The coronavirus 2019 (Covid-19) pandemic has emerged as a global phenomenon that significantly affects almost all sectors, irrespective of whether they have a well-established economic system. The inception of COVID-19 pandemic has increased and accelerated the demand for opera industry embrace digit technology to continue to produce performances and reach audiences. The brutality of the Covid-19 pandemic has affected most sectors, and opera artists are significantly affected in the Global South. South Africa, among others, is at the receiving end. The Covid-19 pandemic has wreaked havoc and exacerbated the existing vulnerability of opera artists. Opera artists have difficulty obtaining employment and finding funding for performing arts organisations have caused seriously challenged opera artists to survive during the Covid-19 pandemic. This study is aimed to examine the quest for new digital skills for opera artists and opera companies during the Covid-19 pandemic. A qualitative research method was adopted using interviews with opera artists, selected retired opera practitioners and managers of opera companies. In this study, scholarly documents were reviewed to yield trustworthy findings. The findings demonstrate a high demand for opera artists to upgrade their current skills to meet the demand for digital skills. This demand for digital skills is partially attributable to the closed and suspension of live theatre performances due to the Covid-19 pandemic. The findings also reveal that digital connectivity in the performing arts sector become an essential driver of economic growth. This study concludes by affirming that digital skills are key skills required for resuscitating the opera industry.

Objectives Assess rates of adverse events (AE) after COVID-19 vaccines experienced by women of reproductive age, focusing on pregnancy and menstruation, using data collected by the US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS) database. Design Population-based retrospective cohort study. Setting US and global entries in US Centers for Disease Control and Prevention (CDC) Vaccine Adverse Events Reporting System (VAERS). Participants CDC VAERS entries from January 1, 1998 to June 30, 2022. Interventions None. Main Outcome Measures A proportional reporting ratio analysis is performed using data in the VAERS system comparing adverse events (AE) reported post-COVID-19 vaccines with that of post-Influenza vaccines. Results COVID-19 vaccines, when compared to the Influenza vaccines, are associated with a significant increase in AE with all proportional reporting ratios of > 2.0: menstrual abnormalities, miscarriage, fetal chromosomal abnormalities, fetal malformation, fetal cystic hygroma, fetal cardiac disorders, fetal arrhythmias, fetal cardiac arrest, fetal vascular malperfusion, fetal growth abnormalities, fetal abnormal surveillance, fetal placental thrombosis, low amniotic fluid, preeclampsia, premature delivery, preterm premature rupture of membrane, fetal death/stillbirth, and premature baby death (all p values were much smaller than 0.05). When normalized by time-available, doses-given, or persons-received, all COVID-19 vaccine AE far exceed the safety signal on all recognized thresholds. Conclusions Pregnancy complications and menstrual abnormalities are significantly more frequent following COVID-19 vaccinations than Influenza vaccinations. A worldwide moratorium on the use of COVID-19 vaccines in pregnancy is advised until randomized prospective trials document safety in pregnancy and long-term follow-up in offspring.

Background: Young adults, particularly university students might be at greater risk of developing psychological distress, and exhibiting symptoms of anxiety and depression during the COVID-19 pandemic. Objective: The primary objective of this study was to explore and compare the determinants and predictors of mental health (anxiety and depression) during and after COVID-19 lockdown among university students. Methods: This was an observational, cross-sectional study with a sample size of 417 students. An online survey utilizing International Physical Activity Questionnaire–Short Form (IPAQ-SF), General Anxiety Disorder–7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) was distributed to Universiti Tunku Abdul Rahman students via Google forms. Results: During lockdown, family income [χ² (1, n=124) = 5.155, p=0.023], and physical activity [χ² (1, n=134) = 6.366, p=0.012] were associated with anxiety, while depression was associated with gender [χ² (1, n=75) = 4.655, p=0.031]. After lockdown, family income was found to be associated with both anxiety [χ2 (1, n=111) = 8.089, p=0.004], and depression [χ2 (1, n=115) =9.305, p=0.002]. During lockdown, family income (OR=1.60, p=0.018), and physical activity (OR=0.59, p=0.011) were predictors for anxiety, and gender (OR=0.65, p=0.046) being the only predictor for depression. After lockdown, family income was a predictor for both anxiety (OR=1.67, p=0.011), and depression (OR=1.70, p=0.009). Conclusion: Significant negative effects attributed to the COVID-19 lockdown, and certain factors predisposed to the worsening of mental health status in university students. Family income, physical activity level, and gender were some of the major determinants that influenced the anxiety and depression.

During the COVID-19 pandemic, percutaneous tracheostomy proved to be an effective option in the management of patients with prolonged periods of intubation; in fact, among other things, it allowed early discharge from ICUs and contributed to reducing overcrowding in intensive care settings, a central critical point in the COVID pandemic. As a direct consequence, the management and the weaning of frail, tracheostomized and ventilated patients was diverted to sub-intensive or normal hospitalisation wards. One central challenge in this setting is the resumption of swallowing and oral feeding, which needs an interdisciplinary management involving Phoniatrician, ENT, Pneumologist and Speech Therapist. With this article, we aim to share the experience of a Swiss COVID-19 Center[1] and to draw up a narrative review on the issues concerning the management of the tracheostomy cannula during swallowing resumption, integrating the most recent evidence from the literature with the clinical experiences of the professionals directly involved in the management of tracheostomized COVID-19 patients. In view of the heterogeneity of COVID-19 patients, we believe that the procedures described in the article are applicable to a larger population of patients undergoing tracheostomy weaning.

The effects of the 2008 financial crisis undoubtedly caused problems not only to the banking sector but also to the real economy of the developed and the developing countries in almost all around the globe. Besides, as is widely known, every banking crisis entails the corresponding cost to the economy of each country affected by it, which results from the shakeout and the restructuring of its financial system. The purpose of this research is to investigate the consequences of the financial crisis and the COVID-19 health crisis and how these affected the course of the four systemic banks (Eurobank, Alpha Bank, National Bank, Piraeus Bank) through the analysis of ratios for the period of 2015-2020.

The COVID-19 pandemic has had a significant impact on all facets of life and has exacerbated many challenges faced by people living with tuberculosis (TB). This study aimed to assess the health-related quality of life (HRQoL) of TB patients in Guinea during the COVID-19 pandemic. A mixed-methods study was conducted using two validated psychometric tools to assess HRQoL and qualitative interviews among TB patients enrolled in treatment at three centers in Conakry, Guinea. Multinomial logistic regression was used to identify factors associated with the deterioration of HRQoL. We included 439 participants in the study, among whom 44% and 31% experienced pain and anxiety, respectively. We found that an increase in the number of household members and the distance from participants’ residence to the health centre were significantly associated with lower HRQoL. Qualitative interviews highlighted nutritional and financial concerns which were exacerbated during COVID-19 pandemic and beliefs that the Guinean Government’s assistance plan was insufficient. This study supports the implementation of specific relief plans for TB patients which includes nutritional and psychological support, especially those whose movements are limited by travel restrictions, impeding access to TB care, reducing work opportunities and exacerbating financial needs and stress.

Background: According to newly published studies, patients with Coronavirus Disease 2019 (COVID-19) have significantly lower serum 25-hydroxyvitamin D 25(OH)D levels than those without the SARS-CoV-2 infection. Vitamin D insufficiency may be a predictor of poor prognosis in COVID-19 patients. Vitamin D supplementation is related to improved clinical outcomes in terms of intensive care unit (ICU) admission and death, particularly in individuals with moderate-to-severe forms of COVID-19 requiring hospitalization. Materials and methods: This placebo-controlled five-day study was performed on 100 hospitalized COVID-19 patients with vitamin D insufficiency randomized into two groups. Vitamin D in the form of a sublingual sprayable microemulsion (LYL love your life® sunD3 LYLmicro™) was given three times daily after breakfast, lunch, and dinner (daily dose 12,000 IU) to 52 patients with blood vitamin D levels below 30 ng/ml. 48 patients in the control group received a placebo spray in the same daily regiment. Results: We observed a statistically significant increase by 8.6 ng/ml in median vitamin D level after five days of high-dose vitamin D3 spray therapy. 90.2% of subjects reached normal serum levels of vitamin D. There was a strong correlation between changes in vitamin D and C-reactive protein (CRP) levels in individuals with moderately severe disease (p<0.05), while mild and severe cases showed no statistical significance comparing case and control groups. There were no statistically significant changes in ferritin and interleukin-6 (IL-6) levels. Conclusions: In this study, we demonstrated the possibility to rapidly increase circulating levels of vitamin D just in 5 days of high-dose intervention and found a statistically significant decrease of CRP levels in patients with moderately severe COVID-19. We were not able to detect statistically significant changes in ferritin and IL-6 levels during the 5-day vitamin D intervention.

During the Covid-19 pandemic in Taiwan, analytical tools of PEST (political, economic, social-cultural, and technological), SWOT (strength, weakness, opportunity, threat), nine building blocks of a business model canvas, and knowledge management were combined to develop a theoretical framework, and used to assess business, smart and sustainable management of two case companies: Tung Sheng Company Limited and its subsidiary, Strong Basic Enterprise Limited. A heuristic inquiry research design was adopted. In addition to secondary data from the two case companies, major top managers were interviewed to reveal constructive questions about the existing business models and to re-interpret strategy. The results showed that case companies own capabilities of R &amp; D (research and development) as a foundation to further apply new smart ICT (information and communication technology) and execute green manufacturing. Additionally, strong key partnerships are used to diversify business investment for leveraging on limited resources given current insufficient qualified employees. Resilient practices adopted new and green technology to help mitigate the negative impacts of the Covid-19 pandemic. This study provides a useful framework and practical information about how to examine business models, smart and sustainable management processes of the two case companies and to make adjustments in strategies for the future.

The pandemic is fast moving, accelerating rapid changes that lead to new challenges and making organizations suffer an impact. A big mark has been left on the workplaces - places where we do business, because an ongoing change to remote work challenges the role of the office. It is highly possible that as the change is progressing, it is not only the workplace that will change its design, but also the way in which work will be planned, organized, done and controlled. However, as the restrictions ease up questions appear: What is the potential of office sustainability? How has the perception of flexible office space changed due to the COVID-19 pandemic? This paper used an online survey as a quantitative research method. In this paper, we looked at the employer’s vision of the office. We investigated employers’ perspectives of where and in what settings the work will be done in the post-pandemic time. Specifically, we discussed the changes employers will apply in terms of work environment and office layout. The findings suggest that an increasing mobile workforce and expansion of the new workstyle will not mean an office exodus, but will certainly have an impact on office utilization.

Background: The COVID-19 pandemic has changed the way dentistry has been practiced world over , this study sought to assess the impact of the COVID-19 pandemic on the patterns of attendance for dental treatment in a large hospital in Kuwait compare them to data from the year prior to the pandemic Methods: A total of 176,690 appointment records of 34,250 patients presenting to the AlJahra specialist hospital, Kuwait for dental treatment from April 2019 to March 2021 were analyzed. Types of procedures and the departments to which they presented were analyzed and the patterns of attendance before and during the pandemic were compared; Results: While there was a significant reduction in the number of orthodontic, endodontic and periodontal procedures there was no impact on oral surgery, restorative procedures or pediatric dentistry; Conclusions: There has been a return in the numbers of patients availing dental treatment, however, there has been a definite shift in the use of certain dental procedures .

The development of antibody therapies against SARS-CoV-2 remains a challenging task during the ongoing COVID-19 pandemic. All approved therapeutic antibodies are directed against the receptor binding domain (RBD) of Spike and lost neutralization efficacy against continuously emerging SARS-CoV-2 variants, which especially mutate in the RBD region. Previously, phage display has been used to identify epitopes of antibody responses against several diseases. Such epitopes have been applied to design vaccines or neutralizing antibodies. Here, we constructed an ORFeome phage display library for the SARS-CoV-2 genome. Open reading frames (ORFs) representing the SARS-CoV-2 genome were displayed on the surface of phage particles in order to identify enriched immunogenic epitopes from COVID-19 patients. Library quality was assessed by both, NGS and epitope mapping of a monoclonal antibody with known binding site. The most prominent epitope captured represented parts of Spike´s fusion peptide (FP). It is associated with the cell entry mechanism of SARS-CoV-2 into the host cell and the serine protease TMPRSS2 cleaves Spike within this sequence. Blocking of this mechanism could be a potential target for non-RBD binding therapeutic anti-SARS-CoV-2 antibodies. As mutations within the FP amino acid sequence were rather rare among SARS-CoV-2 variants so far, this may be an advantage in the fight against future virus variants.

Rare cardiac adverse events are reported post vaccinations. For the SARS-CoV-2 vaccines, higher numbers of these cardiac adverse events are being reported with myocarditis disproportionately occurring in younger males. The etiology of these cardiac adverse events associated with vaccines including SARS-CoV-2 is unknown. The etiology of the higher frequency of these cardiac adverse events temporally associated with SARS-CoV-2 vaccines is also unknown. This article proposes that innate immune responses to vaccines cause elevated histamine levels post vaccination; the histamine level reached may exceed the vaccinees’ histamine tolerance level for several days. This article proposes that the elevated histamine level is causative for the reported cardiac adverse events. For myocarditis reported adverse events, this article proposes that elevated histamine levels induce cardiac capillary pericyte induced vasoconstrictions followed by localized ischemia and anoxia; this is followed by the release of troponin from myocyte cells affected by anoxia. This hypothesis is supported by the temporal onset timing of adverse events reported following SARS-CoV-2 vaccinations in the United States Department of Health and Human Services Vaccine Adverse Event Reporting System (VAERS). This model applies to multiple vaccines with innate immune response histamine levels generated varying by each vaccine and incidence frequencies correlate with vaccine reactogenicity.

