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1.
British Journal of Social Psychology ; : 1, 2022.
Article in English | Academic Search Complete | ID: covidwho-2029287

ABSTRACT

The phrase ‘in it together’ has been used liberally since the outbreak of COVID‐19, but the extent that frontline workers felt ‘in it together’ is not well understood. Here, we consider the factors that built (or eroded) solidarity while working through the pandemic, and how frontline workers navigated their lives through periods of disconnection. Semi‐structured interviews with 21 frontline workers, across all sectors, were conducted in the United Kingdom and Ireland. The qualitative data were analysed systematically using reflexive thematic analysis. The three themes identified in the data were: (1) Solidarity as central to frontline experiences;(2) Leadership as absent, shallow and divisive: highlighting ‘us‐them’ distinctions and (3) The rise of ‘us’ and ‘we’ among colleagues. Our research offers insights into how frontline workers make sense of their experiences of solidarity and discordance during the first year of the COVID‐19 pandemic, with relevance for government and organizational policy‐makers shaping future conditions for frontline workers. [ FROM AUTHOR] Copyright of British Journal of Social Psychology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

2.
2nd IEEE International Conference on Intelligent Technologies, CONIT 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2029223

ABSTRACT

It's been over two years since the novel Coronavirus first appeared and with the constantly evolving new variants found around the world, the havoc of n-Coronavirus seems to be unstoppable. With more than 264 million people being affected by the n-coronavirus as of 2nd December 2021 and 5.2 million deaths around the world, there is a dire need to increase the COVID-19 testing to stop the virus from spreading further. With COVID - 19 devastating the economic situation of various countries across the globe, it has become necessary to come up with a fast, efficient, and inexpensive way to test the presence of the n-Coronavirus in people. However, the methods currently being used to test COVID 19 are rather very expensive and unavailable to a large section of society. One of the most feasible solutions to this problem is through radiological detection i.e., with Chest X - ray images. Contrary to the prevalent testing methods, Chest X - ray scans are much lesser in cost and are readily available. One major problem that arises is that COVID and pneumonia have very similar X-RAY results, so having a binary classification (COVID and NOT COVID) isn't enough. In this paper, we have put forward a model based on Convolutional NN for detection of Pneumonia, COVID - 19, and Normal patients using X - ray photos of Chest. We achieved an AUC score of 90% in our results while classifying the X-Ray Images. Besides Accuracy, we have also made the ROC Curve, confusion matrix, and classification report for our model. To keep our model lightweight, we have used a Genetic Algorithm to get the best hyperparameters possible for the model. © 2022 IEEE.

3.
2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022 ; : 90-96, 2022.
Article in English | Scopus | ID: covidwho-2029203

ABSTRACT

Coronavirus is a disease caused by SARS-CoV-2, which can cause severe respiratory problems in humans. World Health Organization declared it to be a pandemic, as per the rate of spread and scale of its transmission. The mental health of people is impacted rudely by Covid-19. The influence of the Covid19 virus on psychological health leads to depression, anxiety, posttraumatic stress, dementia, mental stress, helplessness, fear of losing, etc. Machine Learning is performing a critical role in the rapid advancement of the healthcare system in the past few years. Machine Learning techniques are employed to forecast, diagnose disease, evaluate data by studying the earlier data, and construct different patterns of it. Therefore, the purpose of this report is to address the issue of psychiatric illnesses by identifying those who are at an elevated risk of mental conditions, due to increased stress throughout the Covid19 crisis. Due to the current ongoing pandemic, the mental health crisis needs time, and proactive interference to confront and endure the anxiety. In this research, A comprehensive literature survey was undertaken to examine some machine learning predictive models for primitive prediction of a particular type of mental illness using machine learning algorithms. Several existing research papers were reviewed and after evaluation results show that among various algorithms like, Gradient Boosting Machine, Support Vector Machines, Naïve Bayes, K-Nearest Neighbors;Support Vector Machine (98.6%), Random Forest, and Random Forest (97.07%) are the most accurate algorithm for predicting mental illness amid the ongoing pandemic. © 2022 IEEE.

