Background: Medical comorbidities increase the risk of severe COVID-19 infection. In some studies, obstructive sleep apnea (OSA) has been identified as a comorbid condition that is associated with an increased prevalence of COVID-19 infection and hospitalization, but few have investigated this association in a general population. Research Question: In a general population, is OSA associated with increased odds of COVID-19 infection and hospitalization and are these altered with COVID-19 vaccination? Study Design: Cross-sectional survey of a diverse sample of 15,057 U.S. adults Results: COVID-19 infection and hospitalization rates were 38.9% and 2.9% respectively. OSA or OSA symptoms were reported in 19.4%. In logistic regression models adjusted for demographic, socio-economic and comorbid medical conditions, OSA was positively associated with COVID-19 infection (aOR: 1.58, 95%CI: 1.39-1.79) and COVID-19 hospitalization (aOR: 1.55, 95% CI: 1.17-2.05). In fully adjusted models, boosted vaccination status was protective against both infection and hospitalization. Boosted vaccination status attenuated the association between OSA and COVID-19 related hospitalization, but not infection. Participants with untreated or symptomatic OSA were at greater risk for COVID-19 infection; those with untreated, but not symptomatic OSA were more likely to be hospitalized. Interpretation: In a general population sample, OSA is associated with a greater likelihood of having had a COVID-19 infection and a COVID-19 hospitalization with the greatest impact observed among persons experiencing OSA symptoms or who were untreated for their OSA. Boosted vaccination status attenuated the association between OSA and COVID-19 related hospitalization.

Pineapple is a highly demanded fruit in international markets, thanks to its unique appearance and flavor, high fiber content, vitamins, folic acid, and minerals. It makes the pineapple production and processing market a significant source of income for producing countries, such as Costa Rica. Nowadays, its processing produces a large amount of waste with negative consequences for the environment. However, pineapple waste is an essential source of cellulose, hemicellulose, lignin, and other high-value products like enzymes (bromelain). These by-products can be obtained by pineapple waste biorefinery, generating an additional source of export goods and foreign currency, framing pineapple processing in the concept of the circular economy. This review discusses how incorporating biorefinery in the pineapple production processes can contribute to the post-COVID 19 economy in Costa Rica. Pineapple production in Costa Rica is explored, and the contamination of generated residues is delineated. Furthermore, the primary processes for by-product extraction via biorefinery, their general characteristics and applications in the medical field, and their contribution to the circular economy are presented.

Background: This study describes the attitudes and practices of Brazilian adults regarding the mandatory vaccination for COVID-19 and the hesitancy to children´s vaccination. Methods: The participants answered an online questionnaire disseminated on social networks. An adaptation of the SAGE-WG questionnaire was used to measure the children's vaccination hesitancy. Results: Among 1,007 participants, 677 (67.4%) believed that vaccination for COVID-19 among adults should be mandatory. Just over half of the participants (51.5%) believe that parents and guardians should be free to decide whether their children should be vaccinated against COVID-19, and 9.1% were unsure about this. Younger, non-religious people who have higher self-perceptions of risk for COVID-19, and who evaluate the federal government's performance in combating the disease as bad or very bad, have a higher agreement with mandatory vaccination, a lower agreement that parents and guardians should be free to vaccinate their children, and lower child vaccination hesitancy scores. Conclusion: In Brazil, mandatory COVID-19 vaccination for adults is far from a consensus, and an expressive part of the population believes that parents and guardians should be free to choose whether or not to vaccinate their children. These perceptions and vaccine hesitancy for children are associated with religious and political inclinations.

Background: A novel virulent coronavirus is what causes Novel Corona-virus Disease 2019 (nCOVID 19). It results in severe respiratory distress syndrome and potentially fatal infectious pneumonia. On March 12, 2020, the World Health Organization first labeled it a pandemic, which was then followed on the same day by a community health emergency of global concern. Vaccines against this deadly virus are now being created. Many drugs with different uses have been repurposed and tested for the prevention and treatment of the infection. Objective: The purpose of this review is to provide an in-depth analysis of data on possible pharmacological targets and available coronavirus treatments. Methods: Following the review protocol, a literature search was conducted. Results: Chloroquine phosphate and hydroxychloroquine, Remdesivir, and Lopinavir-Ritonavir in combination with or without interferon and convalescent plasma therapy are the main treatment candidates, according to the World Health Organization. This review article has elaborated on the current evidence of prospective pharmacological targets and related ongoing research, including inflammatory chemicals, bioactive peptides, beta cells, platelets, and the Angiotensin I Converting Enzyme 2 Receptor. This information was gathered from published journals. In addition, stories of medications and biological products like interferons and vaccinations that are utilized or could be utilized have been provided. Conclusion: There are a variety of pharmacological targets and therapeutic strategies that need more study.

