The COVID-19 pandemic is the biggest public health threat facing the globe today. Multiple vaccines have been approved, however the emergence of viral variants such as the recent Omicron, raises the possibility of booster doses to achieve adequate protection. In Brazil, the CoronaVac (Sinovac) vaccine was used, however it’s important to assess the immune response to this vaccine over time. This study aimed to monitor the anti-SARS-CoV-2 antibody responses in those immunized with CoronaVac and SARS-CoV-2 infected individuals. Samples were collected between August 2020 and August 2021. Within the vaccinated cohort, some individuals had history of infection by SARS-CoV-2 prior to immunization and others not. We analyzed RBD-specific and neutralizing- antibodies. Anti-RBD antibodies were detected in both cohorts, with a peak between 45-90 days post infection or vaccination, followed by a steady decline over time. In those with previous history of COVID-19, a higher, longer, more persistent response was observed. This trend was mirrored in the neutralization assays, where infection followed by immunization resulted in higher, longer lasting responses which were conditioned on the presence of levels of RBD antibodies right before the vaccination. This supports the necessity of booster doses of CoronaVac in due course to prevent serious disease.

After the first weeks of vaccination against the SARS-CoV-2, several cases of acute thrombosis were reported. These news reports began to be shared frequently across social media platforms. The aim of this study was to conduct an analysis of Twitter data related to the overall discussion. Data was retrieved from 14th March to 14th April using the keyword ‘blood clots’. A dataset with n=266,677 tweets was retrieved, and a systematic random sample of 5% of tweets (n=13,334) were entered into NodeXL for further analysis. Social network analysis was used to analyse the data by drawing upon the Clauset-Newman-Moore algorithm. Influential users were identified by drawing upon the betweenness centrality metric. Text analysis was applied to identify the key hashtags and websites used at this time. More than half of the network was comprised of retweets and the largest groups within the network were broadcast clusters where a number of key users were retweeted. The most popular narratives were around highlighting the low risk of obtaining a blood clot from a vaccine and highlighting higher blood clot risks in medicines commonly consumed. A wide-variety of actors drove the discussion on Twitter ranging from writers, physicians, the general public academics, celebrities, and journalists. Twitter was used to highlight the low potential of obtaining a blood clot from a vaccine and encouraged vaccinations among the public.

COVID-19 has a severe risk of spreading rapidly, the quick identification of which is essential. In this regard, chest radiology images have proven to be a practical screening approach for COVID-19 affected patients. This study proposes a deep learning-based approach using Densenet-121 to detect COVID-19 patients effectively. We have trained and tested our model on the COVIDx dataset and performed both 2-class and 3-class classification, achieving 96.49% and 93.71% accuracy, respectively. By successfully utilizing transfer learning, we achieve comparable performance to the state-of-the-art method while using 15x fewer model parameters. Moreover, we performed an interpretability analysis using Grad-CAM to highlight the most significant image regions at test time. Finally, we developed a website that takes chest radiology images as input and detects the presence of COVID-19 or pneumonia and a heatmap highlighting the infected regions. Source code for reproducing results and model weights are available.

Covid-19 has caused infections and deaths worldwide. While research in the field of Data Science has contributed good predictions of positive Covid-19 case numbers, this study's review of literature shows there is little research in the use of variants of the virus in predictions. We set out to define and evaluate novel variant features. We find that features relating to variant trends, thresholds and amino acid substitutions are especially powerful in two tasks. In the first task, predicting Covid-19 case numbers, accuracy improved from 71.53% without variant features to 82.12% with variant features. In the second task, predicting transmission severity of variants between two classes, we created a method to build some variable ensembles through selecting appropriate models that are generated with variant features. The test results showed that our ensembles are more accurate and reliable. One particular ensemble of 14 models correctly classified 90.91% of variants, outperforming other models including the popular Random Forest ensemble. In addition, as the variant features have represented more underlying information about Covid-19 pathophysiology, our ensemble methods use only a few data samples to achieve an accurate prediction. The ensemble of 14 models uses only 50 cases of each variant, an ability that could be exploited for early detection of highly infectious variants. These research findings may benefit public health professionals, policy makers, and the research community in the collective efforts to overcome this disease.

The Physics Informed Neural Networks framework is applied to the understanding of the dynamics of Coronavirus of 2019. To provide the governing system of equations used by the framework, the Susceptible-Infected-Recovered-Death mathematical model is used. The study focused on finding the patterns of the dynamics of the disease which involves predicting the infection rate, recovery rate and death rate; thus predicting the active infections, total recovered, susceptible and deceased at any required time. The study used data that was collected on the dynamics of COVID-19 from the Kingdom of Eswatini between March 2020 and September 2021. The obtained results showed less errors thus making highly accurate predictions.

In response to the COVID-19 pandemic, social distancing measures were put into place to flatten the pandemic curve. It was projected older adults were at increased risk for poor psychological and health outcomes resulting from increased social isolation and loneliness. However, little re-search has supported this projection among community-dwelling older adults. While growing body of research has examined the impact of the COVID-19 pandemic on older adults, there is a paucity of qualitative research that captures the lived experience of community-dwelling older adults. The current study aimed to better understand the lived experience of community-dwelling older adults during the first six months of the pandemic. Semi-structured one on one interviews were conducting with independent living older adults aged 65 years and older. After achieving saturation, 22 interview were analyzed using inductive thematic analysis. Following a recursive process, two overarching themes emerged from the data: perceived threat and challenges of the pandemic and coping with the pandemic. Specifically, participants reflected on the threat of contracting the virus and challenges associated with living arrangement, social isolation, and financial insecurity. Participants shared their coping strategies to maintain health and wellbeing, including behavioral strategies, emotion-focused strategies, and social support. Overall, this re-search highlights resilience among older adults during the first six months of the pandemic.

Pre-COVID-19, doodling was identified as a measure of burnout in researchers attending a weekly, in-person health narratives research group manifesting team mindfulness. Under the group’s supportive conditions, variations in doodling served to measure change in participants’ reported depression and anxiety—internal states directly associated with burnout, adversely affecting healthcare researchers, their employment, and their research. COVID-19 demanded social distancing during the group’s 2020/21 academic meetings. Conducted online, the group’s participants who chose to doodle did so alone during the pandemic. Whether the sequestering of group participants during COVID-19 altered the ability of doodling to act as a measure of depression and anxiety was investigated. Participants considered doodling during the group’s online meetings increased their enjoyment and attention level—some expressed it helped them to relax. However, unlike face-to-face meetings during previous non-COVID-19 years, solitary doodling during online meetings was unable to reflect researchers’ depression or anxiety. COVID-19 limitations necessitating doodling alone maintained the benefits group members saw in doodling but hampered the ability of doodling to act as a measure of burnout in contrast to previous in-person doodling. This result is seen to correspond to one aspect of the group’s change in team mindfulness resulting from COVID-19 constraints.

The Dark Web is known as a place triggering a variety of criminal activities. Anonymization techniques enable illegal operations, leading to the loss of confidential information and its further use as bait, a trade product or even a crime tool. Despite technical progress, there is still not enough awareness of the Dark Web and its secret activity. In this study, we introduced the Dark Web Enhanced Analysis (DWEA), in order to analyze and gather information about the content accessed on the Dark Net based on data characteristics. The research was performed to identify how the Dark Web has been influenced by recent global events, such as the COVID-19 epidemic. The research included the usage of a crawler, which scans the network and collects data for further analysis with machine learning. The result of this work determines the influence of the COVID-19 epidemic on the Dark Net.

COVID-19 has been extremely difficult to control. The lack of understanding of key aspects of pandemics has affected virus transmission. On the other hand, there is a demand to incorporate Computational Thinking (CT) in the curricula with applications in STEM. However, there are still no exemplars in the curriculum that apply CT to real-world problems such as controlling a pandemic or other similar global crises. In this paper, we fill this gap by proposing exemplars of CT for modeling the pandemic. We designed exemplars following the three pillars of the APEC InMside framework for CT: algorithmic thinking, computational modeling, and machine learning. For each pillar, we designed a progressive sequence of activities that covers from elementary to high school. In an experimental study with elementary and middle school students from 2 schools of high vulnerability, we found that the computational modeling exemplar can be implemented by teachers and correctly understood by students. We conclude that it is feasible to introduce the exemplars at all grade levels, and that this is a powerful example of STEM integration that helps reflect and tackle real-world and challenging public health problems of great impact for students and their families.

Several recent surges in COVID-19 cases due to newly emerging variant strains of SARS-CoV-2 with greater transmissibility have highlighted the virus’s capability to directly modulate spike-ACE2 interactions and promote immune evasion by sterically masking the immunogenic epitopes. Recently, there have also been reports of the bidirectional transfer of coronavirus between different animal species and humans. The ability of coronavirus to infect and adapt to a wide range of hosts can be attributed to new variants that modify the molecular recognition profile of the spike protein (S protein). The receptor-binding domain of the spike protein specifically interacts with key host receptor molecules present on the host cell membranes to gain entry into the host and begin the infection cycle. In this review, we discuss the molecular, structural, and functional diversity associated with the coronavirus receptors across their different phylogenetic lineages and its relevance to various symptomatology in the rapid human-to-human infection in COVID-19 patients, tropism, and zoonosis. Despite this seeming diversity of host receptors, there may be some common underlying mechanisms that influence the host range, virus transmissibility, and pathogenicity. Understanding these mechanisms may be crucial in not only controlling the ongoing pandemic but also help in stopping the resurgence of such virus threats in the future.

Based on hospital capacities, facts from past experience with the coronavirus disease 2019 (COVID-19) virus and the number of dark infections during the second wave (DII = 2D2), a reasonable limiting value of 140/D2 for the 7-day incidence per 100,000 persons (MSDIHT) and a second wave herd immunization threshold fraction value of 0.26 in Germany were calculated. If the MSDIHT is held below this limiting value, the German hospital system can cope with the number of new seriously infected persons without any triage decisions. On the basis of the SIRV epidemics model, the classical threshold values for herd immunization were calculated for 18 countries. For these countries, the dates regarding when herd immunization against the second COVID-19 wave will be reached were estimated

The COVID-19 pandemic has severely affected the food supply chain, including producers, retailers, wholesalers, and customers. To minimize the impacts caused by pandemics and epidemics on food supply chains, it is fundamental to implement effective policies that ensure continuity in the provision, affordability, and distribution of basic food items. This research aims to identify the main impacts of pandemics and epidemics on food supply chains and policies that can minimize these impacts. Based on a systematic literature review (SLR), 174 documents are analysed to propose a taxonomy of impacts on four supply chain links: demand-side, supply-side, logistics and infrastructure, and management and operation. The taxonomy presents the main impacts, as well as the respective mitigation policies simultaneously. In addition, the literature review leads to the development of a comprehensive causal loop diagram (CLD) with the identification of main variables and their relationship with food supply chains. Finally, a specific research agenda is proposed by identifying main research gaps. These findings provide a structured method for evaluating policies that ensure the functioning of food supply chains, particularly in disruptions such epidemics and pandemics.

Background. A previous study demonstrated the performance of the Salivette® (SARSTEDT, Numbrecht, Germany) as a homogeneous saliva collection system to diagnose COVID-19 by RT-qPCR, notably for symptomatic and asymptomatic patients. However, for convalescent patients, the corroboration of molecular detection of SARS-CoV-2 in paired nasopharyngeal swabs (NPS) and saliva samples was unsatisfactory. Objectives. The aim of the present work was to assess the concordance level of SARS-CoV-2 detection between paired sampling of NPSs and saliva collected with Salivette® at two time points, with ten days of interval. Results. A total of 319 paired samples from 145 outpatients (OP) and 51 healthcare workers (HW) were collected. Due to significant waiting rate at hospital, most of the patients ate and/or drank in waiting their turn. Consequently, a mouth washing was systematically proposed prior saliva collection. None of the HW were diagnosed SARS-CoV-2 positive using NPS or saliva specimens at both time points (n=95) by RT-qPCR. The virus was detected in 56.3% (n=126/224) of the NPS samples from OP, but solely 26.8% (n=60/224) of the paired saliva specimens. The detection of the internal cellular control, the human RNase P, in more than 98% of the saliva samples, underlined that the low sensitivity of saliva specimens (45.2%) for SARS-CoV-2 detection was not attributed to an improper saliva sample storing or RNA extraction. Conclusions. Then, the mouth washing decreased viral load of buccal cavity conducting to impairment of SARS-CoV-2 detection. Viral loads in saliva neo-produced appeared insufficient for molecular detection of SARS-CoV-2. At the time that saliva tests could be a rapid, simple and noninvasive strategy to assess on large scale schooled children in France, the determination of the performance of saliva collection become imperative to standardize procedures.

