The effect of COVID-19 confinement regulations on air quality in the northwestern Alps is here assessed based on measurements at five valley sites in different environmental contexts. Surface concentrations of nitrogen oxides, ozone, particle matter, together with size, chemical, and optical (light absorption) aerosol properties, complemented by observations along the vertical column are considered. The 2020 concentration anomalies relative to previous years’ average are compared with the output of a machine learning algorithm accounting for weather effects and a chemical transport model, their difference being within 10–20 %. Even in the relatively pristine environment of the Alps, the «lockdown effect» is well discernible, both in the early confinement phase and in late 2020, especially in NOx concentrations (NO decreasing by >80 % and NO2 by >50 %). While ozone shows little variation, secondary aerosols increase due to enhanced transport from the neighbouring Po basin and coarse particles decrease due to missing resuspension by traffic and, in the city, to the shutdown of a steel mill. The NO2 vertical column density decreases by >20 %, whereas the aerosol profile is mainly influenced by large-scale dynamics, except a shallow layer about 500 m thick possibly sensitive to curtailed surface emissions.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiological agent of the coronavirus disease 2019 (COVID-19) pandemic which has been a topic of major concern to global human health. The challenge to restrain the COVID-19 pandemic is further compounded by the emergence of several SARS-CoV-2 variants viz. B.1.1.7, B.1.351, P1 and, B.1.617., which show in-creased transmissibility and resistance towards vaccines and therapies. Importantly, the likelihood of susceptibility to SARS-CoV-2 infection among individuals with dysregulated immune response or comorbidities needs greater attention. Herein, we provide a comprehensive perspective regarding ongoing vaccine (mRNA, protein-based, viral vector based etc.) and therapeutic (mono-clonal antibodies, small molecules, plasma therapy, etc.) modalities designed to curb the COVID-19 pandemic. We also discuss in detail the challenges posed by different SARS-CoV-2 variants of concern (VOC) identified across the globe and their effects on therapeutic and prophylactic interventions.

The rapidly expanding corona pandemic in 2020 brought the world to virtual economic stagna-tion. While the impact on the environment from suspended air traffic, idle industry and economic lockdown has been considerable, so have the economic and social consequences of the crisis. To make matters worse, the resulting state of stagnation is neither economically nor socially sustaina-ble. Nevertheless, we need to ask ourselves what we can learn from the situation in order to ex-plore the benefits of globalization, intercept similar crisis situations more effectively in the future and move towards more sustainable development on an ecological, economic and social level. This paper identifies the areas of expanded externality management needed to further improve environmental quality, digitalization, network expansion and basic income. These central issues need to be addressed both during and after the crisis in order to deal with problems of inequality and climate change mitigation for current and future generations. Concrete concepts will be put forward and discussed in the paper.

There exists a compelling need to better understand the temporal dynamics of public sentiment towards COVID-19 vaccines in the US on a national and state-wise level for facilitating appropriate public policy applications. Our analysis of social media data from early February of 2021 and late March of 2021 shows that in spite of overall strength of positive sentiment, and increasing numbers of Americans being fully vaccinated, negative sentiment about COVID-19 vaccines still persists among sections of people who are hesitant towards the vaccine. In this study, we performed sentiment analytics on vaccine tweets, studied changes in public sentiment over time, conducted vaccination sentiment validation using actual vaccination data from the US CDC and Household Pulse Survey (HPS), explored influence of maturity of Twitter user-accounts and generated geographic mapping of sentiments by location of Twitter users. Furthermore, we leverage the emotion polarity based Public Sentiment Scenarios (PSS) framework which was developed for COVID-19 sentiment analytics, to systematically analyze directions for public policy processes to potentially improve the administration of vaccines. Application of the PSS framework provides important time sensitive insights for state and federal government agencies and associated organizations to better implement public policy processes for healthcare management, communication, transparency, motivation and societal operational policies such as social distancing. These insights are expected to contribute to processes that can expedite the vaccination program and move closer to the cherished herd immunity goal.

To reduce the risk of infection of SARS-CoV-2 during the commute to the clinic or due to the contact with medical staff, The American College of Obstetricians and Gynecologists recommended ar-ranging part of the appointments in the form of “telehealth”. The aim of the study was to assess the access to medical care in pregnancy during the Sars-Cov-2 pandemic and the role of telehealth in implementation of prenatal care standards. This is a cross-sectional study. The study group in-cluded 618 women that were pregnant and or gave birth during the COVID-19 pandemic in Poland. The majority of participants experienced difficulties in access to medical care because of the pandemic. Correlation between this experience and the use of hybrid healthcare model was es-tablished. However, affiliation to public or private healthcare group was irrelevant. There was no relationship between healthcare (private/public or in-person/hybrid) and implementation of the prenatal care standards. To ensure safe access to prenatal care for pregnant women, recommen-dations for a hybrid pregnancy management model should be created with detailed information for which appointments patients must be present and which can be done remotely. To reduce movement risk and interpersonal contact, all visits during which tests and screenings take place should be done in-person. Other appointments can be arranged in the form of telehealth

This research analyzed South Korean companies’ adoption of remote work during the COVID-19 pandemic, by focusing on the dual labor market structure comprising of the primary (large corporations) and the secondary sectors (small and medium enterprises (SMEs)). Companies in the dual labor market were classified as per firm size. We used Statistics Korea’s August supplementary data from the Economically Active Population Survey, covering 2017–2020. This empirical study analyzed the factors affecting remote work in 2020, after the outbreak of the pandemic. The results showed that the probability of large corporations introducing remote work during the pandemic increased by a significantly larger margin than for small and medium-sized firms. This suggests that the polarization within the dual labor market structure between large corporations and SMEs also spilled over into companies’ adoption of remote work, which was initially introduced to prevent the spread of the pandemic. Additionally, the polarization in the use of digital technology is likely to persist even after the pandemic. Hence, based on our analysis of remote work adoption in the dual labor market, this study examined the system and factors of labor-management relations contributing toward such polarization and presented policy directions for the current labor market structure.

The novel coronavirus (COVID-19) was first reported in the U.S. on December 29, 2019 and has spread rapidly throughout the country, affecting individuals with varying severity due to their risk status. According to the Centers for Disease Control and Prevention, it is estimated that 45.4% of US adults are at higher risk for complications from coronavirus disease because of cardiovascular disease, diabetes, respiratory disease, hypertension, or cancer. In this study, we developed a mathematical model to assess the impact of a COVID-19 vaccine among low and high risk groups. Numerical simulations shows vaccinating both low and high risk groups simultaneously, rather than prioritizing the vaccine on high risk group only, further reduces the daily mortality. The result supports the need for an aggressive vaccination program, regardless of whether individuals are within the low or high risk population.

Inhibition of the binding of enveloped viruses surface glycoproteins to host cell receptor(s) is a major target of vaccines and constitutes an efficient strategy to block viral entry and infection of various host cells and tissues. Cellular entry usually requires fusion of the viral envelope with host plasma membranes. Such entry mechanism is often preceded by “priming” and/or “activation” steps requiring limited proteolysis of the viral surface glycoprotein to expose a fusiogenic domain for efficient membrane juxtapositions. The 9-membered family of Proprotein Convertases related to Subtilisin/Kexin (PCSK) serine proteases (PC1, PC2, Furin, PC4, PC5, PACE4, PC7, SKI-1/S1P and PCSK9) participate in post-translational cleavages and/or regulation of multiple secretory proteins. The type-I membrane-bound Furin and SKI-1/S1P are the major convertases responsible for the processing of surface glycoproteins of enveloped viruses. Stefan Kunz has considerably contributed to define the role of SKI-1/S1P in the activation of arenaviruses causing hemorrhagic fever. Furin was recently implicated in the activation of the spike S-protein of SARS-CoV-2 and Furin-inhibitors are being tested as antivirals in COVID-19. Other members of the PCSK-family are also implicated in some viral infections such as PCSK9 in Dengue. Herein, we summarize the various functions of the PCSKs and present arguments whereby their inhibition could represent a powerful arsenal to limit viral infections causing the present and future pandemics.

Background: The primary objective worldwide during the COVID-19 pandemic has been controlling disease transmission. However, lockdown measures used to mitigate transmission have affected human behavior and altered lifestyles, with a likely impact on chronic non-communicable diseases. More than a year into the pandemic, substantial peer-reviewed literature has emerged on altered lifestyles following the varying lockdown measures imposed globally to control the virus spread. Objective: To explore the impact of lockdown measures on the six lifestyle factors, namely diet, physical activity, sleep, stress, social connectedness, and the use of tobacco, alcohol, or other harmful substances.Methods: We comprehensively searched PubMed and the World Health Organization’s global literature database on COVID-19 and retrieved 649 relevant articles for the narrative review. A critical interpretative synthesis of the articles was performed.Results: Most of the articles included in the review identified the negative effect of lockdown measures on each of the lifestyle factors in many parts of the world. Interestingly, encouraging lifestyle trends were also highlighted in a few articles. Such trends can positively influence the outcome of lifestyle-related chronic diseases, such as obesity and diabetes.Conclusions: The COVID-19 pandemic provides an opportunity to better understand the negative impact of strict lockdown measures on lifestyles. At the same time, it helps us identify and initiate positive behavioral changes, which, if consolidated, could improve chronic disease outcomes. It is up to governments, communities, and healthcare/academic entities to derive benefit from lessons learned from the pandemic, with the ultimate objective of better educating and promoting healthy lifestyles among communities.

Background: During the COVID-19 pandemic some family physicians were overburdened and experienced difficulties reaching vulnerable patients and meeting the increased need for psycho-social support. This randomized controlled trial (RCT) tested whether a primary healthcare (PHC) based community health worker (CHW) intervention could tackle psychosocial suffering due to physical distancing measures in patients with limited social networks. Methods: CHWs provided 8 weeks of tailored psychosocial support to the intervention group. Control group patients received ‘care as usual’. The impact on feelings of emotional support, social isolation, social participation, anxiety and fear of COVID-19 were measured longitudinally using a face-to-face survey to determine their mean change from baseline. Self-rated change in psychosocial health at 8 weeks was determined. Results: We failed to find a significant effect of the intervention on the prespecified psychosocial health measures. However, the intervention did lead to significant improvement in self-rated change in psychosocial health. Conclusions: This study confirms partially the existing evidence on the effectiveness of CHW in-terventions as a strategy to address mental health in PHC in a COVID context. Further research is needed to elaborate the implementation of CHWs in PHC to reach vulnerable populations during and after health crises.

Fundamental principles of modern cities and urban planning are challenged during the COVID-19 pandemic, such as the advantages of large city size, high density, mass transport, free use of public space, unrestricted individual mobility in cities. These principles shaped the development of cities and metropolitan areas for more than a century, but currently, there are signs that they have turned from advantage to liability. Cities Public authorities and private organisations responded to the COVID-19 crisis with a variety of policies and business practices. These countermeasures codify a valuable experience and can offer lessons about how cities can tackle another grand challenge, this of climate change. Do the measures taken during the COVID-19 crisis represent a temporal adjustment to the current health crisis? Or do they open new ways towards a new type of urban development more effective in times of environmental and health crises? We address these questions through literature review and three case studies that review policies and practices for the transformation of city ecosystems mostly affected by the COVID-19 pandemic: (a) the central business district, (b) the transport ecosystem, and (c) the tourism-hospitality ecosystem. We assess whether the measures implemented in these ecosystems shape new policy and planning models for higher readiness of cities towards grand challenges. And how, based on this experience, cities should be organized to tackle the grand challenge of environmental sustainability and climate change.

The Covid-19 pandemic is a tragedy for those who have been hard hit worldwide. At the same time, it is also a test of concepts and practices of what good care is and requires, and how quality of care can be accounted for. In this paper, we present our Care-Ethical Model of Quality (CEMQ) and apply it to the case of residential care for older people in the Netherlands during the Covid-19 pandemic. Instead of thinking about care in healthcare and social welfare as a set of separate care acts, we think about care as a complex practice of relational caring, crossed by other practices. Instead of thinking about professional caregivers as functionaries obeying external rules, we think about them as practically wise professionals. Instead of thinking about developing external quality criteria and systems, we think about cultivating (self-)reflective quality awareness. Instead of abstracting from societal forces that make care possible but also limit it, we acknowledge them and find ways to deal with them. Based on these critical insights, the CEMQ model can be helpful to describe, interrogate, evaluate, and improve existing care practices. It has four entries: (i) the care receiver considered from their humanness, (ii) the caregiver considered from their solicitude, (iii) the care facility considered from its habitability and (iv) the societal, institutional and scholarly context considered from the perspective of the good life, justice and decency. The crux is enabling all these different entries with all their different aspects to be taken into account. In Corona times this turns out to be more crucial than ever.

Starting from early 2020, the COVID-19 pandemic has caused a morbidity and mortality excess worldwide. Containment strategies rely firstly on rapid and sensitive laboratory diagnosis with molecular detection of the viral genome in respiratory samples being the gold standard. Reliability of diagnostic protocols could be affected by SARS-CoV-2 genetic variability. In fact, mutations occurring during SARS-CoV-2 genomic evolution can involve the regions targeted by the diagnostic probes. Following a review of the literature and an in silico analysis of the most recently described virus variants (including the UK B 1.1.7 and the South Africa 501Y.V2 variants), we conclude that the described genetic variability should have minimal or no effect on the sensitivity of existing diagnostic protocols for SARS-CoV-2 genome detection. However, given the continuous emergence of new variants, the situation should be monitored in the future, and protocols including multiple targets should be preferred.

