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SARS-CoV-2 proteins

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    JDSR-GAN: Constructing A Joint and Collaborative Learning Network for Masked Face Super-Resolution

    Authors: Guangwei Gao; Lei Tang; Yi Yu; Fei Wu; Huimin Lu; Jian Yang

    id:2103.13676v1 Date: 2021-03-25 Source: arXiv

    With the growing importance of preventing the COVID-19 MESHD virus, face images obtained in most video surveillance scenarios are low resolution with mask simultaneously. However, most of the previous face super-resolution solutions can not handle both tasks in one model. In this work, we treat the mask occlusion MESHD as image noise and construct a joint and collaborative learning network, called JDSR-GAN, for the masked face super-resolution task. Given a low-quality face image with the mask as input, the role of the generator composed of a denoising module and super-resolution module is to acquire a high-quality high-resolution face image. The discriminator utilizes some carefully designed loss functions to ensure the quality of the recovered face images. Moreover, we incorporate the identity information and attention mechanism into our network for feasible correlated feature expression and informative feature learning. By jointly performing denoising and face super-resolution, the two tasks can complement each other and attain promising performance. Extensive qualitative and quantitative results show the superiority of our proposed JDSR-GAN over some comparable methods which perform the previous two tasks separately.

    A Computer Vision System to Help Prevent the Transmission of COVID-19 MESHD

    Authors: Fevziye Irem Eyiokur; Hazım Kemal Ekenel; Alexander Waibel

    id:2103.08773v1 Date: 2021-03-16 Source: arXiv

    The COVID-19 pandemic MESHD affects every area of daily life globally. To avoid the spread of coronavirus and retrieve the daily normal worldwide, health organizations advise social distancing, wearing face mask, and avoiding touching face. Based on these recommended protective measures, we developed a deep learning-based computer vision system to help prevent the transmission of COVID-19 MESHD. Specifically, the developed system performs face mask detection, face-hand interaction detection, and measures social distance. For these purposes, we collected and annotated images that represent face mask usage and face-hand interaction in the real world. We presented two different face datasets, namely Unconstrained Face Mask Dataset (UFMD) and Unconstrained Face Hand Dataset ( UFHD MESHD). We trained the proposed models on our own datasets and evaluated them on both our datasets and already existing datasets in the literature without performing any adaptation on these target datasets. Besides, we proposed a distance measurement module to track social distance between people. Experimental results indicate that UFMD MESHD and UFHD MESHD represent the real-world's diversity well. The proposed system achieved very high performance and generalization capacity in a real-world scenario for unseen data from outside the training data to detect face mask usage and face-hand interaction, and satisfactory performance in the case of tracking social distance. Presented UFMD MESHD and UFHD MESHD datasets will be available at https://github.com/iremeyiokur/ COVID-19 MESHD-Preventions-Control-System.

    Barriers and Facilitators to COVID-19 MESHD screening at Jaipur International Airport, India.

    Authors: Neha Mantri; Nitin Kumar Joshi; Pankaj Bhardwaj; Akhil Dhanesh Goel; Manoj Kumar Gupta; Kuldeep Singh; Sanjeev Misra

    doi:10.21203/rs.3.rs-307039/v1 Date: 2021-03-07 Source: ResearchSquare

    Background:Airports pose a possible threat in facilitating global disease transmission within the community which may be prevented by rigorous systematic entry-exit screening. With the aim to capture the perception of stakeholders associated with COVID-19 MESHD on barriers and facilitators of airport screening at Jaipur International Airport. Also, to assess key outcomes viz. total passengers screened, suspected cases, & confirmed cases.Methods:An inductive-deductive mix-method thematic analysis was conducted to capture qualitative data of key stakeholders. Additionally, quantitative data was obtained from the Rajasthan Medical & Health Department team deployed for COVID-19 MESHD airport screening.Results:Jaipur International Airport screened 4565 passengers (Males=4073 and Females=492) with 23 suspected cases during an outlined period of declaration of Pandemic to Lockdown in India (11th to 24th March 2020). Total 65 passengers had travel history from China (3 from Wuhan). The mean average age of passengers was 40.95 ± 7.8 years. The average screening time per passenger was 2-3 minutes with a load of 25-90 passengers per team per flight. Fishbone analysis of screening challenges revealed poor cooperation of passengers, masking symptoms MESHD, apprehension, and stigma related to quarantine. Moreover, inadequate human resources and changing guidelines overburdened healthcare providers. But, perception of risk, and social responsibility of travelers together with supportive organization behavior act as facilitators. Overall, groundwork on airport screening was insightful to propose key action areas for screening.Conclusions:Globally, COVID-19 MESHD has an impact on health infrastructure and international travel. International coordination with streamlined screening will go a LONG way in virus containment. 