Purpose: The study aimed to investigate if there were any links between liver function biomarkers and immunoglobulins levels in serum, and Toll-like receptors (TLRs) and neuropilin-1 (NRP1) in COVID-19 patients. The study also aimed to assess the accuracy—sensitivity, specificity, and area under the curve (AUC) by the receiver operator curve (ROC) analysis for immunoglobulins levels and TLRs expressions. Patients and Methods: This study included 150 patients (100 patients with confirmed COVID-19 and 50 healthy volunteers as a control group). Patients with COVID-19 were subdivided into two groups according to the severity of symptoms (moderate and severe, with 50 patients each). Serum C-reactive protein (CRP), alanine aminotransaminase (ALT), aspartate aminotransaminase (AST), albumin, lactate dehydrogenase (LDH), immunoglobulin (Ig) G, and IgM levels were estimated. TLRs (TLR2 and TLR4) and NRP1 gene expression in blood samples were investigated using quantitative real-time polymerase chain reaction (qRT-PCR). ROC analysis was also applied to determine the accuracy of various detected parameters in predicting the possibility of COVID-19 infection. Results: In COVID-19 patients, serum parameters related to liver function, except serum albumin, CRP, IgG, IgM, and TLR2, TLR4, and NRP1 mRNA expression levels, significantly elevated compared to controls. Severe COVID-19 patients exhibited significantly higher liver enzymes (ALT, AST and LDH), CRP, and TLR2 mRNA expression levels and lower albumin levels than the moderate group. In the moderate and severe groups, ALT, CRP, TLR2, and TLR4 had a significant positive correlation with IgM levels. ALT, AST, LDH, CRP, TLR2, and TLR4 showed a significant positive correlation with IgG levels in both groups. In both the moderate and severe groups, NRP1 expression was found to be significantly correlated with CRP, IgG, IgM, TLR2, and TLR4. In contrast, serum albumin levels exhibited a significant negative correlation with IgG and IgM levels only in the severe group, but they showed a significant negative correlation with TLR2, TLR4, and NRP1 expression in both moderate and severe groups. Serum ALT and AST activities were positively correlated with NRP1 expression in the moderate group but not in the severe group and as well as TLR2 and TLR4 expression in both the moderate and severe groups. ROC analysis indicated that AUC was higher than 0.800 for serum IgM level and TLR4 gene expression in moderate COVID-19 group. Conclusions: The increased liver function biomarkers in serum and NRP1 expression are closely correlated with sustained activations in humoral and innate immune responses during COVID-19 infection. As a result, TLR2, TLR4, and NRP1 could be targets for limiting COVID-19 infection and impairment effects on liver function. Moreover, detection of IgM level in serum and TLR4 expression in blood have a good accuracy in predicting the possibility of infection with COVID-19 in moderate cases.

The COVID-19 is an exponentially growing disease that has intentioned nations to use technologies to detect the coronavirus infection. Several nations are working greatly to fight against COVID-19. Many nations have been using a range of devices to combat the pandemic, seeking information about growth, monitoring as well as the leaking the confidential information of the residents. This research aims to assist infected people online using the Internet of Things (IoT) and Blockchain technologies through smart devices. IoT-based healthcare devices gather useful information, provide additional insight through symptoms and behaviors, allow remote monitoring, and simply give people better self - determination and healthcare. Blockchain allows the secure transfer of patient health information, regulates the medical distribution network. A four-layer architecture is proposed using IoT and Blockchain to detect and prevent individuals to be COVID 19. This research provides a framework for patients with COVID-19 infectious disease and recognizes health issues and diagnoses online. Smart devices such as smartphones can install any mobile apps such as Aarogya Setu, Tawakkalna, and so on. These applications can track COVID-19 patients properly. The installation of mobile apps on smart devices focuses to reduce the time and cost and increase the performance of the infectious patient's condition. A four-layer architecture is proposed using IoT and Blockchain technologies. Many research works focus on investigating, analyzing, and highlighting the affected individuals through guiding the COVID-19 infection. Eventually, various mobile apps are recognized and addressed in this paper.

The COVID-19 pandemic has highlighted the vitalness of telehealth in our medical world, where considering a restructuring of healthcare services has become paramount. In fact, telemedicine has recently earned a valuable place in many specialties; and its implications in cardiology and cardiovascular medicine were among the leading interests. In this letter, we gathered previous evidence supporting the merit of telemedicine in the fields of cardiology and cardiovascular medicine—medical branches in which patients require meticulous care and continuous monitoring—as well as protrusions of concerns about the uncertainty regarding the efficacy of telemedicine’s future implications and technologies. In sum, in the context of this still on-going pandemic, medical institutions must strive to improve telehealth technologies and implement solid future research directions in this growing field—to be able to persevere in meeting the needs of the patients. As long as no conclusive evidence exists regarding the fields where telemedicine is most worthwhile, healthcare systems will always keep the dread of wasting resources on developing ineffective programs. We conclude that telemedicine has been attributed a considerable attention in managing cardiac and cardiovascular conditions; nevertheless, further studies with solid designs are still needed to confirm its validity and utility in those specialties.

The new SARS-CoV-2 coronavirus has brought with it an increase in the use of digital platforms and an exponential increase in the number of scientific papers worldwide. The purpose of this study is to show a global overview of the digital transformation from 1975 to the present (2021). The main collection of the Web of Science database was used to retrieve global scientific production on digital transformation. Bibliometric indicators of production, visibility, impact, and collaboration were analyzed to assess research progress on the topic. The results show that digital transformation is a construct of recent development, increasingly relevant and transdisciplinary, with a clear growth after the declaration of the global COVID-19 pandemic.