Mechanical ventilation systems, which are used for breathing support when a person is not able to do it by their own, requires a device for measuring the air flow to the patient in order to monitoring and a assure the magnitude establish by a medical staff. Flow sensors are the conventional devices used for the air flow measuring; however, there were not available in Peru, because of the international demand during COVID-19 pandemic. In this sense, a novel air flow sensor based on orifice plate and an intelligent transducer stage were developed as an integrated design. Advanced methodologies in simulations and experiments using specially designed equipment for this application were carried out. The obtained data was used for a mathematical characterization and dimensions validation of the integrated design. The device was tested in its real working conditions, it was implemented in a breathing circuit connected to a low-cost mechanical ventilation system based on cams. Results indicate that the designed air flow sensor/transducer is a low-cost complete medical device for mechanical ventilators able to provide satisfactorily all the ventilation parameters air flow, pressure and volume over time by measuring the air flow and calculating the others. Furthermore, this device provides directly a filtered equivalent electrical signal for a display or a computer.

COVID-19 breakout calls for immediate research explorations. The objective of this study is to perform a bibliometric analysis of all COVID-19-related publications in Science Citation Index Expanded (SCI-EXPANDED) in the early stage of the outbreak. Analysis parameters include performances of authors, institutes, and countries as well as distributions of Web of Science categories, journals, languages, and types of publications. Results show that 32% of total papers were published as editorial materials and an overwhelming production from Chinese research institutes. An association of research indexes with the number of cases was also found.

The COVID-19 pandemic forced the transition to emergency online learning without prior preparation or guidelines. This transition has been particularly challenging in developing countries and low-resource contexts and hindered student engagement. We aim to identify the engagement strategies which students, engaging in emergency online learning in low-resource contexts, perceive to be effective. We conducted a sequential mixed-methods study based on Moore’s interaction framework for distance education. First, we conducted a literature review and interviewed ten teachers and ten students to identify a list of engagement strategies. Then, we designed a questionnaire that examines student perceptions of these strategies. We administered the questionnaire to 313 students engaging in emergency online learning in low-resource contexts. Our analysis results showed that student-content engagement strategies, e.g. screen sharing, summaries, and class recordings, are perceived as the most effective, closely followed by student-teacher strategies, e.g. Q&A sessions and reminders. Student-student strategies, e.g. group chat and collaborative work, are perceived as the least effective. The perceived effectiveness of engagement strategies depends on the context and the students’ characteristics, e.g. gender, major, and technology access. To support instructors, instructional designers, and researchers we propose a ten-level guide for engaging students during emergency online classes in low-resource contexts.

With the COVID-19 pandemic now ongoing for close to a year, people all over the world are still waiting for a vaccine to become available. The initial focus of accelerated global research and development efforts to bring a vaccine to market as soon as possible was on novel platform technologies that promised speed but had limited history in the clinic. In contrast, recombinant protein vaccines, with numerous examples in the clinic for many years, missed out on the early wave of investments from government and industry. Emerging data are now surfacing suggesting that recombinant protein vaccines indeed might offer an advantage or complement to the nucleic acid or viral vector vaccines that will likely reach the clinic faster. Here, we summarize the current public information on the nature and on the development status of recombinant subunit antigens and adjuvants targeting SARS-CoV-2 infections.

Latin America and the Caribbean (LAC) is one of the worst-hit regions globally by COVID-19 pandemic. Yet, scarce literature exists that examines the research strategy of LAC in facing COVID-19. The present study aims to quantify and assess the production of COVID-19 publications in thirty-two countries in LAC during the first half of 2020. A Scopus/PubMed/LILACS search was performed to retrieve research articles related to COVID-19 published from January 1 to July 31, 2020. Subgroup analysis including only original publications was used to better ascertain the contribution of LAC countries, and standardization measures were applied to comparisons of country-specific contributions. We identified 1291 publications across the region. Overall, most articles in the region were non-original (81.6%), and the most productive countries were Brazil (43.9%), Mexico (9.14%), and Colombia (7.98%). This trend shifted to Chile after the standardization. Among original studies, the most common study design was cross-sectional (25.8%). LAC countries generate articles primarily pertaining to diagnosis and treatment (27.4%). In the subgroup analysis, however, epidemiology and surveillance was the most prevalent research focus (24.1%). LAC countries should perform more research with a higher level of evidence to inform health policy making to ease the burden of COVID-19 in the region.

Coronavirus (COVID-19) gained and will continue to gain a lot of global attention over the coming months (and maybe the coming few years). Since its outbreak in Wuhan (China), it has turned into one of the major challenges affecting the whole world. In a comparatively short time, the virus outbreak turned into a pandemic that led to massive negative impacts not only on people health and well-being, but also on the global economy, travel industry, pharmaceutical industry, tourism industry, and many other industries. This research paper aims to investigate the different effects of coronavirus on the global Halal tourism and Halal hospitality industry and whether the coronavirus pandemic is the end of Halal tourism and hospitality as we know it or not. The paper offers an in-depth theoretical examination of the different aspect of the pandemic on Halal tourism and hospitality industry and provides guidance on how to address these different aspects. The current paper is one of very few research papers addressing coronavirus on the tourism and hospitality industry.

Several studies suggest that COVID-19 may be accompanied by symptoms such as a dry cough, muscle aches, sore throat, and mild to moderate respiratory illness. The symptoms of this disease indicate the fact that COVID-19 causes noticeable negative effects on the lungs. Therefore, considering the health status of the lungs using X-rays and CT scans of the chest can significantly help diagnose COVID-19 infection. Due to the fact that most of the methods that have been proposed to COVID-19 diagnose deal with the lengthy testing time and also might give more false positive and false negative results, this paper aims to review and implement artificial intelligence (AI) image-based diagnosis methods in order to detect coronavirus infection with zero or near to zero false positives and false negatives rates. Besides the already existing AI image-based medical diagnosis method for the other well-known disease, this study aims on finding the most accurate COVID-19 detection method among AI methods such as machine learning (ML) and artificial neural network (ANN), ensemble learning (EL) methods.

Urban green spaces provide a range of environmental and health benefits, which may become even more critical during times of crisis such as the current COVID-19 pandemic. However, with a radical shift in mobility, additional concerns over safety, and access temporarily restricted during the implementation of social distancing policies, the experience and use of urban green spaces may be reduced. This is particularly concerning for densely populated cities like New York, considered the first U.S. epicenter or vanguard of the outbreak. To better understand the impact of COVID-19 on the perception and use of urban green spaces, we conducted a social survey during the early months of the Covid-19 pandemic in New York City (May 13 - June 15, 2020). The results of the survey show respondents continued to use urban green spaces during the pandemic and consider them to be more important for mental and physical health than before the pandemic began. However, the study revealed a pattern of concerns residents have about green space accessibility and safety, and found key differences between the concerns and needs of different populations, suggesting a crucial role for inclusive decision-making, support for additional management strategies, and urban ecosystem governance that reflect the differential values, needs and concerns of communities across the City. As urban centers face looming budget cuts and reduced capacity, this study provides some empirical evidence to illustrate the value of urban green spaces as critical urban infrastructure, and may have implications for funding, policy, and management, of urban green spaces in NYC, with potential applications to other cities, particularly during times of crisis.

Background: HIV poses a threat to global health. With effective treatment options available, education and testing strategies are essential in preventing transmission. Text messaging is an effective tool for health promotion and can be used to target higher risk populations. This study reports on the design, delivery and testing of a mobile text messaging SMS intervention for HIV prevention and awareness, aimed at adults in the construction industry and delivered during the COVID-19 pandemic. Method: Participants were recruited at Test@Work workplace health promotion events (21 sites, n=464 employees), including health checks with HIV testing. Message development was based on a participatory design and included a focus group (n=9) and message fidelity testing (n=291) with assessment of intervention uptake, reach, acceptability, and engagement. Barriers to HIV testing were identified and mapped to the COM-B behavioural model. 23 one-way push SMS messages (19 included short web links) were generated and fidelity tested, then sent via automated SMS to two employee cohorts over a 10-week period during the COVID-19 pandemic. Engagement metrics measured were; opt-outs, SMS delivered/read, number of clicks per web link, and four two-way pull messages exploring repeat HIV testing, learning new information, perceived usefulness and behaviour change. Results: 291 people participated (68.3% of eligible attendees). A total of 7,726 messages were sent between March and June 2020, with 91.6% successfully delivered (100% read). 12.4% of participants opted out over 10 weeks. Of delivered messages, links were clicked an average of 14.4%, max 24.1% for HIV related links. The number of clicks on web links declined over time (r= -6.24, p=0.01). Response rate for two-way pull messages was 13.7% of participants. Since the workplace HIV test offer at recruitment, 21.6% reported having taken a further HIV test. Qualitative replies indicated behavioural influence of messaging on exercise, lifestyle behaviours and intention to HIV test. Conclusion: SMS messaging for HIV prevention and awareness is acceptable to adults in the construction industry, has high uptake, low attrition and good engagement with message content, when delivered during a global pandemic. Data collection methods may need refinement for audience and effect of COVID-19 on results is yet to be understood.

Pneumonia cases of unknown etiology in Wuhan, China, were reported to the WHO on 31st of December 2019. Later the pathogen was reported to be a novel coronavirus designated Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that causes Coronavirus Disease 2019 (COVID-19). SARS-CoV-2 is a novel pathogenic beta coronavirus that infects humans causing severe respiratory illness. However, multifarious factors can contribute to the susceptibility to COVID-19 related morbidity and mortality such as age, gender and underlying comorbidities. Importantly, SARS-CoV and SARS-CoV-2 entry into the host cells is mediated via ACE2 receptor. However, ACE2 receptor binding affinity to SARS-CoV-2 is 4 folds higher than that to SARS-CoV. Identification of different aspects such as binding affinity, differential antigenic profiles of spike glycoproteins, and ACE2 polymorphisms might influence the investigation of potential therapeutic strategies targeting SARS-CoV-2/ACE2 binding interface. Here we aim to elaborate on SARS-CoV-2 S1/ACE2 ligand that facilitates viral internalization as well as to highlight the differences between SARS-CoVs binding affinity to ACE2. We also discuss the possible immunogenic sequences of spike glycoprotein and the effect of ACE2 polymorphism on viral binding/infectivity and host susceptibility to disease. Furthermore, targeting of ACE2 will be discussed to understand its role in therapeutics.

The ongoing global pandemic caused by coronavirus disease 2019 (COVID-19) has once again demonstrated the significance of the Coronaviridae family in causing human disease outbreaks. As SARS-CoV-2 was first detected in December 2019, information on its tropism, host range, and clinical presentation in animals is limited. Given the limited information, data from other coronaviruses may be useful to inform scientific inquiry, risk assessment and decision-making. We review the endemic and emerging alpha- and betacoronavirus infections of wildlife, livestock, and companion animals, and provide information on the receptor usage, known hosts, and clinical signs associated with each host for 15 coronaviruses discovered in people and animals. This information can be used to guide implementation of a One Health approach that involves human health, animal health, environmental, and other relevant partners in developing strategies for preparedness, response, and control to current and future coronavirus disease threats.

The outbreak of novel Coronavirus (SARS-COV-2 ) disease (COVID-19) in Wuhan has attracted worldwide attention. SARS-COV-2 known to share a similar clinical manifestation that includes various symptoms such as pneumonia, fever, breathing difficulty, and in particular, SARS-COV-2 also causes a severe in ammation state that leads to death. Consequently, massive and rapid research growth has been observed across the globe to elucidate the mechanisms of infections and disease progression in genotype and phenotype scale. Data Science is playing a pivotal role in in-silico analysis to draw hidden and novel insights about the SARS-COV-2 origin, pathogenesis, COVID-19 outbreak forecasting, medical diagnosis, and drug discovery. With the availability of multi-omics, radiological, biomolecular, and medical data urges to develop novel exploratory and predictive models or customise exiting learning models to t the current problem domain. The presence of many approaches generates the need for the systematic surveys to guide both data scientists and medical practitioners. We perform an elaborate study on the state-of-the-art data science method ologies in action to tackle the current pandemic scenario. We consider various active COVID-19 data analytics domains such as phylogeny analysis, SARS-COV-2 genome identi cation, protein structure prediction, host-viral protein interactomics, clinical imaging, epidemiological analysis, and most importantly (existing) drug discovery. We highlight types of data, their generation pipeline, and the data science models in use. We believe that the current study will give a detailed sketch of the road map towards handling COVID-19 like situation by leveraging data science in the future. We summarise our review focusing on prime challenges and possible future research directions .

The paper presents the most comprehensive and large-scale study to date on how students perceive the impacts of the COVID-19 crisis on various aspects of their lives on a global level. With a sample of 30,383 students from 62 countries, the study reveals that amid the worldwide lockdown and transition to online learning students were most satisfied with the support provided by teaching staff and their universities’ public relations. Still, deficient computer skills and the perception of a higher workload prevented them from perceiving their own improved performance in the new teaching environment. Students were mainly concerned about issues to do with their future professional career and studies, and experienced boredom, anxiety and frustration. The pandemic has led to the adoption of particular hygienic behaviours (e.g. wearing masks, washing hands) and discouraged certain daily practices (e.g. leaving home, shaking hands). Students were also more satisfied with the role played by hospitals and universities during the epidemic compared to the government and banks. The findings also show that students with selected socio-demographic characteristics (male, part-time, first level, applied sciences, lower living standard, from Africa or Asia) were generally more strongly affected by the pandemic since they were significantly less satisfied with their academic work/life. Key factors influencing students' satisfaction with the role of their university are also identified. Policymakers and higher education institutions around the world may benefit from these findings while formulating policy recommendations and strategies to support students during this and any future pandemics.

