Social Studies University Students' Perspectives of e-Learning Classes: A Case Study

Instructional institutions have worked hard to improve their curricula and educational activities to keep up with the information and communication revolution. E-learning is one of these applications that stands out the most since it has changed how traditional education is delivered at institutions and the responsibilities and roles of students and teachers. This study explores how social studies students perceive the effectiveness of online courses offered by Jordanian universities. Data was gathered using a questionnaire that contained scales for e-learning quality and student satisfaction. A Jordanian university 's 421 students made up the study sample. The results showed that the overall content quality of e-learning courses was medium. The student's level of satisfaction with the quality of the e-learning classes was moderate, and the e-learning classes' form quality was very high. According to the study, providing lessons with a clear hierarchy or framework is best to make learning easier. Additionally, the study suggests including as many students as possible in the e-learning session and hearing their opinions.

Functional Properties of Grapefruit Seed Extract Embedded Blend Membranes of Poly(vinyl alcohol)/Starch: Potential Application for Antiviral Activity in Food Safety to Fight Against COVID-19.

The poly(vinyl alcohol) (PVA) and starch-based polymeric films with a ratio of 2:8 were prepared using solution casting followed by a solvent evaporation method. Four types of membranes with varied concentrations of grapefruit seed extract (GSE) i.e., 2.5-10 wt% was incorporated in the films. The prepared membranes were assessed for transparency test, mechanical properties, surface morphology, permeability test for O2, and antimicrobial properties. The PVA/starch-10% GSE loaded film showed excellent mechanical properties showing highest 1344 ± 0.7% elongation at break but poor optical transparency with 53.8% to 68.61%. The Scanning Electron Microscopic study reveals the good compatibility between the PVA, Starch, and GSE. The gas permeability test reveals that the prepared films have shown good resistance to the O2 permeability 0.0326-0.316 Barrer at 20 kg/cm2 feed pressure for the prepared membranes showing excellent performance. By adding the little amount of GSE into the PVA/starch blend membranes showed promising antimicrobial efficacy against MNV-1. For 4 h. incubation, PVA/starch blend membranes containing 2.5%, 5%, and 10% GSE caused MNV-1 reductions of 0.92, 1.89, and 2.27 log PFU/ml, respectively. Similarly, after 24 h, the 5% and 10% GSE membranes reduced MNV-1 titers by 1.90 and 3.26 log PFU/ml, respectively. Antimicrobial tests have shown excellent performance to resist microorganisms. The water uptake capacity of the membrane is found 72% for the PVA/starch pristine membrane and is reduced to 32% for the 10% GSE embedded membrane. Since the current pandemic situation due to COVID-19 occurred by SARSCOV2, the prepared GSE incorporated polymeric blend films are the rays of hope in the packaging of food stuff.

COVID-19 infection leading to acute pustular dermatoses.

Viral infections, including SARS-CoV-2, the virus that causes COVID-19 infection, have been implicated in the development of pustular dermatoses, including generalized pustular psoriasis (GPP) and acute generalized exanthematous pustulosis (AGEP). We performed a literature review of existing cases of GPP and AGEP associated with COVID-19 infection and/or treatment reported over a period of 12 months. We summarize the clinical characteristics of these cases and report an additional six new cases of GPP and AGEP. Seven patients with COVID-19 infection were diagnosed with new-onset or exacerbated GPP, and 33 patients were diagnosed with AGEP. In 55% of the cases, no concomitant potential culprit drug trigger was identified. We present this review of cases of COVID-associated acute pustular dermatoses to further contribute to the spectrum of cutaneous eruption associated with SARS-CoV-2 infection.

The Incidence of Sudden Sensorineural Hearing Loss (SSNHL) in COVID-19 Patients in Tertiary Care Referral Units.

