The measures for tackling the COVID-19 may shrink the global GDP by approximately 6% in 2020, the deepest post-war recession. As a result, the global energy demand declined by 3.8% in the first quarter of 2020. Concerning fossil fuels, this conjuncture reduced the demand drastically and collapsed the prices to historic levels. Despite the general market disruptions, renewable energy sources (RES) seem to be more resilient to the crisis because they are the only sources that will grow in demand in 2020, driven by priority dispatch. The RES´s significant growth in cumulative installed capacity in the last two decades and the significant cost reductions of RES and energy storage technologies are positive signs towards better market conditions for the global energy transition. Currently, the crisis is seen by international agencies and transition scholars as an opportunity to advance a renewable-based energy transformation. Nevertheless, this article aims at caution about another possibility: if societal changes are not urgently implemented, the crisis may weaken the global energy transition. This article examines this last possibility from a three-level perspective: 1) post-COVID economic recovery, 2) low oil and natural gas prices and competitiveness of alternative sources and, 3) reorganization of the world energy market and the OPEC+. This paper exists to stimulate debate.

The world is currently facing a serious pandemic of coronavirus disease 2019 (COVID-19) which started in Wuhan, China, and was then transmitted rapidly to other countries. Countries applied different methods and procedures in an attempt to prevent or reduce and/or control the incidence of cases and manage existing ones. This paper discusses the methods and procedures applied by Kuwait to control this epidemic, and how effective they have been. The State of Kuwait followed WHO, European CDC, US CDC, and/or other countries’ institutional guidelines, and is still working on containing the disease, given the rising number of cases among Kuwaitis returning from affected areas such as the UK and USA, and migrant workers who bear the highest burden, given their cramped living conditions.

The semi-logarithmic plot of the cumulative number of cases of epidemics resembles the response of a first-order systems for a step load. This similarity was utilized to develop a first order model that can be used for extracting information about the dynamics of infectious disease epidemics. The developed model was validated using COVID-19 data of China. It was also heuristically fitted to other 13 countries. Obtained results indicated that the model can reliably forecasts the number of infected person, epidemic growth speed towards steady-state condition (process time constant, T), and time to reach steady-state condition (4T). The developed model will help public health authorities in developing more effective control strategies of epidemics.

Herd immunity happens when a relatively large proportion of a population becomes infected by an agent, subsequently recovers, and attains immunity against the same agent. That proportion thus indirectly protects the naïve population by preventing the spread of the infection. Herd immunity has been suggested to interrupt and control the COVID-19 pandemic. However, relying on establishing herd immunity can be catastrophic considering the virulence and lethality of SARS-CoV-2. Meanwhile our understanding of the pathogenesis, case-fatality rate, transmission routes, and antiviral therapy for COVID-19 remains limited now. Interrupting or slowing the COVID-19 transmission seems more opportune than vaccination, antiviral therapy, or herd immunity, all of which will take some time to yield. Thus, social distancing, face-masking, and hygiene are the most appropriate immediate countermeasures. Because the social fabrics, economic implications, and local demands of various nations are unique, early relaxation of restrictions may seem hasty particularly when fatality rates are high, or when the healthcare systems could be inadequate or become inundated. Conclusively, avoiding any overwhelmingly risky approach in fighting the pandemic is prudent.

Various studies indicate that vaccination, especially with pneumococcal vaccines, protects against symptomatic cases of SARS-CoV-2 infection and death. This paper explores the possibility that pneumococcal vaccines in particular, but perhaps other vaccines as well, contain antigens that might be cross-reactive with SARS-CoV-2 antigens. Comparison of the glycosylation structures of SARS-CoV-2 with the polysaccharide structures of pneumococcal vaccines yielded no obvious similarities. However, while pneumococcal vaccines are primarily composed of capsular polysaccharides, some are conjugated to CRM197, a modified diphtheria toxin, and all contain about three percent protein contaminants, including the pneumococcal surface proteins PsaA, PspA and probably PspC. All of these proteins have very high degrees of similarity, using very stringent criteria, with several SARS-CoV-2 proteins including the spike protein, membrane protein and replicase 1a. CRM197 is also present in Hib and meningitis vaccines. Equivalent similarities were found at lower rates, or were completely absent, among the proteins in diphtheria, tetanus, pertussis, measles, mumps, rubella, and poliovirus vaccines. Notably, PspA and PspC are highly antigenic and new pneumococcal vaccines based on them are currently in human clinical trials so that their effectiveness against SARS-CoV-2 disease is easily testable.

