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The latest outbreak of a coronavirus disease in 2019 (COVID‐19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), evolved into a worldwide pandemic with massive effects on health, quality of life, and economy. Given the short period of time since the outbreak, there are several knowledge gaps on the comparative and zoonotic aspects of this new virus. Within the One Health concept, the current EAACI position paper dwells into the current knowledge on SARS‐CoV‐2's receptors, symptoms, transmission routes for human and animals living in close vicinity to each other, usefulness of animal models to study this disease and management options to avoid intra‐ and interspecies transmission. Similar pandemics might appear unexpectedly and more frequently in the near future due to climate change, consumption of exotic foods and drinks, globe‐trotter travel possibilities, the growing world population, the decreasing production space, declining room for wildlife and free‐ranging animals, and the changed lifestyle including living very close to animals. Therefore, both the society and the health authorities need to be aware and well prepared for similar future situations, and research needs to focus on prevention and fast development of treatment options (medications, vaccines). [ABSTRACT FROM AUTHOR]

Public emergencies are focal events that present possibilities for policy changes. This study aims to explain policy insights on policy change in Iran through analyzing how the Iranian government's policy toward the long‐awaited e‐authentication finally changed in the wake of the outbreak of COVID‐19. Due to the policy context of Iran, it uses the Multiple Stream Model, in which three streams were identified: problem, policy, and political dynamics. The paper contends that while the second stream existed prior to the pandemic, the first one had not yet been appropriately recognized by the government. Furthermore, it identifies the political stream as the third missing link for policy change. With the spread of coronavirus, these three streams converged, thus opening a window of opportunity for enacting this policy change. Two main reasons behind the emergence of this opening are identified: first, arising a new complex problem (COVID‐19) that necessitated new initiatives, and second, growing public anxiety about the pandemic. Iran's desperate circumstances, which included an already severely depressed economy as the result of sanctions, were further exacerbated through the socio‐economic repercussions of the pandemic. Furthermore, the growing demand from prospective traders to register for the stock exchange during the lockdown prompted officials to make a realistic decision. As a result, barriers to e‐authentication were overcome and policy change happened. The paper highlights the security perspective as a necessary condition for policy change in Iran. Finally, it discusses the likelihood of permanency of the change. [ABSTRACT FROM AUTHOR]

The aim of this scoping review was to examine the national and international literature on the response of adult Hospital at Home (HAH) services to the global Covid-19 pandemic and explore key themes to emerge and make recommendations for further research. The databases were searched using agreed search terms and Arksey and O'Malley's scoping review framework was utilized and papers were identified and analyzed for common themes. Thirty-one papers were included in the review. Of the papers included, general adult medicine was the largest service group (n = 15) with geriatric services the next largest (n = 12). Most papers were European in origin (n = 19). Key themes to emerge include (1) similar outcomes for HAH patients compared with traditional inpatient care, (2) expansion of capacity for inpatient care due to HAH use, (3) growth of virtual monitoring in HAH setting, (4) reduction in infection transmission in HAH setting, and (5) cost reduction due to HAH utilization. Hospital at home demonstrated good outcomes for both patients with Covid-19 and other conditions during the pandemic. These services also expanded capacity during a global healthcare crisis. Remote monitoring played a major role in the expansion of capacity and the reduction of infection transmission during the pandemic. Although some papers discuss how HAH is more cost effective than traditional hospital, more work is needed around this as many of the patients may not have been as sick as those admitted to traditional hospital during the pandemic. [ABSTRACT FROM AUTHOR]

In contrast to nearby countries, Jordan achieved a unique situation in mitigating the covid-19 outbreak. The privileged situation lasted for a few months. After that situation, Jordan became one of the worst countries all over the world. Drawing on a conceptual framework derived from Blau’s theory: exchange and power in social life, this paper reevaluates the dynamics of combating covid-19 in Jordan as an exchange process between government and people. Jordan’s government employed maximum power to control people’s movements and gatherings. However, it failed to meet people’s expectations of keeping their lives safe and fulfilling their basic needs. The government tried to legitimize the situation by providing fake information. It has lost the trust of society which supported the efforts of the government. It could not maintain its control of people’s gatherings and movements, resulting in a rise in the number of cases. Transparency, trust, awareness, and society’s efforts are crucial in fighting pandemics. [ABSTRACT FROM AUTHOR]

The spread of infectious diseases was further promoted due to busy cities, increased travel, and climate change, which led to outbreaks, epidemics, and even pandemics. The world experienced the severity of the 125 nm virus called the coronavirus disease 2019 (COVID-19), a pandemic declared by the World Health Organization (WHO) in 2019. Many investigations revealed a strong correlation between humidity and temperature relative to the kinetics of the virus's spread into the hosts. This study aimed to solve the riddle of the correlation between environmental factors and COVID-19 by applying RepOrting standards for Systematic Evidence Syntheses (ROSES) with the designed research question. Five temperature and humidity-related themes were deduced via the review processes, namely 1) The link between solar activity and pandemic outbreaks, 2) Regional area, 3) Climate and weather, 4) Relationship between temperature and humidity, and 5) the Governmental disinfection actions and guidelines. A significant relationship between solar activities and pandemic outbreaks was reported throughout the review of past studies. The grand solar minima (1450-1830) and solar minima (1975-2020) coincided with the global pandemic. Meanwhile, the cooler, lower humidity, and low wind movement environment reported higher severity of cases. Moreover, COVID-19 confirmed cases and death cases were higher in countries located within the Northern Hemisphere. The Blackbox of COVID-19 was revealed through the work conducted in this paper that the virus thrives in cooler and low-humidity environments, with emphasis on potential treatments and government measures relative to temperature and humidity. Highlights: • The coronavirus disease 2019 (COIVD-19) is spreading faster in low temperatures and humid area. • Weather and climate serve as environmental drivers in propagating COVID-19. • Solar radiation influences the spreading of COVID-19. • The correlation between weather and population as the factor in spreading of COVID-19. [ABSTRACT FROM AUTHOR]

The soviet social theorist Mikhail M. Bakhtin developed the theory of the carnivalesque as a logic of exaggeration, inversion and irony. Beyond carnival events themselves, Bakhtin proposed this logic as a creative instance to foresee openings within an assumed normality. The conceptual gaze of the 'carnivalesque' helps to rethink the reconfiguration of actors and practices around mobility, borders and migration during the initial lockdowns of the COVID-19 pandemic. This impasse worked as a corona-carnival in the midst of the current mobility regime. The use of 'carnivalesque' in this article is not related to the playful aspects of carnival as a parade, but to the potential of the carnivalesque impasse for envisioning alternatives, which are not necessarily emancipatory but deeply ambivalent, grotesque and unfinished. That carnivalesque momentum, marked by social norms placed on pause, is captured in artistic and linguistic production, acting as a collective legacy for imagining futures otherwise. This paper compiles some keywords which emerged during the corona-carnival impasse, each holding hopeful and dystopian glimpses of possible alterations to the status-quo. These linguistic productions question assumed notions and practices of migration management, opening the social imagination to other ways of engaging with human mobilities. [ABSTRACT FROM AUTHOR]

