-19. However, it is unclear how different types of masks affect speech recognition in different levels of background noise. To address this, we investigated the effects of four masks (a surgical mask, N95 respirator, and two cloth masks) on recognition of spoken sentences in multi-talker babble. In low levels of background noise, masks had little to no effect, with no more than a 5.5% decrease in mean accuracy compared to a no-mask condition. In high levels of noise, mean accuracy was 2.8-18.2% lower than the no-mask condition, but the surgical mask continued to show no significant difference. The results demonstrate that different types of masks generally yield similar accuracy in low levels of background noise, but differences between masks become more apparent in high levels of noise.