Search Results (4)

Face masking proved essential to reduce transmission of COVID-19 and other respiratory infections in indoor environments, but standards and literature do not provide simple quantitative methods for quantifying air leakage at the face seal. This study reports an original method to quantify outward leakage and how wearing style impacts on leaks and filtration efficiency. The amount of air leakage was evaluated on four medical masks and four barrier face coverings, exploiting a theoretical model and an instrumented dummy head in a range of airflows between 30 and 160 L/min. The fraction of air leaking at the face seal of the medical masks and barrier face coverings ranged from 43% to 95% of exhaled air at 30 L/min and reduced to 10–85% at 160 L/min. Filter breathability was the main driver affecting both leak fraction and total filtration efficiency that varied from 5% to 53% and from 15% to 84% at 30 and 160 L/min, respectively. Minor changes were related to wearing style, supporting indications on the correct mask use. The fraction of air leaking from medical masks and barrier face coverings during exhalation is relevant and varies according to design and wearing style. The use of highly breathable filter materials reduces air leaks and improve total filtration efficiency. Full article

There is strong evidence associating the indoor environment with transmission of SARS-CoV-2, the virus that causes COVID-19. SARS-CoV-2 can spread by exposure to droplets and very fine aerosol particles from respiratory fluids that are released by infected persons. Layered mitigation strategies, including but not limited to maintaining physical distancing, adequate ventilation, universal masking, avoiding overcrowding, and vaccination, have shown to be effective in reducing the spread of SARS-CoV-2 within the indoor environment. Here, we examine the effect of mitigation strategies on reducing the risk of exposure to simulated respiratory aerosol particles within a classroom-style meeting room. To quantify exposure of uninfected individuals (Recipients), surrogate respiratory aerosol particles were generated by a breathing simulator with a headform (Source) that mimicked breath exhalations. Recipients, represented by three breathing simulators with manikin headforms, were placed in a meeting room and affixed with optical particle counters to measure 0.3–3 µm aerosol particles. Universal masking of all breathing simulators with a 3-ply cotton mask reduced aerosol exposure by 50% or more compared to scenarios with simulators unmasked. While evaluating the effect of Source placement, Recipients had the highest exposure at 0.9 m in a face-to-face orientation. Ventilation reduced exposure by approximately 5% per unit increase in air change per hour (ACH), irrespective of whether increases in ACH were by the HVAC system or portable HEPA air cleaners. The results demonstrate that mitigation strategies, such as universal masking and increasing ventilation, reduce personal exposure to respiratory aerosols within a meeting room. While universal masking remains a key component of a layered mitigation strategy of exposure reduction, increasing ventilation via system HVAC or portable HEPA air cleaners further reduces exposure. Full article

Background: The educational process in different medical schools has been negatively affected by the COVID-19 pandemic worldwide. As a part of the Saudi government’s attempts to contain the spread of the virus, schools’ and universities’ educational activities and face-to-face lectures have been modified to virtual classrooms. The purpose of this study was to explore the perceptions of the faculty and the students of an electronic objective structured clinical examination (E-OSCE) activity that took place during the COVID-19 pandemic in the oldest medical school in Saudi Arabia. Methods: An e-OSCE style examination was designed for the final-year medical students by the pediatrics department, College of Medicine at King Saud University in Riyadh, Saudi Arabia. The examination was administered by Zoom™ video conferencing where both students and faculty participated through their laptop or desktop computers. In order to explore the students’ and the faculty’s perceptions about this experience, a newly designed 13-item online questionnaire was administered at the end of the e-OSCE. Results: Out of 136 participants (23 faculty and 112 students), 73 respondents (e.g., 54% response rate) filled out the questionnaire. Most of the respondents (69.8%) were very comfortable with this new virtual experience. Most participants (53.4%) preferred the e-OSCE compared to the classic face-to-face clinical OSCE during the pandemic. Regarding the e-OSCE assessment student tool, 46.6% reported that it is similar to the classic face-to-face OSCE; however, 38.4% felt it was worse. Conclusions: The e-OSCE can be a very effective alternative to the classic face-to-face OSCE due to the current circumstances that still pose a significant risk of infection transmission. Future studies should examine different virtual strategies to ensure effective OSCE delivery from the perspective of both faculty and students. Full article

Timely detection and diagnosis are essentially needed to guide outbreak measures and infection control. It is vital to improve healthcare quality in public places, markets, schools and airports and provide useful insights into the technological environment and help researchers acknowledge the choices and gaps available in this field. In this narrative review, the detection of coronavirus disease 2019 (COVID-19) technologies is summarized and discussed with a comparison between them from several aspects to arrive at an accurate decision on the feasibility of applying the best of these techniques in the biosensors that operate using laser detection technology. The collection of data in this analysis was done by using six reliable academic databases, namely, Science Direct, IEEE Xplore, Scopus, Web of Science, Google Scholar and PubMed. This review includes an analysis review of three highlights: evaluating the hazard of pandemic COVID-19 transmission styles and comparing them with Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) to identify the main causes of the virus spreading, a critical analysis to diagnose coronavirus disease 2019 (COVID-19) based on artificial intelligence using CT scans and CXR images and types of biosensors. Finally, we select the best methods that can potentially stop the propagation of the coronavirus pandemic. Full article