After the arrival of a new airborne virus to the world, science is aiming to develop solutions to withstand the spread and contagion of the SARS-CoV-2 coronavirus. The most severe among the adopted measures is to remain in home isolation for a significant number of hours per day, in order to avoid the spreading of the infection in an uncontrolled way through public spaces. Recent literature showed that the major route of transmission is via aerosols produced especially in poorly ventilated inner spaces. With regard to contagion rates, accumulated incidence or number of hospitalizations due to COVID-19, Spain has reached very high levels, therefore this article develops a quantitative and qualitative analysis of the requirements established in Spain with respect to the European framework in reference to ventilation parameters indoors. For this, a case study has been analyzed, representing a common residence in current Spanish residential developments. Results show that the criteria established in the applicable regulations are not sufficient to ensure health as well as to avoid contagion by aerosols indoors.

India is ranked 5th in world in terms of Covid-19 publications accounting for 6.7% of the total. About 60% of the Covid-19 publications in the year 2020 are from United States, China, UK, Italy, and India. We present a bibliometrics analysis of the publi-cation trends and citation structure along with identification of major research clusters. By performing network analysis of authors, citations, institutions, key-words, and countries, we explore semantic associations by applying visualization techniques. Our study shows lead taken by United States, China, UK, Italy, India in Covid-19 research may be attributed to the high prevalence of Covid-19 cases in those countries witnessing the first outbreak and also due to access to Covid-19 data, access to labs for experimental trials, immediate funding, and overall support from the govt. agencies. Large number of publications and citations from India are due to co-authored publications with countries like United States, UK, China, and Saudi Arabia. Findings show health sciences with highest the number of publications and citations, while physical sciences and social sciences and humanities counts were low. A large proportion of publications fall into the open access category. With India as focus, by comparing three major pandemics SARS, MERS, Covid-19 from biblio-metrics perspective, we observe much broader involvement of authors from multiple countries for Covid-19 studies as compared to SARS and MERS. Finally, by applying bibliometric indicators, we see an increasing number of sustainable develop-ment-related studies from the Covid-19 domain, particularly concerning the topic of good health and well-being. This study allows for a deeper understanding on how the scholarly community from a populous country like India pursued research in the midst of a major pandemic which resulted in closure of scientific institutions.

The novel coronavirus disease (COVID-19) has created immense threats to public health on various levels around the globe. The unpredictable outbreak of this disease and the pandemic situation are causing severe depression, anxiety and other mental as physical health related problems among the human beings. To combat against this disease, vaccination is essential as it will boost the immune system of human beings while being in the contact with the infected people. The vaccination process is thus necessary to confront the outbreak of COVID-19. This deadly disease has put social, economic condition of the entire world into an enormous challenge. The worldwide vaccination progress should be tracked to identify how fast the entire economic as well as social life will be stabilized. The monitor ofthe vaccination progress, a machine learning based Regressor model is approached in this study. This tracking process has been applied on the data starting from 14^th December, 2020 to 24^th April, 2021. A couple of ensemble based machine learning Regressor models such as Random Forest, Extra Trees, Gradient Boosting, AdaBoost and Extreme Gradient Boosting are implemented and their predictive performance are compared. The comparative study reveals that the AdaBoostRegressor outperforms with minimized mean absolute error (MAE) of 9.968 and root mean squared error (RMSE) of 11.133.

In this modern era, continuous change is the first step in forming a new structure between theory and practice. The idea of ​​a juggernaut is very relevant to the theory of structuration with current conditions in the 21st century, where technology becomes a reference that can crush anyone who is not responsive to its power. This technology takes one path and takes many roles from various fields: economic, social, political, legal, and educational. This 21st century is marked by great momentum for changes in human behavior and civilization, namely the industrial revolution 4.0 and the arrival of Covid-19, which have changed many social structures and human activities. This makes history a means of connecting the problems in the 21st century with past events. By using a descriptive qualitative method, this paper will reveal how technological developments are very influential on educational and political developments and what are the challenges faced based on historical perspective?. In this case, the study aims to discuss the history and challenges of Indonesia's education system and government system in the 21st century and give a solution. The data used are from 2 books, 14 journal articles, and 4 websites with a span of 2019-2021. The research results are expected to be used as a further study in the face of the development of the modern era in the fields of education and government. This study also has limitations, namely only on the face of the development of the modern era in the fields of education and government.

Plant species with anti-inflammatory properties might play an essential role in combatting COVID-19 via reducing cytokine storms. We aimed to review the extant evidence of the potential therapeutic efficacy of natural products against cytokine storms by inhibiting interleukin-6 (IL-6) as a major pathological mediator. Data were collected following an electronic search in major databases (Pubmed, Scopus, Web of Science, Google Scholar) and also preprint articles on preprint and medRxiv servers by using a combination of relevant keywords. Seventeen active compounds and medicinal plants were found and reviewed in the present review. Results of both in-vivo and in-vitro experiments conducted on these compounds showed that Phillyrin, SMFM, Qiangzhi decoction, curcumin, Shen-Fu, Forsythia, and Alpha-Mangostin inhibit the production of IL-6. Andrographolide and Liu Shen Wan have an inhibitory effect on releasing this agent, while Ilex Asprella and Deoxy-11,12-didehydroandrographolide and naringin reduce the expression of IL-6. Theaflavin and Cholorogenic acid inhibit the secretion of IL-6, Xuebijing, and Chai-Hu-Gui-Zi-Gan-Jiang-Tang and Lipanpaidu prescription can reduce the serum level of IL-6. These agents also effectively improve infected lungs, increase survival rates, and minimize tissue damage. Medicinal plants and their phytochemical ingredients with down-regulatory effects on the expression of IL-6 have a potential influence on the inhibition of cytokine storms during viral infection caused by COVID-19. Therefore, phytochemicals could be regarded as promising candidates for managing cytokine storm inflammatory responses due to COVID-19 infection.

Clubhouse is an auditory app that allows users to host various rooms surrounding a diverse range of topics from Artificial Intelligence to Philosophy. Along with its educational and serene approach, it is known for its popularity amongst celebrities, including Elon Musk, Mark Zuckerburg, CEO of Shopify, and its elusive invite and ios-only pass into gaining access into Clubhouse. Waiting lists are available in the case of not achieving an invite, but to further speed the process, various sellers on eBay, Reddit, Twitter, etc., charging invites from $10-$200. This research paper covers the phenomenon of Clubhouse and the emergence of audio-only rooms, along with a hypothesis of why Clubhouse and other apps of a similar kind are experiencing a harsh downfall despite its seemingly successful business model.

Abstract: COVID-19 in 2020 brought challenges to the Brazilian public health system with an emerging virus with respiratory contagion called SARS-CoV-2. There are few studies in Brazil and in some countries, on the increased incidence of certain viral respiratory infections, includ-ing H1N1 and coronavirus and their association with low levels of vitamin D, zinc and iron. The aim of this study was to demonstrate that the deficit of vitamin D, zinc and iron has an impact on the infectious process of patients with COVID-19 and to establish new forms of prevention for the worsening of COVID-19 in the human body. Data were collected from medical records and test results from patients being followed up during the treatment period for COVID-19. Patients with low blood levels of vitamin D, zinc and iron during the treatment period of COVID-19 had a higher percentage of worsening and complications requiring hospitalization in intensive care beds. The ingestion of vitamin D, zinc and iron in the treatment period of patients with COVID-19 in addition to being an immunological protector against SARS-CoV-2 and alleviating the process of worsening the disease can also act as a biomarker in cases of this disease.

Objective: To investigate social, economic, and environmental contributors to quit or continue smoking and vaping during the COVID-19 pandemic. Methods: A qualitative study design was adopted to identify smokers’ beliefs in a LMIC, using a small community sample. Results: 276 participants were primarily surveyed. Motivation to continue smoking included temporary pleasurable effects, working remotely, stress or anxiety, whereas a motivator to quit smoking was the overlap with COVID-19 symptomatology. There was a rise in social awareness regarding the potential harm of smoking and vaping during the pandemic yet those participants who were younger felt they were immune from its morbid complications. Conclusions: With paradoxical associations of COVID-19 with cigarette and vape usage, it is important to pay attention to biases in data in favor of educating its users of the increased risk of severe disease.

This paper aims to contribute to the advancement of scientific knowledge about the impact of the COVID-19 pandemic on social workers and the social work profession in Romania. Research has shown that social work is a profession at high risk for developing the burnout syndrome, which has many detrimental effects on both social workers and the clients that they serve. Two conceptual models are used to frame the discussion: the theoretical framework of VUCA (volatility, uncer-tainty, complexity, and ambiguity) to discuss the challenges of the unprecedented context the COVID-19 pandemic has created for social workers; stress and burnout to explain the negative impact of this period of time. Based on convergent mixt methods, the study sample consisted of 83 social workers employed in statutory and private social services in Romania, from different fields of intervention. Results show that 25,3% of respondents suffer from a high level of burnout and 44.6% scored in a range that indicate a medium level of burnout. A group of 31.1% have managed to handle stress factors in a healthy manner. Main stressors found are especially personal (fear of contamination, personal and family) and work-related factors (workload, new legislative rules and decisions, inconsistency, instability, ambiguity of managerial decisions, or even their absence or non-assumption, lack of clarity of working procedures, limited managerial and supervisory support, limited financial resources), less than client related factors (lack of direct contact, risk of contami-nation in two ways, managing beneficiaries fears, difficulties related to technology and digital skills). Study results point to the importance of organizational support and developing a self-care plan that help protect against occupational stress and burnout. Recommendations are made putting forward the voice of fieldworkers and managers fostering initiatives and applications of sustainability-based measures and activities designed to deal with the challenges of the VUCA environment.

Bangladesh has achieved tremendous progress in the fisheries sector that is making evidential contribution to food security, nutrition and livelihoods. Based on secondary data collected from the Department of Fisheries, Bangladesh and related un-published grey literature, this paper highlights the performance and challenges of the fisheries with emphasis on COVID-19 impact as well as the significance of this sector for achieving the Sustainable Development Goals (SDGs). The total fish production is increased more than six times over the last three decades (7.54 to 43.84 lakh MT) due to the dissemination of improved culture techniques and extension services. Inland closed water contributions have been increasing to 16.24%, while inland open water have declined 10.23% and marine fisheries have dropped 6.27% over the past 18 financial years (2000-2001 to 2018-2019). COVID-19, a major health crisis has also affects various issues associated with aquatic resources and communities. Transportation obstacles and complexity in the food supply, abstraction to start production, labour crisis, sudden illness, poor consumer demand, commodity price hike, creditor's pressure and reduced income were identified as affecting COVID-19 drivers. The combined effect of these drivers poses a significant threat to people’s income (SDG1- eliminate poverty), nutrition (SDG2- erase hunger), food security (SDG3- good health and wellbeing, and SDG12- responsible consumption and production) that demands comprehensive actions. Several recommendations have been elicited, which are important to implement for the achievement of SDGs as well management and imprvement of the aquatic sector (SDG14- life below and SDG16- life above water) .

Background: A comprehensive response to the unprecedented SARS-CoV-2 (COVID-19) chal-lenges for public health and its impact on radiation oncology patients and personnel for resilience and adaptability is presented. Methods: The general recommendations included working remote-ly when feasible, implementation of screening/safety and personal protective equipment (PPE) guidelines, social distancing, regular cleaning of treatment environment, and testing for high-risk patients/procedures. All teaching conferences, tumor boards, and weekly chart rounds were con-ducted using a virtual platform. Additionally, specific recommendations were given to each sec-tion to ensure proper patient treatments. The impact of these measures, especially adaptability and resilience, were evaluated through specific questionnaire surveys. Results: These comprehen-sive COVID-19 related measures resulted in most staff expressing a consistent level of satisfaction in regards to personal safety, maintaining a safe work environment, continuing quality patient care and continuing educational activities during the pandemic. There was a significant reduction in patient treatments and on-site patient visits with an appeciable increase in the number of tele-medicine e-visits. Conclusions: Survey results demonstrated substantial adaptability and resili-ence, including in the rapid recovery of departmental activities during the reactivation phase. In the event of a future public health emergency, the measures implemented may be adopted with good outcomes by radiation oncology departments across the globe.

In Mexico, it is estimated that due to the economic system the overexploitation of natural resources, environmental impacts and health have been generated, with high rates of overweight and obesity. This review analyzes the impacts on food safety, environmental health, and the economy in Mexico before and during the COVID-19 contingency. Derived from the analysis, among the lessons learned we can include: the health contingency due to COVID-19 had negative repercussions on food security, environmental health and the economy, which require the promotion of public policies (health, environment and economy) and migrate to a health prevention system and an agroecological model, which includes multidisciplinary and intersectoral interventions (government, academia, researchers, civil society organizations, business groups and citizens themselves) to reform and enforce the right to enjoy adequate food and a healthy environment. The contingency due to COVID19 has shown us that this must go from an ideology to being a reality and the lessons learned will have to focus on promoting an innovative and ethical culture of generating an economy, with a gender balance, resilience to climate change, management transparent technology and a priority in health and this will lead to progress in the food security of the population.