COVID-19 is a new pandemic infectious disease that emerged in Wuhan, China, at the end of 2019. We aimed to evaluate the sudden sensorineural hearing loss (SSNHL) prevalence after COVID-19 infection or even vaccination. This is a two-center retrospective, observational cross-sectional study performed at tertiary care referral Audiovestibular Medicine Units at the period between August 1, 2020, and October 31, 2021. All SSNHL patients diagnosed in a period of a month with COVID-19 or vaccinated with a COVID-19 vaccine were included in this study. Fifty-three cases with confirmed COVID-19 and one patient vaccinated with a COVID-19 vaccine 1 week before, who reported sudden sensory neural hearing loss, were included in this study. Forty-eight patients had unilateral hearing loss and 6 patients had bilateral hearing loss. Forty-nine patients had typical COVID-19 symptoms; one patient discovered them after complaining of anosmia and ageusia and one patient after COVID-19 vaccination; and three patients were complaining only from hearing loss and had a PCR test for nasopharyngeal swabs to prove infection. Different degrees of SSNHL ranged from mild to severe and most of the patients had severe hearing loss. With more patients, COVID-19 may be a potential factor in sudden sensorineural hearing loss. It should be kept in mind that SSNHL may be the only indicator used to identify COVID-19 cases.

Outcomes of Early Versus Late Tracheostomy in Patients With COVID-19: A Multinational Cohort Study.

Timing of tracheostomy in patients with COVID-19 has attracted substantial attention. Initial guidelines recommended delaying or avoiding tracheostomy due to the potential for particle aerosolization and theoretical risk to providers. However, early tracheostomy could improve patient outcomes and alleviate resource shortages. This study compares outcomes in a diverse population of hospitalized COVID-19 patients who underwent tracheostomy either "early" (within 14 d of intubation) or "late" (more than 14 d after intubation). DESIGN: International multi-institute retrospective cohort study. SETTING: Thirteen hospitals in Bolivia, Brazil, Spain, and the United States. PATIENTS: Hospitalized patients with COVID-19 undergoing early or late tracheostomy between March 1, 2020, and March 31, 2021. INTERVENTIONS: Not applicable. MEASUREMENTS AND MAIN RESULTS: A total of 549 patients from 13 hospitals in four countries were included in the final analysis. Multivariable regression analysis showed that early tracheostomy was associated with a 12-day decrease in time on mechanical ventilation (95% CI, -16 to -8; p < 0.001). Further, ICU and hospital lengths of stay in patients undergoing early tracheostomy were 15 days (95% CI, -23 to -9 d; p < 0.001) and 22 days (95% CI, -31 to -12 d) shorter, respectively. In contrast, early tracheostomy patients experienced lower risk-adjusted survival at 30-day post-admission (hazard ratio, 3.0; 95% CI, 1.8-5.2). Differences in 90-day post-admission survival were not identified. CONCLUSIONS: COVID-19 patients undergoing tracheostomy within 14 days of intubation have reduced ventilator dependence as well as reduced lengths of stay. However, early tracheostomy patients experienced lower 30-day survival. Future efforts should identify patients most likely to benefit from early tracheostomy while accounting for location-specific capacity.

Outcomes of Early Versus Late Tracheostomy in Patients With COVID-19: A Multinational Cohort Study

OBJECTIVES: Timing of tracheostomy in patients with COVID-19 has attracted substantial attention. Initial guidelines recommended delaying or avoiding tracheostomy due to the potential for particle aerosolization and theoretical risk to providers. However, early tracheostomy could improve patient outcomes and alleviate resource shortages. This study compares outcomes in a diverse population of hospitalized COVID-19 patients who underwent tracheostomy either “early” (within 14 d of intubation) or “late” (more than 14 d after intubation). DESIGN: International multi-institute retrospective cohort study. SETTING: Thirteen hospitals in Bolivia, Brazil, Spain, and the United States. PATIENTS: Hospitalized patients with COVID-19 undergoing early or late tracheostomy between March 1, 2020, and March 31, 2021. INTERVENTIONS: Not applicable. MEASUREMENTS AND MAIN RESULTS: A total of 549 patients from 13 hospitals in four countries were included in the final analysis. Multivariable regression analysis showed that early tracheostomy was associated with a 12-day decrease in time on mechanical ventilation (95% CI, –16 to –8;p < 0.001). Further, ICU and hospital lengths of stay in patients undergoing early tracheostomy were 15 days (95% CI, –23 to –9 d;p < 0.001) and 22 days (95% CI, –31 to –12 d) shorter, respectively. In contrast, early tracheostomy patients experienced lower risk-adjusted survival at 30-day post-admission (hazard ratio, 3.0;95% CI, 1.8–5.2). Differences in 90-day post-admission survival were not identified. CONCLUSIONS: COVID-19 patients undergoing tracheostomy within 14 days of intubation have reduced ventilator dependence as well as reduced lengths of stay. However, early tracheostomy patients experienced lower 30-day survival. Future efforts should identify patients most likely to benefit from early tracheostomy while accounting for location-specific capacity.