Research have been conducted in many countries around the world to assess air quality during COVID-19 pandemic, especially during lockdown period, some of these studies found an increase or decrease in some pollutants. This paper investigates the impact of COVID-19 on seven air pollutants (i.e., PM_2.5, PM₁₀, NO₂, O₃, SO₂, H₂S, CO) from the period January 2020 to December 2020 in the State of Kuwait. Kuwait is a desert country located in the north-eastern part of the Arabian Peninsula, and the northeast of the Arabian Gulf (Persian as it is sometimes called). Several analytical methods were conducted, such as spatial analysis (spatial interpolation) to study the distribution of the studied variables. The data was also statistically analysed (time series analysis - Kernel density) to study the temporal changes. The analysis also included applying air quality index to the data. We found that concentrations for the pollutants decreased during the pandemic due to the decrease of anthropogenic sources including such as traffic and petroleum activities, but the concentration for PM_2.5 increased, mostly because of the transported dust coming with the northwest winds prevailing in Kuwait from the Arabian deserts and Iraq.

Abstract The article discusses about the current situation of Novel Corona Virus also called as the COVID-19 that hinder for all human’s life including the education. Rapidly escalating COVID-19, has caused havoc in quality education and every educational institution are closed. As the UNESCO report it showed that 1.6 billion children being affected due to the close of institution across 191 countries. With the alternative method every education institution started blended learning virtual classes in order to continue learning environment in students. The articles investigate COVID-19 impact on student’s quality education in Nepal and social work implication. The findings of the study shows that the COVID-19 has seriously effects on the students learning environment. It showed the huge gap between getting the good education in Nepal. However, Nepal has also made some policies to provide equal quality education to all the children through the ICT and also encourage social work to actively participate on providing education to all the majority of group children in Nepal. Whereas social work applied the micro, messo, and macro level of implication in practice to provide the education for children in remote area of Nepal.

Sharing activity is getting higher attention due to increasing popularity in recent years. In the paper, the authors investigated the main elements affecting the sharing activity. (1) Literature review: The theoretical part starts from the revision of definitions of sharing activity; description of the links between sharing and sustainable development, policy recommendations and relevant regulation in the field; later on, the study emphasises the key elements important for sharing. Finally, the authors investigated how the Covid-19 pandemic affected sharing activity; (2) Methods: During empirical research, the authors revised the list of 37 variables. The study uses data for each of the 27 EU countries from 2011 to 2020. The authors investigated correlation between macroeconomics variables to determine key variables for the regression model; (3) Results: The authors constructed a dynamic regression model that can be applied to predict the number of participants visiting sharing platforms in the European Union (EU); (4) Conclusions: The study shows that seeking to forecast the number of visits to sharing platforms it is necessary to use values of main macroeconomic variables such as consumer price index, productivity index, total unemployment rate, the number of users and households connected to the Internet, etc.

This paper will discuss the application of statistic modeling to interpret a health system crisis in Sri Lanka due to COVID- 19.A strong focus on the preventive approach and the contact tracing with the utilization of available resources in a rational manner describes Sri Lanka’s response towards COVID- 19 prevention and mitigation. The early contact tracing, preemptive quarantining, isolation, and treatment were implemented as a concerted effort. This approach, proven efficient during the early phase of the pandemic, was sustainable when there was a rapid increase in the COVID- 19 patients since July 2021, exceeding the health system capacity.The country’s COVID- 19 situation during the period from 01st of August 2021 to 31st of October 2021 was taken into consideration. Variables used for analysis were; total number of cases, recovered cases, comorbid and O₂ dependent patients, ICU patients, and deaths. The regression model was applied to analyze the data by using the EViews 12 (x64) software application.The correlation coefficients of all the independent variables under consideration implies that they have a strong positive relationship with the number of deaths occurred during the said period. According to the computed multiple linear regression model, the number of positive cases and O₂ dependents have a positive relationship with the dependent variable. Further, the Durbin- Watson stat value of the model and multicollinearity test reflect that it is free from serial correlation thereby the model is fit. From the perspective of epidemiological control, these findings highlight the importance of keeping the number of cases within the limits of health system capacity.

Purpose: To identify the impact of dealing with COVID-19 patients in clinical areas on nurses' professional self-concept and self-confidence. Background: Professional self-concept is considered a critical factor in the recruitment/retention process in nursing, nursing shortage, career satisfaction, and academic achievements. Professional self-confidence is also a crucial determinant in staff satisfaction, reducing turnover, and increasing work engagement. Design: Descriptive, comparative study. Methods: The study was conducted between February to May 2021 by utilizing a convenience sampling technique. A total of 170 nurses from two facilities were recruited from two COVID-19 and non-COVID-19 designated facilities. The level of professional self-concept and self-confidence was assessed by utilizing the Nurses' Self-Concept Instrument and Self-Confidence Scale. Results: The professional self-concept level among the exposed group to COVID-19 patients was lower than the comparison group, while the professional self-confidence level among the exposed group to COVID-19 patients was similar to the comparison group. On the other hand, the satisfied staff and those who received professional training in dealing with COVID-19 patients reported a higher level of professional self-concept. Conclusions: Dealing with COVID-19 patients has an impact on professional self-concept; the exposure group was lower than those who did not deal with COVID-19 patients, while the professional self-confidence level among the exposed group was similar to the comparison group. Getting professional training in dealing with COVID-19 patients and being satisfied at work were significant factors in improving the professional self-concept. Policymakers should create strategies that target the improvement of professional training in dealing with COVID-19 patients.

The perceived risk of being infected at work (PRIW) with COVID-19 represents a potential risk factor for workers during the current COVID-19 pandemic. In line with the job demands-resources (JD-R) model applied to safety at work, in this longitudinal study we propose that PRIW can be conceptualized as a job demand, whereas communication (i.e., the exchange of good-quality information across team members) can be conceived as a job resource. Accordingly, we hypothesized that PRIW at Time 1 (T1) would positively predict psychophysical strain at Time 2 (i.e., four months later). Furthermore, we hypothesized that communication at T1 would negatively predict psychophysical strain at T2. Overall, 297 workers took part in the study. The hypothesized relationships were tested using multiple regression analysis. Results supported our predictions: PRIW positively predicted psychophysical strain over time, whereas communication negatively predicted psychophysical strain over time. Also, results did not change after controlling for age, gender, and type of contract. Overall, this study suggests that PRIW and communication can be considered as a risk and a protective factor for work-related stress, respectively. Hence, to promote more sustainable working conditions, interventions should encourage organizations to optimize the balance between job demands and job resources related to COVID-19.

The COVID-19 pandemic caused an unprecedented effect on national radiological investigations. Since the World Health Organization officially declared the COVID-19 as a global pandemic, health policies have been rapidly organized to limit the spread of the virus and decrease the risk of exposure. These restrictions, in combination with home-stay arrangements and the onset of economic recession. As a result of public policies, financial difficulties and patient fear, many radiology departments have suffered a significant reduction in diagnostic examinations with important implications for their economic stability. The aim of this work is to evaluate the economic impact of the COVID-19 pandemic in the Radiology Department of an infectious disease hospital.

The Covid-19 pandemic spreads in waves for a year and a half, despite significant worldwide efforts, the development of biochemical diagnostic methods and population vaccination. One of the reasons for the infection spread is the impossibility of early disease detection through biochemical diagnostics, since biochemical processes slowly develop in a body. At the same time, well known that behavioral characteristics of a person, measured based on reflex movements, are capable for inertialess assessment of psychophysiological parameters. Vibraimage technology is the method of head micromovements video processing by inter-frame difference accumulation and converting spatial and temporal characteristics of the inter-frame difference into behavioral and psychophysiological parameters. Here we shown that behavioral parameters measured by vibraimage changed during COVID-19 infection. The identification of changes signs in behavioral parameters detected by AI trained on patients and controls. The best diagnostic accuracy (higher 94%) obtained using instantaneous values of behavioral parameters measured with the following vibraimage settings: 10Hz frequency of basic measurements; 25 inter-frame difference accumulations and averaging the diagnostic results over period of at least 5 seconds. COVID-19 diagnoses by behavioral parameters showed earlier (5-7 days) detection of the disease compared to symptoms and positive results of biochemical RT-PCR testing. Proposed method for COVID-19 diagnosis indicates infected persons within 5 seconds video processing using standard television cameras (web, IP) and computers, allows mass testing/selftesting and will stop the pandemic spread. We assume that head micromovements analysis for diagnosis of various diseases is possible not only with the help of vibraimage technology. Further research of human head micromovement analysis will help stop the COVID-19 pandemic and will contribute to the development of new contactless and environmentally friendly methods for early diagnosis of diseases.

The Covid-19 pandemic has resulted in the closure of schools at every level, globally, forcing education to move online. Meeting the needs of students online for Science Lab classes, in particular, is a challenge since the physical labs are not available to the teachers or students. OLabs is a virtual Science Lab providing a complete learning environment of theory, experimental procedures, videos, animations, simulations, and assessments that capture real lab experiences with the relevant pedagogy. This study looks at the acquisition and behaviors of users, on the OLabs platform, during pre and Covid-19 times. Using Google Analytics, we observe that, during the pandemic time, users increasingly adopted OLabs as a new learning pedagogy for performing experiments as indicated by parameters like the number of users; the number of unique pages viewed per session; time spent on viewing content; bounce rate; and preference for content types such as theory, simulations, videos, and animations.

The novel coronavirus disease (COVID-19) pandemic is provoking a prevalent consequence on mental health because of less interaction among people, economic collapse, negativity, fear of losing jobs, and death of the near and dear ones. To express their mental state, people often are using social media as one of the preferred means. Due to reduced outdoor activities, people are spending more time on social media than usual and expressing their emotion of anxiety, fear, and depression. On a daily basis, about 2.5 quintillion bytes of data are generated on social media, analyzing this big data can become an excellent means to evaluate the effect of COVID-19 on mental health. In this work, we have analyzed data from Twitter microblog (tweets) to find out the effect of COVID-19 on peoples mental health with a special focus on depression. We propose a novel pipeline, based on recurrent neural network (in the form of long-short term memory or LSTM) and convolutional neural network, capable of identifying depressive tweets with an accuracy of 99.42%. Preprocessed using various natural language processing techniques, the aim was to find out depressive emotion from these tweets. Analyzing over 571 thousand tweets posted between October 2019 and May 2020 by 482 users, a significant rise in depressing tweets was observed between February and May of 2020, which indicates as an impact of the long ongoing COVID-19 pandemic situation.

Patients with underlying health conditions are at risk for a poor outcome from Coronavirus disease 2019 (COVID-19). Using machine reasoning by the sci.AI system, we investigated the pathobiochemistry of this observation to generate therapeutic guidelines. Facts were extracted and linked from publications available in nlm.nih.gov and Europe PMC to form the dataset which was validated by medical experts. Previously we described how preexisting chronic inflammation renders the acute inflammatory response to Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) excessive translating the SARS-CoV-2 infection into the clinical COVID-19 syndrome. Herein we focus on therapeutic interventions that mitigate the immune response. In essence, from bench to bedside, as depicted in the Graphical Abstract, the clinical management of COVID-19 should aim at: A. Control of excessive oxidant production. B. Neutralization of excessive oxidants. C. Upregulation of nitric oxide (NO) production.

Objective The study aims to investigate the risk factors of bad psychosomatic health among students in quarantine during the first wave of the COVID-19 pandemic. Method:The survey was conducted on-line, on a sample of 1,978 respondents in Poland. The study was carried out by the end of the summer semester. The questionnaire was designed in a way which allows for the observation of main risk factors which have impact on the students’ mental health. The variance analysis and the hierarchical regression analysis were used to determine the predictors of mental health. Results:The results indicate that average and high levels of psychosomatic disorders were observed among 61% of respondents. The hierarchical regression analysis has revealed that the main factors influencing the level of mental health disorders were educational burnout, satisfaction with life, strategies for coping with stress and gender. As indicated by the respondents, mental health disorders increase in tandem with educational burnout, the application of emotion-focused coping strategies and the lack of satisfaction with one’s life. Moreover, it was observed that female respondents scored higher on the scale of disorders in comparison to males. Conclusions:The results of research indicate that distance education and negative coping strategies are the main risk factors of mental health disorders among students during the pandemic.