It has not yet been fully established that there is coronavirus disease 2019 (COVID-19) involvement in the synovial fluid and it remains a topic of debate. The aim of this study was to evaluate the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in knee joint synovial fluid of patients with COVID-19. This retrospective study was conducted with an initial screening of patients who were admitted to a tertiary pandemic hospital due to COVID-19 symptoms, and underwent treatment for COVID-19 between March and June 2020. A total of 2476 patients were hospitalized or received treatment for a possible diagnosis of COVID-19. While the RT-PCR test was positive in 318 patients (12.8%), 2158 (87.2%) were computed tomography positive but reverse transcription-polymerase chain reaction (RT-PCR) negative. Twelve patients were consulted due to acute joint effusion. Of five patients with knee joint effusion and a positive RT-PCR test, the synovial tissue RT-PCR test was positive in only one patient. This paper is the first to show the presence of SARS-CoV-2 in synovial fluid. This can be considered of importance for the determination and elimination of the route of transmission, thereby preventing further development and spread of the disease. [ABSTRACT FROM AUTHOR]

Why are mistaken beliefs about COVID-19 so prevalent? Political identity, education and other demographic variables explain only part of the differences between people in their susceptibility to COVID-19 misinformation. This paper focuses on another explanation: epistemic vice. Epistemic vices are character traits that interfere with acquiring, maintaining, and transmitting knowledge. If the basic assumption of vice epistemology is right, then people with epistemic vices such as indifference to the truth or rigidity in their belief structures will tend to be more susceptible to believing COVID-19 misinformation. We carried out an observational study (US adult sample, n = 998) in which we measured the level of epistemic vice of participants using a novel Epistemic Vice Scale that captures features of the current competing analyses of epistemic vice in the literature. We also asked participants questions eliciting the extent to which they subscribe to myths and misinformation about COVID-19. We find overwhelming evidence to the effect that epistemic vice is associated with susceptibility to COVID-19 misinformation. In fact, the association turns out to be stronger than with political identity, educational attainment, scores on the Cognitive Reflection Test, personality, dogmatism, and need for closure. We conclude that this offers evidence in favor of the empirical presuppositions of vice epistemology. [ABSTRACT FROM AUTHOR]

Aim: This study aims to identify the working conditions of Brazilian nursing professionals and the risk factors for these professionals to become infected by coronavirus disease. Background: Understanding the factors that affected nursing professionals during the pandemic can support better nursing management. Design: This is a quantitative, cross‐sectional survey study. Methods: Data collection was carried out between February and March 2022 in Brazil. All nursing professionals registered in the national database received by e‐mail the study instrument with the data collection variables: professionals' sociodemographic and comorbid, professional and institutional characteristics, and professionals' health conditions and disease‐related aspects for COVID‐19. Results: Four thousand eight hundred sixty‐two nursing professionals reported a lack of personal protective equipment for patient care, and 4424 were infected by coronavirus disease. The risk factors to become infected were having cardiovascular disease, being under 60 years of age, living in the northern region, using public transportation, working in a hospital, an emergency department or reference institution for COVID‐19, living with an infected person and lack of respirators or waterproof aprons. Conclusion: Multiple risk factors for infection with SARS‐CoV‐2 were demonstrated for the nursing professionals during the pandemic, highlighting current and future pandemics factors that are modifiable in a worthwhile time frame to minimize nurses' infection risks, such as inadequate working conditions associated with lack of essential personal protective equipment. Summary statement: What is already known about this topic? The health‐care team is essential in managing COVID‐19, but it has been directly affected by the pandemic. What this paper adds? Multiple risk factors for infection with SARS‐CoV‐2, modifiable or not, were demonstrated for these nursing professionals. The implications of this paper: Strategies to protect the health‐care workers should be implemented during this and any future pandemics, especially providing adequate access to essential personal protective equipment. [ABSTRACT FROM AUTHOR]

Objectives: Lebanese frontline nurses were not only fighting off a pandemic for the past year but also facing escalating political, social, economic, and humanitarian turmoil that have accentuated the pressures exerted upon them. However, their needs for psychological support and coping mechanisms have been uncharted in light of the documented stress frontline nurses have been living for the past year. This paper aimed at exploring the perceptions of frontline ground zero nurses in Lebanon regarding their psychological needs and coping mechanisms during the most recent COVID-19 outbreak. Methods: This study was conducted in 2 main ground-zero hospitals in Beirut. This research paper has adopted a qualitative exploratory research design through employing the phenomenological approach, where online interviews were carried out among 15 frontline ground zero nurses in the 2nd week of January 2020. Results: The results of this study showed that the nurses perceived a need for significant psychological support led by their hospital, while they had to employ various coping mechanisms. The qualitative analysis of the verbatim conveyed by participating nurses have resulted in the emergence of five themes; "Need for actual support," "Need for formal psychological counseling," "Praying and being spiritual," "Avoiding the news," and "Self-reminders.". Conclusion: This study demonstrated that sufficient action has not been taken to enhance the mental health of these frontline nurses, where they shared their perspective of inadequate support mechanisms and the necessity for technical, systemic, and structured mental health support. [ABSTRACT FROM AUTHOR]

This paper contains an investigation of the COVID-19 impacts on freight flows and the handling of uncertainty in freight forecasting models, based on data from Greece. It collects and analyses, over a 7-year period before and during the pandemic, data for freight transport operations and some related factors in order to macroscopically examine any statistically significant changes in their values over time. This period wasjudged necessary in order to establish the pattern of fluctuations in the relevant data during the non-pandemic years and thus make the visual comparison with the previous period and the years during the pandemic, more clear. First, the paper tests the impact of the pandemic as expressed by the number of daily COVID-19 cases on freight flow variables in order to find the dynamic behavior of these variables and trace their reactions over time. This analysis is made by using the Vector Autoregressive Model (VAR). By implementing VAR modelling, we analyzed the dynamic relationship between freight transport volumes and other factors such as GDP, the industrial production index, exporting transactions and the number of coronavirus cases. The main result of the model analysis and the employment of impulse response functions revealed that the unexpected shock of COVID has a negative reaction to the economy and the freight transport volumes and a rather shortterm limited duration disruption effect on the growth of exports as well as on the industrial production index, of approximately eight months. Secondly, the paper discusses how, unpredicted events like the pandemic, influence the uncertainty inherent in freight transport modelling and formulates a novel freight modelling framework procedure based on scenario building, regular monitoring and data updates on a permanent basis. [ABSTRACT FROM AUTHOR]