4.
Journal of Physics: Conference Series ; 2318(1):012048, 2022.
Article in English | ProQuest Central | ID: covidwho-2028984

ABSTRACT

The infectious disease in humans is gradually rising for various reasons, and COVID19 is one of the recently discovered diseases caused by SARS-CoV-2. From early 2020, the infection due to COVID19 has gradually increased, and still, its infection exists. COVID19 will cause severe infection in the respiratory tract, and early detection and treatment are essential. The harshness of the infection needs to be examined before implementing the treatment. This research aims to build up and implement a suitable procedure to extract and assess the infected section in lung CT slices. This work extracts the infected section using the pre-trained VGG-UNet scheme. The separated section is validated against the ground-truth (GT) image, and the necessary presentation standards are calculated. The performance of the VGG-UNet is then compared and verified with the UNet and UNet+ schemes. The investigational product of this study authenticate that the effect reached with the proposed study confirms that the VGG-UNet provides better Jaccard, Dice and accuracy compared to UNet and UNet+.

5.
Rna Biology ; 19(1):1019-1044, 2022.
Article in English | MEDLINE | ID: covidwho-2028922

ABSTRACT

Similar to other RNA viruses, the emergence of Betacoronavirus relies on cross-species viral transmission, which requires careful health surveillance monitoring of protein-coding information as well as genome-wide analysis. Although the evolutionary jump from natural reservoirs to humans may be mainly traced-back by studying the effect that hotspot mutations have on viral proteins, it is largely unexplored if other impacts might emerge on the structured RNA genome of Betacoronavirus. In this survey, the protein-coding and viral genome architecture were simultaneously studied to uncover novel insights into cross-species horizontal transmission events. We analysed 1,252,952 viral genomes of SARS-CoV, MERS-CoV, and SARS-CoV-2 distributed across the world in bats, intermediate animals, and humans to build a new landscape of changes in the RNA viral genome. Phylogenetic analyses suggest that bat viruses are the most closely related to the time of most recent common ancestor of Betacoronavirus, and missense mutations in viral proteins, mainly in the S protein S1 subunit: SARS-CoV (G > T;A577S);MERS-CoV (C > T;S746R and C > T;N762A);and SARS-CoV-2 (A > G;D614G) appear to have driven viral diversification. We also found that codon sites under positive selection on S protein overlap with non-compensatory mutations that disrupt secondary RNA structures in the RNA genome complement. These findings provide pivotal factors that might be underlying the eventual jumping the species barrier from bats to intermediate hosts. Lastly, we discovered that nearly half of the Betacoronavirus genomes carry highly conserved RNA structures, and more than 90% of these RNA structures show negative selection signals, suggesting essential functions in the biology of Betacoronavirus that have not been investigated to date. Further research is needed on negatively selected RNA structures to scan for emerging functions like the potential of coding virus-derived small RNAs and to develop new candidate antiviral therapeutic strategies.

6.
Signal Transduction and Targeted Therapy ; 7(1):318, 2022.
Article in English | MEDLINE | ID: covidwho-2028663

ABSTRACT

Excessive inflammatory responses contribute to the pathogenesis and lethality of highly pathogenic human coronaviruses, but the underlying mechanism remains unclear. In this study, the N proteins of highly pathogenic human coronaviruses, including severe acute respiratory syndrome coronavirus (SARS-CoV), middle east respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), were found to bind MASP-2, a key serine protease in the lectin pathway of complement activation, resulting in excessive complement activation by potentiating MBL-dependent MASP-2 activation, and the deposition of MASP-2, C4b, activated C3 and C5b-9. Aggravated inflammatory lung injury was observed in mice infected with adenovirus expressing the N protein. Complement hyperactivation was also observed in SARS-CoV-2-infected patients. Either blocking the N protein:MASP-2 interaction, MASP-2 depletion or suppressing complement activation can significantly alleviate N protein-induced complement hyperactivation and lung injury in vitro and in vivo. Altogether, these data suggested that complement suppression may represent a novel therapeutic approach for pneumonia induced by these highly pathogenic coronaviruses.