The purpose of this study was to investigate the relationships among student athlete’s identity and mental health during the COVID-19 pandemic. In addition, this study aimed to clarify the relationship between perceived social support from teammates and mental health in student-athletes. Two studies were conducted to investigate to clarify the mental health states of student-athletes in Japan during the COVID-19 pandemic. In Study 1 conducted in April 2020, the participants were 402 male student-athletes, and examined the relationships among student-athlete’s identity and mental health. The results of correlational analyses indicated that there were significant negative correlations between degree of student-athlete’s identity and depression and sports helplessness. In Study 2 conducted in March 2021, the participants were 136 male student-athletes, and examined the relationship between perceived social support from teammates, student-athlete’s identity and mental health. The results indicated that there was significant correlation among social support, student athlete’s identity and mental health. These results suggested that mental health may be improved if student-athletes are strongly aware of their social identity, which is their social role, when unforeseen events such as the COVID-19 pandemic occur. In addition, social support provided by significant others such as teammates may contribute to the improvement of mental health.

The severe disease outbreak COVID-19 pandemic impacted public health and safety and the educational systems worldwide. For fear of the further spread of diseases, most educational institutions, including Bangladesh, have postponed their face-to-face teaching. Therefore, this study explores public university student's perceptions towards online classes during the COVID-19 pandemic in Bangladesh. Data were collected among students of Islamic University, Kushtia, Bangladesh, through an online survey. The study followed both a qualitative and quantitative approach, where the survey technique was used as an instrument of data collection. Results showed that most students were facing difficulty participating in virtual classes and could not communicate with their friends correctly during online classes. They faced challenges in online schooling, and the majority of the students preferred conventional types of learning to virtual classes and did not understand the content of virtual classes easily. The study also explored that most students did not feel comfortable in online classes. Still, considering the present pandemic situation, they decided to participate in online classes to continue schooling. Besides, the study discovered that female students showed better real perceptions than male students regarding online classes, and urban students have more optimistic appreciation than rural students. Moreover, laptop or personal computer users showed more positive perceptions towards online education than mobile users. Furthermore, Broadband/ Wi-Fi users have more positive perceptions than mobile network users. These findings would be an essential guideline for governments, policymakers, technology developers, and university authorities for making better policy choices in the future.

One of the unfortunate findings from the ongoing COVID-19 crisis is the disproportionate impact the crisis has had on people and communities who were already socioeconomically disadvantaged. It has, however, been difficult to study this issue at scale and in greater detail using social media platforms like Twitter. Several COVID-19 Twitter datasets have been released, but they have very broad scope, both topically and geographically. In this paper, we present a more controlled and compact dataset that can be used to answer a range of potential research questions (especially pertaining to computational social science) without requiring extensive preprocessing or tweet-hydration from the earlier datasets. The proposed dataset comprises tens of thousands of geotagged (and in many cases, reverse-geocoded) tweets originally collected over a 255-day period in 2020 over 10 metropolitan areas in North America. Since there are socioeconomic disparities within these cities (sometimes to an extreme extent, as witnessed in `inner city neighborhoods’ in some of these cities), the dataset can be used to assess such socioeconomic disparities from a social media lens, in addition to comparing and contrasting behavior across cities.

This review revisits clinical use of antibiotics for most common acute oro-dental conditions; we aim to provide evidence governing antibiotics use when access to oral healthcare is not available, as during the ongoing outbreak of the severe acute respiratory syndrome coronavirus 2. In this rapid review, articles were retrieved after conducting a search on PubMed and Google Scholar. Relevant publications were selected and analyzed. Most recent systematic reviews with/without meta-analyses and societal guidelines were selected. Data were extracted, grouped, and synthesized according to the respective subtopic analysis. There were evidence supporting the use of antibiotics in common oro-dental conditions as temporary measure when immediate care is not accessible, such as in case of localized oral swellings as well as to prevent post-extraction complications. No sufficient evidence could be found in support of antibiotic use for pain resulting from pulpal origin. Consequently, antibiotic use may be justified to defer treatment temporarily or reduce risk of complications in case of localized infection and tooth extraction, when no access to immediate dental care is possible.

This paper presents a two-way factor design incorporating both spatial and temporal variation in the prediction of COVID 19 in Africa. In line with this, the impact of COVID-19on the GDP in Africa is well scrutinized. In contrast to the existing works [1–3], this work also extends the two-factor design into the one-way factor design through incorporating covariates into spatial effects. The data rely on the spatial and temporal obtained from WHO datasets [4, 5]. The one-factor design with more covariates is taken into consideration to identify the major potential predictor variables responsible for the deaths and confirmed cases due to COVID 19 in Africa. The MANCOVA considered population density, temperature, humidity; perception, and wind are all considered as co-variates. Simulations show that the two-way analysis of variance has shown that there is a statistically significant difference between the spatial (Fcal= 8.2704, Pvalue= 3.099∗10−6)and temporal (Fcal= 48.7964, Pvalue= 9.147∗10−16) effects. South Africa and Nigeria are highly influencing due to the pandemic where their GDP also relatively mostly declined. A significant economic change is observed before the pandemic and after the outbreak of the pandemic(tcal= 2.9548, Pvalue= 0.01805). COVID 19 negatively influenced the economy of1 most of the African countries. The population density, temperature, and wind are found to be statistically significantly associated with COVID 19 cases and deaths.

In Southern Asia, Bangladesh is a well-known developing country. Because of COVID-19, we continuously face challenges. Not only can these issues occur beyond economic or health concerns, but they also generate dangerous social problems, such as family abuse. Since the inception of this epidemic, multiple social crimes are looming. Remaining home during the lockout period enhances divorce rates. This research presents a customized forecast of family violence during the COVID-19 outbreak by using machine learning methods. In this paper, we have applied Random Forest, Logistic Regression, and Naive Bayes machine learning classifiers to predict family violence and discovered the feature importance. The performance of the classifiers is evaluated based on accuracy, precision, recall, and F-score. We have employed an oversampling strategy named synthetic minority oversampling technique (SMOTE) to solve the imbalance problem of our data. Even, we have tried to compare three machine learning model performances before and after balancing of normalization data. Finally, ROC analyses and confusion matrices were developed and analyzed by using data augmentation. Our proposed system with the random forest classifier performed better with 77% accuracy in comparison with other two machine learning classifiers.

Coronavirus disease is a newly identified infectious disease that began in Wuhan, China in 2019 and is recognized as COVID-19. This virus has a serious impact on the planet that causes the deaths of millions of people; it produces unemployment and poverty. However, it has constructive environmental effects that reduce the amount of pollution in the atmosphere. Pakistan is also a developing economy caused by this deadly virus. Before 03 April 2021, the percentage of reported cases ranges from 682,888, with about 14,697 casualties and a total of 609,691 cases retrieved. Pakistan’s war against coronavirus can differ from advanced technical countries due to lack of resources. In this article, we will address the relation between COVID-19 and the environment in the particular case of Pakistan. There is evidence that this pandemic has lowered concentrations of greenhouse gases, including CO2 and NO2, as a consequence of global lock-down strategies.

Practicing preventive etiquettes such as hand washing, hand disinfection, wearing a face mask, practicing physical distancing, disinfection of surfaces and objects can help curb the transmission of COVID-19 at the workplace. This paper focuses on interventions and behaviors required to curb the spread of COVID-19 at workplaces. We undertook a detailed multi-disciplinary literature search on the following topics: hand hygiene, respiratory hygiene, physical distancing, quarantine and isolation, disinfection of objects and surfaces, behavior change, and health crisis communication. We identified interventions that are effective for preventing the spread of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) at workplaces. These findings present very useful non-clinical interventions for preventing COVID-19 in the work environment.

: During the period of COVID-19, the Chinese government implemented a series of actions to prevent the spread of the virus. It is noticed that these preventive actions have generated positive effects on air pollution in Wuhan and Beijing. And, due to the differences in city functions, geographic locations, meteorological conditions, and preventive action details between the two cities, noticeable difference is observed on how they reduced air pollution. This unfortunate incident has become a social sample for studying the industrial and livelihood activities impact on air pollution, otherwise would be highly impossible. This paper starts from observing data from NASA's real-time fine particulate matter (PM2.5) and NO2, and comparing the air pollution in this special time domain with previous years. It is discovered that both PM2.5 and NO2 have been reduced in Wuhan, while only NO2 has significant reduction in Beijing, during the COVID-19 responses. This suggests that the human activity suppression by the COVID-19 control yields different effects on different pollutants and in different cities. Possible reasons for such effects are analysed by considering the public health control levels as well as the pollutant migration, industrial activities, and the weather conditions.

Since its initial outbreak in late 2019, the COVID-19 pandemic has profoundly affected the global community. In addition to the negative health consequences of contracting COVID-19, the implementation of strict quarantine and lockdown measures has also disrupted social networks and devastated the global economy. As a result, there is rising concern that the pandemic has taken a toll on the mental health of the general population. To better understand its impact, an increasing number of studies examined the effects of the pandemic on mental health and psychosocial implications of enforced quarantine and lockdown. In this article, we aim to review and summarize the findings from a variety of studies that have explored the psychosociological effects of the pandemic and its impact on the mental well-being of the general population. We will also examine how various demographic groups, such as the elderly and youth, can be more susceptible or resilient to the pandemic’s mental health effects. We hope to provide a broader understanding of the underlying causes of mental health issues triggered by the pandemic and provide recommendations that may be employed to address mental health issues in the population over the long-term.

Introduction: The majority of epidemiological reports focus on confirmed cases of COVID-19. In this study, we aim to assess the health and well-being of adults not infected with Covid-19 after two months of quarantine in Morocco. Materials and methods: Two months after the declaration of quarantine in Morocco following the Covid-19 epidemic, we carried out a descriptive cross-sectional study of 279 Moroccan citizens. We used the Short Form Health Survey (SF-12) as a determinant of quality of life, which is based on eight dimensions of health. The data were collected using an electronic questionnaire distributed online. The participants also indicated their socio-demographic data, their knowledge and practices regarding the Covid-19 pandemic and whether they had chronic health problems. Results: The quality of life of all participants was moderately disrupted during the Covid-19 pandemic with a mental health score (MCS) of 34.49 (± 6.44) and a physical health score (PCS) of 36.10 (± 5.82). Participants with chronic diseases scored lower with 29.28 (± 1.23) in mental health (MCS) and 32.51 (± 7.14) in physical health (PCS). The seriousness of COVID-19 has an impact on the quality of life and health well-being of people and this impact is more marked in people with chronic health problems. Conclusion: Our results confirm the need to pay attention to the health of people who have not been infected with the virus. Our results also point out that uninfected people with chronic illnesses may be more likely to have well-being problems due to quarantine restrictions.

Adverse Outcome Pathways (AOP) provide structured frameworks for systematic organization of research data and knowledge. The AOP framework follows a set of key principles that allow for broad application across diverse disciplines related to human health, including toxicology, pharmacology, virology and medical research. The COVID-19 pandemic engages a great number of scientists world-wide and data is increasing with exponential speed. Diligent data management strategies are employed but approaches for systematically organizing the data-derived information and knowledge are lacking. We believe AOPs can play an important role in improving interpretation and efficient application of scientific understanding of COVID-19. Here, we outline a newly initiated effort to streamline collaboration between scientists across the world towards development of AOPs for COVID-19, and describe the overarching aims of the effort, as well as the expected outcomes and research support that they will provide.

In March 2020, the World Health Organization declared coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2, to be a pandemic. Since the declaration, Nigeria economy has been greatly impacted thus resulting in a recession. This paper considers a couple of misconceptions among Nigerian people in the COVID-19 pandemic era thereby causing the spread of the novel virus and hence making the situation difficult for the government to handle. In particular, we discuss the first and second waves of the pandemic as it affects the Nigerian people. The impact of the pandemic on animals and the role of mathematical epidemiologists in combatting the spread is discussed herein. We give some recommendations that could be adopted by the government and the good people of Nigeria to reduce the further spread of the virus.

To quantify the time-varying reproduction number (Rt) for Malaysia using the COVID-19 incidence data., we used data the from the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus repository. Day 1 was taken from the first assumed local transmission of COVID-19. Data was split into four intervals: a) Interval 1: from Day 1 to Day 10 MCO 1, b) Interval 2: from Day 1 to Day 10 MCO 2, c) Interval 3: from Day 1 to Day 10 MCO 3 and d) Interval 4: from Day 1 to Day 10 MCO 4. We estimated the Rt using the EpiEstim package. The means for Rt at Day 1, Day 5 and Day 10 for all MCOs ranged between 0.665 to 1.147. The average Rt gradually decreased in MCO 1 and MCO 2. However, Rt increased in MCO 3 before stabilized around 0.8 in MCO 4. MCO 1 and MCO 2 which were stricter coincide with the gradual reduction of Rt. However, the more relaxed MCO 3 and MCO 4 correspond to a slight increase in the Rt before it stabilized.

Background: COVID-19 crisis has changed the conditions of many throughout the globe. One negative consequence of the on-going pandemic is anxiety brought by uncertainty and the COVID-19 disease. Increased anxiety is a potential risk factor for wellbeing at work. This study investigated psychological, situational, and socio-demographic predictors of COVID-19 anxiety using longitudinal data. Methods: Nationally representative sample of Finnish workers (N = 1308) was collected before and during the COVID-19 crisis. Eighty percent of the participants responded to the follow-up study (N=1044). COVID-19 anxiety was measured with a modified Spielberger State–Trait Anxiety Inventory. Psychological and situational predictors included perceived loneliness, psychological distress, technostress, personality, social support received from work community, and remote working. Also, number of socio-demographic factors were investigated. Results: Perceived loneliness, psychological distress, technostress, and neuroticism were identified as robust psychological predictors of COVID-19 anxiety. Increase in psychological distress and technostress during the COVID-19 crisis predicted higher COVID-19 anxiety. Recent change in work field and decreased social support from work community predicted COVID-19 anxiety. Women and young people experienced higher anxiety. Conclusions: Different factors explain workers’ COVID-19 anxiety. Increased anxiety can disrupt wellbeing at work, emphasizing organizations’ role in maintaining an inclusive and caring work culture and providing technical and psychological support to workers during crisis.