The emergence of the COVID-19 outbreak has caused a pandemic situation in over 210 countries. Controlling the spread of this disease has proven difficult despite several resources employed. Millions of hospitalization and deaths have been observed, and thousands of cases daily with many measures in place. Due to the complex nature of COVID-19, we proposed a system of time-fractional equations to understand the transmission of the disease better. Nonlocality involved in the model has made fractional differential equations appropriate for modeling the behavior. However, solving these types of models is computationally demanding. Our proposed generalized compartmental COVID-19 model incorporates effective contact rate, transition rate (from exposed quarantine and recovered to susceptible and infected quarantined individuals), quarantine rate, disease-induced death rate, natural death rate, natural recovery rate, recovery rate of quarantine infected for a holistic study of the coronavirus disease. A detailed analysis of the proposed model is carried out, including the existence and uniqueness of solutions, local and global stability analysis of the disease-free equilibrium analysis, and sensitivity analysis. Furthermore, numerical solutions of the proposed model are obtained with the generalized Adam-Bashforth-Moulton method developed for the fractional order model. Our analysis and solutions profile show that each of these incorporated parameters is very important in controlling the spread of COVID-19, especially quarantining exposed and infected individuals and the effective contact rate. Based on the results with different fractional order, we observe that there seems to be a third or even fourth wave of the spike in cases of COVID-19, which is what is happening right now in many countries.

The Covid-19 pandemic caused very serious problems almost to the whole world, so every opportunity must be considered to improve the situation. Decontamination carried out from the air can also be considered for surface clearance of larger areas, so the possibility of this application should also be investigated regarding pandemic. There are many examples of the use of drones for disinfection to improve the epidemic situation, but good practices, as well as factors influencing the effectiveness, have not yet been identified. In the case of using drone for disinfections during a pandemic, based on the reports, we can clearly discover the adapted use of agricultural drones. In this paper, the authors perform calculations with different values of flight speed (10 to 50 km/h), flight altitude (1 to 5 m), and flow rate (1 to 5 l / min) to determine the possible amount of disinfectant fluid per unit area. The results show that by changing the parameters, the amount of disinfectant per unit area can be given within quite wide limits (30 - 0.24 g/m2). Although the results raise many new questions it can help to identify adequate flight parameters depending on different disinfectant liquids.

This study aimed to focus on how to design a low-cost greenhouse for the cultivation of crops, to propose the cost-effectiveness analysis of small agribusiness, and to promote sustainable agricultural production during and after the COVID-19 crisis for helping grassroots and anyone who lost their job. This article is qualitative engineering research, studying of literature reviews of greenhouse farming concept and Micro, Small and Medium Enterprises, then, designing low-cost greenhouse model which was preliminarily adapted for hot climate countries. Three plants that were selected as representative plants of this model include sunflower, water spinach, and wheat. The greenhouse model, measuring 5 x 7 x 4 m (W x L x H), was designed for this mission. The total cost of one building is approximately 97,994 THB. For the worthiness of the investment, farmers should build at least three greenhouse buildings, which will return total income to farmers approximately 34,666.09 THB per month. The suggestion includes further knowledge and financial supports from the government sectors among farmers, then, boost them up using high-level technology and also planting high-price agribusiness production to promote the local economy to be strong and sustainable.

Considering the challenges of sustainable education in emergency remote teaching (ERT) during the coronavirus (COVID-19) pandemic, this study provides basic principles for future ERT implementation based on the experience of higher education in Indonesia. Seven local expert distance educators reviewed the ERT principles, participating in the early stages to check the relevance, content validity, and readability of the five principles proposed in the context of Indonesian education. After an extensive expert review, the ERT principles were evaluated using quantitative data through an online survey (82 students and 45 faculty members). In addition, open-ended questionnaire responses, experiences, and challenges encountered by 21 respondents (College Dean, Associate Dean of Academics, and faculty quality assurance of seven universities/colleges in three provinces in Indonesia) in ERT were used and analyzed. This study suggests that ERT should be designed based on the principles of simplicity, accessibility, affordability, flexibility, and empathy in all learning activities in unfavorable situations. This study complements previous work and can thus be used for generalized principles for teaching activities in similar emergencies, especially in developing countries.

Alcoholism is a condition associated with psychiatric and psychiatric problems, where the respiratory system is damaged through the mucociliary ladder mechanism and alveolar macrophage dysfunction. In the time COVID-19 has been observed a dramatic increase in alcohol consumption mediated by levels of anxiety and situations of confinement. In this work we analyze the relationship between alcoholism and SARS, especially with SARS-CoV-2, explained by a degradation of the host defenses of the respiratory epithelium by changing the barrier function, the discharge of cytokines and the functions of the cilia. All of them involved in the defense mechanism. of the lungs. This leads to a worse prognosis for patients precisely because of alcohol consumption. Based on this approach, alcoholism will exacerbate the consequences of COVID-19.

We report the first detection of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus from a dog in Connecticut during February 2021. Complete genome sequencing and phylo-genetic analysis of the hCoV-19/USA/CT-CVMDL-Dog-1/2021 (CT_Dog/2021) virus were con-ducted to identify the origin and lineage of the virus. The CT_Dog/2021 virus belonged to the GH/B1.2. genetic lineage and was genetically close to SARS-CoV-2 identified from humans in the U.S. during the winter of 2020-2021. However, it was not related to other SARS-CoV-2 identified from companion animals in the U.S. It contained both D614G in spike and P323L in nsp12 substitutions which have become the dominant mutations in the United States. The continued sporadic detections of SARS-CoV-2 in companion animals warrant public health concerns about their potential to become a new reservoir species of SARS-CoV-2.

Background: The COVID-19 pandemic has hit the Spanish economy hard. The result is an unprecedented economic and social crisis due to uncertainty about the remedy, and due to the socio-economic effects on people’s lives. Methods: We performed a retrospective analysis of the macro-economic impact of COVID-19 in 2020, using the principal indicators of the Spanish economic and productive model. National statistics were examined in the search for impacts or anomalies occurring since the beginning of the pandemic. To estimate the strength of the impact on each of the indicators analysed, we used Bayesian structural time series. Results: In 2020, the cumulative impact on the Gross Domestic Product was of -11.41% [95% credible interval: -13.46; -9.29]. The indicator for Business Turnover fell by -9.37% [-12.71; -6.07]. The reduction in business activity was related to the sharp fall in demand. The Spanish employment market was strongly affected; our estimates showed a cumulative increase of 11.9% [4.27; 19.45] in the rate of unemployment during 2020. The autonomous communities which are economically the most heavily dependent on the services sector were those which recorded the worst indicators. Conclusions: Our estimates portray a dramatic situation in our country, and show all too clearly the fragility of a productive system which has to make the behavioural changes that are necessary to confront the COVID-19 pandemic.

Since December 2019, the world is fighting against coronavirus disease (COVID-19). This disease is caused by a novel coronavirus termed as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This work focuses on the applications of machine learning algorithms in the context of COVID-19. Firstly, regression analysis is performed to model the number of confirmed cases and death cases. Our experiments show that autoregressive integrated moving average (ARIMA) can reliably model the increase in the number of confirmed cases and can predict future cases. Secondly, a number of classifiers are used to predict whether a COVID-19 patient needs to be admitted to an intensive care unit (ICU) or semi-ICU. For this, classification algorithms are applied to a dataset having 5644 samples. Using this dataset, the most significant attributes are selected using features selection by ExtraTrees classifier, and Proteina C reativa (mg/dL) is found to be the highest-ranked feature. In our experiments, random forest, logistic regression, support vector machine, XGBoost, stacking and voting classifiers are applied to the top 10 selected attributes of the dataset. Results show that random forest and hard voting classifiers achieve the highest classification accuracy values near 98%, and the highest recall value of 98% in predicting the need for admission into ICU/semi ICU units.

As the world is striving to recover from the shockwaves triggered by the Covid-19 crisis, all hands are needed on deck to transition towards a green recovery and make peace with nature as prerequisites of a global sustainable development pathway. In this paper, we examine the blockchain hype and the gaps in data and tools to build promising use cases for blockchain technology to accelerate global efforts in the decade of action towards achieving the SDGs. We attempted to break the hype-cycle portraying blockchain’s superiority by navigating a rational blockchain use case development approach. By prototyping an SDG Acceleration Scorecard to use blockchain-enabled solutions as SDG accelerators, we aim to provide useful insights towards developing an integrated approach that is fit-for-purpose to guide organizations and practitioners in their quest to make informed decisions to design and implement blockchain-backed solutions as SDG accelerators. Acknowledging the limitations in prototyping such tools, we believe these are minimally viable products and should be considered as living tools that can further evolve as the blockchain technology is getting mature, its pace of adoption increasing, and its lessons learned, good practices and standards widely shared and internalized by teams and organizations working on innovation for development.

Social isolation magnified by the restriction of movement order during the COVID-19 pandemic may lead to negative psychosocial health impact among community-dwelling older adults. We evaluated the feasibility of virtual research methods and virtual group exercises among individuals aged 60 years and over in Malaysia. Participants were recruited from the Promoting Independence in Seniors with Arthritis (PISA) pilot cohort through social media messages. A four-week course of virtual group exercise was offered. Anxiety and depression were assessed with the Hospital Anxiety and Depression Scale (HADS) during the last attended follow-up of the cohort study (pre-pandemic), pre-intervention, and post-intervention. Exercise adherence was recorded using diary with daily entries and attendance to the virtual group exercise sessions were captured daily. The outcomes of interest were changes of anxiety and depression scores from baseline to pre-intervention (pandemic-related) and post-intervention (virtual exercise related). Forty-three individuals were recruited. A significant increase in anxiety scores from baseline to pre-intervention was observed. Comparisons using repeated-measures analysis of variance between those who attendance ≥14 and <14 group exercise sessions revealed no between-within subjects differences in depression scores. There was a 23% dropout rate in the post intervention survey and 60.5% of diaries were returned. This study demonstrated the feasibility of conducting research entirely virtually among older persons during the peak of global first wave of a pandemic. The pandemic has led to increased anxiety among community-dwelling older adults.

— Big Data analytics has come a long way since its inception. This field is growing day by day. With the advent of large handling capacity of computational analysis of modern computing systems as well as Internet of Things (IoT), this field has revolutionized the way we think about data. It has influenced the major domains such as healthcare, automobile, computing, climatology, and space communications. Of late, the health care sector has been largely influenced by this. This communication deals with the areas of healthcare where big data analytics has been largely influential. Encompassing the basics of Big Data Analytics (BDA) driven by IoT, the applications of it in healthcare sector are outlined, accompanied by future expectations. Additionally, it also presents a comprehensive analysis of recent application with special reference to Covid-19 in this sector.

Sound signals from the respiratory system are largely the harbingers of human health. Early diagnosis of respiratory tract diseases is of great importance as it creates irreversible effects on human health when delayed. This diagnostic in the medical world has been made possible thanks to machine learning and signal processing analysis. The coronavirus epidemic, which is in question today and deeply shakes the whole world, has been revealed the importance of this issue even more. In terms of the coronavirus pandemic, it has become the focus of researchers to differentiate symptoms from similar diseases such as normal flu or influenza. Among these symptoms, the difference in cough sound has played a distinctive role in the proposed study. Several pioneering studies have proven that almost two-thirds of people who get corona have a dry cough. At this stage, the information of studies based on cough constitutes the main framework of our study. On the other hand, the basis of this study is based on machine learning algorithms. Clinical data collected under the supervision of doctors in a reliable environment was used as dataset. This dataset consists of 16 subjects suspected of the coronavirus with a specific patient demographic. In this study, using the polymerase chain reaction (PCR) test, suspected subjects were divided into two groups as negative and positive. The negative and positive labels represent the patient with non-COVID and with a COVID-19 cough respectively. Using the 3D plot or waterfall representation of the signal frequency spectrum, the salient features of the cough data are revealed. In this way, COVID-19 can be differentiated from other coughs by applying effective feature extraction and classification techniques. Power Spectral Density (PSD) based on Short Time Fourier Transform (STFT) and Mel Frequency Cepstral Coefficients (MFCC) were chosen as the efficient feature extraction method. Finally, among the classification techniques the Support Vector Machine (SVM) algorithm, was applied to the processed signals in order to identify and classify COVID-19 cough. In terms of results evaluation, the cough of subjects with COVID-19 has obtained with 95.86% classification accuracy thanks to the RBF kernel function of SVM and the MFCC method. In other words, the diagnosis of COVID-19 coughs was obtained with 98.6% and 91.7% sensitivity and specificity measures respectively.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system. The interferons (IFNs) were discovered in 1957, and recombinant IFN-β-1b was approved by the US Food and Drug Administration as the first disease-modifying therapy (DMT) for MS in 1993. Since that time, clinical trials and real-world observational studies have demonstrated the effectiveness of IFN therapies. The pivotal intramuscular IFN-β-1a phase 3 trial was the first to demonstrate that a DMT could reduce accumulation of sustained disability in MS. Patient adherence to treatment is higher with intramuscular IFN-β-1a, given once weekly, than with subcutaneous formulations requiring multiple injections per week. Moreover, subcutaneous IFN-β-1a is associated with an increased incidence of injection site reactions and neutralizing antibodies compared with intramuscular administration. In recent years, revisions to MS diagnostic criteria have improved clinicians’ ability to identify patients with MS and have promoted the use of magnetic resonance imaging (MRI) for diagnosis and monitoring. MRI studies show that treatment with IFN-β-1a, relative to placebo, reduces T2 and gadolinium-enhancing lesions and gray matter atrophy. Since the approval of intramuscular IFN-β-1a, several high-efficacy therapies have been approved for MS, though the benefit of these high-efficacy therapies should be balanced against the increased risk of serious adverse events. For some subpopulations of patients, including pregnant women, the safety profile of IFN-β formulations may provide a particular benefit. In addition, the antiviral properties of IFNs may indicate therapeutic opportunities for IFN-β in the treatment of viral infections such as COVID-19.