During the COVID-19 pandemic, WIC increased the Cash Value Benefit (CVB) for fruits and vegetables by roughly $25/month/person. We sought to understand WIC participant perceptions of this change and barriers and facilitators to using the CVB. We conducted 10 virtual focus groups (5 rural, 5 urban/suburban) with WIC participants (n=55) in North Carolina in March 2022. Focus groups were recorded and transcribed. We open coded the content and used thematic analysis to uncover consistencies within and between sampled groups. Participants expressed favorable perceptions of the CVB increase and stated the pre-pandemic CVB amount was insufficient. Barriers to using the increased CVB were identifying WIC approved fruits and vegetables in stores and insufficient supply of fruits and vegetables. Barriers were more pronounced in rural groups. CVB use facilitators were existing household preferences for fruits and vegetables and the variety of products that can be purchased with the CVB relative to other components of the WIC food package. Participants felt the CVB increase allowed their families to eat a wider variety of fruits and vegetables. The CVB increase may improve fruit and vegetable intake, particularly if made permanent, but barriers to CVB and WIC benefit use may be limiting the potential impact.

The development of inexpensive, fast and reliable screening tests for COVID-19 is, as yet, an unmet need. The present study was aimed at evaluating the usefulness of serum arylesterase activity of paraoxonase-1 (PON1) measurement as a screening test in patients with different severity levels of COVID-19 infection. We included 615 COVID-19 positive patients who were classified as asymptomatic, mildly symptomatic, severely symptomatic, or fatally symptomatic. Results were compared with 50 healthy volunteers, 330 patients with cancer and 343 with morbid obesity. Results showed PON1 activity greatly decreased in COVID-19 compared to healthy vol-unteers; receiver operating characteristics plot showed a high diagnostic accuracy. The degree of COVID-19 severity did not influence PON1 levels. Our results indicated that PON1 determination was efficient for disease diagnosis but not for prognosis. Further, patients with obesity or cancer presented alterations similar to those of COVID-19 patients. As such, elevated levels of PON1 in-dicate the absence of COVID-19, but low levels may be present in various other chronic diseases. The assay is fast and inexpensive. We suggest that PON1 measurement could be used as an initial, high cut-off point screening method, while lower values should be confirmed with the more ex-pensive nucleic acid amplification test.

The urgency of the COVID19 pandemic caused a surge in related scientific literature. This surge made the manual exploration of scientific articles time-consuming and inefficient. Therefore, a range of exploratory search applications have been created to facilitate access to the available literature. In this survey, we give a short description of certain efforts in this direction and explore the different approaches that they used.

Background: In the span of just two years, tracking the COVID-19 pandemic through wastewater surveillance has advanced from early reports of successful SARS-CoV-2 RNA detection in untreated wastewater to implementation of programs in at least 60 countries. Early wastewater monitoring efforts primarily originated in research laboratories and are now transitioning into more formal surveillance programs run in commercial and public health laboratories. A major challenge in this progression has been to simultaneously optimize methods and build scientific consensus while implementing surveillance programs, particularly during the rapidly changing landscape of the pandemic. Translating wastewater surveillance results for effective use by public health agencies also remains a key objective for the field. Objectives: We examine the evolution of wastewater surveillance to identify model collaborations and effective partnerships that have created rapid and sustained success. We propose needed areas of research and key roles academic researchers can play in the framework of wastewater surveillance to aid in the transition of early monitoring efforts to more formalized programs within the public health system. Discussion: Wastewater surveillance has rapidly developed as a public health tool Clinical testing programs are ramping down and home testing is on the rise, making wastewater monitoring important for future surveillance of COVID-19. Our experience in initiating and implementing wastewater surveillance programs in the United States has allowed us to reflect on key barriers and organizational challenges and draw useful lessons. As wastewater surveillance programs are formalized, the working relationships developed between academic researchers, commercial and public health laboratories, and data users should continue and should promote knowledge co-development. While wastewater surveillance has demonstrated utility for tracking COVID-19, there remain technical challenges and open scientific questions that researchers are equipped to address, which will contribute to building robust surveillance programs that provide public health practitioners with new insights into population health.

The purpose of this study was to explore the role of moral distress on physician burnout during COVID-19. Physicians in the US were interviewed between February and March 2021; 479 responded to our survey. Results indicated that moral distress was a key mediator in explaining the relationship between perceived organizational support, medical specialization, emotional labor, and coping on burnout. There was no support for increased burnout among female physicians, and contracting COVID-19 likewise did not play a role in burnout. Our findings suggest that physician burnout can be mitigated by increasing perceived organizational support; likewise, physicians who engaged in deep emotional labor and problem-focused coping tended to fare better when it came to feelings of moral distress and subsequent burnout.