The COVID-19 pandemic caused by SARS-CoV-2 poses a devastating threat to human society in terms of health, economy and lifestyle. Establishing accurate and real-time models to predict and assess the impact of the epidemic on the economy is instructive. We have designed a new model to quantitatively assess the impact of the COVID-19 on the economy of China’s mainland. The nominal GDP in the Q1 of 2020 that we predicted for China’s mainland with the Baidu Mi-gration Data is RMB 20,785.7 billion, which is less by 3.59% than that in 2019. The estimated val-ue is confirmed roughly by the official report released in April 17, 2020 (RMB 20,650 billion, 6.8% year-on-year declined). Strict control measures during the epidemic have greatly reduced Chi-na's economic activity and had a serious impact on the country's economy. Orderly promotion of population mobility plays a decisive role in economic recovery.

Background. The Weekly Mortality Cycle among CoViD-19 patients has been studied.Methods. Mortality data obtained from the 'Worldometer' website were analyzed with a comparison of absolute values, percentages, and p-value. Results. For patients suffering from CoViD-19, the most favorable or the safest days of the week were Sundays and Mondays. Conclusion. The weekly cycle with decreased mortality on Sundays and Mondays is a unique phenomenon observed among victims of CoViD-19. Presumably the decreased mortality on certain days of the week related to the optimized therapeutic protocols used on the "safest days".

School closures (SC) were adopted globally as a COVID-19 disease pandemic containment strategy. This extreme measure provoked a disruption of the educational system involving hundreds of million children worldwide. The return of children to school has been variable and is still an unresolved and contentious issue. Importantly the process has not been directly correlated to the severity of the pandemic s impact and has fueled the widening of disparities, disproportionately affecting the most vulnerable populations. Available evidence shows SC added little benefit to COVID-19 control whereas the harms related to SC severely affected children and adolescents. This unresolved issue has put children and young people at high risk of social, economic and health-related harm for years to come, triggering severe consequences during their lifespan. In this article we describe the process of SC and the reopening timetable across the globe. We highlight the data regarding the international state of educational systems around the world, putting emphasis on the rights of children to come back to school.

Since its emergence in March 2020, the SARS-CoV-2 global pandemic has produced more than 65 million cases and one point five million deaths worldwide. Despite the enormous efforts carried out by the scientific community, no effective treatments have been developed to date. We created a novel computational pipeline aimed to speed up the process of repurposable candidate drug identification. Compared with current drug repurposing methodologies, our strategy is centered on filtering the best candidate among all selected targets focused on the introduction of a mathematical formalism motivated by recent advances in the fields of algebraic topology and topological data analysis (TDA). This formalism allows us to compare three-dimensional protein structures. Its use in conjunction with two in silico validation strategies (molecular docking and transcriptomic analyses) allowed us to identify a set of potential drug repurposing candidates targeting three viral proteins (3CL viral protease, NSP15 endoribonuclease, and NSP12 RNA-dependent RNA polymerase), which included rutin, dexamethasone, and vemurafenib among others. To our knowledge, it is the first time that a TDA based strategy has been used to compare a massive amount of protein structures with the final objective of performing drug repurposing

The air pollutant NO2 is derived largely from transportation sources and is known to cause respiratory disease. A substantial reduction in transport and industrial processes around the globe from the novel SARS-CoV-2 coronavirus and subsequent pandemic resulted in sharp declines in emissions, including for NO2. Additionally, the COVID-19 disease that results from the coronavirus may present in its most severe form in those who have been exposed to high levels of air pollution. To explore these links, we compared ground-based NO2 sensor data from 11 US cities from a two-month window (March-April) over the previous five years versus the same window during 2020 shutdowns. NO2 declined roughly 12-41% in the 11 cities. This decreased coincided with a sharp drop in vehicular traffic from shutdown-related travel restrictions. To explore this link more closely, we gathered more detailed traffic count data in one city, Indianapolis, Indiana, and found a strong correlation between traffic counts/classification and vehicle miles travelled, and a moderate correlation between NO2 and traffic related data. This finding indicates that we can use such analysis in targeting reduction in pollutants like NO2 by examining and manipulating traffic patterns, thus potentially leading to more population-level health resilience in the future.

The ongoing crisis of COVID-19 pandemic that swept across the world, poses serious challenges on health delivery systems particularly in developing countries. In Africa however, the crisis rather inspires and sparks creativity and innovation at the national, institutional, organizational, and individual levels. This paper unravels Africa’s response mechanisms to the virus that might have relatively contributed to the low infection rate of the pandemic within the continent. Some criteria are adopted to assess and assemble the most influential government policies and home-grown innovations from various African countries and territories within the continent. It is found that, some of the innovations do not only help in combating the virus, but also have socio-economic benefits as they substantially complement government efforts in easing the burden of the citizenry as they cope with preventive protocols imposed on them. This study will be helpful in identifying the most significant home-based innovations that can be improved and used to reduce health delivery crises within the continent even after COVID-19.

There has been very widespread contagion of covid-19 in Kichwa indigenous communities in Ecuadorian Amazonia, but the peak of contagion has already passed, and total mortality has been remarkably low. The Kichwa people themselves typically attribute this to the widespread use of medicinal plants.

Background: The Royal College of Surgeons in Ireland - Bahrain (RCSI Bahrain) was closed due to COVID 19. The aim of this paper is to present our experience, in managing teaching and learning, during this pandemic. Methods: Following, ethical approval, several meetings were held with the senior faculty and student representatives to select alternative virtual approaches for teaching, learning and assessment with evidence-based instructional design. Informed consent was obtained from all study participants. All procedures were carried out in accordance with relevant guidelines and regulations. In alignment with global scenario, we decided upon early graduation for our students, and expedited the clinical examinations, with special permission from health and education ministries. Two major clinical examinations were redesigned to form a single hybrid clinical examination with two parts. Following all COVID 19 preventive measures, students were taken in groups of seven and simulated patients were substituted for real patients. No more than 40 students were present at any point of time, with no more than 10 examined in one block. 149 out of 152 RCSI students attended the clinical examinations and 524 students from the three RCSI campuses attended the written online examination. A structured survey was conducted to elicit students’ perceptions and participation was entirely voluntary. Results: 82% of students were happier to be joining the workforce early and, 22% expressed concerns. A comparison of student performance in these examinations against the equivalent components from semester one yielded no significant deviation in student performance, illustrating that the quality was consistent. Conclusion: We recommend that the government accredit online or distance learning programmes and explore appropriate methodologies for evaluation of online learning and assessment. Incorporating practical/clinical training, will continue to be a great challenge.

With the year 2020, the world faced a new threat that affects all areas of life, negatively affects production in all areas, and paralyzes social life. The measures and restrictions taken by the country's governments to prevent the epidemic from spreading rapidly in the society with the effect of the Covid-19 virus, which first appeared in China and spread all over the world, brought a new lifestyle. Covid-19 has been much the impact on electricity use and electricity production in the period in Turkey as in other countries. There was a sharp decline in commercial and industrial electricity use. The coronavirus effect has also been reflected in the electricity demand and the consumption amount has undergone a great negative change. Due to the enactment of measures against the new type of coronavirus (COVID-19) epidemic and the partial or full-time curfews, electricity consumption was moved to homes, supermarkets, and hospitals in April 2020 from places where mass consumption is intense, such as industry, workplaces, and educational institutions. In this study, Covid-19 period, the first cases were examined electricity production and consumption in Turkey as of the date it is seen throughout, in comparison with electricity consumption data in the same month of the previous years corresponding to this period, the effects on electricity generation and consumption habits of this period were examined.

Although rRT-PCR is the gold standard method for SARS-CoV-2 detection, some factors, such as amplification inhibitors presence, lead to false-negative results. Here we describe differences between rRT-PCR results for SARS-CoV-2 infection in normal and diluted samples, simulating the need for dilution due to amplification inhibitors presence. Viral RNA extraction of nasopharyngeal swabs samples from 20 patients previously detected as 'Negative' and 21 patients detected as 'Positive' for SARS-CoV-2 was realized with the EasyExtract DNA-RNA (Interprise®). rRT-PCR was realized with OneStep/COVID-19 (IBMP) kit with normal and diluted (80µl of H₂O RNAse free) samples, totaling 82 tests. The results indicate that there is an average variation (ɑ < 0.05) delaying Cq between the amplification results of internal control (IC), N Gene (NG), and ORF-1ab (OF) of 1.811 Cq, 3.840 Cq, and 3.842 Cq, respectively. The extraction kit does not completely purify the inhibitor compounds, therefore non-amplification by inhibitors may occur. In this study, we obtained a 19.04% false-negative diagnosis after sample dilution, and this process reduces the efficiency of rRT-PCR to 29.80% for detecting SARS-CoV-2. Knowing the rRT-PCR standards of diluted samples can help in the identification of false-negative cases, and consequently avoid a wrong diagnosis.

In this retrospective report we present five cases of critically ill pregnant or newly delivered women positive for Covid-19 admitted to our obstetrical departments at Karolinska University Hospital. They compose 6% of eighty-three pregnant women that tested positive for SARS-CoV-2 during the period March 25 to May 4, 2020. Three patients were at the time of admission in gestational week between 21+4 to 22+5 and treated during their antenatal period, meanwhile the other two were admitted within 1 week postpartum. All of them were in a need of intensive care, one was treated with high flow oxygen therapy, the other four with invasive mechanical ventilation (three with endotracheal intubation and one with extra corporeal membrane oxygenation). Age above thirty, overweight and gestational diabetes are notable factors in the cases presented. At the time of admission, they all presented with symptoms as fever, cough and dyspnea. Chest imaging with computer tomography scan was performed in each case and demonstrated multifocal pneumonic infiltrates in all of them but no pulmonary embolism was confirmed in any. Neither did the echocardiogram indicates any cardiomyopathy. Four of the patients have been discharged from the hospital, with an average of 20 hospital days. One antenatal pregnant woman needed prolonged ECMO therapy, in gestational week 27+3 she went into cardiac arrest, resulting in an urgent c-section on maternal indication. At the time of writing she is still hospitalized. In coherence with other published reports our cases indicate that critically ill pregnant women infected by SARS-Cov-2 may develop severe respiratory distress syndrome requiring prolonged intensive care. The material is limited for conclusions to be taken, more detailed information on symptoms, treatment, and outcomes for pregnant and postpartum women managed in intensive care is therefore needed.

Mass crises are disruptive to people's mental health. The study aimed to explore mental distress during COVID-19 quarantine in a sample of university workers in Brazil. The survey included sets of questions about demographics, health, and support, an open question about major concerns, and the Clinical Outcome Routine Evaluation (CORE-OM), a measure of mental distress. 407 professionals participated in the study: mean age of 40 years (SD = 11.2), mostly female (67.8%), married (64.8%) and fulfilling social distancing to avoid COVID-19 infection (99%). Using the Consensual Qualitative Research for simple qualitative data (CQR-M) the main areas of concern were grouped into six domains, as follows: Work, Health, Isolation, Personal life and routine, Social environment, and Future. Many responses were multiple. They form categories indicating specific concerns within these domains. Quantitative data were analyzed by identifying the simple effects of potential predictors of mental distress. The results indicated medium effects of help with household chores, psychiatric treatment, age and physical exercise. Having someone available to listen was the only variable with a large effect in reducing mental suffering. The hybrid approach showed that the psychological experience during the pandemic is quite multifaceted and complex pointing new clues for public mental health.

The COVID-19 pandemic caused by the novel coronavirus emerged in Wuhan City, Hubei province of China at the end of 2019, has radically transformed the lives of people around the world. Due to its fast spreading, it is currently considered as a worldwide health, social and economic concern. The lack of knowledge on this area has encouraged academic sphere for extensive research, which is reflected in exponentially growing scientific literature in this area. However, current state of COVID-19 research reveals only early development of knowledge, while a comprehensive and in-depth overview remains neglected. Accordingly, the main aim of this paper is to fill the aforementioned gap in the literature and provide an extensive bibliometric analysis of COVID-19 research across science and social science research landscape, using innovative and sophisticated bibliometric approaches (e.g. Venn diagram, Biblioshiny descriptive statistics, VOSviewer co-occurrence network analysis, Jaccard distance cluster analysis, text mining based on logistic regression). The bibliometric analysis is based on the Scopus database including all relevant and latest information on COVID-19 related publications (n=16,866) in the first half of 2020. The empirical results indicate that there is still a lack of publications of COVID-19 and its implications in less-explored (non-health) sciences, especially in social sciences. Accordingly, the findings emphasize an importance of a comprehensive and in-depth approach considering different scientific disciplines in COVID-19 research. The understanding of the evolution of emerging scientific knowledge on COVID-19 is beneficial not only for scientific community but also for evidence-based policymaking in order to prevent and address the COVID-19 pandemic.