    Household COVID-19 MESHD risk and in-person schooling

    Authors: Justin Lessler; M. Kate Grabowski; Kyra H Grantz; Elena Badillo-Goicoechea; C. Jessica E. Metcalf; Carly Lupton-Smith; Andrew S Azman; Elizabeth A Stuart

    doi:10.1101/2021.02.27.21252597 Date: 2021-03-01 Source: medRxiv

    In-person schooling has proved contentious and difficult to study throughout the SARS-CoV-2 pandemic. Data from a massive online survey in the United States indicates an increased risk of COVID-19 MESHD-related outcomes among respondents living with a child attending school in-person. School-based mitigation measures are associated with significant reductions in risk, particularly daily symptoms screens, teacher masking MESHD, and closure of extra-curricular activities. With seven or more mitigation measures, the association between in-person schooling and COVID-19 MESHD- related outcomes all but disappears. Teachers working outside the home were more likely to report COVID-19 MESHD-related outcomes, but this association is similar to other occupations (e.g., healthcare, office work). In-person schooling is associated with household COVID-19 MESHD risk, but this risk can likely be controlled with properly implemented school-based mitigation measures.

    Analysis of the Effectiveness of Face-Coverings on the Death Rate of COVID-19 MESHD Using Machine Learning

    Authors: Ali Lafzi; Miad Boodaghi; Siavash Zamani; Niyousha Mohammadshafie

    id:2102.04419v1 Date: 2021-02-08 Source: arXiv

    The recent outbreak of the COVID-19 MESHD shocked humanity leading to the death of millions of people worldwide. To stave off the spread of the virus, the authorities in the US, employed different strategies including the mask mandate ( MM MESHD) order issued by the states' governors. Although most of the previous studies pointed in the direction that MM can be effective in hindering the spread of viral infections, the effectiveness of MM in reducing the degree of exposure to the virus and, consequently, death MESHD rates remains indeterminate. Indeed, the extent to which the degree of exposure to COVID-19 MESHD takes part in the lethality of the virus remains unclear. In the current work, we defined a parameter called the average death ratio as the monthly average of the ratio of the number of daily deaths to the total number of daily cases. We utilized survey data provided by New York Times to quantify people's abidance to the MM order. Additionally, we implicitly addressed the extent to which people abide by the MM order that may depend on some parameters like population, income, and political inclination. Using different machine learning classification algorithms we investigated how the decrease or increase in death MESHD ratio for the counties in the US West Coast correlates with the input parameters. Our results showed a promising score as high as 0.94 with algorithms like XGBoost, Random Forest, and Naive Bayes. To verify the model, the best performing algorithms were then utilized to analyze other states (Arizona, New Jersey, New York and Texas) as test cases. The findings show an acceptable trend, further confirming usability of the chosen features for prediction of similar cases.

    Inflight Transmission of COVID-19 MESHD Based on Aerosol Dispersion Data

    Authors: Zhaozhi Wang; Edwin R Galea; Angus J Grandison; John Ewer; Fuchen Jia

    doi:10.1101/2021.01.08.21249439 Date: 2021-01-08 Source: medRxiv

    BackgroundAn issue of concern to the travelling public is the possibility of in-flight transmission of COVID-19 MESHD during long- and short-haul flights. The aviation industry maintain the probability of contracting the illness is small based on reported cases, modelling and data from aerosol dispersion experiments conducted on-board aircraft. MethodsUsing experimentally derived aerosol dispersion data for a B777-200 aircraft and a modified version of the Wells-Riley equation we estimate inflight infection probability for a range of scenarios involving quanta generation rate and face mask efficiency MESHD. Quanta generation rates were selected based on COVID-19 MESHD events reported in the literature while mask efficiency was determined from the aerosol dispersion experiments. ResultsThe MID-AFT cabin exhibits the highest infection probability. The calculated maximum individual infection probability (without masks) for a 2-hour flight in this section varies from 4.5% for the "Mild Scenario" to 60.2% for the "Severe Scenario" although the corresponding average infection probability varies from 0.1% to 2.5%. For a 12-hour flight, the corresponding maximum individual infection probability varies from 24.1% to 99.6% and the average infection probability varies from 0.8% to 10.8%. If all passengers wear face masks throughout the 12-hour flight, the average infection probability can be reduced by approximately 73%/32% for high/low efficiency masks. If face masks are worn by all passengers except during a one-hour meal service, the average infection probability is increased by 59%/8% compared to the situation where the mask is not removed. ConclusionsThis analysis has demonstrated that while there is a significant reduction in aerosol concentration due to the nature of the cabin ventilation and filtration system, this does not necessarily mean that there is a low probability or risk of in-flight infection. However, mask wearing, particularly high-efficiency ones, significantly reduces this risk.