7.
Prehospital and Disaster Medicine ; 37(5):571-573, 2022.
Article in English | ProQuest Central | ID: covidwho-2028612

ABSTRACT

In the event of a mass-casualty incident (MCI), hospital emergency departments (EDs) may be called upon to provide care to a large number of critically ill patients. As EDs plan for MCIs, determining how to best allocate staff members can play a significant role in the success or failure of a response. In academic EDs, a group that is often overlooked during MCI planning is the resident physicians. We argue that MCI plans at academic hospitals should consider the re-deployment of emergency medicine resident physicians in non-critical hospital rotations back to the ED.

8.
Prehospital and Disaster Medicine ; 37(5):674-686, 2022.
Article in English | ProQuest Central | ID: covidwho-2028611

ABSTRACT

Introduction:Recent disasters emphasize the need for disaster risk mitigation in the health sector. A lack of standardized tools to assess hospital disaster preparedness hinders the improvement of emergency/disaster preparedness in hospitals. There is very limited research on evaluation of hospital disaster preparedness tools.Objective:This study aimed to determine the presence and availability of hospital preparedness tools across the world, and to identify the important components of those study instruments.Method:A systematic review was performed using three databases, namely Ovid Medline, Embase, and CINAHL, as well as available grey literature sourced by Google, relevant websites, and also from the reference lists of selected articles. The studies published on hospital disaster preparedness across the world from 2011-2020, written in English language, were selected by two independent reviewers. The global distribution of studies was analyzed according to the World Health Organization’s (WHO) six geographical regions, and also according to the four categories of the United Nations Human Development Index (UNHDI). The preparedness themes were identified and categorized according to the 4S conceptual framework: space, stuff, staff, and systems.Result:From a total of 1,568 articles, 53 met inclusion criteria and were selected for data extraction and synthesis. Few published studies had used a study instrument to assess hospital disaster preparedness. The Eastern Mediterranean region recorded the highest number of such publications. The countries with a low UNHDI were found to have a smaller number of publications. Developing countries had more focus on preparedness for natural disasters and less focus on chemical, biological, radiological, and nuclear (CBRN) preparedness. Infrastructure, logistics, capacity building, and communication were the priority themes under the space, stuff, staff, and system domains of the 4S framework, respectively. The majority of studies had neglected some crucial aspects of hospital disaster preparedness, such as transport, back-up power, morgue facilities and dead body handling, vaccination, rewards/incentive, and volunteers.Conclusion:Important preparedness themes were identified under each domain of the 4S framework. The neglected aspects should be properly addressed in order to ensure adequate preparedness of hospitals. The results of this review can be used for planning a comprehensive disaster preparedness tool.

9.
Veterinary Microbiology ; 273:109544, 2022.
Article in English | MEDLINE | ID: covidwho-2028561

ABSTRACT

Autophagy-related 4B (ATG4B) is found to exert a vital function in viral replication, although the mechanism through which ATG4B activates type-I IFN signaling to hinder viral replication remains to be explained, so far. The current work revealed that ATG4B was downregulated in porcine epidemic diarrhea virus (PEDV)-infected LLC-PK1 cells. In addition, ATG4B overexpression inhibited PEDV replication in both Vero cells and LLC-PK1 cells. On the contrary, ATG4B knockdown facilitated PEDV replication. Moreover, ATG4B was observed to hinder PEDV replication by activating type-I IFN signaling. Further detailed analysis revealed that the ATG4B protein targeted and upregulated the TRAF3 protein to induce IFN expression via the TRAF3-pTBK1-pIRF3 pathway. The above data revealed a novel mechanism underlying the ATG4B-mediated viral restriction, thereby providing novel possibilities for preventing and controlling PEDV.