Purpose: Novel coronavirus disease (COVID-19) is the current global concern. Radiotherapy (RT), commonly employed in cancer management, has been considered one of the potential treatments for COVID-19 pneumonia. Here, we present the final report of the pilot trial evaluating the efficacy and safety of low-dose whole-lung irradiation (LD-WLI) in patients with COVID-19 pneumonia. Methods and Materials: We enrolled patients with moderate COVID-19 pneumonia who were older than 60 years. Participants were treated with LD-WLI in a single fraction of 0.5 or 1.0Gy along with the national protocol of COVID-19. The primary endpoints were improvement of SpO₂, the number of hospital/ICU stay days, and the number of intubations after RT and the secondary endpoints were alterations of the c-reactive peptide, interleukin-6, ferritin, procalcitonin, and D-dimer. The response rate (RR) was defined as a rise in SpO₂ upon RT with rising or constant trend in the next two days, and clinical recovery (CR) included patients who were discharged from the hospital or acquired SpO₂ ≥93% on room air. Results: Between 21 May 2020 and 2 July 2020, ten patients were enrolled. The median age was 75 years, 80% were male, and 80% had comorbidities. The first five patients received a single 0.5Gy-WLI, and others received 1.0Gy. Patients were followed for 2-14 days (median 5.5 days). Following one day, nine patients experienced an improvement in SpO₂. Five patients were discharged (median 6^th day, range 2^nd-14^th day), and four patients died (median 7^th day, range 3^rd-10^th day). Overall, the RR and CR were 60.0% and 55.5%, respectively. The RR and CR rates of 0.5- and 1.0Gy group were 80% vs 40% and 75% vs 40%, respectively. No acute radiation-induced toxicity was recorded. Conclusions: LD-WLI with a single 0.5Gy fraction seems to be a more appropriate dose to warrant further evaluation in a large-scale, randomized trial.

Coronavirus is believed to have originated from a wet market in Wuhan, China, and has spread all over the world, resulting in a large number of hospitalizations and deaths. Social scientists are just beginning to understand its consequences on human behavior. One policy that public health officials put in place to help stop the spread of the virus were stay-at-home/shelter-in-place lockdown-style orders. Schools, Colleges and Universities across the country have now been shut down till now due to Covid-19. Some Governments in India impose lockdown to reduce the crises created by this unknown virus. It is now difficult to make final assessments by school, school leaving examinations and entrance tests for undergraduate and post-graduate courses. This disruption implies for students across the socio-economic spectrum, both in terms of learning outcomes , food and economic security. Here the aim is to discuss the implications of lockdown-induced in schools in both urban and rural areas in India.The whole world implemented a nationwide lockdown to curb the transmission of the virus. A survey was over Five hundred families to complete a questionnaire with questions around symptoms of depression, anxiety, stress, and family affluence. The humans who do not have enough supplies to sustain the lockdown were most affected Families with affluence were found to be negatively correlated with stress, anxiety, and depression. Stress, anxiety, and depression more than others are seen in students and healthcare professionals. The main aim of the paper is to find out how symptoms of depression, anxiety and stress on parents due to COVID-19.

It is not established whether SARS-CoV-2 (COVID-19) patients with movement disorders, are at greater risk for more serious outcomes than the larger COVID-19 population beyond the susceptibility associated with greater age. We reviewed electronic health records and conducted telephone interviews to collect the demographics and clinical outcomes of patients seen at our Movement Disorders Center who tested positive for COVID-19 from 8 March 2020 through 6 June 2020. Thirty-six patients were identified, 23 men and 13 women, median age of 74.5 years. They primarily carried diagnoses of idiopathic Parkinson disease (n=22; 61%) and atypical parkinsonism (n=7; 19%) with the balance having other diagnoses. Twenty-seven patients (75%) exhibited alteration in mental status and fifteen (42%) had abnormalities of movement as common manifestations of COVID-19; in 61% and 31%, these were the presenting symptoms of the disease. 67% of patients in our cohort required hospitalization, and the mortality rate was 39%.. These data demonstrate that in patients with movement disorders, the likelihood of hospitalization and death after contracting COVID-19 was substantially greater than in the general population. Patients with movement disorders frequently presented with altered mental status, generalized weakness, or worsening mobility but not anosmia.

This study estimates the negative impacts of the COVID-19 on poverty and unemployment in Indonesia. In doing so, this study develops and uses the SD model that reproduced similar patterns in terms of GDP, poverty, and unemployment. Estimated unemployment and estimated poverty under the COVID-19 are calculated for three different economic scenarios: the optimistic, the mid, and the pessimistic scenarios. This study concludes that Indonesia will experience rising unemployment and poverty in ranges (9-10) and (25-26) million people respectively by the end of this year – depending on projected economy growths. This study suggests that existing financial aids are sufficient to support rising unemployment and rising poverty level. However, if the Indonesia government cannot carefully slow the COVID-19 flow, higher financial supports are required to curb the negative impacts of the COVID-19.

The models used to estimate disease transmission, susceptibility and severity determine what epidemiology can (and cannot tell) us about COVID-19. These include: ‘model organisms’ chosen for their phylogenetic/aetiological similarities; multivariable statistical models to estimate the strength/direction of (potentially causal) relationships between variables (through ‘causal inference’), and the (past/future) value of unmeasured variables (through ‘classification/prediction’); and a range of modelling techniques to predict beyond the available data (through ‘extrapolation’), compare different hypothetical scenarios (through ‘simulation’), and estimate key features of dynamic processes (through ‘projection’). Each of these models: address different questions using different techniques; involve assumptions that require careful assessment; and are vulnerable to generic and specific biases that can undermine the validity and interpretation of their findings. It is therefore necessary that the models used: can actually address the questions posed; and have been competently applied. In this regard, it is important to stress that extrapolation, simulation and projection cannot offer accurate predictions of future events when the underlying mechanisms (and the contexts involved) are poorly understood and subject to change. Given the importance of understanding such mechanisms/contexts, and the limited opportunity for experimentation during outbreaks of novel diseases, the use of multivariable statistical models to estimate the strength/direction of potentially causal relationships between two variables (and the biases incurred through their misapplication/misinterpretation) warrant particular attention. Such models must be carefully designed to address: ‘selection-collider bias’, ‘unadjusted confounding bias’ and ‘inferential mediator adjustment bias’ – all of which can introduce effects capable of enhancing, masking or reversing the estimated (true) causal relationship between the two variables examined. Selection-collider bias occurs when these two variables independently cause a third (the ‘collider’), and when this collider determines/reflects the basis for selection in the analysis. It is likely to affect all incompletely representative samples, although its effects will be most pronounced wherever selection is constrained (e.g. analyses focusing on infected/hospitalised individuals). Unadjusted confounding bias disrupts the estimated (true) causal relationship between two variables when: these share one (or more) common cause(s); and when the effects of these causes have not been adjusted for in the analyses (e.g. whenever confounders are unknown/unmeasured). Inferentially similar biases can occur when: one (or more) variable(s) (or ‘mediators’) fall on the causal path between the two variables examined (i.e. when such mediators are caused by one of the variables and are causes of the other); and when these mediators are adjusted for in the analysis. Such adjustment is commonplace when: mediators are mistaken for confounders; prediction models are mistakenly repurposed for causal inference; or mediator adjustment is used to estimate direct and indirect causal relationships (in a mistaken attempt at ‘mediation analysis’). These three biases are central to ongoing and unresolved epistemological tensions within epidemiology. All have substantive implications for our understanding of COVID-19, and the future application of artificial intelligence to ‘data-driven’ modelling of similar phenomena. Nonetheless, competently applied and carefully interpreted, multivariable statistical models may yet provide sufficient insight into mechanisms and contexts to permit more accurate projections of future disease outbreaks.

A new – syntropic – criterion obtained using the synergetic theory of information has been proposed for determining the start date for the cancellation of restrictive measures in the COVID-19 pandemic. Under this criterion, the restrictions should be lifted when the average number of new cases per day during a week becomes disproportionately smaller than at the peak of the pandemic. The article gives the derivation of this criterion, and its practical use is shown by the example of a number of EU countries. In this case, a comparison is made of the dates set by the syntropic criterion with the actual dates of the beginning of the lifting of restrictions.

The present study investigates the relationship between the transmission of COVID-19 infections and climate indicators in Dhaka City, Bangladesh, using coronavirus infections data available from the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh. The Spearman-ranked correlation test was carried out to study the association of seven climate indicators, including humidity, air quality, minimum temperature, precipitation, maximum temperature, mean temperature and wind speed with the COVID-19 outbreak in Dhaka City, Bangladesh. The study found that, among the seven indicators, only three indicators (air quality, minimum temperature and average temperature) have a significant relationship with new COVID-19 cases. The results of this paper will give health regulators and policymakers valuable information to lessen the COVID-19 infection in Dhaka and other countries around the world.

Background: The COVID-19 among humans is spreading heavily and is largely impacting the mental health of the general population, students, and health care workers worldwide. Hence, this review aims to summarize the literatures addressing the impact of the COVID-19 pandemic on the mental health of the general population, students, and health care workers. Methods: Published articles concerning mental health of the general population, students, and health care workers related to the COVID-19 outbreak have been considered and reviewed. Results and Discussion: Mental health symptoms of stress, anxiety, and depression are common psychological reactions to the COVID-19 pandemic in the general population, students, and health care workers. This collectively influences daily behavior, economy, prevention strategies and decision making from policy makers and health organizations, weakening the strategies of COVID-19 control leading to more morbidity and mental health needs at the global level. Conclusion: There is a need for more evidence-based research from other affected countries, particularly in vulnerable populations such as children and adolescents, people of lower socioeconomic status, and those residing in rural areas, so that valid strategies can be developed and COVID-19 and outbreaks of similar types in the near future can be prevented.

The Covid-19 infodemic can be countered by scientific evidences, clear and consistent communication and improved health literacy of both individuals in need of information and those providing it. A rapid online survey was carried out to evaluate vaccine literacy (VL) skills in the general population and perceptions about candidate Covid-19 vaccines, as well as behavior and beliefs about current vaccinations. Observed VL levels were sufficiently high and consistent with previous observations - where comparable self-reported tools were administered face-to-face and paper-and-pencil - the mean functional score being =2.92, while the interactive-critical one was =3.27, on a maximum of 4. Perceptions regarding future Covid-19 vaccines, along with beliefs about vaccination, were mostly positive and significantly associated with functional and interactive-critical VL scales. Despite obvious limitations, the study confirms that rapid surveys via web are a suitable method to evaluate and trail attitudes during infectious disease outbreaks, and to assess health literacy skills about vaccination, which can be useful to adapt medical communication strategies, for a better understanding of the value of immunization.

Wearable computing is a fast evolving segment of computing that includes smart watches, head mounted wearables such as Magic Leap headsets, Microsoft Hololens, and VR goggles from various vendors. In this report, we present ideas for a smart wearable device that also doubles as a virus protection device. Instead of using the filtering approach that is predominantly used by virus protection equipments such as face masks, we propose to use a computational approach where the device maintains an awareness of the real-time virus spread and use that information to steer the wearer away from the virus. As the wearable has a head enclosing design, viral infection can only happen through the air that is inhaled by the wearer. The objective of the smart wearable is to maintain a repository for clean air and switch the operating modes between stored and fresh air modes depending on the environmental conditions. It can augment this basic operating procedure by recycling the exhaled air to maximize it operating capacity (i.e., time duration for which it could supply the wearer with safe air) and by cleaning the stored air using UVC to further reduces the chance of infection. To maintain an awareness of the virus spread in the environment, the smart wearable will rely on an edge computing framework that will be distributed to cover areas frequented by people. The smart wearable will have modular design so that it can be reconfigured to add or subtract functionality that the wearer wants for a particular situation so that the design remains relevant even after the virus threat recedes.

COVID-19 is fast spreading around the globe in a highly contagious manner. The results from our study showed that after intervention with successive Lockdowns, there was marked decrease in the rate of COVID-19 cases, though there was sporadic volatility in number of COVID-19 cases due to some extrinsic factors. Concomitant with reduction in rate of COVID-19 there was gradual increase in doubling time of COVID-19, steady increase in number of discharged/recovered patients from COVID-19 reaching to ≥ 58% taking the entire Indian population into consideration. Another important aspect was consistent low mortality rate was accompanied by gradual increase in recovery rate of COVID-19 in the population. The possible implication of these results in the development of protective immunity in the population has been discussed.

Covid-19 disease is caused by SARS Cov-2 virus. Despite its high transmissibility, the CFR (Case Fatality Rate) of COVID-19 seems to be lower than the SARS (9,5%) and MERS (34,4%) ones⁹³ , but higher than the influenza one (0-1%)^94,95 . The disease is asymptomatic or paucisymptomatic in most of the patients, although in few cases it can be characterized by serious complications. The main causes of hospitalization in intensive care are represented by ALI (Acute Lung Injury), ARDS (Acute Respiratory Distress Syndrome), cardiovascular problems and coagulopathies (diffuse thrombosis, microthrombosis, embolisms, myocarditis, arrhytmias, heart failure, stroke)^96-98, acute nephropathy^99,100 and encephalopathies¹⁰¹. The virus presence in the vascular wall can cause endotheliitis, which triggers the process of diffuse coagulation that can lead to a worsening of the systemic inflammation. The exaggerated inflammatory response seems to be connected with the development of ARDS, MOF (Multiple Organ Failure) and coagulopathies^102-107.

