Discrepancy of particle passage in 101 mask batches during the first year of the Covid-19 pandemic in Germany.

During the first wave of Covid-19 infections in Germany in April 2020, clinics reported a shortage of filtering face masks with aerosol retention> 94% (FFP2 & 3, KN95, N95). Companies all over the world increased their production capacities, but quality control of once-certified materials and masks came up short. To help identify falsely labeled masks and ensure safe protection equipment, we tested 101 different batches of masks in 993 measurements with a self-made setup based on DIN standards. An aerosol generator provided a NaCl test aerosol which was applied to the mask. A laser aerosol spectrometer measured the aerosol concentration in a range from 90 to 500 nm to quantify the masks' retention. Of 101 tested mask batches, only 31 batches kept what their label promised. Especially in the initial phase of the pandemic in Germany, we observed fluctuating mask qualities. Many batches show very high variability in aerosol retention. In addition, by measuring with a laser aerosol spectrometer, we were able to show that not all masks filter small and large particles equally well. In this study we demonstrate how important internal and independent quality controls are, especially in times of need and shortage of personal protection equipment.

Mapping of UV-C dose and SARS-CoV-2 viral inactivation across N95 respirators during decontamination.

During public health crises like the COVID-19 pandemic, ultraviolet-C (UV-C) decontamination of N95 respirators for emergency reuse has been implemented to mitigate shortages. Pathogen photoinactivation efficacy depends critically on UV-C dose, which is distance- and angle-dependent and thus varies substantially across N95 surfaces within a decontamination system. Due to nonuniform and system-dependent UV-C dose distributions, characterizing UV-C dose and resulting pathogen inactivation with sufficient spatial resolution on-N95 is key to designing and validating UV-C decontamination protocols. However, robust quantification of UV-C dose across N95 facepieces presents challenges, as few UV-C measurement tools have sufficient (1) small, flexible form factor, and (2) angular response. To address this gap, we combine optical modeling and quantitative photochromic indicator (PCI) dosimetry with viral inactivation assays to generate high-resolution maps of "on-N95" UV-C dose and concomitant SARS-CoV-2 viral inactivation across N95 facepieces within a commercial decontamination chamber. Using modeling to rapidly identify on-N95 locations of interest, in-situ measurements report a 17.4 ± 5.0-fold dose difference across N95 facepieces in the chamber, yielding 2.9 ± 0.2-log variation in SARS-CoV-2 inactivation. UV-C dose at several on-N95 locations was lower than the lowest-dose locations on the chamber floor, highlighting the importance of on-N95 dose validation. Overall, we integrate optical simulation with in-situ PCI dosimetry to relate UV-C dose and viral inactivation at specific on-N95 locations, establishing a versatile approach to characterize UV-C photoinactivation of pathogens contaminating complex substrates such as N95s.

The protective performance of reusable cloth face masks, disposable procedure masks, KN95 masks and N95 respirators: Filtration and total inward leakage.

Face coverings are a key component of preventive health measure strategies to mitigate the spread of respiratory illnesses. In this study five groups of masks were investigated that are of particular relevance to the SARS-CoV-2 pandemic: re-usable, fabric two-layer and multi-layer masks, disposable procedure/surgical masks, KN95 and N95 filtering facepiece respirators. Experimental work focussed on the particle penetration through mask materials as a function of particle diameter, and the total inward leakage protection performance of the mask system. Geometric mean fabric protection factors varied from 1.78 to 144.5 for the fabric two-layer and KN95 materials, corresponding to overall filtration efficiencies of 43.8% and 99.3% using a flow rate of 17 L/min, equivalent to a breathing expiration rate for a person in a sedentary or standing position conversing with another individual. Geometric mean total inward leakage protection factors for the 2-layer, multi-layer and procedure masks were <2.3, while 6.2 was achieved for the KN95 masks. The highest values were measured for the N95 group at 165.7. Mask performance is dominated by face seal leakage. Despite the additional filtering layers added to cloth masks, and the higher filtration efficiency of the materials used in disposable procedure and KN95 masks, the total inward leakage protection factor was only marginally improved. N95 FFRs were the only mask group investigated that provided not only high filtration efficiency but high total inward leakage protection, and remain the best option to protect individuals from exposure to aerosol in high risk settings. The Mask Quality Factor and total inward leakage performance are very useful to determine the best options for masking. However, it is highly recommended that testing is undertaken on prospective products, or guidance is sought from impartial authorities, to confirm they meet any implied standards.