Role of Imaging and AI in the Evaluation of COVID-19 Infection: A Comprehensive Survey.

Coronavirus disease 2019 (COVID-19) is a respiratory illness that started and rapidly became the pandemic of the century, as the number of people infected with it globally exceeded 253.4 million. Since the beginning of the pandemic of COVID-19, over two years have passed. During this hard period, several defies have been coped by the scientific society to know this novel disease, evaluate it, and treat affected patients. All these efforts are done to push back the spread of the virus. This article provides a comprehensive review to learn about the COVID-19 virus and its entry mechanism, its main repercussions on many organs and tissues of the body, identify its symptoms in the short and long terms, in addition to recognize the role of diagnosis imaging in COVID-19. Principally, the quick evolution of active vaccines act an exceptional accomplishment where leaded to decrease rate of death worldwide. However, some hurdels still have to be overcome. Many proof referrers that infection with CoV-19 causes neurological dis function in a substantial ratio of influenced patients, where these symptoms appear severely during the infection and still less is known about the potential long term consequences for the brain, where Loss of smell is a neurological sign and rudimentary symptom of COVID-19. Hence, we review the causes of olfactory bulb dysfunction and Anosmia associated with COVID-19, the latest appropriate therapeutic strategies for the COVID-19 treatment (e.g., the ACE2 strategy and the Ang II receptor), and the tests through the follow-up phases. Additionally, we discuss the long-term complications of the virus and thus the possibility of improving therapeutic strategies. Moreover, the main steps of artificial intelligence that have been used to foretell and early diagnose COVID-19 are presented, where Artificial intelligence, especially machine learning is emerging as an effective approach for diagnostic image analysis with performance in the discriminate diagnosis of injuries of COVID-19 on multiple organs, comparable to that of human practitioners. The followed methodology to prepare the current survey is to search the related work concerning the mentioned topic from different journals, such as Springer, Wiley, and Elsevier. Additionally, different studies have been compared, the results are collected and then reported as shown. The articles are selected based on the year (i.e., the last three years). Also, different keywords were checked (e.g., COVID-19, COVID-19 Treatment, COVID-19 Symptoms, and COVID-19 and Anosmia).

The incidence of Sudden Sensorineural hearing loss (SSNHL) IN COVID 19 patients in tertiary care referral units (preprint)

Background: Covid–19 is a new pandemic infectious disease emerged in Wuhan, China at the end of 2019, we aimed to evaluate the Sudden sensorineural hearing loss (SSNHL) prevalence after covid 19 infection or even vaccination.    Methods: Two-centre retrospective, observational cross-sectional study performed at tertiary care referral Audio-vestibular Medicine Units at the period between August 1st 2020 and October 31st 2021. All sudden sensorineural hearing loss (SSNHL) patients diagnosed in a period of a month with Covid -19 or vaccinated with Covid -19 vaccine were participated in this study.  Results: Fifty-three cases with confirmed Covid -19 and one patient vaccinated with Covid -19 vaccine one week before, reported sudden sensory neural hearing loss were included in this study. forty-eight patients had unilateral hearing loss and 6 patients had bilateral hearing loss. Forty-nine patients with typical Covid -19 symptoms, one patient discovered after complaining of anosmia and ageusia, one patient after Covid -19 vaccination and three patient was complaining only from hearing loss and had PCR test for nasopharyngeal swapes to prove infection were participated in our study. Different degrees of SSNHL were ranged from mild to severe and most of the patients had severe hearing loss.  Conclusion:  With more patients, Covid-19 may be a potential factor in sudden sensorineural hearing loss. It should be kept in mind that SSNHL may be the only indicator used to identify Covid- 19 cases.