The eruption of the COVID-19 pandemic has affected every sphere of life and may forever change how we have always lived and conducted our businesses, and no one can resist the wind of change that is blowing. Of all the sectors of governance, the educational sector, particularly at the tertiary level, appears to have been most greatly affected and therefore requires a more pragmatic approach to resolution. As of 29th June, Sub-Sahara Africa has reported 382,190 cases of COVID-19. In rejoinder to the virus epidemic, several Sub Sahara African governments implement the resolution to slam learning institutions to enclose the infection. Consequently, advanced schooling institutions obliged to reorganize their loom, becoming more digitally become forward, and changing to online platforms.

The current emerging COVID-19 pandemic has caused a global impact on every major aspect of our societies. It is known that SARS-Cov-2 can endure harsh environmental conditions for up to 72 h, which may contribute to its rapid spread. Therefore, effective containment strategies, such as sanitizing, are critical. Nanotechnology can represent an alternative to reduce the COVID-19 spread, particularly in critical areas, such as healthcare facilities and public places. Nanotechnology-based products are effective at inhibiting different pathogens, including viruses, regardless of their drug-resistant profile, biological structure, or physiology. Although there are several approved nanotechnology-based antiviral products, this work aims to highlight the use of nanomaterials as sanitizers for the prevention of the spread of mainly SARS-Cov-2. It has been widely demonstrated that nanomaterials are an alternative for sanitizing surfaces to inactivate the virus. Also, antimicrobial nanomaterials can reduce the risk of secondary microbial infections on COVID-19 patients, as they inhibit the bacteria and fungi that can contaminate healthcare-related facilities. Finally, cost-effective, easy-to-synthesize antiviral nanomaterials could reduce the burden of the COVID-19 on challenging environments and in developing countries.

The novel coronavirus disease (COVID-19) pandemic has impacted health and wellbeing globally. To strengthen preventive and clinical care amid this pandemic, technological innovations like artificial intelligence (AI) are increasingly used in different contexts. This bibliometric study aimed to assess the current scholarly development and prominent research domains in applications of AI technologies in COVID-19 research. A total of 105 articles were retrieved from MEDLINE database that emphasized on the use of AI in the context of COVID-19. Most articles had multiple authors with a collaboration index of 7.18. Moreover, most of the articles were produced from the USA (22.86%) and China (21.9%), whereas developing countries were underrepresented among the contributing nations. Furthermore, several research domains were identified, including prevention and control, diagnostics, epidemiological characteristics, therapeutics, psychological conditions, and different areas of data sciences related to COVID-19. The current bibliometric evidence shows the early stage of development in this field, which necessitates equitable applications of AI in COVID-19 research emphasizing on health disparities, socio-legal issues, vaccine development, and applied public health research in this pandemic.

The emergence of COVID -19 pandemic has severely impacted individuals from all walks of life. The rapid spread of the disease to nearly all parts of the country has posed enormous health, economic, environmental and social challenges to the entire human population. In the absence of any effective drugs and vaccines for treatment, social distancing and other preventive measures are the only alternatives. Lockdown is among one of the options suggested by WHO to reduce spread of the virus. India was quick to close its international borders and enforce the world’s largest COVID lockdown on March 22, 2020. The present study attempts to highlight the impact of imposed nationwide lockdown on society and environment alike along with analysis of lifestyle changes. The study was based on an online survey using a structured questionnaire with over 1000 responders across the country. The pandemic situation demands a certain way of shaping the society to reduce virus spread and safeguard oneself. In this study, we analysed the changes that the society has undergone during lockdown to mitigate the spreading of the infection. We also addressed the changes that have become part of our lives during lockdown – hygiene and health consciousness, work from home (WFM), online teaching, digital shopping, changing internet habits and societal changes.

Corona virus disease 2019 (COVID-19) is caused by a Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2), which is a positive strand RNA virus. The SARS-CoV-2 genome and its association to SAR-CoV-1 vary from ca. 66% to 96% depending on the type of betacoronavirdeae family members. With several drugs, viz. chloroquine, hydroxychloroquine, ivermectin, artemisinin, remdesivir, azithromycin considered for clinical trials, there has been an inherent need to find distinctive antiviral mechanisms of these drugs. Curcumin, a natural bioactive molecule has been shown to have a therapeutic potential for various diseases, but its effect on COVID-19 has not been explored. In this study, we show the binding potential of curcumin targeted to a variety of SARS-CoV-2 proteins, viz. spike glycoproteins (PDB ID: 6VYB), nucleocapsid phosphoprotein (PDB ID: 6VYO), membrane glycoprotein (PDB ID: 6M17) along with nsp10 (PDB ID: 6W4H) and RNA dependent RNA polymerase (PDB ID: 6M71) structures. Our results indicate that curcumin has high binding affinity towards nucleocapsid and nsp 10 proteins with potential antiviral activity.

This article describes a simple Susceptible Infected Recovered (SIR) model fitting with COVID-19 data for the month of march 2020 in New York (NY) state. The model is a classical SIR, but is non-autonomous; the rate of susceptible people becoming infected is adjusted over time in order to fit the available data. The death rate is also secondarily adjusted. Our fitting is made under the assumption that due to limiting number of tests, a large part of the infected population has not been tested positive. In the last part, we extend the model to take into account the daily fluxes between New Jersey (NJ) and NY states and fit the data for both states. Our simple model fits the available data, and illustrates typical dynamics of the disease: exponential increase, apex and decrease. The model highlights a decrease in the transmission rate over the period which gives a quantitative illustration about how lockdown policies reduce the spread of the pandemic. The coupled model with NY and NJ states shows a wave in NJ following the NY wave, illustrating the mechanism of spread from one attractive hot spot to its neighbor.

In Japan, schools were suddenly closed all over the country with one month left at the end of the school year to prevent the spread of new coronavirus infections. Although previous studies have shown that quarantine and isolation have a negative impact on mental health, the impact of school closure on children's mental health is not clear. This study examined mental health indicators, such as emotional symptoms, in addition to behavior during school closure and anxiety after school resumes, among children in three primary schools for which survey data existed in December before school closure. No cases of infection have been confirmed in the area where the school was located at the time of the survey. As a result, anxiety about whether they would be able to return to their normal routine after school resumed was associated with mental health. In addition, there was a worsening of emotional symptoms in those who were in medium group of school adjustment as of December.

Since the effects of renin–angiotensin–aldosterone system (RAAS) inhibitors on the clinical outcomes of coronavirus disease-19 (COVID-19) have been conflicting in different studies, we performed this meta-analysis. A systematic search of published articles was performed in PubMed and EMBASE from January-May 5, 2020. Studies that reported the clinical outcomes of patients with COVID-19, stratified by the class of concomitant antihypertensive drug therapy, were included. The Mantel-Haenszel random effects model was used to estimate pooled odds ratio (OR). A total of 6,997 hypertensive patients with COVID-19 were included. The overall risk of poor patient outcomes (severe COVID-19 or death) was lower in patients taking RAAS inhibitors (OR=0.84, 95% CI: [0.73, 0.96]; P=0.017) compared with those receiving non-RAAS inhibitor antihypertensives. Patients taking angiotensin-I-converting enzyme inhibitors (ACEIs) were less likely to experience poor clinical outcomes (OR=0.73, 95% CI: [0.58-0.92]; P=0.01) compared with those receiving angiotensin-II receptor blockers (ARBs). Compared to all other antihypertensives, ACEIs decreases the risk poor COVID-19 outcomes (OR=0.77, 95% CI: [0.63-0.93]) while ARBs did not (OR=1.13, 95% CI: [0.95-1.35]). The risk of poor patient outcomes from COVID-19 was lower in patients who received RAAS inhibitors compared with those who took non-RAAS inhibitors. Unlike ARBs, ACEIs might help in decreasing the severity and mortality of COVID-19.

Governments all over the world are currently grappling with the COVID-19 pandemic. While some countries were very hard hit, others were only mildly hit but all are still taking measures to mitigate the consequences. The virus emerged in December 2019 in Wuhan, China and spread to most continents by the beginning of March 2020, which led to the World Health Organization declaring it as a pandemic on the 11^th of March 2020. Since it was a novel disease, there was limited information on the virus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) belongs to the same family as the Severe Acute Respiratory Syndrome Coronavirus 1 (SARS-CoV-1) and the Middle East Respiratory Syndrome Coronavirus (MERS-CoV). Researchers all over the world started working simultaneously to understand the virus to provide the necessary treatment regime or vaccine in order to reduce the impact of the virus on its victims. Africa and other developing countries with limited resources and poor planning and management are expected to be among the worst hit in the long run. The implications of the COVID-19 on food, water, hygiene, sanitation, and the environment in Africa have been reviewed in this paper, as well as possible implications they may pose to the population, based on the existing common practices and their immediate impacts. This information can assist policymakers in Africa to adequately plan the management of the COVID-19 in order to lessen its impact on the population.

A new coronavirus (SARS-CoV-2) have determined a pneumonia outbreak in China (Wuhan and Hubei) on December 2019. While pharmaceutical and non-pharmaceutical intervention strategies are strengthened worldwide, the scientific community has been studying the risk factors associated with SARS-Cov-2, to enrich epidemiological information. For a long time, before the industrialized era, air pollution has been a real and big health concern and it is today a very serious environmental risk for many diseases and anticipated deaths in the world. It has long been known that air pollutants increasing the invasiveness of pathogens for humans by acting as a carrier and making people more sensitive to pathogens through a negative influence on the immune system. Based on scientific evidences, the hypothesis that air pollution, resulting from a combination of factors such as meteorological data, level of industrialization as well as regional topography, can acts both as an infection carrier as a harmful factor of the health outcomes of COVID-19 disease has been raised recently. This hypothesis is turning in scientific evidence, thanks to the numerous studies that have been launched all over the world. With this review, we want to provide a first unique view of all the first epidemiological studies relating the association between air pollution and SARS-CoV-2. Major findings are consistent, highlighting the important contribution of air pollution on the COVID-19 spread and with a less extent also PM₁₀.

During the period of health emergency linked to the current COVID-19 pandemic, the management of children's oral health presents specific problems related to the infectious spread of the disease. These problems must be faced on the one hand by acting on the oral health prevention methods, and on the other by implementing specific protocols relating both to the conditions of oral pathologies that normally do not represent an emergency, and to those clinical situations that fall into the category of pediatric dental emergencies. In this perspective, in addition to defining rigorous and highly effective infection control protocols in the dental settings, it is of fundamental importance to work on remote communication and education aimed at maintaining the oral health of the children. This article, after an analysis of the risk factors from COVID-19 associated with pediatric dental treatment, presents a series of considerations on potential oral prevention strategies and on the management of emergency and non-emergency dental procedures in a context of disease transmission control, proposing new approaches and models of treatment based also on remote interaction techniques which will then retain their usefulness even at the end of the current emergency period.

At present time world is facing from the coronavirus disease known as Covid-19. The first case of the coronavirus was reported in the December, 2019 in the Wuhan city of China which is known as the major transportation hub of China. After the spread of Covid-19 many countries have shut down their sea ports and airports. They have banned the import and export activities. Also, China is the major distributor of the raw materials which affect the manufacturing activities across the globe due to lockdowns. India is the developing country due to the Covid-19 spread the cases reported in the India government has lockdown the country for 41 days which affected the manufacturing activities and majorly it affects the supply chains and economy of the country. In the present paper we have discussed the effect of Covid-19 on Indian economy and on supply chains in India. There are total of 18 critical barriers are found out which affected the supply chains in the India. It is expected that this study will helpful the researchers to develop the conceptual models to overcome from this issue.

Background: The COVID-19 transmission has been established to occur through respiratory droplets from coughing and sneezing. Health agencies have strongly recommended the use of facemask as a precaution from cross-transmission. Objective: This study investigated the prevalence of facemask use among visitors to the hospital. This study also investigated the demographic factors contributing to unacceptable facemask practice. Setting: This prospective observational study was done among hospital visitors to a district specialist hospital during COVID-19 pandemic outbreak. Methods: Individuals entering through dedicated entry point were observed for the type, category and practice of wearing personal protective equipment. Inclusion criteria for this study were any individual's ≥ 2 years old entering the treatment facility from selected entry points. Patients were categorized into two groups of acceptable and unacceptable facemask practice. The Pearson chi-square was used to test for differences in investigated variables in the univariate setting and Binary Logistic regression model was used in the multivariate setting. Main Outcome Measure: Prevalence, acceptance practice and odds ratio of unacceptance of facemask use. Results: Among 1652 individuals included in the final analysis, 1574 (96.9%) was observed wearing facemask with 1269 (72.0%) of individuals worn medical-grade facemask. However, among them, only 1397 (88.8%) individuals' facemask practice was acceptable while the reaming 177 (11.2) individuals were perceived with unacceptable facemask practice. Male individuals, Malay ethnic and high risk age group are 1.47 times (Odds Ratio: OR=1.47; 95% CI, 1.06-2.06; p=.023), 2.18 times (OR=2.18; 95% CI, 1.55-3.08; p<.001) and 1.99 times (OR=2.18; 95% CI, 1.42 - 2.77; p<.001) more likely to exhibit unacceptable facemask practice respectively. Conclusion: Extensive use of facemasks coupled with environmental hygiene measures is a public health strategy which can help to mitigate the COVID-19 epidemic impact. However, a targeted comprehensive strategy to improve compliance to proper facemask practice among the high-risk population is needed to achieve maximal protective benefit.