The impact of face masks on performance and physiological outcomes during exercise: a systematic review and meta-analysis.

Face masks are promoted for preventing spread of viruses; however, wearing a mask during exercise might increase CO2 rebreathing, decrease arterial oxygenation, and decrease exercise performance. A systematic review and meta-analysis was conducted on the impact of wearing a mask during exercise. Data sources included SPORTDiscus, PubMed, and Medline. Eligibility criteria included all study designs comparing surgical, N95, or cloth masks to a no mask condition during any type of exercise where exercise performance and/or physiological parameters were evaluated. Healthy and clinical participants were included. Mean differences (MD) or standardized mean differences (SMD) with 95% confidence intervals were calculated and pooled effects assessed. Twenty-two studies involving 1573 participants (620 females, 953 males) were included. Surgical, or N95 masks did not impact exercise performance (SMD -0.05 [-0.16, 0.07] and -0.16 [-0.54, 0.22], respectively) but increased ratings of perceived exertion (SMD 0.33 [0.09, 0.58] and 0.61 [0.23, 0.99]) and dyspnea (SMD 0.6 [0.3, 0.9] for all masks). End-tidal CO2 (MD 3.3 [1.0, 5.6] and 3.7 [3.0, 4.4] mm Hg), and heart rate (MD 2 [0,4] beats/min with N95 masks) slightly increased. Face masks can be worn during exercise with no influences on performance and minimal impacts on physiological variables. PROSPERO registration: CRD42020224988. Novelty: Face masks can be worn during exercise with no impacts on performance and minimal impacts on physiological variables.

A dynamic model of the Coronavirus Disease 2019 outbreak to analyze the effectiveness of control measures.

ABSTRACT: The World Health Organization (WHO) classified the spread of COVID-19 (Coronavirus Disease 2019) as a global pandemic in March. Scholars predict that the pandemic will continue into the coming winter and will become a seasonal epidemic in the following year. Therefore, the identification of effective control measures becomes extremely important. Although many reports have been published since the COVID-19 outbreak, no studies have identified the relative effectiveness of a combination of control measures implemented in Wuhan and other areas in China. To this end, a retrospective analysis by the collection and modeling of an unprecedented number of epidemiology records in China of the early stage of the outbreaks can be valuable.In this study, we developed a new dynamic model to describe the spread of COVID-19 and to quantify the effectiveness of control measures. The transmission rate, daily close contacts, and the average time from onset to isolation were identified as crucial factors in viral spreading. Moreover, the capacity of a local health-care system is identified as a threshold to control an outbreak in its early stage. We took these factors as controlling parameters in our model. The parameters are estimated based on epidemiological reports from national and local Center for Disease Control (CDCs).A retrospective simulation showed the effectiveness of combinations of 4 major control measures implemented in Wuhan: hospital isolation, social distancing, self-protection by wearing masks, and extensive medical testing. Further analysis indicated critical intervention conditions and times required to control an outbreak in the early stage. Our simulations showed that South Korea has kept the spread of COVID-19 at a low level through extensive medical testing. Furthermore, a predictive simulation for Italy indicated that Italy would contain the outbreak in late May under strict social distancing.In our general analysis, no single measure could contain a COVID-19 outbreak once a health-care system is overloaded. Extensive medical testing could keep viral spreading at a low level. Wearing masks functions as favorably as social distancing but with much lower socioeconomic costs.

The critical importance of mask seals on respirator performance: An analytical and simulation approach.