    Geographically Masking Addresses MESHD to Study COVID-19 MESHD Clusters

    Authors: Walid Houfaf-Khoufaf; Guillaume Touya

    doi:10.21203/rs.3.rs-128679/v2 Date: 2020-12-14 Source: ResearchSquare

    The spatial analysis of health data usually raises geoprivacy issues. But with the virulence of COVID-19 MESHD, scientists and crisis managers do need to analyse the spatio-temporal distribution and spreading of the disease with spatially precise data. In particular, it is useful to locate each case on a map to identify clusters of cases in space and time. To allow such analyses with breach of geoprivacy, geomasking techniques are necessary. This paper experiments the geomasking techniques from the literature to solve this problem: masking the real address of positive cases while preserving the local cluster patterns. In particular, two different approaches based on aggregation and perturbation are adapted to the geomasking of addresses in areas with different densities of population. A new simulated crowding method is also proposed to preserve clusters as much as possible. The results show that geomasking techniques can spatially anonymize addresses while preserving clusters, and the best geomasking MESHD method depends on the use of the anonymized data.

    Addressing Personal Protective Equipment (PPE) Decontamination: Methylene Blue and Light Inactivates SARS-CoV-2 on N95 Respirators and Masks with Maintenance of Integrity and Fit

    Authors: Thomas S Lendvay; James Chen; Brian H Harcourt; Florine E.M. Scholte; F. Selcen Kilinc-Balci; Ying Ling Lin; Molly M Lamb; Larry F Chu; Amy Price; David Evans; Yi-Chan Lin; Christopher N Mores; Jaya Sahni; Kareem B Kabra; Eric Haubruge; Etienne Thiry; Belinda Heyne; Jan Laperre; Sarah Simmons; Jan Davies; Yi Cui; Thor Wagner; Tanner Clark; Sarah J Smit; Rod Parker; Thomas Gallagher; Emily Timm; Louisa F Ludwig-Begall; Nicolas Macia; Cyrus Mackie; Karen Hope; Ken Page; Susan Reader; Peter Faris; Oliver Jolois; Alpa Patel; Jean-Luc Lemyre; Vanessa Molly-Simard; Kamonthip Homdayjanakul; Sarah R Tritsch; Constance Wielick; Mark Mayo; Rebecca Malott; Jean-Francois Willaert; Hans Nauwynck; Loréne Dams; Simon De Jaeger; Lei Liao; Mervin Zhao; Steven Chu; John Conly; May C Chu