This paper addresses U.S. pandemic-related propaganda, as a mode of administering society, selves, and the COVID-19 virus relevant to other national contexts. The paper examines what I call pandemic revanchism, which, in order to stoke U.S. culture wars, propag(and)ates the COVID-19 epidemic by sensationalizing the trivial and normalizing the extraordinary or absurd. Banal forms of administrative grotesquerie mobilize a community of alt-health (non)sense and tie freedom to a viral and literally infectious resentment and retaliatory collateral mortality. The paper first develops the framework of FOOB ('folklore of operational banality') to scrutinize how ordinary health/medical administration and reactionary power relations alike level sense and non-sense. It then offers a performative analysis that shows human geographies of routinized anti-establishment refusal and conspiratorial organizing related to the pandemic. The FOOB approach refuses to simply admonish pandemic revanchism and, instead, tracks how this form of administration consolidates social terrains and quotidian online activity. The analysis seeks to level criticism in a way that undermines social division. It does so by remaining open to reasonable doubts about biomedicalization that are swept up in alt-health and pandemic-related propaganda, and by foregrounding how policy, affect, and storylines routinize extremisms within the American public terrain. [ABSTRACT FROM AUTHOR]

This paper illustrates how superdiverse youth negotiate their identity in everyday interactions during Australia's Covid-19 outbreak. The discussion is based on oral narratives collected from classroom conversations among international and local students living in Australia. The paper illustrates how participants position themselves and others in narratives, how these positionings reveal complex identity work among youth from diverse backgrounds and how identities are constructed and negotiated through stories about everyday encounters. Students' experiences of racism and microaggressions point to interethnic interactions as sites of struggle where identities come into conflict. The paper contributes to current work on identity in narrative discourse and narratives of racism. [ABSTRACT FROM AUTHOR]

This paper investigated the prevalence of Post-Traumatic Stress Disorder (PTSD) in people who had tested positive for COVID-19. This study also examined the effect of socio demographic characteristics on PTSD levels in people who had tested positive for COVID-19. This descriptive and cross-sectional study was conducted between May and November 2022 at the Azadi Teaching Hospital Kirkuk in Kirkuk, Iraq. The study population consisted of 980 people who had tested positive for COVID-19. The inclusion criteria were (1) being 18 years or older and (2) having been admitted to the hospital. Data were collected online (Google forms) using a socio demographic questionnaire and a Post-Traumatic Stress Disorder Questionnaire (PTSDQ). The data were analyzed using the Statistical Package for Social Sciences (SPSS, v.26) at a significance level of <0.05. Frequencies, percentages, means, and standard deviations were used for categorical variables. The data were analyzed using a one-way analysis of variance (Kruskal Wallis) and a two-sample t-test. More than half of the participants were women (55.8%). More than a quarter of the participants were 26 to 33 years of age. Participants had a mean PTSDQ score of 47.7 ± 11.9. Gender, educational, and method of infection affected their PTSDQ scores. Female participants had a higher PTSDQ score than male participants. [ABSTRACT FROM AUTHOR]

The novel coronavirus (COVID-19) outbreak has affected living standards around the world, and pandemic anxiety has changed social habits. In this context, this paper investigates the relationship between fear of COVID-19 and quality of life, and assesses the mediating effect of loneliness on this relationship among a sample of older adults in Turkey. The study considers data from approximately 400 people, all of whom completed the CASP-19 Quality of Life Scale in Older People, the Loneliness Scale for the Elderly and the Fear of COVID-19 Scale. Confirmatory factor analyses were performed to confirm a one-factor structure for each instrument. Subsequently, mediation analysis, correcting for age as a continuous covariate, was performed to assess the nature of the relationship between fear and quality of life, and the extent to which that relationship is mediated by loneliness. Our study showed that there is a negative and direct relationship between loneliness and quality of life. Another important finding of our research is that fear of COVID-19 has a significant effect on loneliness. Finally, loneliness mediates the relation between fear of COVID-19 and quality of life. This finding strongly suggests that fear of COVID-19 influences quality of life via loneliness. This result is noteworthy, as we could not find any similar finding in the literature. [ABSTRACT FROM AUTHOR]

Background: Public health emergencies raise significant concerns about corruption and accountability; however, these concerns can manifest in different ways across diverse locations. For instance, more developed countries with a stronger rule of law may experience more corruption in vaccine procurement, whereas developing countries may experience more corruption at the point of distribution and delivery to end users. This research focuses on corruption concerns in Nigeria, specifically examining the procurement and distribution of COVID-19 vaccines. Methods: This paper utilizes a scoping review and a qualitative research approach. Key informants (n = 40) involved in the procurement and distribution of COVID-19 vaccines across two states in Nigeria were interviewed. Findings from the scoping review were summarized, and collected data were inductively coded and analysed in themes, revealing clear examples of implementation irregularities and corruption in the country's COVID-19 vaccination processes. Results: Vaccination programme budgeting processes were unclear, and payment irregularities were frequently observed, resulting in vaccinators soliciting informal payments while in the field. Recruitment and engagement of vaccination personnel was opaque, while target vaccination rates incentivized data falsification during periods of vaccine hesitancy. Accountability mechanisms, such as health worker supervision, vaccination data review, and additional technical support provided by donors were implemented but not effective at preventing corruption among frontline workers. Conclusions: Future accountability measures should be evidence-driven based on findings from this research. Personnel recruitment, contracting, budgeting, and remuneration should focus on transparency and accountability. [ABSTRACT FROM AUTHOR]

This paper examines the effects of COVID‐19‐induced lockdowns on recorded crime in England. The enforcement of lockdowns at both the national and local levels allows unveiling the impact on criminal activities by type of shutdown policy. Using official crime data across the universe of local authorities, we find that unlike local lockdowns national lockdowns significantly change the shape of recorded criminal activity, with the first nationally‐imposed lockdown having the strongest impact. Findings also reveal that police operations play a prominent role in explaining changes in reported crimes. Back‐of‐the‐envelope calculations suggest that lockdowns reduced the economic costs of crime by £4.2 billion. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) is a pandemic caused by coronavirus with mild to severe respiratory symptoms. This paper aimed to investigate the effect of nutrients on the immune system and their possible roles in the prevention, treatment, and management of COVID-19 in adults. This Systematic review was designed based on the guideline of the Preferred Reporting for Systematic Reviews (PRISMA). The articles that focussed on nutrition, immune system, viral infection, and coronaviruses were collected by searching databases for both published papers and accepted manuscripts from 1990 to 2020. Irrelevant papers and articles without English abstract were excluded from the review process. Some nutrients are actively involved in the proper functioning and strengthening of the human immune system against viral infections including dietary protein, omega-3 fatty acids, vitamin A, vitamin D, vitamin E, vitamin B1, vitamin B6, vitamin B12, vitamin C, iron, zinc, and selenium. Few studies were done on the effect of dietary components on prevention of COVID-19, but supplementation with these nutrients may be effective in improving the health status of patients with viral infections. Following a balanced diet and supplementation with proper nutrients may play a vital role in prevention, treatment, and management of COVID-19. However, further clinical trials are needed to confirm these findings and presenting the strong recommendations against this pandemic. [ABSTRACT FROM AUTHOR]