A triple-trickle theory for sustainable fashion adoption: the rise of a luxury trend

Purpose>This article critically synthesizes the literature on sustainable fashion, the movement behind it and plausible fashion adoption theories. Then, to build on those studies, developing a new theory about adopting sustainable fashion – mainly among millennials and Generation Z who are behind forwarding and adopting this fashion trend – is sought after.Design/methodology/approach>This is a theory-synthesized conceptual article that presents a literature-informed new theoretical structure pronouncing sustainable fashion adoption and its rise as a new luxury trend. That included explicating and unraveling the conceptual foundations and construction elements that different viewpoints use to articulate the trend under investigation and the searches for a common basis to construct a new and improved conceptual framework.Findings>This study introduces the triple-trickle theory that incorporates the role of media and technology to organize and understand the diffusion of sustainable fashion and identify paths for future trickle-effects on fashion research.Research limitations/implications>Even though this has the benefit of offering a vast array of views and evidence that offers an adequate problem inspection, further studies providing empirical evidence are needed to establish the external validity of the theory derived from this research.Practical implications>This theory can be applied to develop targeted practices to understand the diffusion and adoption of sustainable fashion and further practitioners’ understanding of product positioning, target marketing, marketing strategy and luxury opportunities in general.Originality/value>Though interest in sustainable fashion has increased among consumers, no theory or model exists to explain its adoption. Therefore, the triple-trickle theory is proposed and aimed to be a more relevant framework to offer a theoretical premise for future empirical investigations of sustainable fashion adoption.

The Role of 3D CT Imaging in the Accurate Diagnosis of Lung Function in Coronavirus Patients.

Early grading of coronavirus disease 2019 (COVID-19), as well as ventilator support machines, are prime ways to help the world fight this virus and reduce the mortality rate. To reduce the burden on physicians, we developed an automatic Computer-Aided Diagnostic (CAD) system to grade COVID-19 from Computed Tomography (CT) images. This system segments the lung region from chest CT scans using an unsupervised approach based on an appearance model, followed by 3D rotation invariant Markov-Gibbs Random Field (MGRF)-based morphological constraints. This system analyzes the segmented lung and generates precise, analytical imaging markers by estimating the MGRF-based analytical potentials. Three Gibbs energy markers were extracted from each CT scan by tuning the MGRF parameters on each lesion separately. The latter were healthy/mild, moderate, and severe lesions. To represent these markers more reliably, a Cumulative Distribution Function (CDF) was generated, then statistical markers were extracted from it, namely, 10th through 90th CDF percentiles with 10% increments. Subsequently, the three extracted markers were combined together and fed into a backpropagation neural network to make the diagnosis. The developed system was assessed on 76 COVID-19-infected patients using two metrics, namely, accuracy and Kappa. In this paper, the proposed system was trained and tested by three approaches. In the first approach, the MGRF model was trained and tested on the lungs. This approach achieved 95.83% accuracy and 93.39% kappa. In the second approach, we trained the MGRF model on the lesions and tested it on the lungs. This approach achieved 91.67% accuracy and 86.67% kappa. Finally, we trained and tested the MGRF model on lesions. It achieved 100% accuracy and 100% kappa. The results reported in this paper show the ability of the developed system to accurately grade COVID-19 lesions compared to other machine learning classifiers, such as k-Nearest Neighbor (KNN), decision tree, naïve Bayes, and random forest.