All RNA viruses deliver their genomes into target host cells through processes distinct from normal trafficking of cellular RNA transcripts. The delivery of viral RNA into most cells hence triggers innate antiviral defenses that recognize viral RNA as foreign. In turn, viruses have evolved mechanisms to subvert these defenses, allowing them to thrive in target cells. Therefore, drugs activating defense to exogenous RNA could serve as broad-spectrum antiviral drugs. Here we show that transcriptional signatures associated with cellular responses to the delivery of a non-viral exogenous RNA sequence into human cells predict small molecules with broad-spectrum antiviral activity. In particular, transcriptional responses to the delivery of Cas9 mRNA into human hematopoietic stem and progenitor cells (HSPCs) highly matches those triggered by small molecules with broad-spectrum antiviral activity such as emetine, homoharringtonine, pyrvinium pamoate and anisomycin, indicating that these drugs are potentially active against other RNA viruses. Furthermore, these drugs have been approved for other indications and could thereby be repurposed to novel viruses. We propose that the antiviral activity of these drugs to SARS-CoV-2 should therefore be determined as they have been shown as active against other coronaviruses including SARS-CoV-1 and MERS-CoV. Indeed, two of these drugs- emetine and homoharringtonine- were independently shown to inhibit SARS-CoV-2 as this article was in preparation. These drugs could also be explored as potential adjuvants to COVID-19 vaccines in development due to their potential effect on the innate antiviral defenses that could bolster adaptive immunity when delivered alongside vaccine antigens.

Introduction: We describe the clinical features and inpatient trajectories of older adults hospitalized with COVID-19, and explore relationships with frailty. Methods: This retrospective observational study included older adults admitted as an emergency to a University Hospital who were diagnosed with COVID-19. Patient characteristics and hospital outcomes, primarily inpatient death or death within 14 days of discharge, were described for the whole cohort and by frailty status. Associations with mortality were further evaluated using Cox Proportional Hazards Regression (Hazard Ratio [HR], 95% Confidence Interval). Results: 214 patients (94 women) were included of whom 142 (66.4%) were frail with a median Clinical Frailty Scale (CFS) score of 6. Frail compared to non-frail patients were more likely to present with atypical symptoms including new or worsening confusion (45.1% vs 20.8%, p<0.001) and were more likely to die (66% vs 16%, p=0.001). Older age, being male, presenting with high illness acuity and high frailty were independent predictors of death and a dose-response association between frailty and mortality was observed (CFS 1-4: reference; CFS 5-6: HR 1.78, 95% CI 0.90, 3.53; CFS 7-8: HR 2.57, 95% CI 1.26, 5.24). Conclusions: Clinicians should have a low threshold for testing for COVID-19 in older and frail patients during periods of community viral transmission and diagnosis should prompt early advanced care planning.

Opsoclonus-myoclonus-ataxia syndrome is a heterogeneous constellation of symptoms ranging from full combination of these three neurological findings to varying degree of isolated individual sign. Since the emergence of coronavirus disease 2019 (COVID-19), neurological symptoms, syndromes and complications associated with this multi-organ viral infection have been reported and the various aspects of neurological involvement are increasingly uncovered. As a neuro-inflammatory disorder in nature, one would expect to observe opsoclonus-myoclonus syndrome after a prevalent viral infection in a pandemic scale, as it has been the case for many other neuro-inflammatory syndromes. We report seven cases of opsoclonus-myoclonus syndrome presumably para-infectious in nature and discuss their phenomenology, their possible pathophysiological relationship to COVID-19 and diagnostic and treatment strategy in each case. Finally we review the relevant data in the literature regarding the opsoclonus-myoclonus syndrome and possible similar cases associated with COVID-19 and its diagnostic importance for clinicians in various fields of medicine encountering COVID-19 patients and its complications.

The Coronavirus pandemic is a major challenge to human wellbeing; it directly affects health, and indirectly involves the economic, politic and social spheres. This, in turn, is going to have major systemic, worldwide health, social and environmental consequences. In this paper, I will briefly sum up the history of the pandemic, the worldwide diffusion, the major different political reactions, as well as health and political countermeasures, and the economic consequences / evaluations for the future. The aim of this paper is to show and address all the different spheres involved and their relationships. Emphasis will be placed on the paradoxical presence of a large amount of data and the big uncertainty for the future. The outcomes will be briefly analyzed on a healthcare, political and socio-economical level. The point of view is systemic with human beings, institutions and the environment seen as a whole. Systemic thinking allows interdisciplinary research to be decisive in understanding the worldwide reaction to the pandemic. The global response to this crisis is of historical significance, and therefore potentially decisive for the multi-layered future of the world.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused the Coronavirus Disease 2019 (COVID-19) worldwide pandemic in 2020. In response, most countries in the world implemented lockdowns, restricting their population’s movements, work, education, gatherings, and general activities in attempt to ‘flatten the curve’ of COVID-19 cases. The public health goal of lockdowns was to save the population from COVID-19 cases and deaths, and to prevent overwhelming health care systems with COVID-19 patients. In this narrative review I explain why I changed my mind about supporting lockdowns. First, I explain how the initial modeling predictions induced fear and crowd-effects [i.e., groupthink]. Second, I summarize important information that has emerged relevant to the modeling, including about infection fatality rate, high-risk groups, herd immunity thresholds, and exit strategies. Third, I describe how reality started sinking in, with information on significant collateral damage due to the response to the pandemic, and information placing the number of deaths in context and perspective. Fourth, I present a cost-benefit analysis of the response to COVID-19 that finds lockdowns are far more harmful to public health than COVID-19 can be. Controversies and objections about the main points made are considered and addressed. I close with some suggestions for moving forward.

This research aims to understand the vision and the reaction of the population towards tourism and holidays during this period of the COVID-19 pandemic. It investigates also the tourist needs of the Algerian population after the closure of international borders. Methods: The data were collected using mixed quantitative and qualitative methods through a questionnaire applied to 203 people in different regions of Algeria (a North African country) from 1st June to 13 July 2020. Results: The needs of Algerian tourists are characterized by a great need for leisure to relieve psychological stress caused by COVID-19 (M = 25.33) among the study sample (p <0.05). The results also show an average need to rationalize the costs of tourist services (M = 5.26) according to the respondents (p <0.01). This is in addition to the great need (M = 7.75) among respondents (p <0.05) of the awareness that the tourism sector can contribute to the economic recovery in Algeria after the confinement period. About 75.86% of respondents demand the cleanliness of tourist sites, while 69.95% recommend improving safety because of the size of tourist sites in the Algerian territory and also measures related to social distancing. The results show that 53.69% of respondents preferred the month of August to go on vacation, 29.06% chose the month of September, and 17.25% would prefer the months of October, November and December since they expect a reduction in the risks of the COVID-19 pandemic. Conclusions: The COVID-19 pandemic has affected the tourism needs of the Algerian population, which has become increasingly aware of the consequences of the pandemic in relation to their health and on the country's economy. These results can help the authorities of the tourism sector to better understand and identify the tourism needs of this population in the current period and after the COVID-19 pandemic.

In this COVID-19 pandemic, the use and dependency on Internet has grown exponentially. The number of people doing online activities such as e-learning, remote working, online shopping and others have increased. This has also led to increased vulnerability to cyber crimes. Cyber security attacks have become a serious problem. The common types of cyber security attacks are phishing, malware, ransomware, social engineering, identity theft and denial-of-service. The attackers target the victims in order to get their credential information or financial benefits. Those people who are doing online activities are vulnerable to cyber threats. This is because the network is not safe. The attackers are able to code according to the weaknesses of the Internet. Once the attackers hack into the devices, they have the root access and can do whatever they want to do with the device. In this research paper, the concept of cyber security attack and detailed research about real attacks are discussed. This is followed by detailed review about the recent cyber security attacks with a critical analysis. Moreover, the research paper will be proposing the latest research contribution of cyber security during COVID-19 and the implementation scenario which will give the examples about how the companies maintain privacy as well as the limitations. Then, the paper will be discussing the reasons that people are vulnerable to cyber security and the unique solution to the problems stated. Finally, this paper will conclude with an in-depth analysis and future direction for cyber security research.

Course-based Undergraduate Research Experiences (CUREs) provide active and authentic scientific involvement to tens of thousands of students each year. Through this process, CUREs offer the benefits of increased learning outcomes, improved equity, and increased retention in STEM. During the COVID-19 pandemic, however, research and teaching labs have limited capacity. Some universities are closed for in-person learning altogether, and others are likely to face emergency shut-downs throughout the year. In this setting, the inability to conduct experiments limits a core aspect of CUREs. Without experimentation as a basis for student engagement, interest, and broader relevance, true course-based research this year becomes a major challenge. We suggest that this limitation provides a moment to enhance CUREs with research-enriching learning activities that are obtainable while away from the bench. In this essay we outline a variety of these student-centered activities and review their benefits in terms of student interest, learning, and equity. While useful during emergency teaching transitions during COVID-19, we make the case that these new evidence-based practices for CUREs will also be helpful for the enrichment of research-based learning beyond the current crisis.

This study has been taken during COVID-19. It describes the working scenario of all class of peoples and their mental anxieties are analysed based on their psychological behaviour patterns.

COVID-19 is a potentially fatal viral infection. This study investigates geography, demography, socioeconomics, health conditions, hospital characteristics, and politics as potential explanatory variables for death rates at the state and county levels. Data from the Centers for Disease Control and Prevention, the Census Bureau, Centers for Medicare and Medicaid, Definitive Healthcare, and USAfacts.org were used to evaluate regression models. Yearly pneumonia and flu death rates (state level, 2014-2018) were evaluated as a function of the governors’ political party using repeated measures analysis. At the state and county level, spatial regression models were evaluated. At the county level, we discovered a statistically significant model that included geography, population density, racial and ethnic status, three health status variables along with a political factor. State level analysis identified health status, minority status, and the interaction between governors’ parties and health status as important variables. The political factor, however, did not appear in a subsequent analysis of 2014-2018 pneumonia and flu death rates. The pathogenesis of COVID-19 has greater and disproportionate effect within racial and ethnic minority groups, and the political influence on the reporting of COVID-19 mortality was statistically relevant at the county level and as an interaction term only at the state level.

The world is currently experiencing COVID-19, one of the worst pandemics that have happened in this century, affecting 10.7 million people worldwide. It has caused massive growth in the number of employees working from home. However, employees have minimal cybersecurity resources unlike organizations with security teams protecting them against attacks. Hence, cybersecurity plays an important role as users can be easily targeted by cybercriminals. This paper examines how cyberattacks have increased during this pandemic and shows how greatly they have affected health organizations, individuals and social networking applications. Results of the attacks include data breaches, false announcements and operations being disrupted. Attacks occurring during this pandemic and how they were handled are also critically discussed. The existing contributions do touch on related attacks but do not provide in-depth solutions regarding the issues. Even though there are many works and findings that were done previously, technology is ever evolving. Therefore, we need to be well versed with current and future issues and provide the latest mechanisms to prevent cybersecurity threats from occurring. On our share, we intend to present our findings on the challenges being faced by the population and its increasing threats as well as presenting unique solutions that can help organizations or related persons understand or spread awareness on the importance of cybersecurity. Through the research performed in this paper, it is found that there are many ways these issues can be alleviated. However, the issue is that there is significant lack of action and investment in terms of actual implementation and application of the available solutions.

Background: The novel Coronavirus SARS-CoV-2 (COVID-19) is a global pandemic with an increasing public health concern. Due to the non-availability of a vaccine against the disease, non-pharmaceutical interventions constitute major preventive and control measures. However, inadequate knowledge about the disease and poor perception might limit compliance. Aim: This study examined COVID-19-related knowledge, practices, perceptions and associated factors amongst undergraduate veterinary medical students in Nigeria. Methods: A cross-sectional web survey was employed to collect data from 437 consenting respondents using pre-tested self-administered questionnaire (August 2020). Demographic factors associated with the knowledge and adoption of recommended preventive practices towards COVID-19 were explored using multivariate logistic regression at P ≤ 0.05.Results: The respondents’ mean knowledge and practice scores were 22.7 (SD ± 3.0) and 24.1 (SD ± 2.9), respectively with overall 63.4% and 88.8% displaying good knowledge and satisfactory practice levels. However, relatively lower proportions showed adherence to avoid touching face or nose (19.5%), face mask-wearing (58.1%), and social distancing (57.4%). Being in the 6^th year of study (OR = 3.18, 95%CI: 1.62-6.26, P = 0.001) and female (OR = 2.22, 95% CI = 1.11-4.41, P = 0.024) were significant positive predictors of good knowledge and satisfactory practices, respectively. While only 30% of the respondents perceived the pandemic as a scam or a disease of the elites (24.0%), the respondents were worried about their academics being affected negatively (55.6%). Conclusion: The study revealed good knowledge and satisfactory preventive practices towards COVID-19 among Nigerian Veterinary students; albeit with essential gaps in the key non-pharmaceutical preventive measures recommended by the WHO. Therefore, there is a need to step up enlightenment and targeted campaigns about COVID-19 pandemic.