Ozone therapy (OT), a medical procedure, has been showing good results during the coronavirus disease (COVID-19). We aimed to build an evidence and gaps map (EGM) of OT in the COVID-19 ranking the articles found according to levels of evidence and outcomes. The EGM brings bubbles of different sizes and different colors according to the articles. The OT intervention used was major or minor autohemotherapy, rectal insufflation and ozonized saline solution. EGM was based on 13 clinical studies using OT for COVID-19 involving a total of 271 patients. We found 30 outcomes related to OT in COVID-19. Our EGM divided the outcomes into six groups: 1-clinical improvement; 2-hospitalization; 3-inflammatory, thromboembolic, infectious, or metabolic markers; 4-radiological aspects, 5-viral infection and 6-adverse events. Major autohemotherapy was present in 19 outcomes, followed by rectal insufflation. Improvement in clinical symptoms of COVID-19, improvement of respiratory function, improvement of oxygen saturation, reduction in hospital internment, decrease in C-reactive protein, decrease in ferritin, decrease in lactate dehydrogenase, decrease in interleukin 6, decrease in D-dimer, radiological improvement of lung lesions and absence of reported adverse events were related in the papers. The most commonly used concentrations of OT in major autohemotherapy and in rectal insufflation were 40 µg/mL and 35 µg/mL, respectively. Here, we bring the first EGM showing the efficacy and safety of OT in the treatment of COVID-19. OT can be used as integrative medical therapy in COVID-19 at a low cost and improve the health conditions of the patients. [ABSTRACT FROM AUTHOR]

Objective: The pandemic caused by the coronavirus disease 2019 (COVID-19, SARS-CoV-2 virus) has infected more than 646 million people and caused more than 6.6 million deaths worldwide (December/2022). It is surprising that a virus that affects airways can trigger neurological manifestations. The aim of this study was to create and apply specific questionnaires/evaluations for post-COVID-19 patients to profile any neurofunctional sequelae. Methods: Epidemiological and psychomotor aspects as well as the intensity of cognitive, memory, attention, and concentration impairment were assessed. A total of 184 subjects post-COVID-19 and a control group (n = 30) were evaluated. Results: The most prevalent blood types in the COVID-19 group were the same as those from control group and in Brazilian population (no influence). Loss of smell/taste and headache were the most common reported symptoms. Talking about psychomotor and neurofunctional aspects, COVID-19 induced marked impairments in the tests: fine motor development (diadochokinesis, puppets, fan, and knead paper); balance (immobility, static balance, feet in line, and persistence); episodic memory after distractors; verbal fluency; and clock, compared to the control group data. There was also marked increase of synkinesis. Therefore, COVID-19 induced impairments in psychomotor assessments and in different cognitive aspects of the Mini-Mental State Examination. These results are more surprising considering that most participants did not report pre-existing disease and did not require hospitalisation. Conclusion: COVID-19 induced psychomotor, neurofunctional, and memory impairments, including in young and healthy subjects. The present study revealed neurological impairments, which should be considered in the development of rehabilitation protocols for patients affected by COVID-19. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic had a significant impact on the operations and functionality of the public transport sector in the UK. This paper reflects on the experience of this sector through the pandemic period, and considers recommendations for any future mitigations required for either new COVID-19 waves or a different public health emergency. Methods: Semi-structured interviews were carried out with public transport experts, organisational leaders, workers and passengers in two phases: Phase 1 from January to May 2021, and Phase 2 from December 2021 to February 2022. Interviews were analysed thematically. Results: Using the 'What? So What? Now What?' reflective model, ideas are drawn out to describe (a) what changes occurred, (b) what effects these changes had on service provision as well as perceptions of risk and mitigation and (c) what lessons have been learned and how these findings can feed into pandemic preparedness for the future. Respondent reflections focussed on the importance of communication, leadership, and maintaining compliance. Conclusions: The wealth of experience gained through the COVID-19 pandemic in the public transport sector is extremely valuable. Through reflection on this experience, specific recommendations are made relating to these factors, covering: maintaining links across industry, access to information and data, understanding of mitigation effectiveness, improving messaging, challenges of behavioural mitigations, and clear lines of accountability. The recommendations made on the basis of this reflective process will help to improve public health strategy within the public transport sector. [ABSTRACT FROM AUTHOR]

At the end of 2019, the media cycle was taken over by the news about the coronavirus, soon the whole world was enveloped by the COVID-19 pandemic. According to the New York Times, currently, the number is 4,297,830 deaths worldwide, 202,872,928 total cases. In Brazil, so far, 20,165,672 cases have been registered. Despite the great emergence of this pandemic by the virus caused by SARS-CoV-2 in our country and in the world, several options of diagnostic methodologies have been treated to help us detect this agent, helping to prevent its spread, detecting those who have already had a disease and, in some cases, favoring early treatment. This paper aims at each of these methods, describing how each one of them works in the diagnosis of COVID-19. This work is a bibliographic study, descriptive of the type of integrative literature review, starting from the bibliographic survey and analysisof bibliographic data available from previous researches. [ABSTRACT FROM AUTHOR]

Since December 2019, a novel coronavirus disease (COVID-19) has infected millions of individuals. This paper conducts a thorough study of the use of deep learning (DL) and federated learning (FL) approaches to COVID-19 screening. To begin, an evaluation of research articles published between 1 January 2020 and 28 June 2023 is presented, considering the preferred reporting items of systematic reviews and meta-analysis (PRISMA) guidelines. The review compares various datasets on medical imaging, including X-ray, computed tomography (CT) scans, and ultrasound images, in terms of the number of images, COVID-19 samples, and classes in the datasets. Following that, a description of existing DL algorithms applied to various datasets is offered. Additionally, a summary of recent work on FL for COVID-19 screening is provided. Efforts to improve the quality of FL models are comprehensively reviewed and objectively evaluated. [ABSTRACT FROM AUTHOR]

The objective of this paper is to provide an insight on effect of stringency in Covid-19 spread in India especially in Chennai, a city were more lockdown, and restrictions was imposed to control the infection. Even though the restriction was imposed in the country by the end of March 2020, the growth reduction was seen in the mid of June as the awareness was increased. The average Covid-19 case growth was got reduce from 3.43 to 2.62% by July mid. To analysis the impact of stringency, a detailed analysis was done on Chennai city which was imposed with more repeated lockdowns to flatten the curve. We tried to fit a regression line with three difference scenario of data. The results show a promising R-squared and p value, with a right skewed distribution normal probability plot. The impact of lockdown in people's lives in different sectors were also discussed in this paper. [ABSTRACT FROM AUTHOR]