The widely spread CoronaVirus Disease (COVID)- 19 is one of the worst infectious disease outbreaks in history and has become an emergency of primary international concern. As the pandemic evolves, academic communities have been actively involved in various capacities, including accurate epidemic estimation, fast clinical diagnosis, policy effectiveness evaluation and development of contract tracing technologies. There are more than 23,000 academic papers on the COVID-19 outbreak, and this number is doubling every 20 days while the pandemic is still on-going [1]. The literature, however, at its early stage, lacks a comprehensive survey from a data analytics perspective. In this paper, we review the latest models for analyzing COVID19 related data, conduct post-publication model evaluations and cross-model comparisons, and collect data sources from different projects.

During the current COVID-19 pandemic caused by SARS-CoV-2, clinicians and scientists are working assiduously to unravel its pathophysiology and find effective treatments. An impressive number of papers has been published on SARS-CoV-2, exposing the complexity of the disease, the tendency of scientists to form hypotheses within their area of expertise, and the lack of orchestration of research. Hypotheses and research findings mainly complement each other, though sometimes controversies can be discerned among various theories and study results. Our overview aims to portray the ‘big picture’ of COVID-19, visualising the interwovenness of different pathophysiological pathways, with a focus on cytokine-induced pathology, the sequelae of ACE2 downregulation, and thrombosis associated with microvascular injury. It aids in overseeing the effects of repurposed drugs on intended targets, but also alerts to the (adverse) effects on interacting pathways. The overview shows how comorbidities probably increase susceptibility to (severe) COVID-19 and provides the possible pathophysiological origin of signs, symptoms, and biochemical abnormalities.

COVID-19 is a pandemic with no cure. There is an urgent need for low-cost interventions. Macroclimate work through affecting microclimate. In many situations, man-made microclimate, such as air conditioning, may override the effect of natural macroclimate in determining SARS-CoV-2 pathogenicity. Ambient temperature (AT) has been roughly associated to SARS-CoV-2 transmission. To translate into a feasible practice in controlling COVID-19 pandemic, in-depth and implementable knowledge of AT role in SARS-CoV-2 transmission should be unveiled. This study aimed to determine if there is a ‘safe’ temperature that is comfortable to human beings while significantly inhibitory for SARS-CoV-2 pathogenicity. Data on monthly new deaths or new cases per million population (MDPM or MCPM) and monthly cumulated days with more cases than the previous day (DI) from March 2 to June 30, 2020 were collected from all 118 countries with population over five million. Monthly average AT negatively correlated with the transmission parameters. A significant decrease in transmission was observed when AT reached above 20 ºC. Monthly average (not average high) AT of countries with MDPM <2, MCPM<10, or DI<=7 was found to be between 24.54 and 26.89 ºC (25.18 ºC on average) with average standard error of 4.81. Thus, average AT <20, 20-25, >25 ºC were considered as high, medium, and low risk AT. Furthermore, MDPM in countries with AT <20 ºC were 80.93, 50.23, 13.52, and 5.05 times of those in countries with AT >25 ºC in March, April, May, and June, respectively. MDPM low-risk rates (<2) in countries with AT >25 ºC were 100, 83.33, 52.73, and 52.46%, respectively. In countries with AT <20 ºC, the trends were opposite. Setting indoor temperature to 25 ºC could decrease the need of social distancing for containing SARS-CoV-2 transmission. Ventilation and sanitizing the air with ultraviolet light in nonbusiness hours may be additionally effective. Cooling indoor temperature too low may be a reason of COVID-19 outbreak in some high AT countries. Authorities and the general population can evaluate COVID-19 risk level and manipulate microclimate to reduce the risk anywhere anytime based on local day average AT.