The new 3Ps of sustainability marketing: The case of fashion

Sustainability marketing in the fashion industry is the subject of this theoretical synthesis. This conceptual essay entails dissecting the conceptual underpinnings and construction components of sustainability marketing derived by current scholarly perspectives to offer an updated articulation of sustainability marketing as a flourishing interdisciplinary research area. As a result of our theory synthesis approach, this paper developed a sustainability marketing model, referred to as the new 3Ps of sustainability marketing—Preservation (Environment), Public (Society) and Performance (Economy) which add to the traditional 4Ps- “Product, Price, Place, and Promotion.” The paper further examines the role of these new 3Ps of sustainability marketing in fashion, considering the COVID-19 pandemic. The model offers a uniquely integrated framework for designing marketing strategies in the fashion industry consistent with sustainability marketing and aims to promote, communicate, and educate consumers who are either existing or potential customers of sustainable fashion brands. The framework encompasses segments of the fragmented fashion industry whilst mapping strategies for marketing sustainability and presenting new post-pandemic opportunities across all value-creation stages. Finally, we offer implications and directions for further research.

HLA-B*15 predicts survival in Egyptian patients with COVID-19.

Genetic differences among individuals could affect the clinical presentations and outcomes of COVID-19. Human Leukocyte Antigens are associated with COVID-19 susceptibility, severity, and prognosis. This study aimed to identify HLA-B and -C genotypes among 69 Egyptian patients with COVID-19 and correlate them with disease outcomes and other clinical and laboratory data. HLA-B and -C typing was performed using Luminex-based HLA typing kits. Forty patients (58%) had severe COVID-19; 55% of these patients died, without reported mortality in the moderate group. The alleles associated with severe COVID-19 were HLA-B*41, -B*42, -C*16, and -C*17, whereas HLA-B*15, -C*7, and -C*12 were significantly associated with protection against mortality. Regression analysis showed that HLA-B*15 was the only allele associated with predicted protection against mortality, where the likelihood of survival increased with HLA-B*15 (P < 0.001). Patient survival was less likely to occur with higher total leukocytic count, ferritin, and creatinine levels. This study provides interesting insights into the association between HLA class I alleles and protection from or severity of COVID-19 through immune response modulation. This is the first study to investigate this relationship in Egyptian patients. More studies are needed to understand how HLA class I alleles interact and affect Cytotoxic T lymphocytes and natural killer cell function.

COVID-19 and myocarditis: a brief review.

Cardiovascular complications (especially myocarditis) related to COVID-19 viral infection are not well understood, nor do they possess a well recognized diagnostic protocol as most of our information regarding this issue was derived from case reports. In this article we extract data from all published case reports in the second half of 2020 to summarize the theories of pathogenesis and explore the value of each diagnostic test including clinical, lab, ECG, ECHO, cardiac MRI and endomyocardial biopsy. These tests provide information that explain the mechanism of development of myocarditis that further paves the way for better management.

Locus of control as a moderator of the effects of COVID-19 perceptions on job insecurity, psychosocial, organisational, and job outcomes for MENA region hospitality employees

We develop and test an integrated model to understand how individual differences based on internal or external locus of control influence the effects of COVID-19 perceptions on job insecurity, anxiety, alienation, job satisfaction, customer orientation, organisational citizenship behaviour (OCB), and turnover intention among customer service employees within hospitality organisations in the Middle East and North African (MENA) region. The investigation utilises variance-based structural equation modelling to evaluate a sample of 847 subject responses. We found that externally controlled employees are more likely to develop negative emotions resulting from pandemic-triggered job insecurity as well as poorer customer orientation and engagement in OCB due to worsened job satisfaction than those internally controlled. Wholistically, COVID-19 perceptions tend to indirectly hit externally controlled employees? anxiety, customer orientation, and OCB more intensely than those with internal locus of control.

Who's more vulnerable? A generational investigation of COVID-19 perceptions' effect on Organisational citizenship Behaviours in the MENA region: job insecurity, burnout and job satisfaction as mediators.