It is no doubt that the outbreak of the novel coronavirus caught the world including South Africa, off-guard. This statement refers in particular, to the fact that the outbreak of the pandemic firstly exposed the level of unpreparedness of government and its different departments, including the private sector to deal with unforeseen outbreaks like the coronavirus which leads to COVID-19. This is a typical example of systemic problems within the government and the private sector. Secondly and most importantly, this outbreak exposed the level of inequality between schools in rural areas and those in townships and affluent parts of the country which are mostly habited by black middle class and white people. The purpose of this paper is to investigate the systemic challenges and the emotional impact of this virus on the learners and their parents; the learners and their teachers, and to venture into the policymaking and implementation terrain of the Department of Basic education with a specific focus on how the DBE responded to the outbreak. Furthermore, this paper makes a case out of the emerging case by case approach of the government and the DBE in dealing with the threats which are posed by this pandemic to communities and schools. The researchers hold the view that this paper will expose the levels of inequality between schools in different parts of the country and advocate for a culture of foresight in the education management system; a culture that acknowledges that schools, like communities and business entities, are vulnerable and susceptible to external forces that may have long-lasting effects on their functionality. [ABSTRACT FROM AUTHOR]

Simple Summary: As COVID-19 shifts from pandemic to endemic, emerging variants may be more or less virulent. Predicting whether an emerging COVID-19 variant has of high risk of causing severe disease is needed to plan for potential burdens on hospital capacity and protecting vulnerable populations. However, it takes time to do laboratory and animal experiments to determine whether a new genetic variant might be more severe, and the results may not be representative of when the virus infects humans. By the time there is epidemiological data on the severity of disease associated with a new variant, it can be too late for designing an optimal public health response. There is a critical need for computer models that can predict severe disease risk from genetic sequence data, which can be obtained from just the first few infections in a potential incoming wave. Two key challenges make computer modeling difficult: (1) sequence changes are complex, and (2) using historical data to predict future disease requires accounting for the confounding effects of changing patient demographics, improving therapeutics, and increased vaccination. In this paper, we introduce a novel interpretable deep learning architecture to solve this problem, demonstrating that it can make robust predictions for emerging variants. Through the COVID-19 pandemic, SARS-CoV-2 has gained and lost multiple mutations in novel or unexpected combinations. Predicting how complex mutations affect COVID-19 disease severity is critical in planning public health responses as the virus continues to evolve. This paper presents a novel computational framework to complement conventional lineage classification and applies it to predict the severe disease potential of viral genetic variation. The transformer-based neural network model architecture has additional layers that provide sample embeddings and sequence-wide attention for interpretation and visualization. First, training a model to predict SARS-CoV-2 taxonomy validates the architecture's interpretability. Second, an interpretable predictive model of disease severity is trained on spike protein sequence and patient metadata from GISAID. Confounding effects of changing patient demographics, increasing vaccination rates, and improving treatment over time are addressed by including demographics and case date as independent input to the neural network model. The resulting model can be interpreted to identify potentially significant virus mutations and proves to be a robust predctive tool. Although trained on sequence data obtained entirely before the availability of empirical data for Omicron, the model can predict the Omicron's reduced risk of severe disease, in accord with epidemiological and experimental data. [ABSTRACT FROM AUTHOR]

During the year 2020, the COVID-19 pandemic affected mobility around the world, significantly reducing the number of trips by public transport. In this paper, we study its impact in five South American capitals (i.e., Bogotá, Buenos Aires, Lima, Quito and Santiago). A decline in public transport patronage could be very bad news for these cities in the long term, particularly if users change to less sustainable modes, such as cars or motorbikes. Notwithstanding, it could be even beneficial if users selected more sustainable modes, such as active transport (e.g., bicycles and walking). To better understand this phenomenon in the short term, we conducted surveys in these five cities looking for the main explanation for changes from public transport to active and private modes in terms of user perceptions, activity patterns and sociodemographic information. To forecast people's mode shifts in each city, we integrated both objective and subjective information collected in this study using a SEM-MIMIC model. We found five latent variables (i.e., COVID-19 impact, Entities response , Health risk , Life related activities comfort and Subjective well-being), two COVID-19 related attributes (i.e. , new cases and deaths), two trip attributes (i.e., cost savings and time), and six socio-demographic attributes (i.e. , age, civil status, household characteristics, income level , occupation and gender) influencing the shift from public transport to other modes. Furthermore, both the number of cases and the number of deaths caused by COVID-19 increased the probability of moving from public transport to other modes but, in general, we found a smaller probability of moving to active modes than to private modes. The paper proposes a novel way for understanding geographical and contextual similarities in the pandemic scenario for these metropolises from a transportation perspective. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to proffer a glimpse of diverse e-resources and materials accumulated by National Digital Library of India (NDLI) for facilitating open access resources (OARs) during the difficult times of global pandemic. Out of all the resources, an attempt has been made to place a focus on COVID-19 research repository maintained at NDLI platform to facilitate related research activities for envisaging experiments by scientists and researchers. Design/methodology/approach: The study is based on COVID-19 research repository assimilated by NDLI, and a detailed investigative research has been made about various resources and materials available for research community. The official website of NDLI (direct link of NDLI website: https://ndl.iitkgp.ac.in/) has been referred for collection of requisite data for study. The collected information has been presented through eight tables, two charts and two figures, which have further been analyzed and interpreted to attain the objectives. Findings: The brief examples in this paper indicates that a wealth of OARs related to COVID-19 such as scholarly communications, data sets, documents and videos and journals and conferences, etc. are available for access and research by scientists and researchers to expand their research during and also beyond this global crisis. Social distancing has forced academics to displace to online platform from physical deliverables. Institutions are forced to adopt new technologies for delivering education in online mode such as online teaching, online access of educational resources, online conferences, webinars and a host of such related activities. NDLI has been instrumental in this journey by accumulating providing research materials through its platform. Originality/value: In addition to the blended learning process, this paper provides a structured overview about COVID-19 research repository facilitated by NDLI to provide access about related research activities by scientists and researchers. This investigative research on NDLI platform has been done originally by the author with a sacrosanct aim to help serious academia and has a high referral value for the scientific, technocratic and realistic researchers with deep thrust on availability of all materials under one roof, i.e. NDLI. [ABSTRACT FROM AUTHOR]

Background: The global community has battled the spread of SAR-CoV-2 for almost 2 years, and the projection is that the virus may be recurrent like the seasonal flu. The SARS-CoV-2 pandemic disrupted activities within the food supply chain that cost billions of dollars globally. This has heightened concerns about fomite spread of the virus through surfaces. There is an urgent need to understand the risk portends by this virus along the produce supply chain with conditions (low temperature and high relative humidity) conducive to extended survival of the virus. Main body: Pre-dating SARS-CoV-2 are other types of coronaviruses that had lower infection and mortality rates. There are some similarities between the former and the new coronavirus, especially with regards to transmission modes and their survivability on surfaces. There is evidence of other coronaviruses' survival on surfaces for weeks. Currently, there are limited evidence-based studies to enlighten us on how the virus is transmitted within the produce supply chain. A few studies claim that the virus could spread through the cold supply chains. However, these are not sufficient to make a conclusive inference about the deadly SARS-CoV-2. Conclusions: This paper provides a succinct review of the literature on current understanding of the transmission, survivability, and risk SARS-CoV-2 portend to humans within the produce supply chain and calls for more evidence-based research to allay or alert us of the potential risk of fomite transmission of SARS-CoV-2. The paper also highlights examples of conventional and novel non-thermal inactivation and sanitation methods applicable to this type of virus. [ABSTRACT FROM AUTHOR]