The all-pervasiveness and dynamic nature of the COVID-19 pandemic warrants comprehensive and constant surveillance of the numerous mutations that are accumulating in global SARS-CoV-2 genomes and contributing to the microevoution of the various lineages of the novel coronavirus. This would help us gain insights into the evolving pathogenicity of the virus, and thereby improvise our control and therapeutic strategies. This study explores the genome-wide frequency, gene-wise distribution, and molecular nature, of the large repertoire of point mutations detected across the global dataset of 3,608 SARS-CoV-2 RNA-genomes short-listed from a total 5,485 whole genome sequences deposited in GenBank till 4 June 2020 using a download filter that eliminated all incomplete/gapped sequences. Phylogenomic analysis involving all existing SARS-CoV-2 lineages, represented by 3,740 whole genome sequences from human-source (out of a total of 63,894 sequences stored in the GISAID repository, as on 15 July, 2020), illustrated that the two major-lineages of the virus contributed almost equivalently to the pandemic. However, entities belonging to the early lineages are still mostly spread over Asian countries, whereas those affiliated to recently-derived lineages have a relatively more global distribution. Mutation frequency in the SARS-CoV-2 pan genome was found to be 2.27 × 10^-5 nucleotide positions mutated per nucleotide analyzed. An overwhelming majority (count: 1797) of the total 2452 instances of single nucleotide substitution detected (in the SARS-CoV-2 pan genome) were found to be transition mutations with cytidine to uridine (CàU) as the most ubiquitous molecular-type (count: 987). Of the 655 instances of transversion detected, the guanosine to uridine (GàU) variant was most widespread (count: 367). All transcribed and untranscribed loci of the pan genome were found to contain mutation(s). nsp3, and S, N and orf3a, were the most point-mutation-ridden non-structural and structural protein-coding genes, respectively, with 435, 300, 171 and 128 total mutations; 349/86, 192/108, 107/64 and 76/52 transitions/transversions; and 189/48, 106/55, 59/42 and 43/31 CàU/GàU substitutions respectively. Potential mechanistic backgrounds were envisaged for the molecular bias of mutations observed in SARS-CoV-2.

A vast majority of the countries is under the economic and health crises due to the current epidemic of coronavirus disease 2019 (COVID-19). The present study analyzes the COVID-19 using time series, which is an essential gizmo for knowing the enlargement of infection and its changing behavior, especially the trending model. We have considered an autoregressive model with a non-linear time trend component that approximately converted into the linear trend using the spline function. The spline function split the COVID-19 series into different piecewise segments between respective knots and fitted the linear time trend. First, we obtain the number of knots with its locations in the COVID-19 series and then the estimation of the best-fitted model parameters are determined under Bayesian setup. The results advocate that the proposed model/methodology is a useful procedure to convert the non-linear time trend into a linear pattern of newly coronavirus case for various countries in the pandemic situation of COVID-19.

Safely resuming sporting events while the coronavirus is spreading is challenging – yet possible – if the science is taken into account. Two main ways the coronavirus can spread among football players is through air-suspended microdroplets (and possibly aerosols), and via contact with contaminated surfaces. Here we estimated virus survival in dried saliva droplets on a football pitch (i.e., on the grass) and on the ball itself, and compared these measures between mid-day and nighttime matches. We find, based on experiments with the enveloped phage Phi6 – a surrogate for SARS-Cov-2 – that while the virus survives reasonably well on both pitch and ball during a nighttime match (~10% survival), virtually no viruses survived the 90-minute duration of a mid-day match on a hot, sunny day. These results, taken together with studies reporting rapid deactivation of coronavirus in aerosols by sunlight, suggest that playing football in mid-day reduces the likelihood of transmission between players, and thus increases players’ safety.

We performed a global analysis with data from 149 countries to test whether temperature can explain the spatial variability of the spread rate and mortality of COVID-19 at the global scale. We performed partial correlation analysis and linear mixed effect modelling to evaluate the association of the spread rate and motility of COVID-19 with maximum, minimum, average temperatures and temperature extreme (difference between maximum and minimum temperature) and other environmental and socioeconomic parameters. After controlling the effect of the duration after the first positive case, partial correlation analysis revealed that temperature was not related with the spatial variability of the spread rate of COVID-19. Mortality was negatively related with temperature in the countries with high-income economies. In contrast, temperature extreme was significantly and positively correlated with mortality in the low-and middle-income countries. Taking the country heterogeneity into account, mixed effect modelling revealed that inclusion of temperature as a fixed effect in the model significantly improved model skill predicting mortality in the low-and middle-income countries. Our analysis suggest that warm climate may reduce the mortality rate in high-income economies but in low and middle-income countries temperature extreme may increase the mortality risk.

The report describes organizational and occupational strategies adopted by Lody Public Hospital (the first epicentre of Covid-19 outbreak in Italy) in order to face pandemic. Occupational Safety System (OSH) introduced infection prevention and control strategies (IPC) for the protection of healthcare workers (HCWs, while a reorganization of whole hospital based on the level of intensity of care for COVID-19 patients was estabilished. Screening on HCWs (N= 248) by nasopharyngeal swabs for SARS-CoV-2 and comparison between HCWs and local population (N=1123) are shown. These preliminary data, collected from 25^th February till 25^th March 2020, confirms that measures adopted mitigate the effects of virus transmission within the hospital and reduced the HCW component of the transmission of the infection. Additional studies in depth are currently underway.

As an on-going pandemic caused by the out-break of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or simply COVID-19 sweeps through the globe at an unprecedented rate leaving behind trails of high infection and mortality, it is crucial to understand the propagation dynamics of the virus in a host population in order to take urgent and effective remedial and mitigating steps to save life. It is already observed in many countries and communities that accurate and timely testing, tracing, and tracking of the infection lead to better containment and slowing down of the spread. In this exploratory research, the early growth dynamics of infection within a population is pursued based on real data. The study posits that the early growth in a homogenous population follows an exponential pattern motivating further rigorous quantitative treatment based on a number of analytical models such as logistic model, Richard’s model, and Gompertz model– the acceleration pattern of the outbreak is ascertained from the daily inflection data, and regression analysis against population models yields dynamic growth indices which allow very accurate prediction of the successive outbreak size when calibrated continually with updated data. The performance of the various models is evaluated with the real dataset. More, the basic reproduction number of the COVID-19 virus propagation in the community is estimated based on the on-set phase dataset using multi-compartmental epidemiological model. Also, the maximum infection size, infection doubling time and the scope of the herd immunity are also inferred for COVID-19 in a population.

Background: Australia received its first case of coronavirus on 25 January 2020. Since then the demands of COVID-19 has presented unparalleled levels of strain on the public healthcare systems in the country. In this time of crisis, pharmacists and community pharmacy staff have modified work strategies according to the rapidly changing environment. With a delayed dissemination of resources and guidelines, pharmacist and pharmacies are practicing innovative infection control methods across Australia to protect their staff, patients and the community. This article seeks to explore the current activities undertaken by pharmacists in various community pharmacy settings across Australia in relation to the safety of the workplace environments for staff and patients. Information collected can help inform future decisions in pandemic preparation for pharmacies in response to similar health crisis now and in the future. Methods: An online cross-sectional survey study was conducted in Australia during the COVID-19 outbreak from 1^st to 30^th April 2020. The questionnaire addressed community pharmacist’s awareness and response to infection and sanitation control. Results: A total of 137 pharmacists took part in the survey, with almost half (45.26%) belonging to the age group of 25 to 34 years. Community pharmacy formed the bulk (89.05%) of the respondent’s primary place of practice. There was a good uptake of safety measures by pharmacists and their pharmacies to protect staff and patients. However the task of reassigning high health risk staff was not heavily practiced (34.31%). Regular cleaning took place in the pharmacy, but the use of gloves while cleaning was not practiced in 48.18% of respondents. In addition, only 46.72% of respondents reported observing script baskets being cleaned and disinfected. About one-third (37.96%) of pharmacists were aware of the two-step cleaning and disinfecting process, but only 18.98% of pharmacists reported observing or performing this sanitation procedure. More than half of surveyed pharmacists reported having difficulty keeping up with infection control changes and pharmacy practice guidelines during the pandemic. Conclusion: This study demonstrates that the majority of pharmacists are not fully aware of the infection control measures needed in a community pharmacy setting. The influx of coronavirus updates has made it difficult for pharmacists to implement accurate procedures on some aspects of workplace hygiene, which may have led to some gaps in infection control measures. Pharmacists must aim to uphold their public health ambassador role and aim to keep up-to-date with professional guidance to provide the necessary infection control measures to ensure staff, patient and public health safety.

As early as February 2020, many countries have started imposing measures to curb the spread of Covid-19. Despite the right intention, it is a challenging moment for the people, especially the rural population living in the coastal areas. The document presents the preliminary findings on the impacts of Covid-19 on the small scale fisheries in Tun Mustapha Park, Sabah, Malaysia.

Fractional differential mathematical model unfolding the dynamics of the COVID-19 pandemic in India is presented and explored in this paper. The purpose of this study is to estimate the future outbreak of disease and potential control strategies using mathematical models in India as a whole country as well as in some of the states of the country. This model is calibrated based on reported cases of infections over the month of April 2020 in India. We have used iterative fractional complex transform method to find approximate solutions of the model having modified Riemann Liouville fractional differential operator. We have also carried out a comparative analysis between actual and estimated cumulative cases graphically, moreover, most sensitive parameters for basic reproduction number$(R_0)$ are computed and their effect on transmission dynamics of COVID-19 pandemic is investigated in detail.

Some of the European countries affected by COVID-19 have not learned from previous experience in China. Italy did not learn from China and Spain did neither learn from China nor from Italy. Confinement in Spain was postponed due to pressure from economic interests and traveling of infected people, especially from Madrid to the beaches in South-East Spain, was allowed. Strict confinement and border closure came late, when the curve of infected people and the death toll already had the worse trend worldwide. Tests to SARS-CoV-2 RNA detection by PCR, were first unavailable and, later, faulty and/or detecting antibodies and not the virus itself. Instead of mobilizing research laboratories for making tests, and instead of making masks and ventilators, mediatic scientists asked for money for controversial clinical trials and for obtaining a vaccine. In this scenario, common sense indicates that ad hoc measures should be taken at the end of confinement in order to minimize pain. The chain of errors should be avoided in the management of next pandemics by designing Good Practice Rules (GPRs). In addition, post-confinement measures should be implemented as soon as possible to be ready for SARS-CoV-2 return next season. In this sense a longitudinal study in the most affected cities (Madrid, Barcelona, Vitoria and Pamplona) should be performed with the primary objective of detecting carriers with no symptoms, to stratify patients according to symptoms, and to early detection of virus reappearance. Also relevant is to sequence as many viruses as possible to detect possible variants; there are still patients that are PCR positive.

We review and assess the classic SIR and SEIR epidemiological models regarding possible applications to the COVID-19 pandemic. In spite of numerous more complicated models, we show how the qualitative features of the solution to the SIR and SEIR models continue to provide valuable public health insights in some scenarios. Using estimated COVID-19 data as of this date, the SEIR model shows that if it were possible to reduce R₀ from 2.5 to 1.25 through social distancing and other measures, the maximum fraction of the population that would become infected at any particular time would drop from 17% to 4%, provided that all of the model assumptions are satisfied. Finally, we compare the classic SIR model with a recent stochastic model with favorable results. Since this comparison underscores the importance of underlying connectivity assumptions, we conclude with Monte-Carlo simulations with specific connectivity that reproduce the classical SIR model with standard incidence.

Global severity maps of ongoing dengue epidemic and COVID-19 pandemic do not overlap. Countries with high dengue endemicity (>1.5 million cases/year) are observably less hit by COVID-19 in terms of infection, transmission and mortality. Based on non-overlap of dengue and COVID-19 severity maps and evidence of SARS-CoV-2 serological cross-reactions with dengue, we wonder whether immediate immunization of susceptible populations in Europe, North America and Asia (China, Iran) with available live-attenuated dengue vaccines, will cue the anti-viral immune response to thwart COVID-19 (viral interference). Risk of developing post-vaccination “Antibody-dependent Enhancement” is low as dengue is not endemic in the aforesaid regions.

The emergence of novel SARS-CoV-2 virus in China in December 2019 has turned into a global pandemic through continued spread beyond borders. This review was aimed to extract up-to-date information on the evolution, transmission, clinical manifestations, diagnosis, treatment and prevention of COVID-19 to fight against this common enemy. PubMed, Scopus and Google Scholar were the sources of literature; whereas CDC, WHO and Worldometer provided updated information. Bats served as the reservoirs of this virus while pangolin is believed as an intermediate host to transmit the virus to humans. Direct human-to-human and indirect transmissions were involved. Major clinical manifestations included fever, cough, fatigue, sputum production and shortness of breath. Chest radiographs mostly showed bilateral ground-glass opacities. Aged patients and patients with comorbidities had higher case fatality ratios. Critical cases were vulnerable to develop pneumonia, multi-organ failure and deaths. Overall situation in China has improved substantially. The European region and region of the Americas were the worst hit out of six WHO global regions. PCR based methods are used for the diagnosis of COVID-19. Severe/critical cases essentially require supportive or intensive cares. Avoiding exposure to COVID-19 is the best way to prevent the disease. Thus, this review provides a snapshot on COVID-19.