Since there is no vaccine or regulatory approved therapy available for treatment of SARS-CoV-2 infection, the medical need to prevent the transition of a mild into the severe COVID-19 stage of infection is of outmost importance. Among several drug candidates, Chloroquine (CQN) and Hydroxy-Chloroquine (H-CQN) have been tested most intensively. However, the therapeutic effect of H-CQN and CQN has been discussed controversially in the light of severe side effects. Originally, H-CQN descended from the natural substance Quinine, a medicinal product used since the Middle Ages and is now regulatory approved for various indications. We hypothesized that Quinine also exerts anti-SARS-CoV-2 activity. First, virus production in Vero B4 cells was analyzed by Western blot, showing that Quinine exerts antiviral activity against SARS-CoV-2 that at 10 µM was even stronger than that of H-CQN or CQN. Second, fluorescence end-point and time lapse analysis of SARS-CoV-2-mNeonGreen-infected Caco-2 cells could confirm a similar antiviral effect of Quinine in a human-derived cell line. Thereby, our in vitro studies revealed, that the antiviral effect appears to be specific, since in Vero cells Quinine impacted cell viability at approximately 50-fold higher concentration, while the therapeutic window of H-CQN and CQN was approximately 10-fold lower. In Caco-2 cells no toxic effect was observed while complete block of infection occurred between 50 and 100 µM at high MOIs. In conclusion, our data indicate that Quinine would have the potential of a well tolerable and widely used treatment option for SARS-CoV-2 infections, with a predictable and significantly better toxicological profile when compared to H-CQN or CQN.

Objective: To describe outcomes of patients with coronavirus disease 2019 (COVID-19) in the outpatient setting after early treatment with zinc, low dose hydroxychloroquine, and azithromycin (the triple therapy) dependent on risk stratification. Design: Retrospective case series study. Setting: General practice. Participants: 141 COVID-19 patients with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in the year 2020. Main Outcome Measures: Risk-stratified treatment decision, rate of hospitalization and all-cause death. Results: Of 335 positively PCR-tested COVID-19 patients, 127 were treated with the triple therapy. 104 of 127 met the defined risk stratification criteria and were included in the analysis. In addition, 37 treated and eligible patients who were confirmed by IgG tests were included in the treatment group (total N=141). 208 of the 335 patients did not meet the risk stratification criteria and were not treated. After 4 days (median, IQR 3-6, available for N=66/141) of onset of symptoms, 141 patients (median age 58 years, IQR 40-67; 73% male) got a prescription for the triple therapy for 5 days. Independent public reference data from 377 confirmed COVID-19 patients of the same community were used as untreated control. 4 of 141 treated patients (2.8%) were hospitalized, which was significantly less (p<0.001) compared with 58 of 377 untreated patients (15.4%) (odds ratio 0.16, 95% CI 0.06-0.5). Therefore, the odds of hospitalization of treated patients were 84% less than in the untreated group. One patient (0.7%) died in the treatment group versus 13 patients (3.5%) in the untreated group (odds ratio 0.2, 95% CI 0.03-1.5; p=0.16). There were no cardiac side effects. Conclusions: Risk stratification-based treatment of COVID-19 outpatients as early as possible after symptom onset with the used triple therapy, including the combination of zinc with low dose hydroxychloroquine, was associated with significantly less hospitalizations and 5 times less all-cause deaths.