An outbreak of coronavirus disease 2019 (COVID-19) occurred in Wuhan and it has rapidly spread to almost all parts of the world. In the field of Medical Science, concerning the definition of the topological index on the molecular structure and corresponding medical, biological, chemical, pharmaceutical properties of drugs can be studied by the topological index calculation. In this paper, we compute some of the general topological properties of chloroquine and hydroxychloroquine used to inhibit the outbreak of coronavirus disease-19. The results in this paper may be useful in finding new drug and vaccine for the treatment and prevention of COVID-19. [ABSTRACT FROM AUTHOR]

The entire world has been affected by the outbreak of COVID-19 since early 2020. Human carriers are largely the spreaders of this new disease, and it spreads much faster compared to previously identified coronaviruses and other flu viruses. Although vaccines have been invented and released, it will still be a challenge to overcome this disease. To save lives, it is important to better understand how the virus is transmitted from one host to another and how future areas of infection can be predicted. Recently, the second wave of infection has hit multiple countries, and governments have implemented necessary measures to tackle the spread of the virus. We investigated the three phases of COVID-19 research through a selected list of mathematical modeling articles. To take the necessary measures, it is important to understand the transmission dynamics of the disease, and mathematical modeling has been considered a proven technique in predicting such dynamics. To this end, this paper summarizes all the available mathematical models that have been used in predicting the transmission of COVID-19. A total of nine mathematical models have been thoroughly reviewed and characterized in this work, so as to understand the intrinsic properties of each model in predicting disease transmission dynamics. The application of these nine models in predicting COVID-19 transmission dynamics is presented with a case study, along with detailed comparisons of these models. Toward the end of the paper, key behavioral properties of each model, relevant challenges and future directions are discussed. [ABSTRACT FROM AUTHOR]

During the last three years, numerous research papers have been reported which use social media data to explore several issues related to the COVID-19 pandemic. Bibliometric methods in this work are used to analyze 1427 peer-reviewed documents from the last three years extracted from the Web of Science database. The results of this study show that there was high growth in publications in open access journals with an annual rate reaching 19.3% and they also identify the top cited journals and research papers. The thematic analysis of papers shows that research topics related to social media for surveillance and monitoring of public attitudes and perceptions, mental health, misinformation, and fake news are important and well-developed, whereas topics related to distance-learning education with social media are emerging. The results also show that the USA, China, and the UK have published many papers and received a high number of citations because of their strong international collaboration. [ABSTRACT FROM AUTHOR]

Coronavirus is one of the serious threat and challenge for existing healthcare systems. Several prevention methods and precautions have been proposed by medical specialists to treat the virus and secure infected patients. Deep learning methods have been adopted for disease detection, especially for medical image classification. In this paper, we proposed a deep learning-based medical image classification for COVID-19 patients namely deep learning model for coronavirus (DLM-COVID-19). The proposed model improves the medical image classification and optimization for better disease diagnosis. This paper also proposes a mobile application for COVID-19 patient detection using a self-assessment test combined with medical expertise and diagnose and prevent the virus using the online system. The proposed deep learning model is evaluated with existing algorithms where it shows better performance in terms of sensitivity, specificity, and accuracy. Whereas the proposed application also helps to overcome the virus risk and spread. [ABSTRACT FROM AUTHOR]

Background: The COVID‐19 pandemic has highlighted the importance of transparency and scientific rigour in the development of clinical guidance. Rapid review methodologies were widely used in the development of guidance, and in the United Kingdom, COVID‐19 guidance was criticized for methodological inadequacy and erroneous conclusions. Aims: To summarize the evidence looking at the use of face masks to prevent COVID‐19 infection in clinical practice areas, and to show how this can be used in decision‐making. Design: Overview of systematic reviews. Method: Systematic reviews which included meta‐analyses were sought, and data on the protective effect of face masks on COVID‐19 transmission were extracted. A total of 15 papers yielded 44 effect sizes suitable for quantitative presentation, which showed wide variation in effect depending on the outcome and intervention chosen. Conclusions: Guideline development groups need to take care to choose outcomes that are of most importance to those who are the target of guidance. Quantification of the protective effect of interventions such as different types of face mask will help nurses and others decide on the utility of their use, alongside consideration of the other factors that go into informing clinical recommendations. Implications for Patient Care and the Profession: COVID‐19 has been an unprecedented public health issue, but much clinical guidance was lacking in transparency. Nurses and other healthcare professionals have often expressed a lack of confidence in guidance. Systematic reviews reported a wide range of effect sizes. However, there was a high degree of indirectness and heterogeneity in methods and findings. To produce transparent guidance, those for whom guidance is intended should have evidence of effect where this is available. Impact Guideline authors should reflect these outcomes in their recommendations, clearly balancing both the benefits and harms of recommending face masks to prevent COVID‐19. [ABSTRACT FROM AUTHOR]

The coronavirus pandemic has been globally impacting the health and prosperity of people. A persistent increase in the number of positive cases has boost the stress among governments across the globe. There is a need of approach which gives more accurate predictions of outbreak. This paper presents a novel approach called diffusion prediction model for prediction of number of coronavirus cases in four countries: India, France, China and Nepal. Diffusion prediction model works on the diffusion process of the human contact. Model considers two forms of spread: when the spread takes time after infecting one person and when the spread is immediate after infecting one person. It makes the proposed model different over other state-of-the art models. It is giving more accurate results than other state-of-the art models. The proposed diffusion prediction model forecasts the number of new cases expected to occur in next 4 weeks. The model has predicted the number of confirmed cases, recovered cases, deaths and active cases. The model can facilitate government to be well prepared for any abrupt rise in this pandemic. The performance is evaluated in terms of accuracy and error rate and compared with the prediction results of support vector machine, logistic regression model and convolution neural network. The results prove the efficiency of the proposed model. [ABSTRACT FROM AUTHOR]

Little is known about how portrayals of American unity (i.e. "we're all in this together") have been received by essential workers on the front lines of the COVID risk divide, and how the pandemic may have contributed to perceptions of class inequality among lower-income workers. In this paper, we draw upon 192 in-depth interviews with precarious and gig-based workers in New York City. We find that during the height of the first wave of the pandemic, precarious workers often expressed frustration over class-based inequalities and antagonism toward elites. Many respondents expressed significant skepticism toward messages that the pandemic has brought Americans together. Instead, workers identified two distinct, class-based realities in New York: elite Americans are able to socially-distance in "mansions," or on "yachts," while precarious workers struggled to weather the storm in "dinghies." Likewise, workers felt "abandoned" by wealthy owners and managers, who fled the city to socially-distanced homes in beach communities and surrounding suburbs. Our findings suggest that low-wage, high-risk workers articulate complex conceptualizations of inequality and convey grievances toward elites during the pandemic. This study contributes to broader literature on perceived inequality, the rise of noxious work, and the social consequences of COVID-19. [ABSTRACT FROM AUTHOR]