The role of the Renin-Angiotensin-Aldosterone System (RAAS) in Corona Virus Disease 2019 (COVID-19) infection has become a controversial topic of discussion. RAAS inhibitors, such as Angiotensin Converting Enzyme (ACE) inhibitors and Angiotensin II receptor blockers (ARBs), which are used to treat cardiovascular diseases, have been implicated in potentially increasing cell surface levels of ACE2. ACE2 is the host receptor for COVID-19 that was discovered in Wuhan, China in December 2019. Since December, COVID-19 has transmitted rapidly across the world and has become a global pandemic. COVID-19 is similar to the Middle East respiratory syndrome coronavirus (MERS-CoV) with the first case reported in Saudi Arabia in September 2012. COVID-19, also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is also similar to SARS-CoV, which first infected humans in the Guangdong province of southern China in 2002, and caused an epidemic between November 2002 and July 2003. Both SARS-CoV and COVID-19 use ACE2 to enter host cells. ACE2 is primarily expressed in the mouth, lung, heart, esophagus, kidney, bladder, and intestines, and is a component of RAAS, which serves to maintain vascular tone and blood volume. Inhibition or activation of other components of RAAS has been shown to directly increase or decrease the expression and/or activity of ACE2. Furthermore, RAAS-targeting therapeutics, such as ACE inhibitors and ARBs, have also been shown to regulate the expression and/or activity of ACE2, albeit in animal models. Although these changes in ACE2 have been demonstrated only in animal models, there is no evidence that administration of RAAS-targeting therapeutics to humans for the treatment of hypertension, diabetes, and other cardiovascular diseases (e.g., myocardial infarction and heart failure) causes changes in ACE2 expression. Nor is there clinical evidence that RAAS-targeting therapeutics augment COVID-19 infection, morbidity, or mortality. However, clinical evidence does suggest that ACE2 expression may protect against respiratory distress caused by a variety of noxious agents. This review attempts to provide a balanced overview of the potential role of RAAS in regulating ACE2, and the role of ACE2 during COVID-19 infection. Evidence is provided to show that the expression of ACE2 may mediate both positive and negative outcomes, depending on the timing of ACE2 expression.

Background: Coronavirus disease 2019 (COVID-19) has emerged as a global threat to human health and disease risk increases with advancing age. The regulation of the ACE2 gene that codes for COVID-19 host receptor ACE2 has been shown to be under epigenetic regulation. Here, we examined whether intensive DNA methylation profiling of the ACE2 gene differed by human host tissue and cell type, gender, and age. Results: Accessing four public datasets, we observed unique human cell-type-specific ACE2 DNA methylation patterns. In human lung tissues, gender differences in DNA methylation at 2 sites related to the ACE2 gene were identified. Further, in freshly isolated airway epithelial cells, DNA methylation near the transcription start site of the ACE2 gene associated with biological age. Conclusion: Epigenetic profiling of host tissue may permit discovery of age and gender-related potential risk factors for COVID-19. How perturbations in ACE2 methylation relate to clinical severity across the ages and gender needs to be determined to guide screening tools and potential epigenetic modification targeting to alleviate COVID-19 morbidity in the elderly.

There is a long trail of research studies testing the in vitro and in vivo efficacy of chloroquine and its derivatives in treating and preventing infection by various coronavirus species. More recent findings have highlighted the possibility of treating patients infected with the 2019 novel coronavirus, SARS-CoV-2. This review describes the mechanism of coronavirus infection, the mechanism of action of chloroquine, and summarizes the available literature highlighting the efficacy of chloroquine as an anti-coronavirus agent. These findings should encourage the wider scientific community to conduct thorough research on the possible efficacy of chloroquine and its derivatives in treating and preventing SARS-CoV-2 infection.

SARS-CoV-2 is the betacoronavirus responsible for the COVID-19 pandemic. It was listed as a potential global health threat by WHO due to high mortality, high basic reproduction number and lack of clinically approved drugs and vaccines for COVID-19. The genomic sequence of the virus responsible for COVID-19, as well as the experimentally determined three dimensional structure of the Main protease (Mpro) are available. The reported structure of the target Mpro was utilized in this study to identify potential drugs for COVID-19 using molecular docking based virtual screening of all approved drugs. The results of this study confirm preliminary reports that some of the drugs approved for treatment of other viral infections have the potential for treatment of COVID-19. Selected antiviral drugs, approved for human therapeutic applications, were ranked for potential effectiveness against COVID-19, based on predicted binding energy to the target Mpro of SARS-CoV-2, and novel candidates for drug repurposing were identified in this study. In addition, potential mechanisms for beneficial off target effects of some drugs in clinical trials were identified by using molecular docking.

This study explored the effectiveness of a virtual music therapy program, based on positive psychotherapy principles, for college students during the COVID-19 pandemic. Twenty-four undergraduate students with partial PTSD were initially assigned to either an experimental group or a control group, with 11 participants in each group by the study's end. The experimental group underwent 15 video sessions of the therapy program, completing one session per weekday over three weeks. The program involved worksheets targeting goals aligned with positive psychology, such as positive affect, life meaning, personal strengths, gratitude, hope, and happiness. Activities included writing music autobiographies, creating and analyzing song lyrics, and exploring various music pieces. The effectiveness of the intervention was measured using the 21-item Depression Anxiety Stress Scale and the Korean Version of Positive Psychological Capital (K-PPC) before, immediately after, and three weeks post-program. The experimental group showed significant improvements in stress, anxiety, depression, self-efficacy, resilience, and the K-PPC total score compared to the control group. These improvements were maintained at the three-week follow-up. The findings suggest that positive psychology-based virtual music therapy can significantly enhance the mental health of highly stressed college students, especially during challenging times like the COVID-19 pandemic.

The aim of this article is to present the course of the COVID-19 pandemic in Poland in 2020-2022, the formation of ad hoc health and anti-crisis policies, an assessment of crisis management and the perceived impact of the pandemic and anti-crisis measures.The paper draws on literature, official reports on the pandemic, data from Eurostat and other information from state institutions and public organisations.Particular attention was paid to the analysis and evaluation of the objectives, instruments and effects of the policies pursued by the state in a coordinated manner, i.e. the anti-pandemic policy and the anti-crisis policy. The anti-pandemic policy in Poland has failed to protect the country from significant personal losses and negative impacts on the health of the population and demographic processes.The anti-crisis policy of the state carried out with the mobilisation of businesses and disciplined society, in the form of anti-crisis shields supplemented and adjusted on an ongoing basis, allowed Poland to avoid a deep crisis and economic recession. Attention was drawn to the need to coordinate the management of health and economic crises nationally and internationally, and to the need to have a medium-term anti-crisis state strategy and a system for the early detection of crisis symptoms.

Objective: The COVID-19 pandemic inferred on neuro-oncological patients (PTS) and the caregivers regarding tumor care and emotional functioning. This study aimed to understand how COVID-19 affects their psychological state and relations between PTS and health personnel in neuro-oncology. Methods: A cross-sectional study on neuro-oncological PTS and their caregivers. Results: A total of 162 PTS and 66 caregivers completed the questionnaire. The 37.5% of PTS perceived greater risk of contracting the COVID-19 compared to the general population. On the 0-10 scale, PTS tumor-related anxiety score was 5.8 and COVID-related 4.6. The caregivers reported 7.7 and 5.5 respectively. The QoL was described at least as good in 75% of both PTS and caregivers; the caregivers’ care burden increased in 22.7% during the pandemic, with no correlation with QoL. Future perception often changed both in PTS and in the caregivers. Cancer treatment schedule was changed in 18.5%, including for PTS decision. However, the 93.5% of PTS was satisfied with the overall care. Conclusion: A considerable proportion of PTS and caregivers still perceived the tumor disease as more burdensome than the pandemic, and perceived their future as more uncertain. Such data rinforce the need to build a proficient alliance between PTS and health personnel.

Globally, workplace stress and anxiety are at an all-time high, with 42% of employees experiencing daily work-related stress and anxiety. Drawing from workplace anxiety (WA) theory (Cheng & McCarthy, 2018), we advance a model that considers four job demands – role ambiguity, work overload, job insecurity, and work-home conflict – as sources of daily WA, and in turn the downstream effects of WA on psychological capital (PsyCap). Our model posits gender as a moderator of the association between job demands and WA, and digital technology characteristics as moderators of the association between WA and PsyCap. We tested our predictions on a sample of 162 South African employees. Consistent with our predictions, we found positive effects of job demands on WA, with the relationship being stronger for females. Contrary to expectations, we found positive effects of WA on PsyCap, suggesting an adaptive function of WA. Perceived ease of use of digital technology moderated the association between WA and PsyCap, such that the association was strong at higher levels of perceived ease of use. This research advances our understanding of the sources of WA, the adaptive function of WA, and predictors of PsyCap. Broadly, our study adds to understanding emotions’ impact on workplace behavior.

Many metabolic processes at the molecular level support both viral attack strategies and human defenses during Covid-19. This knowledge is of vital importance in the design of antiviral drugs. In this study, we extracted 18 articles (2021-2023) from PubMed reporting the discovery of hub-nodes specific for the liver during covid-19, identifying 142 hub-nodes. They are highly connected proteins from which to get deep functional information on viral strategies when used as functional seeds. Therefore, we evaluated the functional and structural significance of each of them to endorse their reliable use as seeds. After filtering, the remaining 111 hubs were used to get by STRING an enriched interactome of 1111 nodes (13,494 interactions). It shows the viral strategy in the liver is to attack the entire cytoplasmic translational system, including ribosomes, to take control of protein bio-synthesis. We used the SARS2-Human-Proteome Interaction Database (33,791 interactions), de-signed by us with BioGRID data to implement a reverse-engineering process that identified human proteins actively interacting with viral proteins. The results show 57% of human liver proteins di-rectly involved in Covid, a strong impairment of the ribosome and spliceosome, an antiviral defense mechanism against cellular stress of the p53 system, and, surprisingly, a viral capacity for multiple protein attacks against single human proteins that reveal underlying evolutionary-topological molecular mechanisms. Viral behavior over time suggests different molecular strategies for different organs.

This study aims to understand the changes in management trends among global companies before and after the onset of COVID-19. To achieve this, we employed keyword and topic modeling to analyze 420 CEO messages extracted from the reports of the Fortune Global 100 largest companies. The analysis revealed a noteworthy prevalence of keywords associated with shared culture, such as face-to-face interactions and cooperation, during the initial period. In the subsequent period, we observed a higher frequency of keywords related to community-centeredness and digital trans-formation, including employee health and well-being, inequality reduction, and sustainable cities. Furthermore, we identified common topics before and after COVID-19, such as risk management and competitive advantage. However, the topics that exhibited variation were the significance of corporate leadership and the evolution of digital technologies. This study is significant in that it enables us to analyze CEO messages and deduce the trajectory of corporate management post-COVID-19.

The work presented in this paper makes multiple scientific contributions related to the investigation of the global fear associated with COVID-19 by performing a comprehensive analysis of a dataset comprising survey responses of participants from 40 countries. First, the results of subjectivity analysis of responses where participants indicated their biggest concern related to COVID-19 showed that the average subjectivity in responses by the age group of 41-50 decreased from April 2020 to June 2020, the average subjectivity in responses by the age group of 71-80 drastically increased from May 2020, and the age group of 11-20 indicated the least level of subjectivity in their responses between June 2020 to August 2020. Second, subjectivity analysis also revealed the percentage of highly opinionated, neutral opinionated, and least opinionated responses per age-group where the analyzed age groups were 11-20, 21-30, 31-40, 41-50, 51-60, 61-70, 71-80, and 81-90. For instance, the percentage of highly opinionated, neutral opinionated, and least opinionated responses by the age group of 11-20 were 17.92%, 16.24%, and 65.84%, respectively. Third, data analysis of responses from different age groups showed that the highest percentage of responses indicating that they were very worried about COVID-19 came from individuals in the age group of 21-30. Fourth, data analysis of the survey responses also revealed that in the context of taking precautions to prevent contracting COVID-19, the percentage of individuals in the age group of 31-40 taking precautions was higher as compared to the percentages of individuals from the age groups of 41-50, 51-60, 61-70, 71-80, and 81-90. Finally, a deep learning model was developed to detect if the survey respondents were seeing or planning to see a psychologist or psychiatrist for any mental health issues related to COVID-19. The deep learning model used the responses to multiple questions in the context of fear, preparedness, and response related to COVID-19 from the dataset and achieved an overall performance accuracy of 91.62% after 500 epochs.