As the coronavirus disease 2019 (COVID-19), which is caused by the novel SARS-CoV-2, continues to spread rapidly around the world, there is a need for well validated serological assays that allow the detection of viral specific antibody responses in COVID-19 patients or recovered individuals. In this study, we established and used multiple indirect Enzyme Linked Immunosorbent Assay (ELISA)-based serological assays to study the antibody response in COVID-19 patients. In order to validate the assays we determined the cut off values, sensitivity and specificity of the assays using sera collected from pre-pandemic healthy controls, COVID-19 patients at different time points after disease-onset, and seropositive sera to other human coronaviruses. The developed SARS-CoV-2 S1 subunit of the spike glycoprotein and nucleocapsid (N)-based ELISAs not only showed high specificity and sensitivity but also did not show any cross-reactivity with other CoVs. We also show that all RT-PCR confirmed COVID-19 patients tested in our study developed both virus specific IgM and IgG antibodies as early as week one after disease onset. Our data also suggest that the inclusion of both S1 and N in serological testing would capture as many potential SARS-CoV-2 positive cases as possible than using any of them alone. This is specifically important for tracing contacts and cases and conducting large-scale epidemiological studies to understand the true extent of virus spread in populations.

The main manifestation of new coronavirus disease 2019 (COVID-19) is respiratory disease. The new coronavirus (SARS-CoV-2) attacks the lungs and may result in severe acute respiratory syndrome. In such cases, the infected person has difficulty breathing, which impairs oxygen uptake in the body. If pneumonia or another respiratory illness develops, and the host immune system is unable to combat SARS-CoV-2, the infected person may eventually die. Meanwhile, reports on unexpected symptoms in organs other than the nasal cavity, throat, and lungs are emerging. To elucidate the causes of such symptoms, we analyzed the expression status of angiotensin-converting enzyme 2 (ACE2), the host receptor used by SARS-CoV-2, in various tissues. This study confirmed that alveolar macrophages appear to be involved in pneumonitis and thrombus formation. In this report, we introduce some new symptoms.

The main goal of this article is to demonstrate the impact of environmental data on the spreading of Covid-19. In this research, data has been collected from 70 cities/provinces that are affected by Covid-19. Here, environmental data refers to temperatures, humidity and population density in each of these cities/provinces. This data has been analyzed using statistical models such as Poisson, Quasi-Poisson and negative Binomial. It is found that a negative Binomial regression model is the best fit for our data. Our results reveal that average high temperature is the vital factor to slow down the spread of Covid-19. In addition, higher population density found to be an important factor for the quick spreading of Covid-19 where it is quite impossible to maintain the social distance and the virus can spread easily.

Background: The healthcare workers are exposed to dangerous pathogen agents during the outbreak of the new coronavirus COVID-19. To minimize the risk of becoming infected by this virus, healthcare workers need to wear the most appropriate personal protective equipment (PPE). Objective: The objective of this study was to analyze the guidelines that the World Health Organization (WHO) and the Centers for the Disease Control and Prevention (CDC) recommend for the rational use of EPP to protect healthcare workers against the novel coronavirus COVID-19.Methodology: To learn how to effectively protect healthcare workers against the COVID-19, a detailed analysis and comparison of the WHO and CDC guidelines related to the proper use of personal protection equipment (PPE) in different healthcare settings was carried out. Results: The results of this study based on an analysis of PPE recommended by the World Health Organization (WHO) and the Centers for the Disease Control and Prevention (CDC) indicated that the safety and protection of healthcare workers can be maximized if the guidelines suggested by these institutions are followed. In general, the WHO and CDC recommendations based on medical practices are similar, and depending on the healthcare activities and settings where the healthcare workers perform their work, suggest wearing medical/surgical facemasks, respirators, googles and face shields (eye protection), gloves, gowns and aprons. Conclusions: The protection and safety of the healthcare workers can be maximized during the outbreak of COVID-19 by following the WHO and CDC recommendations described in this study. The general guidelines offered by these institutions are similar and based on medical practices.

This paper is an attempt to present a COVID-19 prediction model for India. Lockdown plays an important role in the arrest of community spread of the disease. This was evident from the study of other countries such as Russia, Belgium and Germany, where peak cases were recorded within a month of the imposition of lockdown, that it showed an immediate positive effect. However, in India, even after 65 days of lockdown, there is no decrease in the number of daily new cases reported. There were many models prepared for India and almost all of them were proven wrong by the increase in the number of cases. The model in this paper is prepared using the COVID-19 trend in other countries, population density and the pandemic bell curve. Based on the available data until 24^th May 2020, two scenarios have been presented. In one, the peak shall be obtained when the number of daily new cases per million reaches 190 and in the second when the daily new cases per million reach 724. One model predicts the number of cases to reach 1 million by mid-July 2020. The other model predicts the number of cases to peak by mid-July with the total cases reaching 20 million. The predicted cases were compared with the actual cases recorded for the period 25^th May to 11^th June 2020. It was observed that the actual values matched quite reasonably with the predicted values.

