Check the gap: Facemask performance and exhaled aerosol distributions around the wearer

Effectiveness of Face Mask for Prevention of Respiratory Tract Infection during Hajj: A Systematic Review and Meta-Analysis

The Hajj is an annual mass gathering of people in Makkah, Saudi Arabia. Respiratory infections are common due to their potential for rapid spread in crowded settings. There is a lack of data regarding the effectiveness of face masks in preventing respiratory tract infections (RTIs), specifically during Hajj. We systematically searched PubMed, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials until July 3, 2023 for studies comparing the incidence or prevalence of RTIs in those who used any face mask during Hajj compared with no mask. Risk ratio (RRs) and 95% CIs were calculated using either a fixed or random-effect model, depending on the heterogeneity. A comprehensive analysis encompassed 10 studies involving 5007 participants. The overall RR favored wearing masks over not wearing masks regarding the incidence of RTIs; however, the difference was not statistically significant (RR = 0.78; 95% CI = 0.55-1.10; P = 0.16). A significantly lower incidence of RTIs was found in those wearing masks most of the time versus intermittently (RR = 0.59; 95% CI = [0.38-0.94; P = 0.02). In subgroup analyses, there was no difference between wearing masks and not wearing masks across different study designs (cohort/case-control), different groups (pilgrims/healthcare workers), and different years of Hajj, except from 2000 to 2008, when there was a significant difference favoring wearing face masks. This meta-analysis found wearing masks most of the time was associated with significantly lower risk of RTIs than wearing it intermittently.

A critical review on the role of leakages in the facemask protection against SARS-CoV-2 infection with consideration of vaccination and virus variants

The protection provided by facemasks has been extensively investigated since the beginning of the SARS-CoV-2 outbreak, focusing mostly on the filtration efficiency of filter media for filtering face pieces (FFP), surgical masks, and cloth masks. However, faceseal leakage is a major contributor to the number of potentially infectious airborne droplets entering the respiratory system of a susceptible individual. The identification of leaking spots and the quantification of leaking flows are crucial to estimate the protection provided by facemasks. This study presents a critical review on the measurement and calculation of facemask leakages and a quantitative analysis of their role in the risk of SARS-CoV-2 infection. It shows that the pairing between the mask dimensions and the wearer's face is essential to improve protection efficiency, especially for FFP2 masks, and summarizes the most common leaking spots at the interface between the mask and the wearer's face. Leakage is a crucial factor in the calculation of the protection provided by facemasks and outweighs the filtration performances. The fit factors measured among mask users were summarized for different types of face protection. The reviewed data were integrated into a computational model to compare the mitigation impact of facemasks with vaccination with consideration of new variants of SARS-CoV-2. Combining a high adoption rate of facemasks and a high vaccination rate is crucial to efficiently control the spread of highly infectious variants.

Bridge the gap: correlate face mask leakage and facial features with 3D morphable face models

BACKGROUND

Face masks have been proven to be effective in protecting the public against airborne transmitted diseases when fitted appropriately. However, for homemade cloth masks and surgical masks, the fit is often poor, allowing viruses to escape through the gap.

OBJECTIVE

This work aims to identify the correlation between the mask leakage, mask configurations, and individual's facial features.

METHODS

A novel locally morphing 3D face model, and a minimum-energy-based mask deployment model are used to systematically examine the mask fit for a large cohort of exemplars.

RESULTS

The results show that the mask size and tuck-in ratio, along with selective facial features, especially nose height and chin length, are key factors determining the leakage location and extent. A polynomial regression model is presented for mask fitness based on localized facial features.

SIGNIFICANCE

This study is a complete pipeline to test various masks on a wide range of faces with controlled modification of distinct regions of the face, which is difficult to achieve with human subjects, and provide knowledge on how the masks should be designed in the future.