PURPOSE: Our research interrogates Professor Peter Doherty’s warning to Australians in April 2020 that ‘COVID-19 is just as lethal as the Spanish flu’. METHODS: We identified the epicentres of both pandemics, namely metropolitan Sydney in 1919 and metropolitan Melbourne in 2020. Using original sources, we compared the lethality of COVID-19 in these two cities. Lethality was measured by the number and rate of hospitalisations and deaths per 100,000 of population. Using these two measures, we diagnosed the waves of infection, their severity at various points in time and the cumulative impact of the viruses by the end of our in-depth study period, i.e. 30 September in 1919 and 2020. RESULTS: Spanish Flu in 1919 was more than 30 times more lethal than COVID-19 in 2020. The hospital admission and death rates of COVID-19 in Melbourne in 2020 constituted a small fraction of the devastation wrought by the Spanish Flu in Sydney in 1919. The patterns and lethality of the pandemic waves were also strikingly different. DISCUSSION AND CONCLUSION: Both pandemics broke out with the arrival of unknown pathogens against which vaccines and antivirals did not exist. Professor Doherty’s warning was perhaps taken seriously and that partly explains the findings of this study. Containing infection in 1919 and 2020 threw the burden on nonpharmaceutical interventions (NPIs) such as ‘protective sequestration’ (quarantine), contact tracing, lockdowns and masks. We discuss the effectiveness of these. Despite the failures of genomic analysis and the weaknesses of the contact tracing system due to mismanagement, it was persistent and detailed contact tracing that provided the best explanation for why NPIs in 2020 were more effective than in 1919 and therefore contributed to the lower lethality of the COVID-19 pandemic in its first year.

More than 13.5 billion COVID-19 vaccine doses have so far been delivered between 2021 and 2023 through a mix of delivery platforms, with mass vaccination campaigns being the main approach. In 2022, with the most likely scenario of continued circulation of SARS-CoV-2 and the need for periodic booster doses, there was a need for countries to plan for more sustainable approaches to provide COVID-19 vaccination. In this context of uncertainty, a global tool for integrating COVID-19 vaccines into immunization programmes and primary health care was published jointly by WHO and UNICEF to respond to country needs. The guidance leveraged existing health system frameworks, proposed four steps for the COVID-19 integration journey, and identified investment areas. The development process maximized robust global stakeholder and country engagement, and the timeframe was aligned with donor funding windows to support the integration of COVID-19 vaccination. The rapid dissemination of guidance allowed its use by countries to ascertain their readiness for integrating COVID-19 vaccination and inform the development of national plans and funding applications. While progress has been made in specific areas (e.g., optimizing cold chain and logistics leveraging COVID-19 vaccination), in the context of decreasing demand for COVID-19 vaccines, reaching adult COVID-19 vaccine high-priority-use groups and engaging and coordinating with other health programmes (beyond immunization) remains a challenge. We share the learning that despite the uncertainties of a pandemic, guidance documents can be developed and used within a short timeframe. Working in partnership with stakeholders beyond immunization towards a common objective is powerful and can allow progress to be made on integrating health services and preparing better for future pandemics.

Post-viral fatigue syndrome (PVFS) encompasses a wide range of complex neuroimmune disorders of unknown cause characterized by disabling post-exertional fatigue, myalgia and joint pain, cognitive impairments, unrefreshing sleep, autonomic dysfunction, and neuropsychiatric symptoms. It includes myalgic encephalomyelitis, also known as chronic fatigue syndrome (ME/CFS), fibromyalgia (FM), and more recently post-COVID-19 condition (Long COVID). To date, there are no definitive clinical case criteria and no FDA-approved pharmacological therapies for PVFS. Given the current lack of effective treatments, there is a need to develop novel therapeutic strategies for these disorders. Mitochondria, the cellular organelles responsible for tissue energy production, have recently garnered attention in research into PVFS due to their crucial role in cellular bioenergetic metabolism in these conditions. Accumulating literature has identified a link between mitochondrial dysfunction and low-grade systemic inflammation in ME/CFS, FM, and Long COVID. To address this issue, this article aimed to critically review the evidence relating to mitochondrial dysfunction in the pathogenesis of these disorders; in particular, to evaluate the effectiveness of coenzyme Q10 supplementation on chronic fatigue and pain symptoms as a novel therapeutic strategy for the treatment of PVFS.

Patients with COVID-19 have coagulation and platelet disorders, with platelet’s alterations and thrombocytopenia representing negative prognostic parameters, being associated with severe forms of the disease, and increase lethality. Methods: Aim of this study was to study expression of platelet glycoprotein IIIa (CD61), playing a critical role in platelet aggregation, together with TRL-2 as a marker of innate immune activation Results: a total of 25 patients were investigated, with the majority (24/25, 96%) having co-morbidities and dying from a fatal form of SARS-CoV-2(+) infection (COVID-19 +), with 13 men and 12 females ranging in age from 45 to 80 years. When compared to a control group of SARS CoV-2 (-) negative lungs (COVID-19 -), TLR-2 expression was up-regulated in a subset of patients with deadly COVID-19 fatal lung illness. The proportion of Spike-1 (+) patients found by PCR and ISH correlates to the proportion of Spike-S1 positive cases as detected by digital pathology examination. Furthermore, CD61 expression was considerably higher in the lungs of dead patients. In conclusion, we demonstrate that innate immune prolonged hyperactivation is related to platelet/megakaryocytes over-expression in the lung. Conclusions: microthrombosis in deadly COVID-19+ lung disease is associated with an increase in the number of CD61+ platelets and megakaryocytes in the pulmonary interstitium as well as their functional activation; this phenomenon is associated with increased expression of innate immunity TLR2+ cells, which binds the SARS-CoV-2 E protein, and significantly with the persistence of the Spike-S1 viral sequence.

A simple bounded stochastic motion is employed for modelling equity price dynamics under shocks, where the prices are constrained to lie between two positive bounds. While the stochastic process has an inaccessible boundary, the other boundary is quasi-bounded, implying that the boundary can be breached if the probability leakage condition is met. The quasi-boundedness of the process at the boundary can thus provide an indicator of possible risk of equities under price shocks. Empirical calibration of model parameters of the proposed process for equities can be performed easily due to the availability of an analytically tractable probability density function which generates fat-tailed distributions consistent with empirical observations. The volatility and mean-reversion of the S&P500 dynamics calibrated by the process is positively and negatively co-integrated respectively with the VIX index representing the level of market distress. The process captures the high likelihood of Hertz’s default about two months earlier, using only information until that point, and before the firm filed for Chapter 11 bankruptcy in May 2020 as a result of the Covid-19 pandemic. Empirical calibration of the process for GameStop’s stock price shows that the short squeeze of the stock occurred when the condition for breaching an upper boundary was met on 14 January 2021, i.e., about two weeks before major short sellers closed out their positions with significant losses. The trading volume of the stock was positively co-integrated with the probability leakage ratio.

Coronavirus disease 2019 (COVID-19) affected not only individuals but also families. The purpose of this study was to clarify the temporal changes in the impact of the COVID-19 pandemic on entire families with older adults susceptible to infection living on small islands in Japan over the duration of the pandemic. Family ethnographic research was conducted from 2021 to 2023, using the Concentric Sphere Family Environment Theory as the theoretical framework. Formal interviews were conducted with 20 families. In addition, data from informal interviews, participant observation and other sources were compiled into field notes. All data on the impact on the entire family were extracted and content analysis was conducted. Five categories and a total of 85 subcategories were extracted. The results show that COVID-19 exerted not only negative but also positive impacts on the entire family, and their temporal changes are clarified. The impact on families is believed to have been influenced by the family external environment, such as increases and decreases of infection cases or events that occurred outside the family. The knowledge acquired from these studies will help healthcare professionals in providing appropriate family support.

The impact of the COVID-19 pandemic and the quarantine measures on children and adolescents’ hospitalization psychiatric has been poorly studied, especially in Italy, the first European country to adopt social restrictions. To fill this gap, this retrospective study examined changes in admissions to our child and adolescent psychiatry ward from the emergency department during the two COVID-19 quarantine periods in Italy (March to June 2020; October 2020 to January 2021) compared with two reference periods (defined as 12 months prior to the respective quarantine periods). Specifically, we examined data on the number of inpatients and the distribution of psychopathological disorders (i.e., psychosis, mood disorder) and self-injurious behaviors. The results revealed significantly fewer admissions during the first quarantine period relative to the first reference period and, conversely, significantly more admissions during the second quarantine period relative to the second reference period. Of note, the results showed an increased frequency of mood disorders, non-suicidal self-injurious behaviors and suicidal ideation during the quarantine periods, compared to the reference periods. The findings underline the need to focus on the psychopathological profile of children and adolescents with patient-tailored therapeutic interventions and suggest the importance of developing psychological healthcare services for future emergency periods..

A recent study has suggested that the age profiles for deaths due to COVID-19 variants differs between variants and shows male/female specificity. This study demonstrates the age and sex dependency is common among human pathogens. The often-reported higher susceptibility to infections among the young and elderly is true in general but does not apply to individual pathogens. Even among different types of pneumonia there are subtle differences in the age profile. The gender ratio between pathogens likewise shows wide variation from as low as 10% female admissions for leptospirosis to around 90% for gonococcal admissions. The observed age/sex variation observed for mortality due to COVID-19 variants is an expression of a far wider phenomenon with implications to the age/sex response to vaccines. We propose that such differences are likely to be controlled by small noncoding RNAs which act as potent regulators of gene expression leading to altered cell morphology, metabolism, immune function, and response to vaccines.

Listerias of the phylogenetic lineage II (PLII) are common in the European environment, and are hypovirulent. Despite this, they caused more than a third of sporadic cases of listeriosis, and multi-country foodborne outbreaks. L. monocytogenes ST37 is one of them. During the COVID-19 pandemic ST37 appeared in the clinical cases and ranked second in occurrence among food isolates in the Moscow region. The aim of this study was to describe the genomic features of ST37 isolates from different sources. All clinical cases of ST37 were in the cohort of male patients (age, 48-81 years) with meningitis-septicemia manifestation, and COVID-19 or Influenza in the anamnesis. The core genomes of the fish isolates were closely related. The clinical and meat isolates revealed a large diversity. Prophages (2-4/genome) were the source of the unique genes. Two clinical isolates displayed the pseudolysogeny, and excided prophages were A006-like. Absence of the plasmids, the assortment of virulence factors and resistance determinants in chromosome corresponded to the hypovirulent characteristics. However, all clinical isolates caused severe disease with deaths in four cases. Thus, these studies allow us to speculate that a previous viral infection increases a human susceptibility to listeriosis.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) often causes severe viral pneumonia, especially among older individuals and those with underlying health conditions. The C57BL/6 mouse is widely used to develop mouse models of obesity, diabetes, hypertension, and immune disorders, conditions that are associated with increased risk of severe COVID-19. Although many studies using these mouse models have examined the pathogenicity of SARS-CoV-2, COVID-19 pathogenesis remains poorly understood. In vivo imaging analysis using two-photon excitation microscopy is useful for elucidating the pathology of COVID-19, providing pathological insights that are not available from conventional histological analysis. However, there is no reporter SARS-CoV-2 that demonstrates pathogenicity in C57BL/6 mice and emits sufficient light intensity for two-photon in vivo imaging. Here, we generated SARS-CoV-2 expressing the fluorescent protein Venus to facilitate in vivo pathological studies using C57BL/6 mouse models. We generated a mouse-adapted strain of SARS-CoV-2, by performing sequential lung-to-lung passages in BALB/c mice, followed by in C57BL/6 mice. We observed that the C57BL/6-adapted SARS-CoV-2 (named MASCV2-p25) replicated efficiently in the lungs of C57BL/6 mice, causing fatal pneumonia. Histopathologic analysis revealed severe inflammation and infiltration of immune cells in the lungs of MASCV2-p25-infected C57BL/6J mice, not unlike that observed in COVID-19 patients with severe pneumonia. Subsequently, we generated a mouse-adapted reporter SARS-CoV-2 (named MASCV-Venus-p9) by inserting the fluorescent gene Venus into MASCV2-p25, and sequential lung-to-lung passages in C57BL/6 mice. C57BL/6 mice infected with MASCV2-Venus-p9 exhibited severe pneumonia similar to that induced by MASCV2-p25. In addition, two-photon excitation microscopy of the lungs of the infected C57BL/6J mice showed that the infected cells emitted sufficient levels of fluorescence for easy observation. These findings suggest that MASCV2-Venus-p9 will be useful for two photon in vivo imaging studies of the pathogenesis of severe COVID-19 and for the development of therapeutic agents for severe pneumonia.

In post-COVID-19 syndrome, clinical presentation of the nerve fiber dysfunction plays an important role. The possibility of autoantigen cross-mimicry of coronavirus infection and the peripheral nervous system need to be investigated. The bioinformatic analysis was applied to search for possible common protein sequences located in the immunological epitopes. Among the autoantigens of the human nervous system, fibroblast growth factor receptor protein 3, myelin protein P0, myelin protein P2, sodium channel protein type 9, alpha protein subunit, plexin-D1 protein and ubiquitin-carboxyl-terminal hydrolase protein of the L1 isoenzyme were selected. The “Alignmentaj” program was created. The UniProt database, Protein Data Bank and AlphaFold databases were used. The analysis of protein sequence similarities of spike glycoproteins in human coronaviruses revealed common pentapeptides of the MERS-CoV-2 virus with the fibroblast growth factor receptor 3 and myelin protein P2. Among seasonal coronaviruses, common peptide sequences were identified in HCoV-HKU-1 virus with sodium channel protein type 9 subunit alpha and Plexin-D1, HCoV-OС43 with Plexin-D1, as well as HCoV-NL63 with Plexin-D1 and Ubiquitin carboxyl-terminal hydrolase isozyme L1. The data obtained make it possible to identify new potential targets for the development of autoimmune reactions that occur against the background of the activity of highly pathogenic and seasonal coronaviruses.