Coronavirus, also known as COVID-19, has been declared a pandemic by the World Health Organization (WHO). At the time of conducting this study, it had recorded over 1.6 million cases while more than 105,000 have died due to it, with these figures rising on a daily basis across the globe. The burden of this highly contagious respiratory disease is that it presents itself in both symptomatic and asymptomatic patterns in those already infected, thereby leading to an exponential rise in the number of contractions of the disease and fatalities. It is therefore crucial to expedite the process of early detection and diagnosis of the disease across the world. The case-based reasoning (CBR) model is an effective paradigm that allows for the utilization of cases’ specific knowledge previously experienced, concrete problem situations or specific patient cases for solving new cases. This study therefore aims to leverage the very rich database of cases of COVID-19 to solve new cases. The approach adopted in this study employs the use of an improved CBR model for state-of-the-art reasoning task in classification of suspected cases of Covid19. The CBR model leverages on a novel feature selection and semantic-based mathematical model proposed in this study for case similarity computation. An initial population of the archive was achieved with 68 cases obtained from the Italian Society of Medical and Interventional Radiology (SIRM) repository. Results obtained revealed that the proposed approach in this study successfully classified suspected cases into their categories at an accuracy of 97.10%. The study found that the proposed model can support physicians to easily diagnose suspected cases of Covid19 base on their medical records without subjecting the specimen to laboratory test. As a result, there will be a global minimization of contagion rate occasioned by slow testing and as well reduce false positive rates of diagnosed cases as observed in some parts of the globe.

The role of innate immunity in neutralization of viral infections (including COVID-19) and forming long-lasting and specific immune memory is considered. It is assumed that antiviral protection is generated by the mechanism of RNA interference (RNAi) and is based on the presence of specific viral patterns in the DNA library of the host cells.

The emergence of novel coronavirus (SARS-CoV-2) in marked as the highest pathogenic coronavirus that has crossed from the hosts to the human population in the twenty-first century. The spreading of COVID-19 in different chinese cities and around the world is travel-related viral spread with the unprecedented nosocomial outbreaks. It has also shown with high case-fatality rates, indeed to urgent prophylactic and therapeutic settings. Scientific advancements of the SARS-CoV-2 pandemic allowed for rapid progress to understand the epidemiology and pathogenesis of SARS-CoV-2. This review highlights the the genomic structure of SARS-CoV-2 with the proposed roles of genotype and phenotype of SARS-CoV-2 in pathogenesis and discuss recent results supporting treatment strategies of COVID-19 with a special focus on how these new insights may facilitate rational development of SARS-CoV-2 for targeted therapies in the future.

A novel coronavirus (2019-nCoV) responsible for a severe acute respiratory disorder (SARS-CoV-2) in humans, with its epicentre in Wuhan, China emerged in December 2019. This coronavirus, by far, has hit >200 countries, affecting 7 million worldwide accounting 11% death of the affected population. The transmission is majorly caused by human-to-human contact and, through fomite. In view of the increasing number of COVID-19 cases and the absence of definitive treatment or vaccinations, WHO has deemed the viral infection a pandemic of international concern. In such grave situations, there is a need for expanding the health sector workforce, government and police workforce, sanitation and prevention strategies. The current article describes the virology aspect, control of COVID-19 and revisits the various treatment options available at present this deadly infection. Epidemiology of COVID-19 is also discussed to further understand the pandemic status of India. The article also discusses implicating quarantine or social distancing, and in extreme cases, lockdown or alternative approaches such as herd or indirect immunity, as a measure to control the pandemic. Lockdown or social distancing will give rise to economic, emotional, political and social downfall in the country. It is estimated that a lockdown period will set back the country, possibly, by $240 billion, yet it stands unavoidable in the spread of control of infection. Thus, policymakers should strategize economic revival depending upon the best possible data and critical understanding.