BACKGROUND: This paper is an empirical investigation that examines a path model linking COVID-19 perceptions to organisational citizenship behaviour (OCBs) via three mediators: job insecurity, burnout, and job satisfaction. The research examines the path model invariance spanning Generations X, Y, and Z. Three countries in the Middle East and North Africa (MENA) were the focus of the study. METHODS: The data was collected from a sample of employees in service companies (n = 578). We used a Partial Least Square Structural Equation Modelling (PLS-SEM) to analyse the data. RESULTS: Our findings reveal that COVID-19 perceptions positively predict job insecurity, which positively impacts burnout levels. Burnout negatively predicts job satisfaction. The findings established that job satisfaction positively predicts OCBs. The mediation analysis determined that job insecurity, burnout and job satisfaction convey the indirect effects of COVID-19 perceptions onto OCBs. Finally, our hypothesised model is non-equivalent across Generations X, Y and Z. In that regard, our multi-group analysis revealed that the indirect effects of COVID-19 perceptions on OCBs were only valid amongst younger generations, i.e., Generation Y and Generation Z. Specifically, younger generations are substantially more vulnerable to the indirect effects of COVID-19 perceptions on their engagement in OCBs than Generation X whose job satisfaction blocks the effects of COVID-19 perceptions on OCBs. CONCLUSIONS: The present study extends our knowledge of workplace generational differences in responding to the perceptions of crises or pandemics. It offers evidence that suggests that burnout, job attitudes and organisational outcomes change differently across generations in pandemic times.

No one is safe! But who's more susceptible? Locus of control moderates pandemic perceptions' effects on job insecurity and psychosocial factors amongst MENA hospitality frontliners: a PLS-SEM approach.

BACKGROUND: The research aimed to formulate and test a model concerning COVID-19 perceptions effects on job insecurity and a set of psychosocial factors comprising anxiety, depression, job burnout and job alienation in the Middle East and North African (hereafter, MENA) regional context. Also, the study attempted to examine whether locus of control can moderate these hypothesised linkages amongst customer service employees working in MENA hospitality organisations. METHODS: The study is based on a sample of 885 responses to an online survey and Partial Least Square Structural Equation Modelling (PLS-SEM). RESULTS: The main findings show the existence of a significant correlation between COVID perceptions and job insecurity and all psychosocial factors, i.e., more intense COVID-19 perceptions accompany higher levels of job insecurity, anxiety, depression, job burnout and job alienation. Furthermore, our results revealed that, in pandemic time, hospitality customer service employees with external locus of control are more likely to suffer higher alienation, anxiety and depression than those with internal locus of control. CONCLUSIONS: The research originality centres on the establishment that COVID-19 has a severe negative impact within the hospitality customer service labour force (in the MENA region). These effects were more profound for participants who claimed external locus of control than those with internal locus of control.

Novel deep neural network technique for detecting environmental effect of COVID-19

The studies claim that COVID-19 has positive impacts on the environment because it minimizes air pollution, water pollution, and noise pollution due to lockdown. On the contrary, COVID-19 is harming the environment due to increased medical wastage. COVID-19 has been declared a pandemic by the World Health Organization (WHO). Due to the exponential growth of COVID-19 cases people using large quantities of medical accessories to shield themselves from coronavirus, a large amount of medical wastage is produced per day. This medical wastage is a major concern for the expert because this medical waste is not adequately handled. The early detection of the COVID patient is the only solution to control this coronavirus. Several COVID detection models have been proposed in the last few months. Most of the existing models have a high false-positive rate where COVID patients are classified as healthy. To address this problem, this paper explores the positive and negative environmental consequences of COVID-19 and suggests a novel method based on artificial intelligence (AI) to identify COVID-19 disease. A comparative analysis of different previously trained models such as Visual Geometry Group Network (VGGNet-19), Residual Network (ResNet50), and Inception ResNet V2 is presented in this paper. Experimental results show that Inception_ResNet_V2 is a better choice for COVID detection. It has a minimal false-positive rate and offers 99.26% and 94% higher training and test accuracy compared to VGGNet and ResNet, respectively. [ABSTRACT FROM AUTHOR] Copyright of Energy Sources Part A: Recovery, Utilization & Environmental Effects is the property of Taylor & Francis Ltd 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 abstract 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 abstract. (Copyright applies to all Abstracts.)

Acceptability and feasibility of strategies to shield the vulnerable during the COVID-19 outbreak: a qualitative study in six Sudanese communities.