To ensure high-quality care, operationalize resilience and fill the knowledge gap regarding how to improve the prerequisites for resilient performance, it is necessary to understand how adaptive capacity unfolds in practice. Coronavirus 2019 stress-tested complex healthcare systems, and intensive care was driven to an unprecedented escalation. The main aim of this research was to explain the escalation process of intensive care from a microlevel perspective, including expressions of resilient performance, intervening conditions at the micro-meso-macrolevels and short- and long-term consequences. A secondary aim was to provide clinical recommendations regarding how to optimize the prerequisites for resilient performance in intensive care. A grounded theory methodology was used. First-person stories from different healthcare professionals (n70) in two Swedish regions were analyzed using the constant comparative method. A novel conceptual model of the escalation process of intensive care emerged, and 41 clinical recommendations concerning the optimal prerequisites for resilient performance were identified. Escalation was conceptualized as a transition from threatening chaos to temporary order through a complex process of adaptation. To prepare for the future, the components space, stuff, staff, system and science with associated continuity plans must be implemented, anchored and communicated to actors at all levels of the system.

This study examines the psychological repercussions of the COVID-19 pandemic on a medical team in an Israeli general hospital. The research explores the professional quality of life, burnout symptoms, secondary traumatic stress, and mindfulness among team members across three distinct phases of the pandemic. Analysis was conducted for different subgroups based on job roles and seniority, allowing for an evaluation of the phase-specific effects on the ProQOL (Professional Quality of Life) and mindfulness. Results align with established crisis trajectories, encompassing honeymoon/heroic phases, inventory, disillusionment, and recovery. The findings demonstrate a negative correlation between compassion satisfaction and burnout, as well as between mindfulness and burnout/secondary traumatic stress. Remarkably, male doctors exhibit a more pronounced negative impact on mindfulness compared to their female counterparts, primarily comprising healthcare workers. Temporal analysis reveals significant differences in compassion satisfaction and mindfulness, with baseline measurements being notably higher. Furthermore, the study sheds light on the vulnerability of male doctors, emphasizing the crucial role of hospital management in conveying the message and implementing effective measures to support professional quality of life. These findings underscore the necessity of prioritizing the well-being of medical professionals, particularly male doctors who face unique challenges in seeking assistance.

Not in the history of transmissible illnesses has there been an infection as strongly associated with acute cerebrovascular disease as the novel human coronavirus, SARS-CoV-2. While the risk of stroke has known associations with other viral infections, such as influenza and human immunodeficiency virus, the risk of ischemic and hemorrhagic stroke related to SARS-CoV-2 is unprecedented. Furthermore, the coronavirus disease 2019 (COVID-19) pandemic has so profoundly impacted psychosocial behaviors and modern medical care that we have witnessed shifts in epidemiology and have adapted our treatment practices to reduce transmission, address delayed diagnoses, and mitigate gaps in health care. In this narrative review, we summarize the history and impact of the COVID-19 pandemic on cerebrovascular disease, and lessons learned regarding the management of patients as we endure this period of human history.

Public Health Officers' (PHO) experiences in reaction to the COVID-19 pandemic can be based on whether the PHO is passive or active. Therefore, the study’s objectives are to identify the types of experiences and analyse the predictors of proactive practical experiences in solving COVID-19 among PHOs in the upper southern region of Thailand. Methods: An explanatory mixed-methods approach was used to collect data, through questionnaires and online in-depth interviews. The study was conducted from August 4, 2020, to August 3, 2021. Results: The results included 60 PHOs from 60 PCUs in 6 provinces, with 41 (68.3%) females and an average age of 35.57 years (SD = 11.61). The PHOs’ knowledge, understanding, and participation experience aspects were mostly proactive rather than passive. Factors that significantly predicted proactive practical experiences included sex (ORadj = 1.52, 95% CI = 1.04–2.21), age (ORadj = 1.69, 95% CI = 1.16-2.48), married status (ORadj = 1.69, 95% CI = 1.16-2.48), education level (ORadj = 1.50, 95% CI = 1.02–2.20), and position for work (ORadj = 1.69, 95% CI = 1.16-2.48). Conclusions: PHOs’ knowledge, understanding, opinion, and participation experiences were significant predictors of practical experience. Primary health care systems should promote proactive experiences in all four aspects to increase proactive practical experiences.

During the infection by SARS-CoV-2, the virus is changing infected host cell into its own factory producing new viral particles. As infection progresses, infected cell undergoes many changes in various pathways. One of the events caused by changes is cytokine storm, which leads to the severe symptoms. In this study, we investigated transcriptomic changes caused by COVID-19 disease using RNA-seq data obtained from COVID-19-positive patients and COVID-19-negative donors. RNA-seq data were collected for the purpose of identification of potential biomarkers associated with a different course of the disease. Here, the first datasets of 96 samples were analyzed to validate the methods. The aim of this publication is to report pilot results. In search of potential biomarkers associated with different disease severity, we performed differential expression analysis of human transcriptome, focusing on COVID-19 positivity and symptom severity. Since we detected plenty of potential biomarkers, we performed KEGG enrichment analysis to get better view of altered pathways. Results show, that affected were pathways related to immune processes and response to infection, also multiple signaling pathways, while most of them were also reported to be influenced by SARS-CoV-2 infection in previous studies.

During the COVID-19 pandemic, online media were the most widely used source of scientific information. Often, they are also the only ones on science-related topics. Research has shown that much of the information available on the Internet about the health crisis lacked scientific rigor and that misinformation about health issues can pose a threat to public health. In turn, millions of Catholics were found to be demonstrating against vaccination against COVID-19 based on "false" and misleading religious arguments. This research analyses publications about the vaccine in Catholic online media with the aim of understanding the presence of information (and misinformation) in this community. An algorithm designed for each media outlet collected COVID-19 vaccine-related publications from 109 Catholic media outlets in five languages. In total, 970 publications were analysed for journalistic genres, types of headlines and sources of information. The results show that most publications are informative and most of their headlines are neutral. However, opinion articles have mostly negative headlines. Also, a higher percentage of the opinion authors come from the religious sphere and most of the sources cited are religious. Finally, 35% of the publications relate the vaccine to the framing issue of abortion.

Building on the job demands-resources (JD-R) and the allostatic load (AL) models, in this study we investigated the role of smart working (SW) in the longitudinal association between workload/job autonomy (JA) and a possible biomarker of work-related stress (WRS) in the hair, namely the cortisol to dehydroepiandrosterone sulphate (DHEA(S)) ratio, during the COVID-19 pandemic. Overall, 124 workers completed a self-report questionnaire (i.e., psychological data) at Time 1 (T1) and collected a strand of hair (i.e., biological data) three months later (Time 2, T2). Results from moderated multiple regression analysis showed that smart working at T1 was negatively associated with hair cortisol/DHEA(S) ratio at T2. Additionally, the interaction between workload and SW was significant, with workload at T1 being positively associated with hair cortisol/DHEA(S) ratio at T2 among smart workers. Overall, this study indicates that SW can be conceived as a double-edged sword, with both positive and negative consequences on employee well-being. Furthermore, our findings suggest that hair cortisol/DHEA(S) ratio is a promising biomarker of WRS. Practical implications that organizations and practitioners can adopt to promote organizational well-being are discussed.

COVID-19 pandemic-related pressures on primary care may have driven inappropriate continuation of antibiotic prescriptions. Yet prescribing modality (repeat/non-repeat) has not previously been investigated in a pandemic context. Using the OpenSAFELY-TPP analytics platform, we analysed repeat/non-repeat prescribing frequency in monthly patient cohorts between Jan 2020–2022. In-depth analysis was conducted on Jan 2020 (“pre-pandemic”) and Jan 2021 (“pandemic”) cohorts. Per-patient prescribing and clinical conditions were determined by searching primary care record data using clinical code lists. Repeat prescribing was defined as >=3 prescriptions in a 6 month lookback period. Associations between demographics (e.g. age, sex, geography) and repeat/non-repeat prescribing were explored using unadjusted risk ratios. Antibiotic prescribing declined from May 2020; non-repeat prescribing declined more strongly than repeat prescribing (maximum declines -26% vs -11%, respectively). In the pandemic cohort, older patients were at higher risk of prescribing (especially repeat prescribing). The most common clinical conditions for repeat prescribing were COPD comorbidity and urinary tract infection. Comorbidities were more common among repeat vs non-repeat prescribed patients. In the pandemic cohort, vs pre-pandemic, repeat and non-repeat prescribing for comorbidities generally declined less compared with shorter-term conditions (infections, including COPD exacerbation/lower respiratory tract infection). Our findings inform ongoing development of stewardship interventions in England..

Childhood hygiene education has resulted in individuals engaging in hand washing and mask wearing to cope with COVID-19. Individuals can form sustainable development-related habits through childhood education.

This study evaluated the anti-inflammatory effects, protection of gut barrier integrity, and stimulation of phagocytosis in peripheral cells of a nutritional supplement based on a synergistic combination of yeast-based ingredients with a unique 1,3/1,6-glucan complex and a consortium of postbiotic Saccharomyces cerevisiae rich in selenium and zinc. The anti-inflammatory effect in Caco-2 cells in the presence and absence of a pro-inflammatory challenge (tumour necrosis factor alpha [TNF-α]/interferon gamma [IFN-ɣ]) showed statistically significant reductions of IFN-ɣ induced protein-10 (IP-10), and monocyte chemoattractant protein-1 (MCP-1) levels vs. controls (p < 0.001). Disruption of the gut integrity in the presence or absence of Escherichia coli (ETEC H10407) showed transepithelial electrical resistance (TEER) values higher in the ABB C1® group after 6 hours of testing. Spontaneous build-up of the gut epithelium monolayer over 22 days was also greater in the ABB C1® condition vs. a negative control. ABB C1® showed a significantly higher capacity to stimulate phagocytosis as compared with controls of algae β-1,3-glucan and yeast β-1,3/1,6 glucan (p < 0.001). This study supports the mechanism of action by which ABB C1® may improve the immune response and be useful to prevent infection and allergy in clinical practice.

The article describes how atherosclerosis and coronavirus disease 19 (COVID-19) may affect each other. The features of this comorbid pathogenesis at various levels (vascular, cellular and molecular) are considered. A bidirectional influence of these conditions is described: the presence of cardiovascular diseases affects different individual susceptibility to viral infection. In turn, SARS-CoV-2 can have a negative effect on the endothelium and cardiomyocytes, causing blood clotting, secretion of pro-inflammatory cytokines, and thus exacerbating the development of atherosclerosis. In addition to the established entry into cells via ACE2 принимая во внимание его влияние на, other mechanisms of SARS-CoV-2 entry are currently under investigation, for example, through CD147. Pathogenesis of comorbidity can be determined by the influence of the virus on various links which are meaningful for atherogenesis: generation of oxidized forms of LDL, launch of a cytokine storm, damage to the endothelial glycocalyx, and mitochondrial injury. The transformation of a stable plaque into an unstable one plays an important role in the pathogenesis of atherosclerosis complications and can be triggered by COVID-19. The impact of SARS-CoV-2 on large vessels such as aorta is more complex than previously thought considering its impact on vasa vasorum. Current information on the mutual influence of the medicines used in the treatment of atherosclerosis and acute COVID-19 is briefly summarized

RNA viruses exhibit a great tendency to mutate. Starting from 2019, the wild type that was labeled Hu-1 has during the last 3 years evolved to produce several dozen new variants, as a consequence of mutations. Mutations cause changes in empirical formulas of new virus strains, which lead to change in thermodynamic properties of biosynthesis and binding. These changes cause changes in the rate of reactions of binding of virus antigen to the host cell receptor and the rate of virus multiplication in the host cell. Changes in thermodynamic and kinetic parameters lead to changes in biological parameters of infectivity and pathogenicity. SARS-CoV-2 has starting from in 2019, until today, evolved towards increase in infectivity and maintaining constant pathogenicity, or for some variants a slight decrease in pathogenicity. In the case of Omicron BQ.1, BQ.1.1, XBB and XBB.1 variants pathogenicity is identical as in the Omicron BA.2.75 variant. On the other hand, infectivity of the Omicron BQ.1, BQ.1.1, XBB and XBB.1 variants is greater than those of previous variants. This will most likely result in the phenomenon of asymmetric coinfection, that is circulation of several variants in the population, some being dominant.

Biothermodynamics of viruses is among the youngest, but rapidly developing scientific disciplines. During the COVID-19 pandemic, it has closely followed the results published by molecular biologists. Empirical formulas were published for 50 viruses and thermodynamic properties for multiple viruses and virus variants, including all variants of concern of SARS-CoV-2, SARS-CoV, MERS-COV, Ebola virus, Vaccinia and Monkeypox virus. A review of development of biothermodynamics of viruses during the last several decades and intense development during the last 3 years has been described in this paper.

Burnout, a negative job-related psychological state particularly associated with the health professions, equates to a loss of valuable research in healthcare researchers. Team mindfulness, recognized to enhance personal fulfilment through work engagement, represents one important aspect found effective in reducing burnout. In a specific series of diverse membership academic meetings intended to reduce research burnout—employing writing prompts, doodling and continuous developmental feedback to do so—team mindfulness was demonstrated when conducted in person. Therefore, determining if team mindfulness is evident when holding such academic meetings online is relevant. When COVID-19 limitations required moving these academic meetings online, it was previously noted and reported that team mindfulness was affected in no longer being present during the first eighteen months of restrictions. To discover if this result persisted, question asking, doodles submitted and feedback responses were analyzed of the following year’s academic meetings for the same group, both quantitively and qualitatively. In finding the team mindfulness of these meetings additionally compromised the second full year, online practices actually found successful at creating and supporting team mindfulness—online games—are identified and considered. Concluding implications are noted and recommendations made regarding team mindfulness in reducing burnout for future online academic meetings.