Filtering facepiece respirators (FFRs) and medical masks are widely used to reduce the inhalation exposure of airborne particulates and biohazardous aerosols. Their protective capacity largely depends on the fraction of these that are filtered from the incoming air volume. While the performance and physics of different filter materials have been the topic of intensive study, less well understood are the effects of mask sealing. To address this, we introduce an approach to calculate the influence of face-seal leakage on filtration ratio and fit factor based on an analytical model and a finite element method (FEM) model, both of which take into account time-dependent human respiration velocities. Using these, we calculate the filtration ratio and fit factor for a range of ventilation resistance values relevant to filter materials, 500-2500 Pa∙s∙m-1, where the filtration ratio and fit factor are calculated as a function of the mask gap dimensions, with good agreement between analytical and numerical models. The results show that the filtration ratio and fit factor are decrease markedly with even small increases in gap area. We also calculate particle filtration rates for N95 FFRs with various ventilation resistances and two commercial FFRs exemplars. Taken together, this work underscores the critical importance of forming a tight seal around the face as a factor in mask performance, where our straightforward analytical model can be readily applied to obtain estimates of mask performance.

Three-Dimensional Analysis of Particle Distribution on Filter Layers inside N95 Respirators by Deep Learning.

The global COVID-19 pandemic has changed many aspects of daily lives. Wearing personal protective equipment, especially respirators (face masks), has become common for both the public and medical professionals, proving to be effective in preventing spread of the virus. Nevertheless, a detailed understanding of respirator filtration-layer internal structures and their physical configurations is lacking. Here, we report three-dimensional (3D) internal analysis of N95 filtration layers via X-ray tomography. Using deep learning methods, we uncover how the distribution and diameters of fibers within these layers directly affect contaminant particle filtration. The average porosity of the filter layers is found to be 89.1%. Contaminants are more efficiently captured by denser fiber regions, with fibers <1.8 µm in diameter being particularly effective, presumably because of the stronger electric field gradient on smaller diameter fibers. This study provides critical information for further development of N95-type respirators that combine high efficiency with good breathability.

Factors associated with asymptomatic infection in health-care workers with severe acute respiratory syndrome coronavirus 2 infection in Wuhan, China: a multicentre retrospective cohort study.

OBJECTIVES: To describe the fraction of asymptomatic health-care workers (HCWs) in two designated hospitals for coronavirus disease 2019 (COVID-19) treatment in Wuhan and explore the factors associated with asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. METHODS: All HCWs in Wuhan Union Hospital and Wuhan Red Cross Hospital with either positive SARS-CoV-2 nucleic acid or positive antibody test before 18 April 2020 were included. Exposure, epidemiological and demographic information were retrospectively collected by a structured questionnaire. Medical records were also reviewed for clinical characteristics and CT images of HCWs. RESULTS: As of 18 April 2020, a total of 424 HCWs were identified. Among them, 276 (65.1%) were symptomatic and 148 (34.9%) were asymptomatic. Fifty-five (19.9%) families of the symptomatic HCWs and 16 (10.8%) families of the asymptomatic HCWs were infected with SARS-CoV-2. HCWs with infected family members tended to be symptomatic (OR 2.053, 95% CI 1.130-3.730; p 0.018). Multivariable logistic regression analysis exhibited that performing tracheal intubation or extubation (OR 4.057, 95% CI 1.183-13.909; p 0.026) was associated with an increased likelihood of symptomatic SARS-CoV-2 infection, whereas consistent use of N95 respirators (OR 0.369, 95% CI 0.201-0.680; p 0.001) and eye protection (OR 0.217, 95% CI 0.116-0.404; p < 0.001) were associated with an increased likelihood of asymptomatic SARS-CoV-2 infection. CONCLUSIONS: Asymptomatic SARS-CoV-2 infection in HCWs comprised a considerable proportion of HCW infections during the pandemic of COVID-19. Those who performed tracheal intubation or extubation were most likely to develop related symptoms, whereas those taking aggressive measures, including consistent use of N95 masks and eye protection, tended to be asymptomatic cases.