The COVID-19 pandemic has highlighted the adverse consequences created by an infodemic specifically on compliance with public health guidance and vaccine uptake. COVID-19 vaccine hesitancy is a complex construct that is related to health beliefs, misinformation exposure, and perceptions of governmental institutions. This study draws on theoretical models and current data on the COVID-19 infodemic to explore the association between perceived risk of COVID-19, levels of misinformation endorsement, and opinions about the government response on vaccine uptake. We surveyed a sample of 2,697 respondents from the US, Canada, and Italy using a mobile platform between 21-28 May, 2021. Using multivariate regression, we found that country of residence, risk perception of contracting and spreading COVID-19, perception of government response and transparency, and misinformation endorsement was associated with the odds of vaccine hesitancy. Higher perceived risk was associated with lower odds of hesitancy, while lower perceptions of government response, and higher misinformation endorsement were associated with higher hesitancy.

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.

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.

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 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.

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) .

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.

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.

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.

— 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.

Appropriate diagnostic testing to identify persons infected with SARS-COV-2 is a vital part of a health system’s ability to control the global pandemic of COVID-19 disease. The primary purpose of this review is to provide an overview of the mass testing strategy implemented throughout the UAE and the overall impact it has made on containing and controlling the spread of the disease. This study describes the mass testing strategy and capacity of the UAE during the pandemic of the new coronavirus SARS-COV-2. The UAE has conducted 15 million polymerase chain reaction (PCR) tests to SARS-COV-2, as of 15 November 2020. The number of tests per day varied from 10,000 by the end of March to 120,000 tests per day in November 2020. The mass testing initiative across the entire UAE forms an integral part of a bigger strategy focusing on testing, tracing contacts and isolating positive cases.

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.

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 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.

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.

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 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.

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.

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 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.

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 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.

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 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.

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.

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.

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.

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.

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.

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.

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.

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.

In attempting to predict the further course of the novel coronavirus (COVID-19) pandemic caused by SARS-CoV-2, mathematical models of different types are frequently employed and calibrated to reported case numbers. Among the major challenges in interpreting these data is the uncertainty about the amount of undetected infections, or conversely: the detection ratio. As a result, some models include assumptions about the percentage of detected cases among total infections while others completely neglect undetected cases. Here, we illustrate how model projections about case and fatality numbers vary significantly under varying assumptions on the detection ratio. Uncertainties in model predictions can be significantly reduced by representative testing, both for antibodies and active virus RNA, to uncover past and current infections that have gone undetected thus far.

The recent 2019-nCoV outbreak, spreading infection around the globe is jeopardizing the public health and global economy. The virus was reported to have emerged from an animal market in Wuhan, China at the end of 2019 and presumed to have originated from bats and eventually transmitted in humans. The entry of the virus into human cells is triggered by a series of molecular events initiated with the binding of a receptor-binding domain of viral spike protein to human Ace2 cell surface receptor. Based on the comparative sequence analysis of the well-known binding hotspots of human Ace2, cross-interacting potential of 2019-nCoV was predicted, which suggests Ace2 of wild animals like tiger, bear, orangutan, etc.; aquatic mammals like whale and dolphins; and domestic animals like cat, horse, goat, sheep, dog etc. as potential target. However, the recognition of Ace2 of bats, rats and mice by the 2019-nCoV spike protein remains under question. The study indicates that 2019-nCoV might have broad host range and may thus intensify the gravity of 2019-nCoV outbreak

We analyze the Covid-19 mortality scenario in India and compare it with those in other large-population regions such as Asia-excluding-China, Africa, European Union, South America, and USA. We compare existing fatality data and offer an interpretation for low fatality based on immunity due to endemic malaria and TB. We identify the hot climate in the past summer as a possible cause for low death count in southern-hemisphere countries without endemic malaria and TB. We also make India-specific observations for easing the lockdown and estimations for the time required to attain herd immunity. Whatever optimism we present should be viewed as a guarded optimism. There should not be room for complacency.

Till date there are three full length COVID 19 virus genome sequences available from India. The earlier two were reported from Kerala, Southern India and the more recent one has been reported from Gujarat, western part of India. In this paper we report two novel mutations in the Spike protein sequence of Gujarat’s isolate. These mutations are based on comparison with the original Wuhan sequence. The two mutations have been found to be located just upstream and downstream of the receptor binding domain (RBD). Out of these two one has also been found to affect the secondary structure of the S1 domain. Since both of these mutations lie near the receptor binding domain, they might influence the spike receptor interactions by changing the conformation of the spike protein S1 domain. These mutations are uniquely placed and might be important in the context of vaccine engineering and therapeutic interventions.

Azithromycin has been shown to have a clinical efficacy against severe acute respiratory syndrome coronavirus 2 (SARS CoV-2); ivermectin has also demonstrated a remarkable experimental efficacy with a potential to be used for Coronavirus disease 2019 (COVID-19). Further, BCG vaccination is being considered for clinical trials aiming to test its potential for lowering COVID-19 morbidity and mortality. This article illustrates some structural and functional relationships that may gather these drugs and the author, basing on a combined pathophysiological and pharmacological approach, recommends the FDA-approved antidiarrhea drug; nitazoxanide, which has been previously suggested but unfortunately ignored, to be tested in combination with azithromycin for their potential activity against SARS CoV-2 soonest. The author recommends testing their combined administration as early during the clinical course of COVID-19 as possible. Further, basing on the same represented concept, the author recommends more trials for interferons to be tested against SARS CoV-2 especially in severe and critical cases.