Seroprevalence studies suggest that the number of PCR-confirmed COVID-19 cases is significantly smaller than the true number of infections. I study logintidual seroprevalence data from 7 sites across the US, from early April 2020 to June 27. I show that not only COVID-19 seroprevalence does not seem to increase over time, there is no clear association between the number of cases reported during a period and the change in seroprevalence during the same time. I conclude that as they are, seroprevalence studies can only be used in the qualitative sense and distinguish between populations with no COVID-19 exposure, to those populations where the virus had already started spreading.

The impact of nutrition on immunity is an intense area of research. Malnutrition is linked to a higher risk of microbial infections, while severe infections usually lead to a nutritional imbalance in affected patients. The nutritional status has an impact on the severity of the ongoing SARS-CoV-2 infection. Studies conducted on small numbers of patients have shown the benefits of maintaining optimal vitamin (B12 and D) and mineral (zinc and magnesium) balance in reducing the intensity of COVID-19. Although consuming a balanced diet with a healthy lifestyle is always desirable, the importance of such practice is even more meaningful during the COVID-19 pandemic. Keeping an optimal balance of vitamins and minerals through healthy dietary habits helps to maintain a robust immune system that is essential to combat invading microbial pathogens, including SARS-CoV-2.

An intense scientific debate is ongoing as to the origin of SARS-CoV-2. An oft-cited piece of information in this debate is the genome sequence of a bat coronavirus strain referred to as RaTG13 1 mentioned in a recent Nature paper 2 showing 96.2% genome homology with SARS-CoV-2. This is discussed as a fossil record of a strain whose current existence is unknown. The said strain is conjectured by many to have been part of the ancestral pool from which SARS-CoV-2 may have evolved 7, 8, 9. Multiple groups have been discussing the features of the genome sequence of the said strain. In this paper, we report that the currently specified level of details are grossly insufficient to draw inferences about the origin of SARS-CoV-2. De-novo assembly, KRONA analysis for metagenomic and re-examining data quality highlights the key issues with the RaTG13 genome and the need for a dispassionate review of this data. This work is a call to action for the scientific community to better collate scientific evidence about the origins of SARS-CoV-2 so that future incidence of such pandemics may be effectively mitigated.

Background – The profound impact of COVID-19 on the U.S. healthcare industry cannot be overstated. Telemedicine utilization exploded virtually overnight as healthcare systems, hospitals, and clinical practices rushed to implement this delivery model to ensure accessibility and continuity of patient care access across myriad service lines and dimensions. Objective – The purpose of this systematic literature review is to examine the measures that were implemented to accommodate community and individual patient needs not only to afford access to critical services, but to also maintain safety standards for affected parties. Methods – Boolean operators were crafted with the expressed intent of identifying articles within multiple database domains germane to our chosen topic. Results – 52,206 articles were captured from a general search query and subsequently distilled to 44 through group consensus based on pertinence to our basic research question. The four health service lines identified encountered similar, surmountable obstacles in their care delivery models, but adapted accordingly to the respective needs of their patient populations. Conclusion – This review showcased the healthcare industry’s ability to rapidly acclimate and change due to the pervasive spread of COVID-19 throughout the U.S. Although imperfect, unique responses were developed within telemedicine platforms to broadly and effectively mitigate disruptions in care and treatment modalities.

The novel coronavirus named by WHO and Coronavirus Study Group (CSG) as SARS-COV-2 is the etiological agent of the newly emerged Coronavirus disease (COVID-19). COVID-19 has become a pandemic threat as the WHO declared it a public health emergency of international concern. Early and precise detection of the virus is important for effective diagnosis and treatment. Various testing kits and assays, including real-time reverse Transcriptase PCR, thermal screening guns, ELISA-based immunoassays, and Point-of-Care (POC), have been implemented or are being explored to detect the virus and/or characterise cellular and antibody responses to the infection. However, these approaches have inherent limitations such as non-specificity, high cost, characterize by long turnaround times for test results, and can be labour intensive. Aptamers, which are single-stranded oligonucleotides, generated artificially by SELEX (Evolution of Ligands by Exponential Enrichment) may offer the capacity to generate high affinity bioprobes for monitoring relevant SARS-COV 2 and COVID-19 biomarkers. This article discusses the prospects of implementing aptasensing technologies for rapid point-of-care detection of SARS-COV-2.

The tourism sector in general and the hotelier in particular face the challenge of managing appropriate measures to deal with the covid-19 pandemic. In this sense it is useful to know what the measures are most demanded by the clientele. This research, by analyzing the variance (ANOVA) of a factor concluded that women are more demanding than men in terms of the level of demand in relation to the measures to be taken in hotels. This, as a practical application, allows to know more accurately the expectations, demands and demands of the client segmented by sex, in order to satisfy and improve the tourist experiences.

Africa is gradually becoming an epicentre for the COVID-19 pandemic. From the current trends of the disease, Africa might be the last hardest hit continent. While scientific investigations are ongoing to develop effective management through medications and vaccines, existing knowledge, perceptions and attitudes could be harnessed to develop an effective strategy to curb community transmission of the COVID-19. The present study assessed the awareness level, perceptions and attitudes of people living in rural, peri-urban and urban communities in Northern Ghana and their preparedness for the prevention and containment of COVID-19. We conducted a face-to-face interview and administered 553 semi-structured questionnaires in eighteen (18) rural and peri-urban/urban communities under Tolon District, Kumbungu Districts, Sagnarigu Municipality, Savelugu Municipality and Tamale Metropolis from 23^rd of April to 8^th of June 2020. The percentage of male to female among the respondents was 56.8% and 43.2%, respectively. Nearly half (41%) of the respondents had no formal education and 91.3% of them were Muslims. Most of the respondents (85%) held the view that COVID-19 is a punishment from God. There was a significant difference (P<0.05) between the time rural and peri-urban/urban communities first heard of COVID-19. Majority (63%) of the rural respondents depended on radio, while the peri-urban/urban respondents (51%) relied on television for information on COVID-19. All respondents were aware of COVID-19 and 91.7% could mention at least two symptoms of the disease but 18% believed there was no COVID-19 in Ghana. Most of the respondents (69.6%) believed they will not contract the virus. Our findings may provide useful data to government and other stakeholders in the COVID-19 fight.

Introduction: A large number of COVID-19 publications has created a need to collect all research-related material in practical and reliable centralized databases. The aim of this study was to evaluate the functionality and quality of the compiled World Health Organisation COVID-19 database and compare it to Pubmed and Scopus. Methods: Article metadata for COVID-19 articles and articles on 8 specific topics related to COVID-19 was exported from the WHO global research database, Scopus and Pubmed. The analysis was conducted in R to investigate the number and overlapping of the articles between the databases and the missingness of values in the metadata. Results: The WHO database contains the largest number of COVID-19 related articles overall but retrieved the same number of articles on 8 specific topics as Scopus and Pubmed. Despite having the smallest number of exclusive articles overall, the highest number of exclusive articles on specific COVID-19 related topics was retrieved from the Scopus database. Further investigation revealed that PubMed and Scopus have more comprehensive structure than the WHO database, and less missing values in the categories searched by the information retrieval systems. Discussion: This study suggests that the WHO COVID-19 database, even though it is compiled from multiple databases, has a very simple and limited structure, and significant problems with data quality. As a consequence, relying on this database as a source of articles for systematic reviews or bibliometric analyses is undesirable.

Currently, the COVID‐19 has directly affected the millions of humans lives. The symptoms of the disease involving fever, malaise, chest infection, and breathing difficulties, were identified, and its existence is continuously becoming restructured. The World Health Organization (WHO) had mentioned the wide diagnostics test besides COVID-19 that would also assist medical facilities to recognize infectious diseases as well as currently focusing efficiently on preventing and afterward defeating this viral disease. The infection is usually transmitted among human beings in direct contact, greatest through the liquid bubbles generated through cough, sneeze, or speaking. This paper reviews the COVID 19 pandemic, its history, current updates, contact tracing applications, and use of emerging technologies like the Internet of Things (IoT) and Blockchain for stopping the spreading and provide service online to the patient from a distance.

During this epidemic of COVID-19, children are in need of much concentration and profound love of the senior family members. Although the measures taken by the organizations are necessary to prevent the spread of the novel coronavirus, they may be causing widespread mental health issues, including depression and loneliness. Therefore, it is imperative that parents have to spend the lion-share of time with children while listening to them cordially. Parents can participate in sports with them to help them stay fit so that they can enjoy commemorating moments. However, in this additional time, the parents can also make them habituated to practice the rules of health, so does social distancing.

Some COVID-19 patients develop interstitial pneumonia that can evolve into Acute Respiratory Distress Syndrome (ARDS). This is accompanied by an inflammatory cytokine storm. SarS-CoV has proteins capable of promoting cytokine storm, especially in patients with comorbidities, including obesity. Since there is currently no resolutive therapy for ARDS and given the scientific literature regarding the use of adenosine, its application has been hypothesized. Adenosine through its receptors is able to inhibit the acute inflammatory process, increase the protection capacity of the epithelial barrier and reduce the damage due to an overactivation of the immune system, such as in cytokine storms. These features are known in ischemia / reperfusion models and could also be exploited in acute lung injury, with hypoxia. In light of these hypotheses, for compassionate use, a COVID-19 patient, with unresponsive respiratory failure, was treated with adenosine. The results showed a rapid and clear improvement in clinical conditions, with the negative effect of detection of SarS-CoV2.

Background: Coronavirus disease (COVID-19) related pneumonia is leaded by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which infects host cells through receptors named Angiotensin-converting enzyme 2 (ACE2). Smoking is thought to be related to poor disease prognosis, as a large amount of evidence highlights the negative effects of smoking on lung health and its causal relationship with various respiratory diseases. Methods: We first evaluated the role of ACE2 expression level with tobacco effect. And correlation analyses were used to identify the related genes of ACE2 both in smoker trait and human normal multi-tissues. After intersections, hub genes were later used to further GSEA and co-regulated mechanisms were explored by GeneMANIA. We used UALCAN to perform survival curves of pan-cancers included 33 types of cancers. New clinical model of top co-occurrence cancer type was constructed and validated. Results: Effected by cigarette smoking, the expression level of ACE2 expressed statistically upwards in current smokers compared with never smokers, upwards in groups after acute smoke exposed compared with normal control. But no strong evidence detected in third-hand smoke, as poor amounts of samples, only 4. A little trend of expressing upwards became in groups after third-hand smoke compared with groups after clean air exposing. 4 genes included PIR, ADH7, AKR1C2 and AKR1C3 were identified as ACE2 related genes in smoker trait and human normal multi-tissues. Then, we made the survival curves of pan-cancers in 4 genes. Brain lower grade glioma was the co-occurrence type as both ACE2, PIR and AKR1C3 had the significantly prognostic situation. Later, we made the new clinical prediction model as the C-index was 0.827 and the Area Under Curves (AUCs) of 1-year survival, 2-year survival and 3-year survival were 0.921(95%CI, 0.882-0.961), 0.911(95%CI, 0.860-0.962) and 0.878(95%CI, 0.818-0.939). In inner validation, the AUCs of 1-year survival, 2-year survival and 3-year survival were 0.777(95%CI, 0.640-0.914), 0.916(95%CI, 0.842-0.990) and 0.888(95%CI, 0.768-1.000). In outer validation one, the AUCs of 1-year survival, 2-year survival and 3-year survival were 0.764(95%CI, 0.672-0.856), 0.848(95%CI, 0.783-0.913) and 0.748(95%CI, 0.656-0.841). And in outer validation two the AUCs of 1-year survival, 2-year survival and 3-year survival were 0.740(95%CI, 0.654-0.826), 0.766(95%CI, 0.688-0.843) and 0.794(95%CI, 0.721-0.866). Conclusions: In our study, we compared the ACE2 expression level between smokers and non-smokers crowds and identified associated hub genes. Then we explored the further role of hub genes in tumor fields to identify the correlation and influence between the avoidable host factors such as smoking on COVID-19 contamination and tumor. ACE2 and AKR1C3 are potential prognostic genes for brain lower grade glioma, and we created the web dynamic nomogram and encapsulation app through validations.