    doi:10.1101/2020.12.11.20236919 Date: 2020-12-11 Source: medRxiv

    BackgroundThe coronavirus disease 2019 MESHD ( COVID-19 MESHD) pandemic has resulted in severe shortages of personal protective equipment (PPE) necessary to protect front-line healthcare personnel. These shortages underscore the urgent need for simple, efficient, and inexpensive methods to decontaminate SARS-CoV-2-exposed PPE enabling safe reuse of masks and respirators. Efficient decontamination must be available not only in low-resourced settings, but also in well-resourced settings affected by PPE shortages. Methylene blue (MB) photochemical treatment, hitherto with many clinical applications including those used to inactivate virus in plasma, presents a novel approach for widely applicable PPE decontamination. Dry heat ( DH MESHD) treatment is another potential low-cost decontamination method. MethodsMB and light (MBL) and DH MESHD treatments were used to inactivate coronavirus on respirator and mask material. We tested three N95 filtering facepiece respirators (FFRs), two medical masks (MMs), and one cloth community mask ( CM MESHD). FFR/MM/CM materials were inoculated with SARS-CoV-2 (a Betacoronavirus), murine hepatitis virus MESHD (MHV) (a Betacoronavirus), or porcine respiratory coronavirus (PRCV) (an Alphacoronavirus), and treated with 10 {micro}M MB followed by 50,000 lux of broad-spectrum light or 12,500 lux of red light for 30 minutes, or with 75{degrees}C DH for 60 minutes. In parallel, we tested respirator and mask integrity using several standard methods and compared to the FDA-authorized vaporized hydrogen peroxide plus ozone (VHP+O3) decontamination method. Intact FFRs/MMs/CM were subjected to five cycles of decontamination (5CD) to assess integrity using International Standardization Organization (ISO), American Society for Testing and Materials (ASTM) International, National Institute for Occupational Safety and Health (NIOSH), and Occupational Safety and Health Administration (OSHA) test methods. FindingsOverall, MBL robustly and consistently inactivated all three coronaviruses with at least a 4-log reduction. DH MESHD yielded similar results, with the exception of MHV, which was only reduced by 2-log after treatment. FFR/MM integrity was maintained for 5 cycles of MBL MESHD or DH treatment, whereas one FFR failed after 5 cycles of VHP+O3. Baseline performance for the CM MESHD was variable, but reduction of integrity was minimal. InterpretationMethylene blue with light and DH MESHD treatment decontaminated masks and respirators by inactivating three tested coronaviruses without compromising integrity through 5CD. MBL decontamination of masks is effective, low-cost and does not require specialized equipment, making it applicable in all-resource settings. These attractive features support the utilization and continued development of this novel PPE decontamination method.

    How effective are face coverings in reducing transmission of COVID-19 MESHD?

    Authors: Joshua F. Robinson; Ioatzin Rios de Anda; Fergus J. Moore; Florence K. A. Gregson; Jonathan P. Reid; Lewis Husain; Richard P. Sear; C. Patrick Royall

    doi:10.1101/2020.12.01.20241992 Date: 2020-12-03 Source: medRxiv

    In the COVID-19 pandemic MESHD, among the more controversial issues is the use of face coverings. To address this we show that the underlying physics ensures particles with diameters (> 1 micron) are efficiently filtered out by a simple cotton or surgical mask. For particles in the submicron range the efficiency depends on the material properties of the masks, though generally the filtration efficiency in this regime varies between 30 to 60 % and multi-layered cotton masks MESHD are expected to be comparable to surgical masks. Respiratory droplets are conventionally divided into coarse droplets (> 5-10 micron) responsible for droplet transmission and aerosols (< 5-10 micron) responsible for airborne transmission. Masks are thus expected to be highly effective at preventing droplet transmission, with their effectiveness limited only by the mask fit, compliance and appropriate usage. By contrast, knowledge of the size distribution of bioaerosols and the likelihood that they contain virus is essential to understanding their effectiveness in preventing airborne transmission. We argue from literature data on SARS-CoV-2 viral loads that the finest aerosols (< 1 micron) are unlikely to contain even a single virion in the majority of cases; we thus expect masks to be effective at reducing the risk of airborne transmission in most settings.

    How effective are face coverings in reducing transmission of COVID-19 MESHD?

    Authors: Joshua F. Robinson; Ioatzin Rios de Anda; Fergus J. Moore; Florence K. A. Gregson; Jonathan P. Reid; Lewis Husain; Richard P. Sear; C. Patrick Royall

    id:2012.01314v1 Date: 2020-12-02 Source: arXiv

    In the COVID-19 pandemic MESHD, among the more controversial issues is the use of face coverings. To address this we show that the underlying physics ensures particles with diameters & 1 $\mu$m are efficiently filtered out by a simple cotton or surgical mask. For particles in the submicron range the efficiency depends on the material properties of the masks, though generally the filtration efficiency in this regime varies between 30 to 60 % and multi-layered cotton masks MESHD are expected to be comparable to surgical masks. Respiratory droplets are conventionally divided into coarse droplets (> 5-10 $\mu$m) responsible for droplet transmission and aerosols (< 5-10 $\mu$m) responsible for airborne transmission. Masks are thus expected to be highly effective at preventing droplet transmission, with their effectiveness limited only by the mask fit, compliance and appropriate usage. By contrast, knowledge of the size distribution of bioaerosols and the likelihood that they contain virus is essential to understanding their effectiveness in preventing airborne transmission. We argue from literature data on SARS-CoV-2 viral loads that the finest aerosols (< 1 $\mu$m) are unlikely to contain even a single virion in the majority of cases; we thus expect masks to be effective at reducing the risk of airborne transmission in most settings.

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