In this empirical article, we argue that, while emergency remote teaching (ERT) may have achieved its goal of saving the academic years during the COVID-19 pandemic, it also constructed unintended pedagogical consequences that were possibly overlooked at the time of advocating it. The research question that the article attempted to answer is, what unintended pedagogical consequences did students and lecturers suffer because of the move to ERT at rural-based universities (RBUs) in South Africa? Drawing on students' and lecturers’ lived experiences of ERT, this article foregrounds unintended pedagogical consequences that arose at one RBU in South Africa during the transition from face-to-face teaching to ERT. Underpinned by the tenets of critical realism philosophy, as well as student integration theory, in-depth interviews with three lecturers and six students were conducted. The findings of the study indicate that home conditions, individual characteristics, pre-COVID-19 blended learning experiences, university training and support, and teaching, learning, and assessment practices and policies altogether contributed to the construction of unintended pedagogical consequences of ERT presented in this article. These consequences include (1) exclusion of low-income students in active teaching and learning, (2) equipping middle-class students with better chances of success than working-class students. (3) distressing female students and lecturers more than their male counterparts, and (4) unproductive assessment practices. This study may be beneficial to academics and policymakers from similar contexts in their plight to continue with remote teaching and assessment (RTA) beyond the pandemic.

Research has provided substantial evidence on the role of parents’ well-being in the quality of parent-child relationship and children’s adjustment. Parents’ stress and parental couple conflict have been linked to children’s adverse developmental outcomes. However, little is known about the factors that affect parent’s wellbeing when coping with multiple with stressors such as those brought by the recent COVID-19 global pandemic. Our study intended to examine the predictors of parental well-being looking at the contextual factors of COVID-19 home confinement, i.e. the use of digital media and parents’ domestic workload, and family resilience. Also, age and number of children were controlled as potential variables impacting parents’ well-being. A three-step hierarchical regression analysis was applied. The results showed that family resilience was a very strong predictor of parents’ well-being after controlling for any other variable. Parental couple’s conflict over the use of technology predicted lower levels of family well-being, while notably parent child-conflict and domestic workload were not associated with parents’ well-being. Additionally, age of children did play a role: the higher the mean age of children in the family the better the parents’ well-being. The findings are discussed in the light of their implications for research and practice.

SARS-CoV-2, is the cause of the COVID-19 pandemic which has claimed more than six million lives worldwide, devastating the economy and overwhelming healthcare systems globally. The development of new drug molecules and vaccines has played a critical role in managing the pandemic; however, new variants of concern still pose a significant threat as the current vaccines cannot prevent all infections. This situation calls for the collaboration of biomedical scientists and healthcare workers across the world. Repurposing approved drugs is an effective way of fast-tracking new treatments for recently emerged diseases. To this end, we have assembled and curated a database consisting of 7817 compounds from the Compounds Australia Open Drug collection. We developed a set of eight filters based on indicators of efficacy and safety that were applied sequentially to down-select drugs that showed promise for drug repurposing efforts against SARS-CoV-2. Considerable effort was made to evaluate approximately 14000 assay data points for SARS-CoV-2 FDA/TGA-approved drugs and provide an average activity score for 3539 compounds. The filtering process identified 12 FDA approved molecules with established safety profiles that have a plausible mechanism for treating COVID-19 disease. The methodology developed in our study provides a template for prioritising repurposable drug candidates that are safe, efficacious, and cost-effective for the treatment of COVID-19, long COVID, or any other future disease. We present our database in an easy-to-use interactive interface (CoviRx, https://www.covirx.org/) that was also developed to enable scientific community to access to the data of over 7000 potential drugs and to implement alternative prioritisation and down-selection strategies.

The recent COVID-19 pandemic has caused tremendous damage to social economy and people’s health. Some major issues fighting COVID-19 include early and accurate diagnosis and the shortage of ventilator machines for critical patients. In this work, we propose a closed-loop solution to deal with COVID-19: portable biosensing and wearable photoacoustic imaging for early and accurate diagnosis of infection and magnetically neuromodulation or minimally invasive electrical stimulation to replace the traditional ventilation. Proposed technique can guarantee ubiquitous and onsite detection, and electrical hypoglossal stimulator can be more effective in helping severe patients as well as reducing complications caused by ventilators.

This paper presents a computational approach designed to construct and query a literature-based knowledge graph for predicting novel drug therapeutics. The main objective is to offer a platform that discovers drug combinations from FDA-approved drugs and accelerates their investigations by domain scientists. Specifically, the paper introduced the following algorithms: (1) an algorithm for constructing the knowledge graph from drug, gene, and disease mentions in the biomedical literature; (2) an algorithm for vetting the knowledge graph from drug combinations that may pose a risk of drug interaction; (3) and two querying algorithms for searching the knowledge graph by a single drug or a combination of drugs. The resulting knowledge graph had 844 drugs, 306 gene/protein features, and 19 disease mentions. The original number of drug combinations generated was 2,001. We queried the knowledge graph to eliminate noise generated from chemicals that are not drugs. This step resulted in 614 drug combinations. When vetting the knowledge graph to eliminate the potentially risky drug combinations, it resulted in predicting 200 combinations. Our domain expert manually eliminated extra 54 combinations which left only 146 combination candidates. Our three-layered knowledge graph, empowered by our algorithms, offered a tool that predicted drug combination therapeutics for scientists who can further investigate from the viewpoint of drug targets and side effects.

The aim of this study was to investigate the spatio-temporal association between socio-economic deprivation and the incidence of COVID-19 and how this association changes through the seasons and due to the existence of restrictive public health measures. A retrospective observational study was conducted among COVID-19 cases that occurred in the Apulia region from 29 February 2020 to 31 December 2021, dividing the period into four phases with different levels of restrictions. A generalized estimating equations model was applied to test the independent effect of deprivation on the incidence rate of COVID-19, taking into account age, sex, and regional incidence rate as possible confounding effects and covariates such as season and levels of restrictions as possible modifying effects. The highest incidence rate was in areas with a Very High deprivation Index (DI) in winter (107.2 for 100,000 ab. ± 7.5), while in autumn, the highest Rate Ratio (RR) was estimated between Very High vs. Low DI (3.83, p<.001). During total lockdown, no RR between areas with different levels of DI was significant, while during soft lockdown, areas with Very High DI were more at risk than all other areas. The effects of social inequalities on incidence rate of COVID-19 change in as-sociation with the seasons and restrictions on public health. Disadvantaged areas showed a higher incidence rate of COVID-19 in the cold seasons and in the phases of soft lockdown.

Socioeconomic conditions and social attitudes are known to represent epidemiological determinants. Credible knowledge on socioeconomic driving factors of the COVID-19 epidemic is still incomplete. Based on a linear random effects regression, a predictive model is derived to estimate COVID-19 incidence in German rural districts from local socioeconomic factors and popularity of political parties in terms of their share of vote. Thereby, time series provided by Germany's public health institute (Robert Koch Institute) of weekly notified 7-day incidences per 100,000 inhabitants per district from the outset of the epidemic in 2020 up to December 1, 2021, have been used to construct the dependent variable. Local socioeconomic conditions including share of votes, retrieved from the Federal Statistical Office of Germany, have been used as potential risk factors. Popularity of the right-wing party Alternative for Germany (AfD) bears a considerable risk of increasing COVID-19 incidence both in terms of predicting the maximum incidences during three epidemic periods (alternatively, cumulative incidences over the periods are used to quantify the dependent variable) and in a time-continuous sense. Thus, districts with high AfD popularity rank on top in the time-average regarding COVID-19 incidence. The impact of the popularity of the Free Democrats (FDP) is markedly intermittent in the course of time showing two pronounced peaks in incidence but also occasional drops. A moderate risk emanates from popularities of the Green Party (GRÜNE) and the Christian Democratic Union (CDU/CSU) compared to the other parties with lowest risk level. Socioeconomic parameters like \emph{per capita} income, proportions of protection seekers and social benefit claimants, and educational level have negligible impact. To the contrary, incidence significantly increases with population density. In order to effectively combat the COVID-19 epidemic, public health policymakers are well advised to account for social attitudes and behavioural patterns reflected in local popularities of political parties, which are conceived as proper surrogates for these attitudes. Whilst causal relations between social attitudes and the presence of parties remain obscure, the political landscape in terms of share of votes constitutes at least viable predictive "markers" relevant for public health policy making.

COVID-19 affects many organs in our body, including the heart and lungs. COVID-19 cases that require hospitalization often exhibit pulmonary hypertension (PH) due to changes in the lung microvasculature in which the blood vessels become stiff, damaged, or narrow, causing increased pulmonary arterial pressure. This review examines the hypothesis that PH can lead to right ventricular hypertrophy (RVH) as a long-lasting aftereffect of COVID-19. Recent studies have shown that significant percentages of hospitalized patients develop right ventricular hypertension and right ventricular dilatation (RVD), which may lead to right ventricular failure and death. Despite recommendations for echocardiogram reports to include right ventricular wall thickness to assess RVH, few published reports have reported this parameter. Relevant studies on animal models of PH in which the timing of PH can be precisely controlled suggest that one to three weeks of PH can cause RVH. Thus, according to the hypothesis proposed here COVID-19 patients who have long-lasting severe disease (e.g., needed to be on a ventilator for one or more weeks) accompanied by PH and RVD may develop RVH as a long-lasting sequela outlasting the infection itself. Echocardiogram studies of recovered COVID-19 patients may determine whether oft-reported cardiovascular sequelae include RVH.

Abstract: Background: Our goal was to evaluate whether wearing personal protective equipment (PPE) such as an N95, or a surgical mask during the (COVID-19) pandemic had really reduced the cases of influenza in the state of Wisconsin. Methods: Respiratory Virus Surveillance Reports from the Wisconsin Department of Health Services (DHS) and the Centers for Disease Control and Prevention (CDC) were used to compare the rates of Influenza during the seasons of 2018-2019 and 2020-2021. Results: The number of cases, hospitalizations, and mortality rates with Influenza had significantly decreased in the 2020-2021 season compared to the Influenza season of 2018-2019. Discussion: Reducing the burden of influenza illnesses, hospitalizations, and deaths on the health care system is imperative. Wearing masks should be addressed for the most vulnerable.

The COVID-19 pandemic affects all parameters, especially health care professionals, drugs and medical supplies. The KERRA is a mixed medicinal plant capsule that is used for the treatment of patients with high fever with food and drug administration approved by FDA Thailand. Recently, KERRA showed quicker recovery for COVID-19 patients. Therefore, it is possible that some ingredients in KERRA could inhibit SARS-CoV-2. In this study, two important replication-related enzymes in SARS-CoV-2, a main protease and an RNA-dependent RNA polymerase (RdRp), were used to study the effect of KERRA. The results showed that KERRA inhibited the SARS-CoV-2 main protease and SARS-CoV-2 RdRp with IC50 values of 49.91 ± 1.75 ng/mL and 36.23 ± 5.23 µg/mL, respectively. KERRA displayed no cytotoxic activity on macrophage cells at concentrations lower than 1 mg/mL and exhibited anti-inflammatory activity. Additionally, KERRA was against a feline coronavirus (feline infectious peritonitis [FIP]) infection with an EC50 value of 134.3 g/mL. This study supports the potential use of KERRA as a candidate drug for COVID-19.

Malaysia implemented a movement control order (MCO) to curb the spread of the SARS-CoV-2 virus in March 2020. Despite healthcare services remaining operational, rising COVID-19 infections and MCO restrictions have forced healthcare professionals to seek a compromise between service capacity and standard operating procedure compliance. A cross-sectional survey was conducted among public and private sector doctors, dentists and pharmacists to determine how lockdown measures impacted healthcare services. Responses from 413 doctors, 193 dentists, and 163 pharmacists were analysed. Pharmacy services remained mostly unaffected throughout the MCO. In contrast, operational capacities for surgical and dental services were severely affected during the MCO. All service sectors reported restricting patients or accompanying individuals at the workplace, reductions in staffing capacity, and shortened patient contact time at various degrees. Many pharmacy and medical participants reported supplying extended medication supplies to patients. Adoption of virtual healthcare services was generally poor. All private service sectors suffered financial losses ranging between 59 to 75%. Periodic assessments of the healthcare system throughout the pandemic are required to identify which patients have their treatment compromised so that healthcare managers and policy makers can plan and implement appropriate interventions that help alleviate pressure within the health system.

Background and Objectives: In the current Covid-19 pandemic, children below the age of 12 could manifest Covid-19 symptoms and serve as a reservoir for the virus in the community. The present study was conducted to evaluate the reactogenicity, and immunogenicity of BBIBP-CorV, prior to involving this age group in the vaccination program in the kingdom of Bahrain. Subjects and Methods: The study included 582 children from 3 to 12 years old of Bahraini and non-Bahraini nationality, all of which contributed to the reactogenicity study. Of those, 401 contributed to the immunogenicity study. All children received 2 doses of BBIBP-CorV inactivated virus 3 weeks apart. To assess reactogenicity, children were followed up for 5 weeks to evaluate any vaccine-related adverse events (AE). To assess immunogenicity, blood was collected on day 0 and day 35 to assess antibody titer against S, N, and neutralizing antibody. Results: Of the 582 participants, (45.4%) were female, (54.61%) were male, with 49% in 9-12 age group. Of the 401 children contributing to the immunogenicity study, 274 (68.3%) had no prior exposure to Covid-19. The overall incidence of AE was 27.7%. No significant difference was found among different age groups. The most frequent AE was local (at the injection site) and occurred in 16% of children, followed by fever in 9.3%. No serious adverse events were reported. The Seroconversion rate was 100% among children with no prior exposure to Covid-19. Children with previous Covid-19 exposure had higher averages of anti-S (2379 U/ml compared to 409.1), anti-N (177.6 U/ml compared to 30.9) and neutralizing antibody (93.7 U/ml compared to 77.1) than children with no prior exposure at day 35. Conclusions: Two doses of COVID-19 BBIBP-CorV on the subjects aged between 3 to 12 has good safety and tolerance and can induce an effective immune response and neutralizing antibody titer.