Coronavirus disease (COVID-19) has caused mankind serious confusion, economic havoc and psychological distress. This study evaluated the level of knowledge, attitude and perception about COVID-19 pandemic, infection control and impact among veterinarians in Nigeria. A cross-sectional online survey was used to collect data from consenting respondents during implementation of lockdown in the country (April 23 - May 31, 2020). Purposive and chain referral sampling techniques were used to recruit 368 respondents from various sectors of the profession. The proportion of respondents surveyed 197/368 (53.5 %) were from the public sector, 35.3 % from private sector, 1.1 % were unemployed and 0.8 % retired. Majority of the respondents were males (72.8 %), within 30 – 39 years (39.7 %) and had 1 – 10 years work experience. Respondents displayed good level of knowledge about COVID-19 (72.4 % ± 9.9 %, range 44.1-91.2 %), with information mostly derived from TV/Radio (81.5%) and social media (81.0 %). The overall attitude level was poor and various determinants for good attitude among respondents were if they were above 60 years (p = 0.013), possessed postgraduate qualification ( p = 0.031), worked over 30 years post DVM (p = 0.001), had household members between 5 and 10 (p = 0.012), and were resident in states on total lockdown (p = 0.024). There was no correlation between the knowledge level score and respondents’ attitude towards the pandemic (p = 0.12). With increasing rate of COVID-19 transmission, research data are needed to develop evidence-driven strategies, policies and effective risk mitigations to reduce the pandemic’s adverse impacts.

Coronavirus disease of 2019 (COVID-19) is the clinical manifestation of the respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While primarily recognized as a respiratory disease, it is clear that COVID-19 is systemic illness impacting multiple organ systems. One defining clinical feature of COVID-19 has been the high incidence of thrombotic events. The underlying processes and risk factors for the occurrence of thrombotic events in COVID-19 remain inadequately understood. While severe bacterial, viral or fungal infections are well recognized to activate the coagulation system, COVID-19 associated coagulopathy is likely to have unique mechanistic features. Inflammatory-driven processes are likely primary drivers of coagulopathy in COVID-19, but the exact mechanisms linking inflammation to dysregulated hemostasis and thrombosis are yet to be delineated. Cumulative findings of microvascular thrombosis has raised question if the endothelium and microvasculature should be a point of investigative focus. Von Willebrand Factor (VWF) and its protease, ADAMTS13 play important role in the maintenance of microvascular hemostasis. In inflammatory conditions, imbalanced VWF-ADAMTS13 characterized by elevated VWF levels and inhibited and/or reduced activity of ADAMTS13 has been reported. Also, an imbalance between ADAMTS13 activity and VWF antigen is associated with organ dysfunction and death in patients with systemic inflammation. A thorough understanding of VWF-ADAMTS13 interactions during early and advanced phases of COVID-19 could help better define the pathophysiology, guide thromboprophylaxis and treatment and improve clinical prognosis.

Background: The novel emerging virus SARS-CoV-2 has affected all human-kind during the first half of 2020. The aim of the study was to survey the actual circumstances from January until May. Methods: The data are collected and released systematically, by law, from the National Epidemiological Surveillance of Infectious Disease (NESID). Findings: Analysis of these data revealed that the infection spread in Japan from late March to early April 2020. The SARS-CoV-2 infection rate at its peak was estimated to be 10%. Thus, the size of the population who may have been exposed to the novel virus in Japan is estimated at 0.2 million, which is relatively small. The number of related deaths is likely to converge on 1,000 people. Interpretation: Applying the law of large numbers allows estimation of the infection rate as well as of the size of the affected population by statistical analysis. How to collect the data must be defined before the data analysis is suggested to be important to reflect the actual circumstances about COVID-19.

SARS-CoV-2 infections underlie the current Coronavirus disease (COVID-19) pandemic and are causative for a high death toll particularly among elderly subjects and those with comorbidities. Selenium (Se) is an essential trace element of high importance for human health and particularly for a well-balanced immune response. Mortality risk from severe disease like sepsis or polytrauma is inversely related to Se status. We hypothesized that this relation also applies to COVID-19. Serum samples (n=166) from COVID-19 patients (n=33) were collected consecutively and analysed for total Se by X-ray fluorescence and selenoprotein P (SELENOP) by a validated ELISA. Both biomarkers showed the expected strong correlation (r=0.7758, p<0.001), pointing to an insufficient Se status for optimal selenoprotein expression. In comparison to reference data from a European cross sectional analysis (EPIC, n=1915), the patients showed a pronounced deficit in total serum Se (mean±SD, 50.8±15.7 vs. 84.4±23.4 µg/L) and SELENOP (3.0±1.4 vs. 4.3±1.0 mg/L). A Se status below the 2.5th percentile of the reference population, i.e., [Se] < 45.7 µg/L and [SELENOP] < 2.56 mg/L was present in 43.4% and 39.2% of COVID samples, respectively. The Se status was significantly higher in samples from surviving COVID patients as compared to non-survivors (Se; 53.3±16.2 vs. 40.8±8.1 µg/L, SELENOP; 3.3±1.3 vs. 2.1±0.9 mg/L). We conclude that Se status analysis in COVID patients provides diagnostic information. However, causality remains unknown due to the observational nature of this study. Nevertheless, the findings strengthen the notion on a relevant role of Se for COVID convalescence, and support the discussion on adjuvant Se supplementation in severely diseased and Se-deficient patients.

The recent COVID-19 outbreak in China led to a worldwide pandemic associated with a severe acute respiratory illness. A higher incidence of COVID-19 infection was demonstrated in cancer patients, including patients with lung cancer. This study was conducted to get insights into the reasons for this enhanced frequency of COVID-19 infection. Methods: Using different bioinformatic tools, the expression and methylation pattern of ACE2 and TMPRSS2 gene were analyzed in healthy and malignant tissues with a focus on lung adenocarcinoma (LUAD) and correlated to clinical parameters and smoking history. Results: ACE2 and TMPRSS2 were heterogeneously expressed across 36 healthy tissues with the highest expression in digestive, urinary and reproductive organs, while their expression was significantly lower in 36 cancer tissues. In LUAD, ACE2, but not TMPRSS2 was overexpressed, which inversely correlated to the promoter methylation. An age-dependent upregulation of ACE2 expression was found in LUAD compared to normal lung tissues. In a healthy lung, TMPRSS2 expression was dependent on sex and smoking history and downregulated in LUAD of smokers. Cancer progression was associated with decreased TMPRSS2, but unaltered ACE2 expression, while ACE2 expression in lung metastases of different cancers was higher than in metastasis of other sites. TMPRSS2, but not ACE2 expression, was associated with LUAD patients’ survival. Conclusions: Comprehensive molecular analyses revealed a heterogeneous, distinct expression and methylation profile of ACE2 and TMPRSS2 in healthy lung vs LUAD tissues across sex, age and smoking history, which is associated with clinical parameters and might have implications for COVID-19 disease.

The coronavirus disease 2019 (COVID-19), the pandemic is an unprecedented health emergency never seen in the recorded history of humankind due to its sheer scale, rapid spread, and subsequent shock to the global economy. The past respiratory viral pandemics of the 21st century (SARS-CoV-2 in 2003, Influenza AH1N1 in 2009) have revealed seasonality in environmental factors to play a role in the dynamics of their spread. Here, we report the observed state-level relationship between environmental factors such as temperature (T), relative humidity (RH), specific humidity (SH), and solar radiation (SR) on the COVID-19 spread over the Indian region. The results show that T and RH have a significant impact on the disease growth rate and doubling time. Every degree rise in temperature corresponds to a 0.99 % decrease in the number of cases and an increase in doubling time by ~ 1.13 days implying a slowing down of spread. A similar analysis for RH reveals that more moisture leads to a higher growth rate and reduced doubling time. Lower SH and higher surface-reaching SR are found to reduce the spread and increase the doubling time similar to that of temperature. The range of average state-level T (RH) encountered during this period was between 24 and 35^oC (30 and 87%) which implies that environmental impact is still effective at all these T (RH) and is not limited to specific T (RH) ranges. The progression of the season towards monsoon, post-monsoon, and thereafter winter with a continuous reduction in temperature will prove a major challenge for health workers and policymakers attempting to enforce mitigation and control measures.

The novel respiratory disease COVID-19 has reached the status of worldwide pandemic and large efforts are currently being undertaken in molecularly characterizing the virus causing it, SARS-CoV-2. The genomic variability of SARS-CoV-2 specimens scattered across the globe can underly geographically specific etiological effects. In the present study, we gather the 48,635 SARS-CoV-2 complete genomes currently available thanks to the collection endeavor of the GISAID consortium and thousands of contributing laboratories. We analyze and annotate all SARS-CoV-2 mutations compared with the reference Wuhan genome NC_045512.2, observing an average of 7.23 mutations per sample. Our analysis shows the prevalence of single nucleotide transitions as the major mutational type across the world. There exist at least three clades characterized by geographic and genomic specificity. In particular, the clade G, prevalent in Europe, carries a D614G mutation in the Spike protein, which is responsible for the initial interaction of the virus with the host human cell. Our analysis may drive local modulation of antiviral strategies based on the molecular specificities of this novel virus.

Abstract Background: The highest incidence rate of covid-19 in Iran was reported from Shahroud County. This study was conducted by geographic information systems (GIS) to determine the geographical distribution of Covid-19 in 60 days. Study design: A cross-sectional study Methods: This study was conducted in counties covered by Shahroud University of Medical Sciences, namely Shahroud and Mayami, from February 20, 2020 to April 18, 2020. The GIS can better show the spread of epidemics. This software indicates geographical distribution of disease spread and is very helpful in controlling the epidemics. Therefore, maps of spatial distribution and risk of infection to COVID-19 were prepared in different regions of Shahroud county using Arc-GIS software to better implement health policies. Results: During this sixty-day period, 529 confirmed cases were detected, of which 51% were men and the average age was 55 years. The maps showed high-risk to risk-free regions. Shahroud and Bastam cities were known as the coronavirus hot spots. The eastern region of Shahroud has the highest number of cases but some high risk areas are spread throughout the Shahroud city due to high infectivity of virus. Risk-based time maps indicated a reduction in the risk of infection at the end of the research period due to some mitigation and suppression strategies. Conclusions: Shahroud and Bastam are the most dangerous cities that, the number of patients and dissemination has decreased over time because of tracking definite patients and people in contact with them and implementation of preventive care.

The crux of the paper is to present a detailed analysis of COVID-19 data which is available on global basis. This analysis is performed using some specific package of R software. It provides various insights from the data and help to understand the current status of this pandemic in India so that effective measures can be formulated by policymakers. These insights include global summary of this disease, growth rate of this pandemic and performance of SIR model for the given global data. The analysis has been presented in different tables and graphs to understand the outputs of the problem in a more detailed point of view.

The outbreak of Corona Virus effected negatively on the world’s economy which has already touched the maximum sectors. Readymade garments sector has the large contribution in Bangladesh’s economy. For increasing the locked down period, it is hitting badly by stopping production and cancellation of orders with some issues. This paper will represent the brief scenario and impacts of garments sector in recent days and the economy status of Bangladesh for the pandemic. The study is based on secondary data, collected from different authentic journals and web portals etc. Bangladesh’s garments earnings mostly depended on export but on these days, the buyers are cancelling their orders and the factories are being failed to give payments to the worker, some are being shut down also. As the duration of locked down is increasing, there is a huge chance to get unemployed and Bangladesh can be faced an undisciplined condition in near future. BGMEA and BKMEA are taking necessary steps to support the worker. Ensuring health security, the authorities are trying to reopen the factories limitedly to meet up the immediate needs. The government has taken the situation on most priority and introduce some improvement packages to run the economy smoothly and reduce the losses of the country for the pandemic.

All over the world, development of micro blog and other social platform indicate that Social Media is now the focus and trend of the Internet. Daily life, study and work are influenced by news in Social Medias . Micro blog is new emergent type of media and it spreads information rapidly in the crowd in recent years. Suppose an user searches for specific information about one topic on micro blog. He/she found easily plenty of information related to his/her search in social medias. The problem is to find out the correct information. Normally, multi-document summarization method deals with a collection of documents about one topic for extracting the valuable points and discards useless information. Actually, it needs to extract the topic content by adding topic factors and social patterns. Topic factor is the lexical information related to the topic. Social pattern relates to special interactive mode owned by online social network, such as comment and repost. People has been seen the fake news on mobile/internet during lockdown period. It is of no doubt that anyone with a social media account has seen at least one example of this.Humanity’s greatest challenges are to detect false information. Fake news are collected from 150 persons using social media The aim of the paper is to investigate the truthfulness of the news people share on social media using K-nearest Neighbour (KNN) based Classifier method.

In the present time, the biggest problem of the world is the outbreak of novel coronavirus. Novel coronavirus (COVID-19), this one name has become a part of our daily lives over the past few months. Beyond the boundaries of medical science, coronavirus is now the main subject of research in all fields like Applied Mathematics, Economy, Philosophy, Sociology, Politics upto living room. The epidemic has brought unimaginable changes in our traditional habits and daily routines. Thousands of people in our country are fighting with the rest of the world to survive in various new situations. There are different kinds of coronavirus appeared in different times. In this time, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is responsible for the coronavirus disease of 2019 (COVID-19). This virus was first identified towards the end of 2019 in the city of Wuhan in the province of Hubei in China. Within very short duration of time and very fast, it has spread throughout a large part of the world. In this study, the main aim is to investigate the spreading rate, death rate, recovery rate due to corona virus infection and to study the future of the coronavirus in India by using mathematical modeling based on the previous data. Mathematical models, in this situation, are the important tools in recruiting effective strategies to fight this epidemic. India is at high risk of spreading the disease and is facing many losses in socio-economic aspects. With current infection rates and existing levels of personal alertness, the number of infected people in India will increase at least in the next three months. Proper social awareness, maintain of social distance, large rate of testing and separation may break the chain of the Coronavirus-2.