10.
J Autoimmun ; 132:102899, 2022.
Article in English | PubMed | ID: covidwho-2028166

ABSTRACT

Coronavirus disease 2019 (COVID-19) and vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been associated with autoimmune phenomena. However, the interplay between COVID-19 or vaccination against SARS-CoV-2 and Berger glomerulonephritis or Henoch-Schönlein vasculitis, two diseases mediated by immunoglobulin A, has never been comprehensively investigated. Therefore, we carried out a systematic review of the literature on this topic. Following databases were used: Google Scholar, Excerpta Medica and the United States National Library of Medicine. Eighty-seven patients with immunoglobulin A-mediated diseases associated with SARS-CoV-2 infection or vaccination against coronavirus were sorted out (53% males, 47% females;34 17-51 years of age, median and interquartile range): 47 cases of Berger glomerulonephritis and 40 of Henoch-Schönlein vasculitis. Approximately 50% (N = 24) of Berger glomerulonephritis and 10% (N = 4) of Henoch-Schönlein vasculitis patients presented with a pre-existing history of immunoglobulin A-mediated disease. Almost all cases of Berger glomerulonephritis were vaccine-associated (N = 44;94%), while most cases of Henoch-Schönlein vasculitis were infection-associated (N = 23;57%). Among vaccine-associated immunoglobulin A diseases, about 90% were associated to mRNA-based vaccines. Our analysis supports the hypothesis that COVID-19 and vaccination against SARS-CoV-2 may trigger or exacerbate an immunoglobulin A-mediated diseases.

11.
Int J Infect Dis ; 2022.
Article in English | PubMed | ID: covidwho-2028099

ABSTRACT

Severe neurological disorders and vascular events during COronaVIrus Disease-2019 (COVID-19) have been described. Here, we describe the first case of a female patient infected with Omicron SARS-CoV-2 BA.2 Variant of Concern (VoC) meningitis with newly diagnosed central demyelinating disease.

12.
Lessons from COVID-19: Impact on Healthcare Systems and Technology ; : 213-240, 2022.
Article in English | Scopus | ID: covidwho-2027814

ABSTRACT

Novel coronavirus commonly known as coronavirus disease 19 (COVID-19) has rapidly spread worldwide and triggered the current global health crisis. It mostly affects humans through the zoonotic transmission of coronavirus 2 (SARS-CoV-2). This chapter focuses on the various epidemics and pandemics (plague, cholera, Spanish flu, etc.) in the history of human civilization, principal component analysis (PCA) for the interpretation of COVID-19 spreading kinetics during the first wave (in the year 2020), the potential use of herbal medicines, dietary remedies, and allopathic therapy to fight COVID-19, and various preventive measures undertaken to combat the pandemic during the first wave. The numbers of confirmed, recovered, active, and deceased cases is considered for the mapping of PCA within different countries. This study can be used as an informative approach for anticipating and strategy-making against COVID-19 or some other pandemics in the ensuing times. © 2022 Elsevier Inc. All rights reserved.

13.
Stem Cells and COVID-19 ; : 169-227, 2022.
Article in English | Scopus | ID: covidwho-2027798

ABSTRACT

The outbreak of the Coronavirus disease 2019 (COVID-19) caused by the viral pathogen, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rampantly spread across the globe and has been declared a pandemic by the World Health Organization in 2020. COVID-19 has impacted the economy, public health system, and even daily life. Several viral epidemics, mainly SARS-CoV, H1N1, and MERS-CoV, were reported in the past two decades, whereas SARS-CoV-2 is a newly discovered virus from the coronavirus family. In this chapter, we give a brief overview of the structure, etiology, and transmission of the SARS-CoV-2 and move on to describe the clinical manifestations, diagnosis, and current methods adopted for the treatment of COVID-19 patients. An in-depth insight into the role of immunomodulators, repurposed drugs, thromboprophylactics, convalescent plasma, and stem cells as therapeutics is provided. The chapter also focuses on future perspectives and research strategies that are being actively explored for the management and mitigation of COVID-19. The role of the route of administration of therapeutics with pertinence on nasal vaccines is highlighted. Finally, the use of biomaterials and tissue engineering approaches for designing effective interventional strategies is detailed. It is of paramount importance that host-pathogen interactions and pathomechanisms of infections are delineated in order to identify suitable targets for intervention. The attained knowledge may be extended to manage other infectious viral diseases and thereby future pandemics. © 2022 Elsevier Inc. All rights reserved.

19.
Ultrasound in Obstetrics & Gynecology ; 60(S1):16, 2022.
Article in English | ProQuest Central | ID: covidwho-2027409
20.
Ultrasound in Obstetrics & Gynecology ; 60(S1):15, 2022.
Article in English | ProQuest Central | ID: covidwho-2027407
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