Hydroxychloroquine, a known antiviral metabolite of chloroquine, is increasingly used along with antibiotic azithromycin for the treatment of COVID-19 infection. In about one month India, the world’s largest manufacturer, delivered hydroxychloroquine for treating COVID-19 to over 50 countries. The therapy is being used across the world both for patients staying at home at the early phase of symptoms, as well as for patients hospitalized. We summarize achievements as of late April 2020, review possible modes of action and suggest avenues for the quick scale-up of production of hydroxychloroquine.

The recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread so rapidly and severely affected the people of almost every country in the world. The highly contagious nature of this virus makes it difficult to take control of the present pandemic situation. With no specific treatment available, the coronavirus disease 2019 (COVID-19) presents a threat to people of all ages including the elderly people and people with other medical complications as a vulnerable group to this disease. Better understanding of viral pathogenesis, appropriate preventive measures, early diagnosis and supportive treatments of the infected patients are now the general solutions to fight against this viral transmission. But, as an emerging disease, most about it remains still poorly understood. This article holds an overview on the origin and structure, pathogenesis, diagnosis and possible therapeutic options for the causative agent, SARS-CoV-2 and disease, COVID-19. However, few therapeutic options, laboratory experiments and other strategies proposed here need to be further clinically tested.

With the emergence of COVID-19 we are confronted with a new clinical picture of acute respiratory distress syndrome in the intensive care unit. In the majority of patients, the respiratory mechanics are very different from the “normal” ARDS patient. We measured transpulmonary pressure and dead space ventilation to assess the effects of high and low PEEP levels on lung compliance and ventilation-perfusion mismatching. Advanced respiratory mechanics were assessed in 14 patients. Compared to ARDS patients, lung compliance was relatively high (61 ± 5 mL/cmH₂O). COVID-19 patients had high dead space ventilation and gas exchange impairment (Bohr 52 ± 3%; Enghoff modification 67 ± 2%; ventilatory ratio 2.24 ± 0.23). we show that higher PEEP levels decrease lung compliance and in most cases increase dead space ventilation, indicating that high PEEP levels probably cause hyperinflation in patients with COVID-19. We suggest using prone position for an extended period of time, and apply lower PEEP levels as much as possible.

World is currently experiencing a new pandemic for which no curative treatment is available. At this time, coronavirus disease 2019 (Covid-19) has reached 183 countries and has caused several deaths. Many reports presented chloroquine (CQ) and hydrochloroquine (HCQ), former drugs used against malaria, as the best current choice to fight this terrible disease. As these molecules had been withdrawn in malaria treatment policy due to chemoresistance, their reintroduction could have some consequences. Though local malaria prevalence could decrease for a while, molecular changes are likely to happen on some plasmodium falciparum genes involved in conferring drug resistance. This could threaten efforts in malaria control, if these molecules are widely administered.

With frequencies varying up to 20%, treatment resistant pulmonary failure is a major life-threatening complication in COVID-19 (SARS-CoV-2, HCoV19) disease pathology. Both acute respiratory distress syndrome (ARDS), proposed to be caused by an over-reacting immune system which floods the lung with edema, a liquid consisting of inflammatory cells, and diminished lung perfusion, have been postulated to cause this treatment resistant lung failure. Aging, co-morbidities, male gender and obesity are pre-existing factors associated with the more severe outcome. Thrombosis is more frequently observed than usually seen during ICU admission. Different hypotheses explaining the pathophysiological cascade leading to fast progressing severe COVID-19 disease and how to counteract it have been proposed. A variety of intervention studies to control severity are ongoing or planned. Not suggested so far, we here hypothesize that the inflammatory lipid modulator prostaglandin E₂ (PGE₂) executes a prominent role in COVID-19 pathophysiology. Based on this we suggest measuring PGE₂ in patients and evaluating selective inhibition of the human microsomal prostaglandin E synthase-1 (mPGES-1) as a potential innovative therapeutic approach in this devastating condition for which sonlicromanol, a drug currently in phase 2b studies for mitochondrial disease, is a candidate.

Background: Countries around the world are facing extraordinary challenges in implementing various measures to slow down the spread of the novel coronavirus (COVID-19). Guided by international recommendations, Saudi Arabia has implemented a series of infection control measures after the detection of the first confirmed case in the country. However, in order for these measures to be effective, public attitudes and compliance must be conducive as perceived risk is strongly associated with health behaviors. The primary objective of this study is to assess Saudis’ attitudes towards COVID-19 preventive measures to guide future health communication content. Methods: Naïve Bayes machine learning model was used to run Arabic sentiment analysis of Twitter posts through the Natural Language Toolkit (NLTK) library in Python. Tweets containing hashtags pertaining to seven public health measures imposed by the government were collected and analyzed. Results: A total of 53,127 tweets were analyzed. All measures, except one, showed more positive tweets than negative. Measures that pertain to religious practices showed the most positive sentiment. Discussion: Saudi Twitter users showed support and positive attitudes towards the infection control measures to combat COVID-19. It is postulated that this conducive public response is reflective of the overarching, longstanding popular confidence in the government. Religious notions may also play a positive role in preparing believers at times of crises. Findings of this study broadened our understanding to develop proper public health messages and promote stronger compliance with control measures to control COVID-19.