The outburst of the CoVid-19 pandemic has raised several questions leading to a complex system in terms of modeling. Indeed, the modeling of the epidemic, at the level of a country, needs considering each of the different sources of contamination as well as the public health authorities' strategy, in a specific way. With this in mind, in the present paper, we develop a mathematical model of the CoVid-19 epidemic in Senegal. In the model, the population is subdivided into five compartments: susceptible, infected but asymptomatic, symptomatic, quarantined, and recovered immune people. In addition, due to its important impact on the propagation of the disease, we add one more variable: the number of infected objects. %\vspace{1mm} Therefore, the model corresponds to a system of six non-linear ordinary differential equations we submit to an analytical study to prove the relevancy of the model, simulate the evolution of the epidemic, and retrieve epidemiological parameters, namely the infection rate and the basic reproduction number, ${\cal R}_0$. Based on the senegalese territory CoVid-19 data, we simulate various scenarios as for the evolution of the epidemic in the country, in order to predict the peak and its magnitude with regard to the application of barrier measures. We also explore the option of collective immunity with special protection for vulnerable people. In doing so, non-available parameters are identified using some mathematical identification technics.

It is highly likely that the wearing of face masks reduces the rate of respiratory infections (e.g. SARS-CoV-2), to protect both the user and those around them. This paper sets out to review the areas that effect the efficacy of masks, the materials, design, hygiene and fit testing, in order to make recommendations as to how to make mask from resources found in most homes for when commercial models are unavailable. This paper finds that a mask constructed with a filter made from high thread count cotton is likely to provide a reasonable level of protection (~70% filtration) and that if a layers of other materials such as chiffon or silk is added the filtration may be much higher (~90%). There is also some promise in less available materials such as vacuum cleaner bags and air conditioner filters. Examples of fabric and rigid designs are reviewed but most are limited by the fit to the users which is hard to determine in a home setting. It would be extremely helpful if a method was devised for people to test or be tested for the fit of home made masks. In the mean time careful thought should be given to whether the user judges a good fit. Users should also be careful to practice other means of hygiene and distancing.

COVID-19 has been a major issue in most countries throughout the world with 213 countries being affected till date due to the disease. The pandemic has raised concerns over the healthcare facilities available in various countries and question the government decisions made during this period of outbreak. Despite having the best healthcare facilities several countries across Europe and America have found it difficult to contain the disease outbreak questioning the available solutions to contain an area. This paper focuses on presenting information on solutions available to control outbreaks in order to prevent another pandemic occurring in the future. The paper also highlights the strategies and plans implemented by various governments who have been successful in combatting the disease with minimum damage. By using available resources such as technology, scientific innovation and digitalized healthcare this paper focuses on providing solutions which are already available to be utilized in the right manner.

Watching the international COVID-19 epidemics unfold during February and early March 2020, we began to highlight how outbreaks in care homes were inevitable, given the vulnerable patients in close proximity, and pressures on social care to help relieve pressure on the NHS. We suggested public health measures would significantly impact on care homes. Specifically we felt all homes would have multiple individuals isolated within days of introduction of guidance requiring isolation of new cough (or fever), and that a clear definition of an outbreak would be needed that differentiated COVID19 from influenza. We share the experiences of a GP practice looking after 900 nursing or dual registration care homes in the London Borough of Ealing in the early stages of the COVID19 Pandemic 2020. We believe that the altered presentation of cases of COVID19 in care homes contributed to the size of outbreaks, and that keeping COVID19 out of homes is the only way to manage this disease, with early isolation and complete segregation of positive and negative cases. We have seen over 300 suspected cases resulting in four fold (n=175) average monthly death rates, three fold usual issue of anticipatory medications, and approximately 32% mortality rate (up to 43% in over 90’s). Discharge pathways from hospital and admissions to care homes must be clear and robust. COVID19 naïve patients should not be admitted to units with outbreaks and COVID19 positive patients should not be admitted to anything other than a designated “hot” home until risk of contagion is passed. Some patients are testing positive at over 30 days since initial mild symptoms.

The probability of zoonoses, such as the novel coronavirus (COVID-19), emerging is strongly related to remediable factors such as habitat encroachment and trade in wild animals. Tackling these underlying determinants is important to prevent future pandemics from the approximately 700,000 viruses with the potential to cause zoonoses. Reversing habitat destruction is also vital to halt the accelerating rate of extinction of a wide array of life forms - with all the adverse consequences these extinctions will have for human health. These insights depend on viewing health and disease from within an ecological theoretical framework. We therefore argue that preventing future zoonotic outbreaks as well as dealing with a range of contemporary health issues would be facilitated by grounding our health sciences in more a more explicitly ecological conceptual framework.

Globally, an approximate of 380,000 patients succumbed to death due to the pandemic COVID-19 which also infected more than six million people since December 2019. Not sparing anyone, COVID-19 infections are widely reported among healthcare professionals, sanitation workers and researchers too while global leaders and various governments are providing their best in defending their citizens against this airborne and contact spread virus. In order to contain the virus and protect millions of lives from this deadly coronavirus, there is a need to have a combination of advanced engineering technology and medical facilities. Application of applied science, engineering and technology diffuse almost every aspect of contemporary living. Grasping the fundamentals to determine humanity's most imperative and forthcoming challenges is essential. Artificial Intelligence, the technology that learns, adapts and reciprocates the actions according to the situations, finds optimum position in the fight against corona virus and acts as a powerful tool against this pandemic. In this research article, the authors discusses how Artificial Intelligence (AI) can be leveraged to fight the deadly virus. The research paper further discusses the efficient utilization of AI across the globe to help in testing, treating and serving the population in these hard times. This manuscript focuses on the potential impact of the process in which AI can be implemented to prevent, test and treat.

Whilst large-scale changes in population behaviour are required to reduce the transmission of the SARS-COV-2 virus, the emergency context is not conducive to the sort of careful communications planning that would normally be required to meet such a task. Rapid strategic communications planning in a pandemic by governments is, however, possible and necessary. Steps include setting up a dedicated communications task force, mobilising partners and resources, developing a creative brief and theory of change and overseeing the creation, testing, roll out and revision of content. In this short guide we argue that a minimum of strategic planning can be undertaken rapidly, and that good use can be made of simple principles of behaviour change, even during pandemics. Our aim here is to provide a blueprint that governments and their partners, especially in low-income settings, can follow to design, coordinate and resource national communications efforts to combat the COVID-19 pandemic immediately and for the longer term.

Background: Lung CT provides an effective modality to evaluate patients with suspected COVID-19. However, overlapping imaging findings with cardiogenic pulmonary oedema have been reported. Reports comparing lung CT features of these diseases have not been elaborated. Thus, we aimed to investigate these gaps in the knowledge regarding low-dose lung CT features of patients with COVID-19 pneumonia with those with acute heart failure (HF). Methods: This retrospective analysis enrolled hospitalized patients with COVID-19 (n=10) and acute heart failure (n=9) that exclusively underwent low-dose lung CT scans within 24-hours of admission. Clinical and lung CT characteristics were collected and analysed. Results: Ground-glass-opacities (GGO) appearance has been recorded in all subjects in HF and COVID-19 group. There was no significant statistical difference between the two groups for rounded morphology, consolidation, crazy paving pattern, lesion distribution, parenchymal band (P> 0.05). However, diffuse lesions were more frequent in HF cases (55.6% vs. 0%) than in COVID-19 pneumonia, which had predominantly multifocal pattern. Notably, CT images in HF patients were more likely to have signs of interstitial tissue thickening such as the interlobular septums, fissures and peribronchovascular interstitium (55.6% vs 0%, 88.9% vs 20% and 44.4% vs 0%,respectively), as well as cardiomegaly (77.8% vs 0%), increased artery to bronchus ratio (55.6% vs 0%), and pleural effusions (77.8% vs 0%). Conclusions: Major overlaps of lung CT imaging features existed between COVID-19 pneumonia and acute HF cases. However, signs of fluid redistribution are clues that favour HF over COVID-19 pneumonia.

It has been hypothesized that social distancing as the prevention measures for COVID 19 can affect the air quality including PM_2.5 and PM₁₀ in urban areas. According to this situation, this study aims to compare the PM_2.5 and PM₁₀ before and after the implementation of social distancing. Likewise, this study also forecasts the benefits of social distancing on PM_2.5 and PM₁₀ if social distancing period is continued and extended. To achieve these objectives, an Auto Regressive Integrated Moving Average (ARIMA) model to investigate the daily PM_2.5 and PM₁₀ trends has been developed for social distancing periods (March– May 2020) and after May as well. The model confirms that if social distancing period is extended after May 2020 then the PM_2.5 and PM₁₀ are estimated will be 4% and 9% lower. To confirm that the PM_2.5 and PM₁₀ reductions are only due to social distancing effect, the study has investigated the possible effects of wind speed and rainfall on PM_2.5 and PM₁₀. Nonetheless, the reductions do not correlate with those factors. To conclude social distancing should be considered as an option to control PM_2.5 and PM₁₀ in urban areas.

The pandemic caused by SARS-CoV-2 virus obstructed the Chinese economy and has expanded to the rest of the world at a rapid pace affecting at least 215 countries, areas and territories. The advancement of the disease and its economic repercussions is profoundly ambiguous, making it challenging for policymakers to formulate suitable microeconomic and macroeconomic policy responses. The scenarios in this paper illustrate how an outbreak could significantly affect the global economy in the short run. It has been estimated that each additional month of crisis would cost from about 2.5-3% of the global GDP and that the GDP growth would take a blow, reaching about 3-6%, depending on the country. Scenarios also suggest that GDP can drop by more than 10% and even exceed 15% in some countries. Via addressing the economic consequence of COVID-19 in different industries and countries, the paper presents assessments of the likely global economic costs of COVID-19 and the GDP growth of different countries. Economies will be negatively affected because of the high number of jobs at risk. Countries highly dependent on foreign trade are more negatively affected. Given that disease and its economic influence are highly unpredictable in numerous aspects, the global economy at the moment is the most critically threatened in history.

The world is facing new challenges every day; however, with the spread of the pandemic around the world, this new challenge is different. The pandemic is increasing and concentrating various challenges simultaneously. Although different sectors are facing consequences, the most important sectors, that is, health and economy are the most affected. When the pandemic began, it was not known how long it would last, which complicated health and economic planning. Therefore, it is important for decision makers and the public to know the predictions and expectations of the future of these challenges. In this work, the current situation is analyzed. Then, an expectation model is developed based on the statistics of the pandemic using a growth rate model based on an exponential and logarithmic rate of increase. Based on the available open data about the pandemic spread, the model can successfully predict future expectations, including the duration and maximum number of cases of the pandemic. The model uses the equilibrium point as the day the cases decrease. The model can be used for planning and the development of strategies to overcome these challenges.

Introduction: COVID-19 is an unprecedented global public health emergency currently impacting India in an unprecedented manner. Aim of this study was to assess knowledge, awareness, perceptions and related factors of Indian dentists on COVID-19. Methodology: A cross-sectional, on-line questionnaire-based study was conducted over one week between 3rd May, 2020 to 10th May, 2020. The sample comprised 403 Indian dentists in solo, group practices and in the academic arena. The self-administered questionnaire assessed 1) knowledge/awareness on factors related to COVID-19 patient identification and symptomatology, 2) knowledge/awareness of COVID-19 transmission and 3) perceptions of COVID-19 history taking procedure. Statistical analyses were conducted using Statistical Package for Social Sciences for Windows, version 21.0 (IBM Corp., Armonk, NY., USA). Frequency distributions and logistic regression analyses were used. Results: Indian dentists demonstrated an overall modest level of knowledge on identification of patients with COVID-19. Moreover, they had a high level of awareness of the COVID-19 transmission means, and the generally accepted procedural perceptions on patient history taking. However, there were some gaps in specific aspects of knowledge and perceptions. Those who were aged ≥ 30-years had a significantly higher level of knowledge of patient identification means than those who were < 30-years (OR=1.78:1.12-2.83); p=0.01. Moreover, specialized dentists were significantly knowledgeable of COVID-19 transmission means than the general dentists (OR=1.89:1.22-2.93; p=0.004). Conclusions: Our findings demonstrate identifiable gaps in knowledge/awareness and perceptions of COVID-19 in Indian dental professionals. These gaps should be fulfilled, at the earliest, due to the rising burden of COVID-19 in India, to ensure safe dental care delivery.