The ongoing COVID-19 pandemic is shaking the foundations of public health governance all over the world. Researchers are challenged by informing and supporting authorities on acquired knowledge and practical implications. This commentary applies established theories of risk perception research to COVID-19 and reflects on the role of risk perceptions in these unprecedented times. Moreover, it calls for utilizing the knowledge on risk perception to improve health risk communication, build trust and contribute to a collaborating governance.

COVID-19 is fast spreading around the globe in a highly contagious manner. In this article we have described that after prolonged interventions the percentage growth curve for COVID-19 cases showed a flattened nature, after prolonged volatility in number of COVID-19 cases. The stability in the growth curve was continuously maintained from 18 April, 2020 to 29 April, 2020. The significance of this sustained stable curve on survival & doubling time has been discussed. One significant part of the study reflected that the doubling time of COVID-19 cases showed a negative correlation with the percent increase in COVID-19 cases (R=0.301). It is plausible that if such negative correlation is maintained with further flattening of the growth curve at a lower level, it may influence the infective ability of nCoV-19 & ultimately have a positive evolutionary implication on the spread of COVID-19 among the population.

Dental services are significantly impacted by the COVID-19 pandemic. Almost all dental procedures carry a high infection risk for providers and patients due to spread of aerosols. As a consequence, national public health agencies, and dental professional associations have issued guidelines for enhanced infection control, personal protection equipment and limiting care to urgent or emergency services. However, there is no dental service concept for disaster preparedness or response that might be applied. Similarly, pathways to care provision in a post-pandemic future are missing. We propose Safe Aerosol-free, Emergent Dentistry (SAFE Dentistry) as one approach to dental services during and emerging from pandemics. The concept’s starting point is the identification of the most common patient needs. The next step is to replace common treatments relating to the most common needs with alternative interventions with less infection risk because they do not generate aerosols. SAFE Dentistry is innovative, safe, and responds to the requirements of a pandemic and post-pandemic emergence where the risk of disease transmission remains high. SAFE Dentistry thereby ensures continuity of dental services while protecting providers and patients from infectious pathogens. Moreover, SAFE Dentistry allows dental service providers to remain operational and generate income even under pandemic conditions. Implementation and policy options for SAFE Dentistry include universal availability without co-payments by patients and a uniform bundled payment scheme for providers to simplify budgeting, reimbursement and to provide easier administration during a pandemic. Adaptations and adjustments of the concept are possible and encouraged, as long as the principle of avoiding aerosol-generation is maintained.

Global pandemic COVID-19 is in stage 4 of widespread local transmission in Bangladesh- the country which did not have a noteworthy health policy and legislative structures to combat COVID-19 like a pandemic. Early strategic planning and groundwork for evolving and established challenges are crucial to assemble resources and react in an appropriate timely manner. This article, therefore, focuses on the public perception of comparative lockdown scenario analysis and how they may affect the sustainable development and the strategic management regime of COVID-19 pandemic in Bangladesh socioeconomically. Response from 159 respondents was collected via a purposive sampling survey method through a questionnaire, and 54 statements were collected for scenario analysis. Datasets were analyzed through a set of statistical techniques including Principal Component Analysis (PCA), hierarchical Cluster Analysis (CA), Pearson’s correlation matrix (PCM), Linear regression analysis (LRA), and psychometric characteristics were included in the Classical Test Theory (CTT) analysis. There were good associations among the lockdown scenarios and response strategies to be formulated. A strong significant positive relationship was observed between people who will start moving towards regular life and the formal and informal economic activities will be started in lockdown scenario 1(r=0.671, p<0.01). The scenario one describes how the death and infection rate will increase if Govt withdraw the partial lockdown before 40 to 50 days. Scenario 2 outlines people’s movement will enable low-level community transmission of COVID-19 with the infection and death rate will increase slowly (r=0.540, p<0.01). Moreover, there will be less supply of necessities of daily use with a price hike (r= 0.680, p<0.01). Scenario 3, full lock down will reduce the community transmission and death from COVID-19 (r=0.545, p<0.01). Moreover, along with the other problems gender discrimination and gender-based violence will increase rapidly (r=0.661, p<0.01). Form regression analysis, due to full lockdown, the formal and informal business, economy and education sector will be hampered severely (R=0.695), there was a strong association between the loss of livelihood and unemployment rate will increase due to business shutdown (p<0.01) and poor communities both in urban and rural areas will be affected severely (p<0.01).All these will further aggravate the humanitarian needs of the most vulnerable groups in the country in the coming months to be followed which needs to be dealt with proper response plans. It will undoubtedly affect the targets of global sustainable development goals (SDGs) of 2030 and all other development targets.

Nowadays tourism is growing as a gigantic, global business accounting for 10.4 % of Global GDP and 10% of global employment (Joppe, 2020). This review paper aims to explore the risks borne for tourism sector by the outbreak of corona-virus in 2020. Tourism sector is a highly vulnerable sector and the costs that will be borne from corona-virus pandemic will be devastating, particularly for the countries relying on this sector as a basic source of income. The paper suggests possible solutions and adaptation routes, while at the same time reviews lessons of the past from other pandemics and crisis. This paper is very useful for tourism policy makers and governments in countries where tourism contributes a significant part of their GDP, but also for other economic sectors closely but indirectly connected in the tourism value chain.

The very first case of corona-virus illness was recorded on 30 January 2020, in India and the number of infected cases, including the death toll, continues to rise. In this paper, we present short-term forecasts of COVID-19 for 28 Indian states and five union territories using real-time data from 30 January to 20May 2020. Applying Holt’s second-order exponential smoothing method and autoregressive integrated moving average (ARIMA) model, we generated 10-day ahead forecasts of the likely number of infected cases and deaths in India until 29 May2020. Our results show that the number of cumulative cases in India will rise to169109 [PI 95% (14426, 19455)], concurrently the number of deaths may increase to 4863 [PI 95% (4221, 5551)] by 29 May 2020.Further, we have marked the states (e.g. Delhi, Uttar Pradesh, Rajasthan, Madhya Pradesh, Maharashtra, Gujarat, and Tamil Nadu) where outburst is expected by considering the cases above three standard deviations. Under the worst-case scenario, Maharashtra is likely to be the most affected state with around 62628 [PI 95% (52840, 73555)] cumulative cases by 29 May 2020. However, Kerala and Karnataka are likely to remain in the lesser affected region. The presented results mark the states where lockdown by 1 June2020, can be loosened.

BackgroundThe novel virus COVID-19, also known as SARS-CoV‑2, is currently rapidly spreading around the globe and pushing healthcare systems to the limits of their capacity. One of the functions of predictive models is to timely act for epidemic preparedness including hospital preparedness. In Egypt, like many other countries in the world, the epidemic situation and forecasting have not yet sufficiently studied. ObjectiveThe study was carried out to develop a short-term forecast scenario for the COVID-19 epidemic situation in Egypt and predict the hospital needs to accommodate the growing number of cases.MethodsSecondary data from the COVID-2019 daily reports and the report issued 8^th of April by the Egyptian Ministry of Health and Population were used. Due to the daily changing level of knowledge and data, the article reflects the status up to 18 April 2020. The prediction was based on the exponential growth rate model. For the depiction of the situation, the full length of the epidemic timeline was analyzed (from February 14^th till April 18^th). The growth rates and their rates of decline during the period from the 22^nd of March till the 18^th of April were calculated and extrapolated in the coming 7 weeks. The predicted hospital needs were assessed against the announced allocated resources.ResultsThe epidemic curve in Egypt is on the ascending arm as of April, 18. The active cases showed exponential growth from the start of the epidemic till April, 18. At the end of this period time, the recovery rate was 23.12% and the case fatality rate (CFR) was7.39. The case fatality rate median level during the last four weeks was 6.64. The active cases are expected to reach more than 20,000 by late May then starts to decline. The allocated regular hospital beds are predicted to show shortage by the time of the release of the paper. The intensive care units (ICU) beds and ventilators are predicted to show insufficiency on May 6.Conclusions: The COVID-19 epidemic in Egypt is expected to continue on the rise for the next few weeks and expected to start to decline late in May, 2020. Our estimates should be useful in preparedness planning. Serious actions should be taken to provide ICU beds and ventilators enough for the predicted number of cases that would need them, not later than the end of April. Mitigation actions have to continue for the coming 6 weeks or until the epidemic situation is more clearly seen.

This review chronicles the indirect transmission method which seems to be overlooked by most people and makes attempts to clearly document the various transmission ways with a hope that such information may strengthen the knowledge base of researchers towards methods of eradicating the pandemic. Current knowledge of transmission and exposure of SARS-CoV-2 has been explained. Various researchers have put forward different ways of exposure and transmission. Literature does not reveal whether the indirect transmission route is the dominant one. However total lockdown could be a veritable means to reduce both direct and indirect transmission routes. In many countries where the indirect transmission has been reduced, the scourge of the virus is less. The work creates awareness on the need to watch out for those routes of transmissions that may not be popular and suggested key knowledge gaps that needs to filled.

Rapidly spreading disease, COVID-19 is classified as the human-to-human transmission-able disease and currently is a pandemic in the Globe. In this paper, we propose conceptual mathematical models for COVID-19 outbreak and it's control measurement; quarantine, hospitalization and the effect of panic and anxiety. In this situation, mathematical models are a important tool to employ an effective strategy in order to fight against this pandemic. We establish the positivity and boundedness of solutions, local and global stability analysis of equilibria to examine its epidemiological relevance. To validate the model and estimating the important model parameters and prediction about the disease, we consider the real cases of Italy from $15^{th}$ Feb to $13^{th} $ April 2020. In a series of graphical map, we have presented the comparative study to estimate the current scenarios and to predict the control measurement time boundary of the outbreak.

Objectives: This study aims to identify, report, and analyze registered and published clinical trials and observational studies for the pharmacological treatment of COVID-19 conducted in China. Methods: A strategic search was conducted via the Chinese Clinical Trial Registry to identify and extract clinical trials and observational studies registered and conducted in China for the pharmacological treatment of COVID-2019 between January 1^st, 2020 and March 21^st, 2020. This was further supplemented by searches conducted via the China National Knowledge Infrastructure (CNKI) database, the MEDLINE database, the World Health Organization (WHO) database, and MedRxiv and BioRxiv electronic platforms for preprint articles, published up until April 8^th, 2020. Studies available in Chinese and English were included in the searches and extracted. A primary descriptive analysis was performed for registered clinical trials and observational studies identified in the Chinese Clinical Trial Registry based on the extraction of the following clinical study information: trial ID, planned date of enrollment, recruitment status, study design, population, sample size, intervention/exposure group, control /reference group, dosage, and primary outcomes. A secondary descriptive analysis was performed for published clinical trials and observational studies identified from the supplementary databases based on the extraction of the following published clinical study information: study design, population, intervention/exposure group, control /reference group and main results as appropriate. Results: A total of 221 clinical trials and observational studies were included from all databases searched. From the Chinese Clinical Trial Registry, 195 registered clinical studies including 170 clinical trials and 25 observational studies were identified and included for primary analysis. From the supplementary databases, 26 published clinical studies including 8 clinical trials and 18 observational studies were included for secondary analysis. Of these 26 published clinical studies, 18 studies, including 3 clinical trials and 15 observational studies were identified from CNKI, 2 studies including 1 clinical trial and 1 observational study from MEDLINE, 2 including 1 clinical trials and 1 observational studies from the WHO database, and 4 including 3 clinical trials and 1 observational studies from MedRxiv and BioRxiv platforms. In the primary analysis, among the 170 clinical trials included from the Chinese Clinical Trial Registry, 101 investigated western medicines (WMs), while 15 investigated Traditional Chinese Medicines (TCMs), and 54 investigated a combination of TCMs and WMs. Among the 25 included observational studies from the Chinese Clinical Trial Registry, 2 investigated WMs, 2 investigated TCMs, and 21 investigated a combination of TCMs and WMs. The total number of exposed patients in all 195 clinical studies from the Chinese Clinical Trial Registry amounted to 24,500. In the secondary analysis, treatment with Lopinavir-ritonavir and treatment with Hydroxychloroquine was not associated with a difference from standard of care in the rate of RT-PCR negativity; treatment with a combination of Lopinavir-ritonavir, interferon α, and Lian-Hua-Qing-Wen capsule was found to significantly improve the effective rate of treatment compared with Interferon α combined with Lian-Hua-Qing-Wen capsule. Conclusions: China is generating a massive source of evidence that is critical for defeating the COVID-19 pandemic. Not only the clinical experience, but also the scientific evidence should be shared with the global scientific community.