Most striking observations in COVID-19 patients are the hints on pulmonary edema (also seen on CT scans as ground glass opacities), dry cough, fluid restrictions to prevent more severe hypoxia, the huge PEEP that is needed while lungs are compliant, and the fact that anti-inflammatory therapies are not powerful enough to counter the severity of the disease. We propose that the severity of the disease and many deaths are due to a local vascular problem due to activation of B1 receptors on endothelial cells in the lungs. SARS-CoV-2 enters the cell via ACE2, a cell membrane bound molecule with enzymatic activity that next to its role in RAS is needed to inactivate des-Arg⁹ bradykinin, the potent ligand of the bradykinin receptor type 1 (B1). In contrast to bradykinin receptor 2 (B2), the B1 receptor on endothelial cells is upregulated by proinflammatory cytokines. Without ACE2 acting as a guardian to inactivate the ligands of B1, the lung environment is prone for local vascular leakage leading to angioedema. Angioedema is likely a feature already early in disease, and might explain the typical CT scans and the feeling of people that they drown. In some patients, this is followed by a clinical worsening of disease around day 9 due to the formation antibodies directed against the spike (S)-antigen of the corona-virus that binds to ACE2 that could contribute to disease by enhancement of local immune cell influx and proinflammatory cytokines leading to damage. In parallel, inflammation induces more B1 expression, and possibly via antibody-dependent enhancement of viral infection leading to continued ACE2 dysfunction in the lung because of persistence of the virus. In this viewpoint we propose that a bradykinin-dependent local lung angioedema via B1 and B2 receptors is an important feature of COVID-19, resulting in a very high number of ICU admissions. We propose that blocking the B1 and B2 receptors might have an ameliorating effect on disease caused by COVID-19. This kinin-dependent pulmonary edema is resistant to corticosteroids or adrenaline and should be targeted as long as the virus is present. In addition, this pathway might indirectly be responsive to anti-inflammatory agents or neutralizing strategies for the anti-S-antibody induced effects, but by itself is likely to be insufficient to reverse all the pulmonary edema. Moreover, we provide a suggestion of how to ventilate in the ICU in the context of this hypothesis.

Computational studies suggest that hesperidin, a flavonoid abundant in citrus peel, binding the three main cellular receptors of SARS-CoV-2 virus can act in the prophylaxis and treatment of COVID-19. Herein we urge the uptake of hydrodynamic cavitation industrial-scale reactors based on the low cost, reliable Venturi tube for the extraction of citrus pectin rich in hesperidin (and in other bioflavonoids including naringing) by very fast processing of waste orange peel or waste lemon peel in water only. A device able to process up to 500 kg of waste peels per session, similar to the one lately deployed in Italy for hydrodynamic cavitation-assisted brewing, is capable to provide 36,000 doses of 1000 mg hesperidin per day.

With the current rapid spread of COVID-19, global health systems are increasingly overburdened by the sheer number of people that need diagnosis, isolation and treatment. Shortcomings are evident across the board, from staffing, facilities for rapid and reliable testing to availability of hospital beds and key medical-grade equipment. The scale and breadth of the problem calls for an equally substantive response not only from frontline workers such as medical staff and scientists, but from skilled members of the public who have the time, facilities and knowledge to meaningfully contribute to a consolidated global response. Here, we summarise community-driven approaches based on Free and Open Source scientific and medical Hardware (FOSH) currently being developed and deployed to bolster access to personal protective equipment (PPE), patient treatment and diagnostics.

While the COVID-19 pandemic advances, the scientific community struggles in the search for treatments. Several improvements have been made, including the discovery of clinical efficacy of chloroquine (CQ) in COVID-19 patients, but the effective treatment protocols are still missing. In order to find novel treatment options many scientists utilize the in silico approach to identify compounds that could interfere with the key molecules involved in entrance, replication, or dissemination of the SARS-CoV-2. However, most of the identified molecules are currently not available as pharmacological agents, and assessing their safety and efficacy could take many months. Here, we took a different approach based on the proposed pharmacodynamic model of CQ in COVID-19. The main mechanism of action responsible for the favourable outcome of COVID-19 patients treated with CQ seems to be related to pH modulation-mediated effect on the endolysosomal trafficking, a characteristic of chemical compounds often called lysosomotropic agents because of the physico-chemical properties that enable them to passively diffuse through the endosomal membrane and undergo protonation-based trapping in the lumen of the acidic vesicles. In this review, we discuss lysosomotropic and lysosome targeting drugs that are already in clinical use and are characterized by good safety profiles, low cost, and wide availability. We emphasize that some of these drugs, in particular azithromycin and other macrolide antibiotics, indomethacin and some other non-steroidal anti-inflammatory drugs, proton pump inhibitors, and fluoxetine could provide additional therapeutic benefits in addition to the potential antiviral effect that still has to be confirmed by well-controlled clinical trials. As some of these drugs, mostly antibiotics, were already empirically used in the treatment of COVID-19, we encourage our colleagues all over the world to publish patient data so potential efficacy of these agents can be evaluated in the clinical context and rapidly implemented in the therapeutic protocols if the beneficial effect on clinical outcome is observed.