IMPACT STATEMENT

The face mask "fit" affects the mask's efficacy in preventing airborne transmission. To date, research on the face mask fit has been conducted mainly using experiments on limited subjects. The limited sample size in experimental studies makes it hard to reach a statistical correlation between mask fit and facial features in a population. Here, we employ a novel framework that utilizes a morphable face model and mask's deployment simulation to test mask fit for many facial characteristics and mask designs. The proposed technique is an important step toward enabling personalized mask selection with maximum efficacy for society members.

Effects of surgical masks on aerosol dispersion in professional singing

BACKGROUND

In the CoVID-19 pandemic, singing came into focus as a high-risk activity for the infection with airborne viruses and was therefore forbidden by many governmental administrations.

OBJECTIVE

The aim of this study is to investigate the effectiveness of surgical masks regarding the spatial and temporal dispersion of aerosol and droplets during professional singing.

METHODS

Ten professional singers performed a passage of the Ludwig van Beethoven's "Ode of Joy" in two experimental setups-each with and without surgical masks. First, they sang with previously inhaled vapor of e-cigarettes. The emitted cloud was recorded by three cameras to measure its dispersion dynamics. Secondly, the naturally expelled larger droplets were illuminated by a laser light sheet and recorded by a high-speed camera.

RESULTS

The exhaled vapor aerosols were decelerated and deflected by the mask and stayed in the singer's near-field around and above their heads. In contrast, without mask, the aerosols spread widely reaching distances up to 1.3 m. The larger droplets were reduced by up to 86% with a surgical mask worn.

SIGNIFICANCE

The study shows that surgical masks display an effective tool to reduce the range of aerosol dispersion during singing. In combination with an appropriate aeration strategy for aerosol removal, choir singers could be positioned in a more compact assembly without contaminating neighboring singers all singers.

Fabrication of a highly protective 3D-printed mask and evaluation of its viral filtration efficiency using a human head mannequin

Facemasks are one of the most effective and low-cost prophylactics for COVID-19. In the spring 2020, when a severe shortage of facemasks occurred worldwide, various types of 3D-printed masks were designed and proposed. However, the protective effects conferred by most of these masks were not experimentally evaluated. Here, we provide a new simple design of 3D-printed mask and evaluate its protective effect in a viral filtration test using a human head mannequin. The developed mask can be constructed with a low-cost 3D printer, with an approximate production cost of US $4. This mask has three parts: the main part, wearing parts, and a piece of non-woven fabric filter. The volume of the filter, which needs to be changed daily, was reduced to approximately 1/10 of that of commercially available surgical masks used in this study. The developed mask is fabricated from polylactic acid, a biodegradable plastic, and its surface contour contacting the face may be adjusted after softening the material with hot water at 60-80°C. The viral filtration efficiency of the developed mask was found to be over 80%. This performance is better than that of commercially available facemasks, such as surgical masks and cloth masks, and equal to those of KN95 and KF94.

Prediction of N95 Respirator Fit from Fogging of Eyeglasses: A Pilot Study

Aim and objective

Fogging of eyeglasses while wearing N95 respirators is common. It is commonly held that the N95 respirator has a poor fit if there is fogging of eyeglasses. We conducted this prospective, pilot study to determine if fogging of eyeglasses predicts poor fit of N95 respirator.

Materials and methods

Seventy volunteer healthcare workers from a tertiary intensive care unit in Sydney, Australia participated. The participants donned one of the following N95 respirators: three-panel flat-fold respirator (3M 1870), cup-shaped respirator (3M 1860), or a duckbill respirator. After a satisfactory "user seal check" as recommended by the manufacturer, the participants donned eyeglasses and checked for fogging. A quantitative fit test (QnFT) of the respirator was then performed (using PortaCount Respirator Fit Tester 8048, TSI Inc., Minnesota, USA). A fit factor of <100 on quantitative fit testing indicates poor fit. The sensitivity and specificity for fogging of eyeglasses (index test) to predict the poor fit of N95 respirator was determined, compared to QnFT (gold standard test).