Introduction The COVID-19 virus was initially reported in Dec 2019 as the causative agent of a pneumonia breakout in Wuhan China. This virus rapidly spread from China to Europe and the East Coast of the United States eventually reaching the South West United States and indigenous tribes in mid -March. Since, then the indigenous tribes have been devasted by the virus which the Governor of New Mexico has likened as an existential threat. Methodology A PubMed search was performed utilizing the words: Navajo Indian, Indigenous Indian, Wuhan Virus, COVID-19, SARs coronavirus, ACE2, S protein, virulence, clinical presentation, epidemiology, genome, treatment, structure, MERs, pathogenesis and/or pathology alone and in combination with other terms. Each paper was evaluated by three content experts for quality, reproducibility, credibility and reputation of the journal Results: Navajo’s and other indigenous peoples may have elevated levels of ACE2 receptors in their lungs and other tissues allowing greater susceptibility to the COVID-19 virus. Increased levels of diabetes and protein nutrition are directly related to increased morbidity and mortality in this group while obesity, COPD, and heart diseas are not. The increased morbidity and mortality is exasperated by an inability to test for COVID-19 Conclusion: The infectivity rate of Navaho’s on the reservation is 22 times higher than the national average with a death rate near 4%. Comorbidites account for some of the increased morbidity and mortality while lack of access to adequate health care unnecessarily magnifies the poor outcome. The threat to indigenous tribes in the Southwest of COVID-19 is dire.

The symptoms most commonly reported by patients affected by coronavirus disease 2019 (COVID-19) include cough, fever, and shortness of breath. However, other major events usually observed in COVID-19 patients (e.g. high blood pressure, thrombosis, pulmonary embolism) seem to suggest that the virus is targeting the endothelium, one of the largest organs in the human body. Herein, we report both clinical and preclinical evidence supporting the hypothesis that the endothelium is a key target organ of COVID-19.

Background: The world, now in an emergency of preventing the drastic spread of COVID-19. After the infection was first reported in December 2019, almost every country did not pay attention to this highly contaminated disease and failed to react swiftly. Now the whole universe is in an vulnerable state, loosing a great loss of lives and facing difficulties in all socio-economic aspects. That is why we have the urge to develop an efficient mathematical model (quarantine) based on social consciousness to control the epidemic. Methods: This is a quarantine mathematical model. The outcome of the system is dependent on social consciousness. We have calculated the awareness level by considering various socio-economic factor of each country. In our model, the parameters are Education Index, GDP per capita, population density, high literacy and stable economy. To maximize the efficiency of the model, it has to be implemented in initial stage. However, strict application of the method in vigorous stage of epidemic will also bring a satisfactory outcome. Results: Higher social consciousness will decrease the number of infected population dramatically while minimal or lower awareness will do a outburst. Conclusion: Outbreak will be in control of health care system, lower the death rate and will ensure social and economic stability.

We report smooth weaning from mechanical ventilation in a patient with COVID-19. The use of the supraglottic airway device can cause fewer coughs in weaning from mechanical ventilation. This procedure avoids the aerosol-generating procedure, tracheal extubation, and is beneficial in terms of occupational health for health care workers.

The SARS-CoV-2 is a recently identified positive sense single stranded RNA virus and member of the coronavirus family of viruses. It is thought to be the etiological factor for the ongoing COVID-19 pandemic. This virus is thought to have originated from bats and acquired ability of human-to-human transmission. While SARS-CoV-2 is relatively benign, it has infected more than half a million people (as of March 29^th 2020) worldwide and the number of infected people continues to rise. More than 170 countries have reported COVID-19 positive cases. With a mortality rate of less than both the previous coronavirus outbreaks, COVID-19 has (conversely) caused the death of over 33,980 (as of 29^th March, 2020 at 22.00 hours EDT) people worldwide and the number is increasing. Given the enormous impact of this virus on human health and wellbeing and consequent devastating impacts on world trade, economics and quality of life, it is important to understand this virus better and get insight into its pathogenic mechanisms which will aid in devising effective measure to curb its spread and predict future pattern of its interaction with humans. Though very little is known about this SARS-CoV-2 but its mechanisms and patterns of spread can be speculated (with caution, nevertheless) from what we know about its closest relatives SARS-CoV-1 (responsible for SARS-2002 epidemic) and MERS-CoV (responsible for MERS-2012 epidemic). In the present review, we aim at bringing together the coherent and peer reviewed literature about the SARS-CoV-2 and its close relatives and try to understand its infection patterns and reconstruct its pathogenic mechanisms with anecdotes on diagnosis and future directions. We hope that this paper will serve the purpose of being a reliable source of information to scientists, clinicians and general public.

The current outbreak of the novel coronavirus also known as COVID-19 was declared as a public health emergency by the WHO where over a million people have been affected by the disease with over 50000 deaths till date. Social distancing is a method to minimize crowd interactions and prevent the spread of disease within groups of people. This is a common practice which has been carried out over generations to minimize the spread of virus by limiting its reproduction rate (R0) among communities. The article focuses on how social distancing has been used to deal previous pandemics globally and the issues that needs to be addressed to tackle the COVID-19 threat.

Since the Coronavirus disease (COVID-19) outbreak at the end of 2019, the past two month has seen an acceleration both in and outside China in the R&D of the diagnostics, vaccines and therapeutics for this novel coronavirus. As one of the molecular forces that determine protein structure, electrostatic effects dominate many aspects of protein behaviour and biological function. Thus, incorporating currently available experimental structures related to COVID-19, this article reports a simple python-based analysis tool and a LaTeX-based editing tool to extract and summarize the electrostatic features from experimentally determined structures, to strengthen our understanding of COVID-19's structure and function and to facilitate machine-learning and structure-based computational design of its neutralizing antibodies and/or small molecule(s) as potential therapeutic candidates. Finally, this article puts forward a brief update of the structurally observed electrostatic features of the COVID-19 coronavirus.

The outbreak of novel coronavirus (COVID-19) infections in 2019 is in dire need of finding potential therapeutic agents. In this study, we used molecular docking to repurpose HIV protease inhibitors and nucleoside analogues for COVID-19, with evaluations based on docking scores calculated by AutoDock Vina and RosettaCommons. Our results suggest that Indinavir and Remdesivir possess the best docking scores, and comparison of the docking sites of the two drugs reveal a near perfect dock in the overlapping region of the protein pockets. After further investigation of the functional regions inferred from the proteins of SARS coronavirus, we discovered that Indinavir does not dock on any active sites of the protease, which may give rise to concern in regards to the efficacy of Indinavir. On the other hand, the docking site of Remdesivir is not compatible with any known functional regions, including template binding motifs, polymerization motifs and nucleoside triphosphate (NTP) binding motifs. However, when we tested the active form (CHEMBL2016761) of Remdesivir, the docking site revealed a perfect dock in the overlapping region of the NTP binding motif. This result suggests that Remdesivir could be a potential therapeutic agent. Clinical trials still must be done in order to confirm the curative effect of these drugs.

The ongoing outbreak of the novel coronavirus pneumonia (also known as COVID-19) has triggered a series of stringent control measures in China, such as city closure, traffic restrictions, contact tracing and household quarantine. These containment efforts often lead to changes in the contact pattern among individuals of the population. Many existing compartmental epidemic models fail to account for the effects of contact structure. In this paper, we devised a pairwise epidemic model to analyze the COVID-19 outbreak in China based on confirmed cases reported during the period February 3rd--17th, 2020. By explicitly incorporating the effects of family clusters and contact tracing followed by household quarantine and isolation, our model provides a good fit to the trajectory of COVID-19 infections and is useful to predict the epidemic trend. We obtained the average of the reproduction number $R=1.494$ ($95\%$ CI: $1.483-1.507$) for Hubei province and $R=1.178$ ($95\%$ CI: $1.145-1.158$) for China (except Hubei), suggesting that some existing studies may have overestimated the reproduction number by neglecting the dynamical correlations and clustering effects. We forecasted that the COVID-19 epidemic would peak on February 13th ($95\%$ CI: February $9-17$th) in Hubei and 6 days eariler in the regions outside Hubei. Moreover the epidemic was expected to last until the middle of March in China (except Hubei) and late April in Hubei. The sensitivity analysis shows that ongoing exposure for the susceptible and population clustering play an important role in the disease propagation. With the enforcement of household quarantine measures, the reproduction number $R$ effectively reduces and epidemic quantities decrease accordingly. Furthermore, we gave an answer to the public concern on how long the stringent containment strategies should maintain. Through numerical analysis, we suggested that the time for the resumption of work and production in China (except Hubei) and Hubei would be the middle of March and the end of April, 2020, respectively. These constructive suggestions may bring some immeasurable social-economic benefits in the long run.

The outbreak of the 2019 Novel Coronavirus (2019-nCoV) has rapidly spread from Wuhan, China to multiple countries, causing staggering number of infections and deaths. A systematic profiling of the immune vulnerability landscape of 2019-nCoV is lacking, which can bring critical insights into the immune clearance mechanism, peptide vaccine development, and antiviral antibody development. In this study, we predicted the potential of all the 2019-nCoV viral proteins to induce class I and II MHC presentation and form linear antibody epitopes. We showed that the enrichment for T cell and B cell epitopes is not uniform on the viral genome, with several focused regions that generate abundant epitopes and may be more targetable. We showed that genetic variations in 2019-nCoV, though fewer for the moment, already follow the pattern of mutations in related coronaviruses, and could alter the immune vulnerability landscape of this virus, which should be considered in the development of therapies. We create an online database to broadly share our research outcome. Overall, we present an immunological resource for 2019-nCoV that could significantly promote both therapeutic development and mechanistic research.

People from Black and Asian backgrounds are more likely to die from Covid-19 but less likely to be vaccinated, threatening to exacerbate health inequalities already experienced by ethnic minority groups. Literature suggests that mistrust rooted in structural inequality may be a key barrier to Covid-19 vaccine uptake. We need to better understand how structural inequalities influence vaccine confidence. Understanding and addressing these processes is likely to lead to longer-term impacts than information alone. We draw on health and sociological theories of structure and agency to inform our understanding of structural factors. We conducted qualitative interviews and focus groups with 22 people from London and surrounding areas in December 2021 to March 2022. Fifteen participants were members of the public from ethnic minority backgrounds and 7 were professionals working with the public to address concerns and encourage vaccine uptake. Our findings suggest that people from ethnic minority backgrounds make decisions regarding Covid-19 vaccination based on a combination of how they experience external social structures (including political authority, social positioning and racial inequality) and internal processes (what they believe and understand about Covid-19 vaccines). We may be able to support knowledge accumulation through the provision of reliable and accessible information, particularly through primary and community care. But we recommend a number of changes to research, policy and practice which address structural inequalities. These include working with communities to improve ethnicity data collection, increasing funding allocation to health conditions where ethnic minority communities experience poorer outcomes, greater transparency and public engagement in the vaccine development process, and culturally adapted research recruitment processes.

The aim of study was to investigate epidemiology aspects of magnetic resonance imaging (MRI) during COVID-19 pandemic. The study comprised depersonalized residents of Tomsk and Tomsk Region (n = 1714). Invitations to take online survey were sent to 50,000 residents by target SMS with response rate of 1.2% (n = 727, Cohort 1). Cohort 2 comprised retrospective patients (n = 987) who underwent contrast-enhanced cardiac MRI (CMR) in 2019-2022. Referrals, clinical characteristics, diagnosis, gender, age, past COVID-19, MRI study protocols, and MRI data were analyzed. 29% of respondents in cohort 1 received MRI examination within past two years; 26% of respondents considered MRI the most informative imaging modality for detecting COVID-19 pneumonia; 12% of respondents reported MRI unavailable. Proportion of CMR among MRI studies increased during COVID-19 pandemic, and maximum incidence of cardiac diseases detected by MRI was in 2021. Incidence of myocardial fibrosis increased from ~67% in 2019 to ~84% in 2022. The rate of outpatient MRI studies significantly increased in 2020, but returned to pre-pandemic level in 2021. COVID-19 pandemic increased the need for MRI and CMR. Patients with history of COVID-19 had persistent and newly occurring symptoms of myocardial damage suggesting chronic cardiac involvement requiring continuous follow-up.

Human coronaviruses cause both upper and lower respiratory tract infections in humans. In 2012 a sixth human coronavirus (hCoV) was isolated from a patient presenting with severe respiratory illness. The 60-year-old man died as a result of renal and respiratory failure after admission to a hospital in Jeddah, Saudi Arabia. The aetiological agent was eventually identified as a coronavirus and designated Middle East respiratory syndrome coronavirus (MERS-CoV). MERS-CoV has now been reported in more than 27 countries across the Middle East, Europe, North Africa and Asia. As of July 2017, 2040 MERS-CoV laboratory confirmed cases, resulting in 712 deaths, were reported globally, with a majority of these cases from the Arabian Peninsula. This review summarises the current understanding of MERS-CoV, with special reference to the (i) genome structure, (ii) clinical features, (iii) diagnosis of infection and (iv) treatment and vaccine development.