COVID-19, a rapidly spreading new strain of coronavirus, has affected more than 150 countries and received worldwide attention. The lack of efficacious drugs or vaccines against SARS-CoV-2 has further worsened the situation. Thus, there is an urgent need to boost up research for the development of effective therapeutics and affordable diagnostic against COVID-19. The crystallized form of SARS-CoV-2 main protease (Mpro) was demonstrated by a Chinese researcher Liu et al. (2020) which is a novel therapeutic drug target. This study was conducted to evaluate the efficacy of medicinal plant-based bioactive compounds against COVID-19 Mpro by molecular docking study. Molecular docking investigations were performed by using Molegro Virtual Docker 7 to analyze the inhibition probability of these compounds against COVID-19. COVID-19 Mpro was docked with 80 flavonoid compounds and the binding energies were obtained from the docking of (PDB ID: 6LU7: Resolution 2.16 Å) with the native ligand. According to obtained results, hesperidin, rutin, diosmin, apiin, diacetylcurcumin, (E)-1-(2-Hydroxy-4-methoxyphenyl)-3-[3-[(E)-3-(2-hydroxy-4- methoxyphenyl)-3-oxoprop-1-enyl]phenyl]prop-2-en-1-one, and beta,beta'-(4-Methoxy-1,3- phenylene)bis(2'-hydroxy-4',6'-dimethoxyacrylophenone have been found as more effective on COVID-19 than nelfinavir. So, this study will pave a way for doing advanced experimental research to evaluate the real medicinal potential of these compounds to cure COVID-19.

The novel coronavirus 2019 (COVID-19) pandemic is rapidly advancing despite public health measures. Pharmaceutical prophylaxis is an established approach to potentially control infectious diseases and is one solution to the urgent public health challenge posed by COVID-19. Screening and development of new vaccines and antivirals is expensive and time consuming while the repositioning of available drugs should receive priority attention as well as international government and agency support. Here we propose an old drug chloroquine (CQ) to be urgently repositioned as an ideal antiviral prophylactic against COVID-19. CQ has ability to block viral attachment and entry to host cells. Its proven clinical efficacy against a variety of viruses including COVID-19 and its current deployment in COVID-19 therapeutic trials strengthens its potential candidacy as a prophylactic. Furthermore, CQ has a long safety record, is inexpensive and widely available. Here we reviewed CQ's antiviral mechanisms, its laboratory efficacy activity against COVID-19, as well as CQ's pharmacokinetics in its established use against malaria and autoimmune diseases to recommend safe and potentially efficacious dose regimens for protection against COVID-19: a pre-exposure prophylaxis of 250-500mg daily and post-exposure prophylaxis at 8mg/kg/day for 3 days. We recommend further urgent research on CQ for COVID-19 prevention and urge that the above regimens be investigated in parallel with mass deployment by relevant agencies in attempts to contain the pandemic without unnecessary regulatory delays as benefits far outweigh risks or costs.

The appearance of the novel betacoronavirus 2019-nCoV represents a major threat to human health, and its diffusion around the world is predicted to have dramatic economic consequences. The knowledge of the 3D structures of 2019-nCoV proteins can facilitate the development of diagnostic and therapeutic molecules. Herein, we apply our energy-based method for the prediction of potential epitopes on viral proteins to design peptide-based molecules that can subsequently be used in diagnostic and therapeutic applications. We discuss these aspects in the paper.The designs have not been tested. Our aim is to share information that can be useful in the development of novel biomolecules with potential interesting activities against 2019-nCoV.

Coronavirus disease 2019 (COVID-19) has been first appeared in Wuhan, China but its fast transmission, led to its widespread prevalence in various countries and make it a global concern. In addition, lack of a definitive treatment is another concern that needs to be attention. Researchers have come up with several options, which are not certain, but protease inhibitor and some antiviral agent are in the forefront. In this study a virtual screening procedure employing docking of different databases including 1615 FDA approved drugs was used to identify new potential small molecule inhibitors for protease protein of COVID-19. The docking result indicates that among all, simeprevir (Hepatitis C virus (HCV) NS3/4A protease inhibitor) could fit well to the binding pocket of protease and because of some other positive features including ADME profile, might be a helpful treatment option for COVID-19.

A novel coronavirus strain (severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) first appeared in December 2019 and can cause acute respiratory distress syndrome and death. However, there are only limited therapy choices and no vaccine for SARS-CoV-2 is currently available. Here we report about a case of a SARS-CoV-2 caused pneumonia successfully treated with thalidomide. Thalidomide is an immunomodulatory and anti-inflammatory agent and was combined with a low-dose glucocorticoid. We suggest, that the effects of thalidomide might be related to regulating immunity, inhibiting the inflammatory cytokine surge, alleviating anxiety to reduce oxygen consumption, relieving vomit and lung exudation.