The recent covid crisis has proven important lessons for academia and industry regarding digital reorganization. Among fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and over. Moreover, drug development is a costly and time-consuming business, and only a minority of approved drugs return the revenue that exceeds the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper will review the most significant research on artificial intelligence in the de novo drug design for COVID-19 pharmaceutical research.

Background. We aimed to assess the validity of the Mat-O-Covid Job Exposure Matrix (JEM) on SARS-CoV2 using compensation data from the French National Health Insurance compensation system for occupational-related COVID-19. Methods. Deidentified compensation data for occupational COVID-19 in France were obtained between August 2020 and August 2021. The acceptance was considered as the reference. Mat-O-Covid is an expert based French JEM on workplace exposure to SARS-CoV2. Bivariate and multivariate models were used to study the association between the exposure assessed by Mat-O-Covid and the reference, as well as the Area Under Curves (AUC), sensitivity, specificity, predictive values, and likelihood ratios. Results. In the 1140 cases included, there was a close association between the Mat-O-Covid index and the reference (p&lt;0.0001). The overall predictivity was good, with an AUC of 0.78 and an optimal threshold at 13 per thousand. Using Youden’s J statistic resulted in 0.67 sensitivity and 0.87 specificity. Both positive and negative likelihood ratios were significant: respectively 4.9 [2.4-6.4] and 0.4 [0.3-0.4]. Discussion. It was possible to assess Mat-O-Covid’s validity using data from the national compensation system for occupational COVID-19. Though further studies are needed, Mat-O-Covid exposure assessment appears to be accurate enough to be used in research.

The interactions between work and personal life are important for ensuring well-being especially during COVID-19 where the lines between work and home are blurred. Work-life interference/imbalance can result in work-related burnout, which has been shown to have negative effects on faculty members’ physical and psychological health. Although our understanding of burnout has advanced considerably in recent years, little is known about the effects of burnout on nursing faculty turnover intentions and career satisfaction. Thus, this study aimed to test a hypothesized model examining the effects of work-life inference on nursing faculty burnout (emotional exhaustion and cynicism), turnover intentions and ultimately, career satisfaction. A predictive cross-sectional design was used. An online national survey of nursing faculty members was administered throughout Canada in Summer 2021. Nursing faculty who held full-time or part-time positions in Canadian academic settings were invited via email to participate in the study. Data was collected from an anonymous survey housed on Qualtrics. Descriptive statistics and reliability estimates were computed. The hypothesized model was tested using structural equation modeling. Data suggest that work-life interference significantly increase burnout which contribute to both higher turnover intentions and lower career satisfaction. Turnover intentions in turn was negatively associated with career satisfaction. The findings add to the growing body of literature linking burnout to turnover and dissatisfaction, highlighting key antecedents and/or drivers of burnout among nurse academics. These results provide suggestions for suitable areas for the development of interventions and policies within the organizational structure to reduce the risk of burnout during and post-COVID-19 and improve faculty retention.

The confinement experienced due to the COVID-19 pandemic has prompted a rethink of the teaching-learning process to which teachers have responded without planning and instead using their resources. This study aims to analyze the relationships between work-family interactions, technostress, and perceived organizational support in teachers during the confinement period in Spain that began in March 2020. An online survey was administered to 640 pre-school, primary, and secondary school teachers. Positive reciprocal work-family interactions and their relationship with organizational support were found, with differences according to gender, with women showing a more negative perception of the impact on the family. There were no marked levels of technostress in the overall sample, although higher levels of perceived ineffectiveness and skepticism were found in teachers aged 46 years or older. Teachers in private and subsidized schools showed a higher level of perceived support than those in public schools. There is a need to continue this work to verify the values of these dimensions in other contexts and to apply institutional measures and public policies to improve these indicators in this group.

The emergence of the COVID-19 pandemic has propelled the use of alcohol-based hand sanitizers to the fore as a SARS-CoV-2 control measure. To be effective these products must comply with relevant quality parameters such as alcohol concentration, methanol limits and purity. The current study was designed to determine the quality of alcohol-based hand sanitizer products in the Nairobi metropolitan area. For this purpose, 74 commercially marketed samples were collected and subjected to analysis by gas chromatography. Only three samples (4.1%) complied with the regulatory specifications for alcohol content, methanol limits and pH. Five samples (6.8%) complied with the specification for alcohol content but did not meet methanol or pH limits. A total of 44 (59.5%) samples had methanol levels that exceeded threshold limits. Eleven samples (14.9%) were found with methanol substitution (i.e., methanol, instead of ethanol or isopropanol, was the main alcohol component). The results show that users of alcohol-based hand sanitizers are being exposed to substandard and falsified products which in addition to being non-efficacious pose harm due to unacceptable levels of toxic impurities. Regular, routine post-market surveillance is needed to prevent such products from reaching the market.

The present paper proposes a fractal analysis of the Covid-19 dynamics in 45 European countries. We introduce a new idea of using the box-counting dimension of the epidemiologic curves as a means of classifying the Covid-19 pandemic in the countries taken into consideration. The classification can be a useful tool in deciding upon the quality and accuracy of the data available. We also investigated the reproduction rate, which proves to have significant fractal features, thus enabling another perspective on this epidemic characteristic. Moreover, we studied the correlation between two meteorological parameters: global radiation and daily mean temperature and two Covid-19 indicators: daily new cases and reproduction rate. The fractal dimension differences between the analysed time series graphs could represent a preliminary analysis criterion, increasing research efficiency. Daily global radiation was found to be stronger linked with Covid-19 new cases than air temperature (with a greater correlation coefficient -0.386, as compared with -0.318), and consequently it is recommended as the first-choice meteorological variable for prediction models.

Though there have been works highlighting the advantages and disadvantages of online learning, no study focused on university-level economics students. None of the studies explored students' opinions about improving the quality and effectiveness of online classes. Many used questionable samples, closed-ended questions, and all those researches were carried out at the beginning of online classes. In this paper, we overcome these limitations of earlier studies. Using a convenience sampling technique and open-ended questions, we collect data from 154 university-level economics students after being exposed to the online class for a year. Some advantages of online classes are: students can do classes from home without being exposed to health risks, easily accessible, flexible class schedule, students remained connected with the study, it saves costs, reduce the likelihood of semester loss, easy to understand, less stressful, and learning new technologies. Major problems from students' perspectives include network problems, difficulties in understanding the topic, unsuitable for mathematical courses, concentration problem, class not interactive, financial constraint, adverse health impacts, device issues, power outages, unfamiliarity with digital technology, internet problem, and unfixed class-schedule. Disadvantages outnumbered advantages. Students made several suggestions to improve the quality and effectiveness of online classes. Some of the vital suggestions are: using state-of-the-art digital tools, recording and uploading lectures, resolving internet issues, holding classes regularly, higher efforts to make the topics easier, resolving network issues, lowering class duration, institutional support, implementing a fixed class schedule, and introducing online evaluation system.

A distinctive feature of the SARS-CoV-2 spike protein is its ability to efficiently fuse cells, thus producing syncytia found in COVID-19 patients. This commentary proposes how this ability enables spike to cause COVID-19 complications as well as side effects of COVID-19 vaccines, and suggests how these effects can be prevented..

The aim of this study was to build a tool to analyze, using artificial intelligence, the sentiment perception of users who answered two questions from the CSQ – 8 questionnaires with raw Spanish free-text. Their responses are related to mindfulness, which is a novel technique used to control stress and anxiety caused by different factors in daily life. As such, we proposed an online course where this method was applied in order to improve the quality of life of health care professionals in COVID 19 pandemic times. We also carried out an evaluation of the satis-faction level of the participants involved, with a view to establishing strategies to improve fu-ture experiences. To automatically perform this task, we used Natural Language Processing (NLP) models such as swivel embedding, neural networks and transfer learning, so as to classify the inputs into the following 3 categories: negative, neutral and positive. Due to the lim-ited amount of data available - 86 registers for the first and 68 for the second - transfer learning techniques were required. The length of the text had no limit from the user’s standpoint, and our approach attained a maximum accuracy of 93.02 % and 90.53 % respectively based on ground truth labeled by 3 experts. Finally, we proposed a complementary analysis, using com-puter graphic text representation based on word frequency, to help researchers identify relevant information about the opinions with an objective approach to sentiment. The main conclusion drawn from this work is that the application of NLP techniques in small amounts of data using transfer learning is able to obtain enough accuracy in sentiment analysis and text classification stages

This study aimed to assess the differences in the importance and performance of health awareness in Korean middle school students according to the types of online physical education classes they attended during the coronavirus disease-2019 pandemic. Overall, 583 participants were selected using a convenience sampling method; the data were obtained through an online survey using Google forms. Frequency analysis, reliability analysis, independent sample t-test, and importance-performance analysis were performed. First, the differences between importance and performance were found to be the most for sleep and physical activity management, and the least for disease and hygiene management. In addition, both the groups demonstrated higher importance and performance for hygiene and disease management. There were significant differences in the importance and performance of all the sub-factors. Second, hygiene, disease management, and mental health management were found in quadrant I in both the groups, while physical activity, sleep, and dietary habit management were in quadrant III. No factors were in quadrant II and IV.

Advancements in deep learning and availability of medical imaging data have led to use of CNN based architectures in disease diagnostic assisted systems. In spite of the abundant use of reverse transcription-polymerase chain reaction (RT-PCR) based tests in COVID-19 diagnosis, CT images offer an applicable supplement with its high sensitivity rates. Here, we study classification of COVID-19 pneumonia (CP) and non-COVID-19 pneumonia (NCP) in chest CT scans using efficient deep learning methods to be readily implemented by any hospital. We report our deep network framework design that encompasses Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory (biLSTM) architectures. Our study achieved high specificity (CP: 98.3%, NCP: 96.2% Healthy: 89.3%) and high sensitivity (CP: 84.0%, NCP: 93.9% Healthy: 94.9%) in classifying COVID-19 pneumonia, non-COVID-19 pneumonia and healthy patients. Next, we provide visual explanations for the CNN predictions with gradient-weighted class activation mapping (Grad-CAM). The results provided a model explainability by showing that Ground Glass Opacities (GGO), indicators of COVID-19 pneumonia disease, were captured by our CNN network. Finally, we have implemented our approach in three hospitals proving its compatibility and efficiency.

The availability of simple SARS-CoV-2 detection methods is crucial to contain the COVID-19 pandemic. This study examined whether a commercial LAMP assay can reliably detect SARS-CoV-2 genomes directly in respiratory samples without having to extract nucleic acids (NA) beforehand. Nasopharyngeal swabs (NPS, n = 220) were tested by real-time reverse transcription (RT)-PCR and with the LAMP assay. For RT-PCR, NA were investigated. For LAMP, NA from 26 NPS in viral transport medium (VTM) were tested. The other 194 NPS were analyzed directly without prior NA extraction [140 samples in VTM; 54 dry swab samples stirred in phosphate buffered saline]. Ten NPS were tested directly by LAMP using a sous-vide cooking unit. The isothermal assay demonstrated excellent specificity (100%) but moderate sensitivity (68.8%), with a positive predictive value of 1 and a negative predictive value of 0.65 for direct testing of NPS in VTM. The use of dry swabs, even without NA extraction, improved the analytical sensitivity; up to 6% of samples showed signs of inhibition. The LAMP could be performed successfully with a sous-vide cooking unit. This technique is very fast, requires little laboratory resources and can replace rapid antigen tests or verify reactive rapid tests on site.

Social media has become the most influential battleground for political and societal debate. The reach, the speed, and the fact that everybody can participate make this medium very popular but also highly manipulative, subject to biases and extremely precious to control. Misinformation spreads in an unforeseeable way. Sometimes it just follows usual non-malicious social interaction patterns, but often a targeted and designed-for-purpose manner. In this paper, we propose a novel method to identify the most effective opportunities to moderate the social media debate at a large scale using the properties of social signed graphs, such as structural balance. After building the topic universe for a particular political debate in a given time frame, we extract the most active and influential users and mine their position regarding the topic based on their interactions with other users. The result is a signed graph where each edge represents either support or challenge between a pair of users in the context of the topic. This graph can be modelled as an Ising model, with the goal of minimizing its energy state by using the advantages of Adiabatic Quantum Computing. Applying this principle, we use a Quantum Annealing implementation to solve the problem of finding the edges violating the structural balance of this graph, which in classic computing is known to be an NP-hard problem. We then provide a non-intrusive moderation technique for those violations to mitigate or increase the structural imbalance, depending on the desired strategy. The methodology is shown in the context of the COVID-19 skeptics’ debate in Twitter and implemented using a D-Wave 2000Q-6 quantum annealer.