The novel coronavirus (COVID-19) pandemic still has a significant impact on the worldwide population's health and well-being. Effective patient screening, including radiological examination employing chest radiography as one of the main screening modalities, is an important step in the battle against the disease. Indeed, the earliest studies on COVID-19 found that patients infected with COVID-19 present with characteristic anomalies in chest radiography. In this paper, we introduce COVID-ConvNet, a deep convolutional neural network (DCNN) design suitable for detecting COVID-19 symptoms from chest X-ray (CXR) scans. The proposed deep learning (DL) model was trained and evaluated using 21,165 CXR images from the COVID-19 Database, a publicly available dataset. The experimental results demonstrate that our COVID-ConvNet model has a high prediction accuracy at 97.43% and outperforms recent related works by up to 5.9% in terms of prediction accuracy. [ABSTRACT FROM AUTHOR]

Background: Coronavirus-19 disease (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Respiratory viruses damage not only the upper respiratory tract in humans, but also several different organs such as the brain. Some of the neurological consequences of COVID-19 reported are anosmia, headache, stroke, declined cognitive function, and impaired mental health, among others. People who had COVID-19 have a higher risk of sequelae in the central nervous system (CNS). However, it is not known which are all possible sequelae and how long will last the long-term effects of the COVID-19 pandemic on behavioral patterns and quality of life. Aim: We intend to address the long-term impacts of COVID-19 on mental health and the relevance of physical exercise during the pandemic. Methods: We conducted a literature search using PubMed to find the articles that were related to these themes. Results: We found 23,489 papers initially, and then we applied the inclusion/exclusion criteria to narrow down our search to 3617 articles and selected 1380 eligible articles after a thorough reading of titles and abstracts. The findings indicated that COVID-19 impacted general mental health and led many not only hospitalized patients to develop cognitive decline, memory impairment, anxiety, sleep alterations, and depressive-like behavior. Furthermore, the fear of vaccines and their effects had negatively affected mental health and directly impacted mortality rates in unvaccinated COVID-19 patients. Conclusions: Preventive measures must be undertaken, such as the vaccination of the entire population, vaccination hesitancy discouragement by creating awareness among individuals, and people's engagement in a physically active lifestyle, since being physically active is a low-cost and effective measure to restore or inhibit the negative outcomes from COVID-19 on mental health. [ABSTRACT FROM AUTHOR]

Indonesia, like many other countries, has encountered a slew of social, political, economic, and public health challenges in the aftermath of the COVID-19 pandemic. In response to these challenges, the Indonesian government implemented security measures by instituting large-scale social restrictions (Indonesian: Pembatasan Sosial Berskala Besar) and, later, micro-scale social restrictions (Pemberlakukan Pembatasan Kegiatan Masyarakat) to restrict people’s mobility and virus transmission. Using securitisation theory as a framework, this article examines how the nationwide dilemma between public health and economic security arose. Based on official documents, government papers, and political speeches, this study reveals how the country’s COVID-19 responses were largely defined by carefully constructed and flexible measures known as the ‘gas and brake’ policy (Kebijakan Gas dan Rem), which were aimed at resolving the health-economic dilemma. This policy is deemed appropriate given the country’s limited public health and economic resources, despite the fact that many argue that such an approach reflects indecisiveness and a lack of coordination among the country’s authorities. This article also demonstrates that policymakers in Indonesia use this policy to resolve the securitisation dilemma by reinforcing the hierarchical ordering of security sectors as a readjustment strategy. The policy is used to justify tightening or easing social restrictions by changing the security narrative throughout the pandemic. [ABSTRACT FROM AUTHOR]

The expansion of the Covid-19 virus in early 2020 grew in parallel with the spread of rumours, false or unverified news and even contradictions between information sources and health sources. It has been the first pandemic to be broadcast live on social media and has generated disinformation which was described by the WHO as an "infodemic", a pandemic as serious as the virus itself. The aim was to identify and analyse the impact generated by the first wave of Covid-19 (January-June 2020) on public health communication. The review was carried out under the Prisma guidelines. A systematic search was performed in PubMed, Scopus and Web of Science databases, which yielded a figure of 1.157 papers. Using seven keywords as a filter a corpus of 193 articles was reached. Four main themes were identified: 1) Need for massive public health literacy; 2) Social networks as an information and disinformation during pandemic; (3) The uncertain response of institutional communication; and (4) Media coverage of the pandemic. The authors propose large-scale health literacy and point out the need to work on health information together -governments, health institutions and the media-. [ABSTRACT FROM AUTHOR]

COVID-19 is known in recent times as a severe syndrome of respiratory organ (Lungs) and has gradually produced pneumonia, a lung disorder all around the world. As coronavirus is continually spreading rapidly globally, the computed tomography (CT) technique has been made important and essential for quick diagnosis of this dangerous syndrome. Hence, it is necessitated to develop a precise computer-based technique for assisting medical clinicians in identifying the COVID-19 influenced patients with the help of CT scan images. Therefore, the multilayer perceptron neural networks optimized with Garra Rufa Fish optimization using images of CT scan is proposed in this paper for the classification of COVID-19 patients (COV-19-MPNN-GRF-CTI). The input images are taken from SARS-COV-2 CT-scan dataset. Initially, the input images are pre-processed utilizing convolutional auto-encoder (CAE) to enhance the quality of the input images by eliminating noises. The pre-processed images are fed to Residual Network (ResNet-50) for extracting the global and statistical features. The extraction over the features of CT scan images is made through ResNet-50 and subsequently input to multilayer perceptron neural networks (MPNN) for CT images classification as COVID-19 and Non-COVID-19 patients. Here, the layer of Batch Normalization of the MPNN is separated and added with ResNet-50 layer. Generally, MPNN classifier does not divulge any adoption of optimization approach for calculating the optimal parameters and accurately classifying the extracted features of CT images. The Garra Rufa Fish (GRF) optimization algorithm performs to optimize the weight parameters of MPNN classifiers. The proposed approach is executed in MATLAB. The performance metrics, such as sensitivity, precision, specificity, F -measure, accuracy and error rate, are examined. Then the performance of the proposed COV-19-MPNN-GRF-CTI method provides 22.08%, 24.03%, 34.76% higher accuracy, 23.34%, 26.45%, 34.44% higher precision, 33.98%, 21.95%, 34.78% lower error rate compared with the existing methods, like multi-task deep learning using CT image analysis for COVID-19 pneumonia classification and segmentation (COV-19-MDP-CTI), COVID-19 classification utilizing CT scan depending on meta-classifier approach (COV-19-SEMC-CTI) and deep learning-based COVID-19 prediction utilizing CT scan images (COV-19-CNN-CTI), respectively. [ABSTRACT FROM AUTHOR]