Vaccines are crucial for controlling the COVID-19 pandemic, and booster doses are becoming increasingly important. This study aimed to assess the efficacy of the ChAdOx1 nCoV-19 vaccine from AstraZeneca as a third dose in healthcare workers at different time intervals (one, three, and six months). Two methods to measure immune response—ELISA (EUROIMMUN Medizinische Labordiagnostika AG, Luebeck, Germany) and ELISpot (Mabtech AB, Macka Strand, Sweden)—were used. A total of 170 participants were included in the study. The results showed that while IgG levels decreased at six months compared to levels at one and three months, they were still significantly higher than the baseline. Furthermore, neutralizing levels at three and six months after the third dose were not significantly different. These findings suggest that the immune response induced by the vaccine is robust and effective for several months. These results have significant implications for public health policymakers, as they provide strong support for booster vaccinations. The ChAdOx1 nCoV-19 vaccine appears to be a reliable option for preventing the spread of COVID-19, and this study provides valuable information for healthcare workers and policymakers in managing the pandemic.

Patients with COVID-19 often experience significant cardiovascular complications, including heart failure, myocarditis, and acute coronary syndrome. We present the case of a male patient with severe COVID-19 pneumonia, complicated with inferior ST-segment elevation myocardial infarction (STEMI), which was attributed to spontaneous coronary artery dissection (SCAD). We also make a review of the literature on case reports of patients with COVID-19 and acute myocardial infarction due to SCAD. Through these clinical cases, a potential correlation between SCAD and COVID-19 infection is implied. Endothelial dysfunction, thrombotic complications and disturbance of the vascular tone are established COVID-19 sequelae, triggered either by direct viral injury or mediated by the cytokines’ storm. These abnormalities in the coronary vasculature and the vasa vasorum could result in SCAD. Moreover, disturbances of the vascular tone can cause coronary vasospasm, a reported precipitant of SCAD. Thus, SCAD should be considered in COVID-19 patients with acute coronary syndrome (ACS), and in the case of STEMI, an early angiographic evaluation, if feasible, rather than thrombolysis performed, to avoid potential adverse events of the latter in the setting of SCAD.

The transcriptional response of human blood leukocytes to SARS-CoV-2 infection was investigated focusing on the differences between mild and severe cases and between age subgroups. Weighted gene co-expression network analysis and comparative gene expression analysis were used. Three transcriptional modules positively associated with the traits of interest and their respective high hierarchy genes were identified. Enrichment analyses showed that the yellow module, associated with severe cases and older patients, had an overrepresentation of genes involved in inflammatory and innate immune responses, and neutrophil activation. The magenta and black modules, associated with disease severity and younger patients, contained genes related to innate immunity and inflammation and genes that regulate those responses. Subnetworks for these modules were constructed using genes enriched for innate immunity, inflammation, immunoregulation and differentially expressed genes (severe vs. mild). Their analysis evidenced that immunoregulatory functions are more activated in the modules associated with younger patients, what may help to explain the better disease course and faster recovery observed in younger COVID-19 patients. Comparative gene expression analysis between severe and mild groups, followed by gene enrichment and normalized gene expression analyses, revelated a set of 23 potential biomarkers for COVID-19 severity, of which 13 are newly described.

Background: The incidences of COVID-19 related suicide among adolescents and youths have been reported across the world. There is no cumulative study focusing on nature, patterns, and causative factors that lead to the present investigation. Methods: A purposive sampling of google news between 15 February to 6 July was performed. After excluding duplicate reports, the final list comprised a total of 37-suicide cases across 11 countries. Results: More male suicides were reported (21-cases, i.e., 56.76%), and the mean age of the total victims was 16.6±2.7 years (out of a total of 29-cases). About two-thirds of the suicides were from three countries named India (11-cases), United Kingdom (8-cases), and the USA (6-cases). Out of 23-student victims, 14 were school-going students. Hanging was the most common suicide method accounting in 51.4% of cases. The most common suicide causalities were related to mental sufferings such as depression, loneliness, psychological distress, etc., whereas either online schooling or overwhelming academic distress was placed as the second most risk factors followed by TikTok addiction-related psychological distress, and tested with COVID-19. Conclusion: The finding of the temporal distribution of suicides concerning lockdowns may help in exploring and evolving public measures to prevent/decrease pandemic-related suicides in young people.

Macrophage-derived chemokine belongs to the CC subfamily. It is produced by dendritic cells (DCs) and macrophages with or without external stimulation. We have previously shown a statistically significant depletion of MDC/CCL22 concentrations in a number of studies concerning COVID-19. These shifts in concentrations demonstrated stability unrelated to the SARS-CoV-2 genetic variant and remained noticeable even in convalescent patients. In this work, we analyze MDC/CCL22 dynamics in various diseases, including those that manifest with inflammation in lung tissue. In addition, we provide our hypothesis on such a decrease in MDC/CCL22 concentrations in COVID-19. If its secretion by producer cells is unperturbed, then it is possible for viral products to bind to this chemokine and to block its functional activity. There is, however, another possible explanation directly linked to depletion in DC subpopulations and the inhibition of their function. We also discuss MDC/CCL22's role in the immunology of novel coronavirus infection, based on both our own data and other studies.