BACKGROUND: Shielding of high-risk groups from coronavirus disease (COVID-19) has been suggested as a realistic alternative to severe movement restrictions during the COVID-19 epidemic in low-income countries. The intervention entails the establishment of 'green zones' for high-risk persons to live in, either within their homes or in communal structures, in a safe and dignified manner, for extended periods of time during the epidemic. To our knowledge, this concept has not been tested or evaluated in resource-poor settings. This study aimed to explore the acceptability and feasibility of strategies to shield persons at higher risk of severe COVID-19 outcomes, during the COVID-19 epidemic in six communities in Sudan. METHODS: We purposively sampled participants from six communities, illustrative of urban, rural and forcibly-displaced settings. In-depth telephone interviews were held with 59 members of households with one or more members at higher risk of severe COVID-19 outcomes. Follow-up interviews were held with 30 community members after movement restrictions were eased across the country. All interviews were audio-recorded, transcribed verbatim, and analysed using a two-stage deductive and inductive thematic analysis. RESULTS: Most participants were aware that some people are at higher risk of severe COVID-19 outcomes but were unaware of the concept of shielding. Most participants found shielding acceptable and consistent with cultural inclinations to respect elders and protect the vulnerable. However, extra-household shielding arrangements were mostly seen as socially unacceptable. Participants reported feasibility concerns related to the reduced socialisation of shielded persons and loss of income for shielding families. The acceptability and feasibility of shielding strategies were reduced after movement restrictions were eased, as participants reported lower perception of risk in their communities and increased pressure to comply with social commitments outside the house. CONCLUSION: Shielding is generally acceptable in the study communities. Acceptability is influenced by feasibility, and by contextual changes in the epidemic and associated policy response. The promotion of shielding should capitalise on the cultural and moral sense of duty towards elders and vulnerable groups. Communities and households should be provided with practical guidance to implement feasible shielding options. Households must be socially, psychologically and financially supported to adopt and sustain shielding effectively.

Early assessment of lung function in coronavirus patients using invariant markers from chest X-rays images.

The primary goal of this manuscript is to develop a computer assisted diagnostic (CAD) system to assess pulmonary function and risk of mortality in patients with coronavirus disease 2019 (COVID-19). The CAD system processes chest X-ray data and provides accurate, objective imaging markers to assist in the determination of patients with a higher risk of death and thus are more likely to require mechanical ventilation and/or more intensive clinical care.To obtain an accurate stochastic model that has the ability to detect the severity of lung infection, we develop a second-order Markov-Gibbs random field (MGRF) invariant under rigid transformation (translation or rotation of the image) as well as scale (i.e., pixel size). The parameters of the MGRF model are learned automatically, given a training set of X-ray images with affected lung regions labeled. An X-ray input to the system undergoes pre-processing to correct for non-uniformity of illumination and to delimit the boundary of the lung, using either a fully-automated segmentation routine or manual delineation provided by the radiologist, prior to the diagnosis. The steps of the proposed methodology are: (i) estimate the Gibbs energy at several different radii to describe the inhomogeneity in lung infection; (ii) compute the cumulative distribution function (CDF) as a new representation to describe the local inhomogeneity in the infected region of lung; and (iii) input the CDFs to a new neural network-based fusion system to determine whether the severity of lung infection is low or high. This approach is tested on 200 clinical X-rays from 200 COVID-19 positive patients, 100 of whom died and 100 who recovered using multiple training/testing processes including leave-one-subject-out (LOSO), tenfold, fourfold, and twofold cross-validation tests. The Gibbs energy for lung pathology was estimated at three concentric rings of increasing radii. The accuracy and Dice similarity coefficient (DSC) of the system steadily improved as the radius increased. The overall CAD system combined the estimated Gibbs energy information from all radii and achieved a sensitivity, specificity, accuracy, and DSC of 100%, 97% ± 3%, 98% ± 2%, and 98% ± 2%, respectively, by twofold cross validation. Alternative classification algorithms, including support vector machine, random forest, naive Bayes classifier, K-nearest neighbors, and decision trees all produced inferior results compared to the proposed neural network used in this CAD system. The experiments demonstrate the feasibility of the proposed system as a novel tool to objectively assess disease severity and predict mortality in COVID-19 patients. The proposed tool can assist physicians to determine which patients might require more intensive clinical care, such a mechanical respiratory support.