In response to the heightened risk that coronavirus disease 2019 (COVID-19) poses to the health and lives of people with obesity, in 2020 the U.K. government launched a new package of policies intended to stimulate weight loss among the country's population. In this article, I present a critical discourse analysis of the policy paper which announced these new measures. I identify the discourses that are used to represent things, people, and processes in this policy text. These discourses are interpreted in terms of broadly neoliberal ideologies of public health management. Taken together, the discourses identified contribute to a broadly neoliberal ideology of public health management. It is argued that the policy paper represents an instance of "lifestyle drift," as it initially appears to engage with social and economic determinants of health but ultimately neglects these in favor of focusing on individual lifestyle factors, particularly in the shape of individuals' "choices." [ABSTRACT FROM AUTHOR]

Novel coronavirus (COVID-19) pandemic, has raised a serious situation across world human population and has become serious threat as contagious outbreak. This paper aims to overview the recently intelligent systems based on Artificial Intelligence using different medical imaging modalities like Computer Tomography (CT) and X-ray. This paper specifically discusses the machine learning techniques developed for COVID-19 diagnosis and provides insights on well-known data sets used to train these AI based networks. It also highlights the use of AI in COVID detection and classification at faster process where normal COVID testing takes couple of days to produce. Finally, we conclude by addressing the challenges associated with the use of Machine Leaming methods for COVID-19 detection and probable future trends in this research area. This paper is intended to provide experts (medical or otherwise) and technicians with new insights into the ways machine learning techniques are used and how they potentially further work in com batting the outbreak of CO VID-19. [ABSTRACT FROM AUTHOR]

This paper explores a contingent sub-public sphere promoted by a group of former critical journalists in China during the coronavirus outbreak at the beginning of 2020. During the initial outbreak of coronavirus in China, the observed former journalists, who left the field of critical journalism during the re-structure of Chinese news industries under Xi Jinping's leadership, drew on their knowledge of Chinese politics and censorship to contest information cover-up by the state, online censorship, and the state's discourses of China as a successful model of combating the virus. Their activities effectively engaged mass participation of Chinese people and promoted critical opinions of the public. The paper bears the primary aim to deepen the understanding of the episodic formation of elite-driven public spheres in China by investigating the nuances of each case. I therefore, in this particular case study, explore concepts of habitus and capital from Bourdieu's field theory as analytical tools in the investigation of the persistence of political participation and government scrutiny by former critical journalists on social media after leaving the field of critical journalism. The empirical research combines materials collected through 15 former critical journalists' WeChat accounts between January and May 2020, along with in-depth interviews. [ABSTRACT FROM AUTHOR]

COVID-19 outbreaks are the critical challenge to the administrative units of all worldwide nations. India is also more concerned about monitoring the virus's spread to control its growth rate by stringent behaviour. The present COVID-19 situation has huge impact in India, and the results of various preventive measures are discussed in this paper. This research presents different trends and patterns of data sources of States that suffered from the second wave of COVID-19 in India until 3rd July 2021. The data sources were collected from the Indian Ministry of Health and Family Welfare. This work reacts particularly to many research activities to discover the lockdown effects to control the virus through traditional methods to recover and safeguard the pandemic. The second wave caused more losses in the economy than the first wave and increased the death rate. To avoid this, various methods were developed to find infected cases during the regulated national lockdown, but the infected cases still harmed unregulated incidents. The COVID-19 forecasts were made on 3rd July 2021, using exponential simulation. This paper deals with the methods to control the second wave giving various analyses reports showing the impact of lockdown effects. This highly helps to safeguard from the spread of the future pandemic. [ABSTRACT FROM AUTHOR]

Kōfuku no Kagaku is a most visible new religious actor in contemporary Japan thanks to the vast publishing activities of its founder and its widespread professional use of new media. This paper examines how Kōfuku no Kagaku engages with the COVID-19 pandemic in practical and doctrinal terms. Notably, early in the pandemic, Kōfuku no Kagaku's international promotion of spiritual cures and vaccines even prompted The New York Times to feature the group in a widely circulated article in April 2020. This paper outlines these "spiritual technologies" and examines their doctrinal rationale as well as the wider doctrinal appropriation of the COVID-19 pandemic. It will be shown how the latter is instrumentalised to echo Kōfuku no Kagaku's millenarian agenda. [ABSTRACT FROM AUTHOR]

The sequencing of SARS-CoV-2 provides essential information on viral evolution, transmission, and epidemiology. In this paper, we performed the whole-genome sequencing of SARS-CoV-2 using nanopore and Illumina sequencing to describe the circulation of the virus lineages in Armenia. The analysis of 145 full genomes identified six clades (19A, 20A, 20B, 20I, 21J, and 21K) and considerable intra-clade PANGO lineage diversity. Phylodynamic and transmission analysis allowed to attribute specific clades as well as infer their importation routes. Thus, the first two waves of positive case increase were caused by the 20B clade, the third peak caused by the 20I (Alpha), while the last two peaks were caused by the 21J (Delta) and 21K (Omicron) variants. The functional analyses of mutations in sequences largely affected epitopes associated with protective HLA loci and did not cause the loss of the signal in PCR tests targeting ORF1ab and N genes as confirmed by RT-PCR. We also compared the performance of nanopore and Illumina short-read sequencing and showed the utility of nanopore sequencing as an efficient and affordable alternative for large-scale molecular epidemiology research. Thus, our paper describes new data on the genomic diversity of SARS-CoV-2 variants in Armenia in the global context of the virus molecular genomic surveillance. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic that has gripped the world stands unprecedented in living memory. The crisis presented by the COVID-19 pandemic is urgent, massive in impacts, and global in scale. First recorded in Wuhan, China, the virus caught the world unprepared; developed and developing nations are struggling to contain it. While many studies have failed to move beyond the biomedical foundation of the virus, this paper attempts to capture the underlying socio-economic factors of the COVID-19 pandemic in the context of the neoliberal order and its resulting crisis, which saw the dismantling of the post-war welfare state. Against this background, this paper demonstrates how the COVID-19 pandemic exposed the inadequacies of self-regulating marketbased solutions. As a way forward, the paper has made a strong case for a return to the welfare state as an alternative to the free market system that has characterised the age of neoliberalism. [ABSTRACT FROM AUTHOR]

Purpose : The main objective of this study was to provide a comprehensive overview of the latest studies on COVID-19-related social work issues. Method : This systematic review aimed to collect, review, and synthesize all COVID-19-related papers published in 43 major social work journals, a year after the first known case was reported. Results: The final sample (n = 256) consisted of 85 research articles and 171 in other formats. All the studies involved a total of 46,195 research participants. The majority of papers (75.4%) could be accessed freely online. Service users including families, students, older adults, caregivers, refugees, patients, health care workers, etc. were either researched or discussed. Discussion: Gerontological social work was one of the fields that received ample attention. Papers published in the Journal of Gerontological Social Work yielded the highest number of citations. Academics and social workers came up with innovative ways of practicing and researching during the pandemic. [ABSTRACT FROM AUTHOR]