Results

Fogging of eyeglasses as a predictor of poor respirator fit (i.e., fit factor <100 on QnFT) had sensitivity of 71% (95% CI, 54-85%) and specificity 46% (95% CI, 29-63%). The odds ratio of fogging as a predictor for poor fit was 2.10 (95% CI, 0.78-5.67), with a two-tailed p-value of 0.22 (not significant). The receiver operating characteristic curve for fogging of eyeglasses as a diagnostic test had the area under the curve of 0.59.

Conclusion

Fogging of eyeglasses is neither a sensitive nor a specific predictor for poor fit of N95 respirators.

How to cite this article

Kyaw S, Johns M, Lim R, Stewart WC, Rojas N, Thambiraj SR, et al. Prediction of N95 Respirator Fit from Fogging of Eyeglasses: A Pilot Study. Indian J Crit Care Med 2021;25(9):976-980.

A computational model for predicting changes in infection dynamics due to leakage through N95 respirators

In the absence of fit-testing, leakage of aerosolized pathogens through the gaps between the face and N95 respirators could compromise the effectiveness of the device and increase the risk of infection for the exposed population. To address this issue, we have developed a model to estimate the increase in risk of infection resulting from aerosols leaking through gaps between the face and N95 respirators. The gaps between anthropometric face-geometry and N95 respirators were scanned using computed tomography. The gap profiles were subsequently input into CFD models. The amount of aerosol leakage was predicted by the CFD simulations. Leakage levels were validated using experimental data obtained using manikins. The computed amounts of aerosol transmitted to the respiratory system, with and without leaks, were then linked to a risk-assessment model to predict the infection risk for a sample population. An influenza outbreak in which 50% of the population deployed respirators was considered for risk assessment. Our results showed that the leakage predicted by the CFD model matched the experimental data within about 13%. Depending upon the fit between the headform and the respirator, the inward leakage for the aerosols ranged between 30 and 95%. In addition, the non-fit-tested respirator lowered the infection rate from 97% (for no protection) to between 42 and 80%, but not to the same level as the fit-tested respirators (12%). The CFD-based leakage model, combined with the risk-assessment model, can be useful in optimizing protection strategies for a given population exposed to a pathogenic aerosol.

Maximizing Fit for Cloth and Medical Procedure Masks to Improve Performance and Reduce SARS-CoV-2 Transmission and Exposure, 2021

Universal masking is one of the prevention strategies recommended by CDC to slow the spread of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19) (1). As of February 1, 2021, 38 states and the District of Columbia had universal masking mandates. Mask wearing has also been mandated by executive order for federal property* as well as on domestic and international transportation conveyances.† Masks substantially reduce exhaled respiratory droplets and aerosols from infected wearers and reduce exposure of uninfected wearers to these particles. Cloth masks§ and medical procedure masks¶ fit more loosely than do respirators (e.g., N95 facepieces). The effectiveness of cloth and medical procedure masks can be improved by ensuring that they are well fitted to the contours of the face to prevent leakage of air around the masks' edges. During January 2021, CDC conducted experimental simulations using pliable elastomeric source and receiver headforms to assess the extent to which two modifications to medical procedure masks, 1) wearing a cloth mask over a medical procedure mask (double masking) and 2) knotting the ear loops of a medical procedure mask where they attach to the mask's edges and then tucking in and flattening the extra material close to the face (knotted and tucked masks), could improve the fit of these masks and reduce the receiver's exposure to an aerosol of simulated respiratory droplet particles of the size considered most important for transmitting SARS-CoV-2. The receiver's exposure was maximally reduced (>95%) when the source and receiver were fitted with modified medical procedure masks. These laboratory-based experiments highlight the importance of good fit to optimize mask performance. Until vaccine-induced population immunity is achieved, universal masking is a highly effective means to slow the spread of SARS-CoV-2** when combined with other protective measures, such as physical distancing, avoiding crowds and poorly ventilated indoor spaces, and good hand hygiene. Innovative efforts to improve the fit of cloth and medical procedure masks to enhance their performance merit attention.