This paper is purposed to delineate the current situation around Bangladesh as well as impacts of Coronavirus Disease-2019 (COVID-19) around the country and how the people over here are encountering this threatening pandemic. COVID-19 is an international epidemic that has got rapid wide-spread throughout different countries of the world to date. After its first outbreak in China different continents started to make sense and get aware against COVID-19 though, due to its special strategy of transmission several countries have been quite deteriorated preventing it. All the countries are moving at their best forward to find out any solution so that whole world could get rid of this horrifying situation as soon as possible. The authors here have reported an overview of how the outbreak of COVID-19 had put its commence in Bangladesh and to date how people over here have been tracing the way to tackle this havoc. Also, the changes that have brought around due to the crisis have offered us some fertile lessons that are enunciated here by the authors. To conclude, special considerations are anticipated to be highlighted pertaining COVID-19 outbreak in Bangladesh.

Background: The question of whether children are less likely to pass on SARS-CoV-2 is important for planning society’s response to the pandemic. A document available on the Charité hospital website has not been formally published but is frequently referred to as supporting the notion that viral loads are similar in children and adults. Methods: The summary data from this document was extracted and used to produce summary statistics for three age groups: younger children (ages up to 11), older children (ages 12 to 19) and adults (ages 20 and above). Viral loads between the two children’s groups and the adult group were compared using Welch’s t test, which only requires group means and standard deviations and which is robust against moderate departures from normality. Findings: Viral loads were significantly lower than in adults for both younger children (p=0.04) and older children (p=0.04). Overall, viral loads were lower in children than adults (p=0.005). Interpretation: For both younger and older children, on average those with detectable SARS-CoV-2 have significantly lower viral loads than adults. Funding: No funding was received for this analysis.

Objectives: In December 2019 a novel human-infecting coronavirus, SARS-CoV-2, has emerged. The WHO has stated the epidemic as a “public health emergency of international concern”. A dramatic situation has emerged with thousands of deaths, occurring mainly in the aged and very ill people. Epidemiological studies suggest that immune system function is impaired in elderly individuals and these subjects often present a severe deficiency in nutrients as fatsoluble and hydrosoluble vitamins. Design: In this second part of the review about Cov2 in aged people, we searched for studies describing the possible efficacy of vitamins A, D, E and C in improving the immune system function and their possible activities against viruses. Results: Vitamins may shift the proinflammatory Th17 mediated immune-response arising in the autoimmune diseases towards a T-cell regulatory phenotype. These diseases may serve as a paradigm for the study of CRS emerging in the course of SARS CoV-2 infection. Conclusion: This review discusses about the possible activity of Vitamin A, D, E and C in restoring normal antiviral Immune System function or the potential therapeutic role of these micronutrients as a part of a multi-treatment strategy against SARS-CoV-2 infection.

Objectives: In December 2019 a novel human-infecting coronavirus, SARS-CoV-2, has emerged. The WHO has stated the epidemic as a “public health emergency of international concern”. A drammatic situation has emerged with thousands of deaths, occurring mainly in the aged and very ill people. Epidemiological studies suggest that immune system function is impaired in elderly individuals and these subjects often present a severe deficiency in nutrients as fatsoluble and hydrosoluble vitamins. Design: In this first part of the review about Cov2 in aged people, we searched for reviews describing the characteristics of autoimmune diseases and the available therapeutic protocols for their treatment. We sed them as a paradigm with the purpose to retrieve pathogenetic mechanisms in common among these pathological conditions and SARS-CoV-2 infection, as well as the alteration induced in immune system function by this virus, or by its homologous SARS-CoV. Results: SARS-CoV-2 infection induces an important immune system dysfunction with the development of an exhuberant proinflammatory response in the host, and with the development of a life-threatening condition defined as Cytokine Release Syndrome (CRS). This leads to the Acute Respiratory Syndrome (ARDS), mainly in the aged people. High mortality and lethality rates have been observed in the elderly subjects with CoV-2-related infection. Conclusion: These diseases may serve as a paradigm for the study of CRS emerging in the course of SARS CoV-2 infection. This review discusses about the possible activity of Vitamin A, D, E and C in restoring normal antiviral Immune System function or the potential therapeutic role of these micronutrients as a part of a multi-treatment strategy against SARS- CoV-2 infection.

A novel coronavirus has been reported as the causative pathogen of the Coronavirus disease 2019 (COVID-19) outbreak Wuhan city, China in December 2019. Due to the rapid spreading of COVID-19 worldwide, it has been announced as a pandemic by the World Health Organization (WHO). Hospitalized patients in Wuhan are associated with the Huanan seafood wholesale market where live animals, such as poultry, bats, snakes, frogs, rabbits, marmots, and hedgehogs are sold in that market which suggests a possible zoonotic infection. Therefore, it is essential to identify the potential animal reservoir, and the possibility of infection for other animal species. This short review aims to provide an overview on the relation between severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) infection and animals.

Globally, there is massive uptake and explosion of data and challenge is to address issues like scale, pace, velocity, variety, volume and complexity of this big data. Considering the recent epidemic in China, modeling of COVID-19 epidemic for cumulative number of infected cases using data available in early phase was big challenge. Being COVID-19 pandemic during very short time span, it is very important to analyze the trend of these spread and infected cases. This chapter presents medical perspective of COVID-19 towards epidemiological triad and the study of state-of-the-art. The main aim this chapter is to present different predictive analytics techniques available for trend analysis, different models and algorithms and their comparison. Finally, this chapter concludes with the prediction of COVID-19 using Prophet algorithm indicating more faster spread in short term. These predictions will be useful to government and healthcare communities to initiate appropriate measures to control this outbreak in time.

On 11 March 2020, the coronavirus disease (COVID-19) was defined by the World Health Organization as a pandemic. Severe acute respiratory syndrome-2 (SARS-CoV-2) is the newly evolving human coronavirus infection, causing (COVID-19), first appeared in Wuhan, China in December 2019 and spread rapidly all over the world. COVID-19 is being increasingly investigated in virology, epidemiology, and clinical management strategies. There is currently no established consensus on the standard of care in the pharmacological treatment of COVID-19 patients. However, certain medications suggested for other diseases tend to be potentially effective for treating this infection, although, so far, without clear evidence. Therapies include new agents which are currently tested in several clinical trials, in addition to other medications that have been repurposed as antiviral and immune-modulating therapies. Previous high-morbidity human coronavirus epidemics such as the 2003 SARS-CoV and the 2012 Middle East respiratory syndrome coronavirus (MERS-CoV) prompted the identification of compounds that could theoretically be active against the emerging coronavirus SARS-CoV-2. Moreover, the advances in molecular biology techniques and computational analysis allowed better recognition of the virus structure and quicker screening of chemical libraries to suggest potential therapies. This review aims to summarize rationalized pharmacotherapy considerations in COVID-19 patients, to serve as a tool for health care professionals at the forefront of clinical care during this pandemic. All the therapies reviewed require either additional drug development or randomized large-scale clinical trials to be justified for clinical use.

Amid the covid-19 pandemic, other diseases, including viruses, are still acting to the detriment of their seasonality and risk factors for contagion. For this reason, it is interesting to know the degree of impact of other viruses, mainly respiratory, in which they have similar symptoms, in diagnoses for contamination by the new coronavirus based on epidemiological surveys, via epidemiological weeks, in Brazil. To what extent there may be a hypothesis of confusion of contaminated data, harming the health system, with regard to the need for intensive care units and control of viruses, and negatively or positively implying in the control or uncontrolling of viruses in general.

Evidence for the potential for airborne transmission of SARS-CoV-19 continues to accumulate, with important implications for healthcare workers, as well as the general public. Three lines of evidence support this conclusion.

The COVID 19 related social distancing is hypothesized can affect the environmental quality including the air and water quality. Correspondingly, this study aims to study how the reduction of activities of people living near the rivers and the coastal areas due to social distancing may decrease the discharges of materials and nutrients to the water body. The chlorophyll-a was used as bio indicators of nutrient contents related to the anthropogenic activities in the coast. The study was conducted in the Jakarta coast considering that this coast was surrounded by populated cities with total population equal to 16 million people. The chlorophyll-a was measured in mg/m³ and monitored using remote sensing data from January to April 2020 representing the period before and after the implementation of social distancing. The determinant environmental factor measured was sea surface temperature (⁰C). The study considered that there were reductions of levels and areas of chlorophyll-a in the coast. The chlorophyll-a levels were reduced from January to April (p<0.05). The chlorophyll-a levels for January, February, March, and April were 7.36 mg/m³ (95%CI: 6.34-8.37), 7.90 mg/m³ (95%CI: 7.32-8.47), 6.52 mg/m³ (95%CI: 5.37-7.66), and 4.21 mg/m³ (95%CI: 3.34-5.07) respectively. However, the differences of chlorophyll-a were not influenced by the sea surface temperature factor (p>0.05). Based on remote sensing data in January and February, the sizes of coastal areas with chlorophyll-a levels >7.00 mg/m³ were larger than areas observed in March and April. Contrarily, the coastal area sizes with low chlorophyll-a levels <5.00 mg/m³ were increasing in April. To conclude the dynamic of anthropogenic activities in coastal setting is responsible and associated with the water quality and nutrient contents as indicated by chlorophyll-a levels.

This paper aims to analyze the effects of Covid-19 on financial markets from the perspective of Complexity. The Covid-19 pandemic has caused turmoil in financial markets and is already one of the most important financial crises in history, causing a fall in several stock markets as well as great volatility. Unlike past crises, which in most cases were caused either by problems of fiscal deficits or in the financial system, this crisis has its origin in an epidemic disease, which occurred in Wuhan, China, and quickly spread across the globe affecting transport networks, commerce and finance, and will affect the public debt of many countries. This is a systemic situation in which there is a need to consider several interconnected systems, financial instability and high financial risk, something that econophysics and some complexity theorists already do. Therefore, this paper intends to show, theoretically, the systemic and complex character of the recent financial crisis caused by Covid-19.

Background: World Health Organization (WHO) declared that COVID-19 as a pandemic on March 11, 2020. There is sudden need of statistical modeling due to onset of COVID-19 pandemic across the world. But health planning and policy requirements the estimates of disease problem form clinical data. Objective: To predict recovery rate, cases load rate on the basis of cumulative confirmed Novel Corona virus (NCV) cases, recovered cases and deaths form COVID-19 in India. Methods: The reported COVID-19 cases in the country were obtained from website (https://datahub.io/core/covid-19#resource-covid-19_zip/). The cumulative NCV confirmed cases; recovery cases and deaths were used for estimating recovery rate, cases load rate and death rate till date 24 April 2020. Results: A total of 24530 NCV confirmed cases were reported nationwide in India on 24 April 2020. It is found that the recovery rate increased 22% and case load rate decreased 74%. Death rate is found to be very low 3%. The difference of cases load rate and recovery rate (delta) coincide at 50 % then NCV cases expected would be declined. Conclusion: The epidemic in the country was mainly caused by the importation of India. Lockdown as restricting the migration of population and decided to quarantine of population may greatly reduce the risk of continued spread of the epidemic in India. This study predicts that by 20 May 2020, the cases load rate lesser than recovery rate there after COVID-19 patients would be started to reducing.

During December 2019, a novel coronavirus named SARS-CoV-2 has emerged in Wuhan, China. The human to human transmission of this virus has also been established. The virus has so far infected more than 2 million people and spread over 200 countries. The World Health Organization (WHO) has declared COVID-19 a global health emergency due to its spread well beyond China. It has been established that this virus originates from bats and uses an intermediate host for transfer to humans. The knowledge about the intermediate host is important to find the virus shuttle mechanism to stop future outbreaks. For this, the genetic and structural analysis of coronaviruses spike proteins was performed using a computer-assisted approach.To conduct the In silico analysis, 43 sequences of spike protein belong to different species were retrieved from the NCBI nucleotide database. Pairwise and multiple sequence alignments were performed to check the similarities and differences of the retrieved sequences. Moreover, to highlight relationships among different species, phylogenetics analysis was performed using the MEGA software tool. In the end, protein structure alignment (superimposition) was performed against the reference structure by UCSF Chimera software. The results highlighted that the maximum similarity of human protein was found against Bat and Pangolinsequences. Moreover, among Bat and Pangolin, the highest similarity was found against pangolin based on phylogenetics analysis. These results suggest that SARS-CoV-2 transfers from bats to humans through pangolins.

The disease of COVID-19 comprises the most serious against human health worldwide with a high rate of virulence and mortality. The disease is caused by the 2019-nCoV virus from the beta coronavirus family. The virus makes use of its surface glycoprotein named S protein or spike to enter the human cells. The virus attached to its receptor named angiotensin-converting enzyme 2 on host cells surface via its receptor-binding domain and its fusion is mediated by cleavage at S2' site that is carried out by surface protease. Vaccines or drugs interfering with S protein binding or cleavage sites could be considered as drugs to get rid of the infection. In the current work and though docking and molecular dynamic experiments we have checked more than 100 drugs with high enough molecular weights for their shielding potency toward S protein binding sites and processing S2' sites. Our results indicate the shielding potency of: fidaxomicin > ivermectin > heparin > azithromycin > clarithromycin > eryhthromycin > niclosamide > ritonavir. Considering affluent reports regarding the complex disturbance in the immune system and multi-organ involvement in the disease there is no single or binary drug regime for cure expectedly and instead, we claim the multi-drug regime should be the choice in this context. Accordingly, we suggest our extracted drugs as an adjuvant for clinical trials.