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), mainly affects the respiratory system with some patients rapidly progressing to acute respiratory distress syndrome (ARDS). The most common symptoms of the patients are fever, cough, dyspnea, myalgia, and fatigue. Nasopharyngeal and oropharyngeal swab specimens tested by real-time reverse transcription-polymerase chain reaction (RT-PCR) are the most commonly used methods to diagnose COVID-19. Herein, we investigate and discuss a young case of COVID-19, without any pre-existing medical conditions, whose both nasopharyngeal and oropharyngeal swab tests of SARS-CoV-2 were negative in the prodromal phase. However, after three days, with severe dyspnea and rapidly progressed acute respiratory distress syndrome (ARDS), the case was identified as infected by COVID-19 by testing bronchoalveolar lavage fluid (BALF). The patient was intubated in the intensive care unit (ICU) but expired on the fourth day. This case shows the importance of active and accurate monitoring of the patients showing COVID-19 symptoms. Although the BALF test has a higher exposure risk, it is considered more accurate and recommended if performed by an expert operator.

Purpose: At a time of a pandemic SARS-CoV2 infection, and in the context of the multiorgan crosstalk widely accepted as a mechanism participating in the pathophysiology of all organs and systems, a correlation between adipose tissue, muscle and the immune system has been investigated. Physical Activity (PA) represents the first line of defence against metabolic diseases and infections, like SARS-CoV2, modulating several crucial functions such as inflammation and immune response. Conversely, obesity, type 2 diabetes and cardiovascular disorders – all correlated with PA - negatively impact on general health status, including susceptibility to infections. Here we review the complex interplay between type 2 diabetes, obesity, immune response, inflammation and viral infections, such as the current SARS-CoV2, focusing on the molecular mechanisms modulated by exercise. Methods: A comprehensive literature search was completed to identify joint biomarkers previously used to investigate acute and chronic exercise training. Results: we show that PA may counteract/mitigate viral adverse effects. We also describe data suggesting that vitamin D supplementation, frequently observed in practitioners of sport and regular exercise, could represent an additional positive factor in supporting COVID-19 with fighting against the virus. Conclusion: Altogether this evidence confirms that an active lifestyle and PA not only counteract dysmetabolic diseases but could also be effective for counteracting SARS-CoV2 infection. It is therefore essential to persuade people to keep active.

The COVID-19 pandemic has disrupted the supply chain for personal protective equipment (PPE) for medical professionals, including N95-type respiratory protective masks. To address this shortage, many have looked to the agility and accessibility of additive manufacturing (AM) systems to provide a democratized, decentralized solution to producing respirators with equivalent protection for last-resort measures. However, there are concerns about the viability and safety in deploying this localized download, print, and wear strategy. Several polymer-based AM processes produce porous parts, and inherent process variation between printers and materials also threaten the integrity of tolerances and seals within the printed respirator assembly. The goal of this paper is to quantitatively measure particle transmission through printed respirators of different designs, materials, and AM processes, and assess the viability of printed respirators as N95 equivalents. Results from this study show that respirators printed using desktop/industrial-scale fused filament fabrication processes and industrial-scale powder bed fusion processes have insufficient filtration efficiency at the size of the SARS-CoV-2 virus, even while assuming a perfect seal between the respirator and the user’s face. Almost all printed respirators provided <60% filtration efficiency at the 100-300 nm particle range. Only one respirator, printed on an industrial-scale fused filament fabrication system provided >90% efficiency as-printed. Post-processing procedures including cleaning, sealing surfaces, and reinforcing the filter cap seal generally improved performance, but no respirator sustained the filtration efficiency of an N95 respirator, which filters 95% of SARS-CoV-2 virus particles. Instead, the printed respirators showed similar performance to various cloth masks. While continued optimization of printing process parameters and design tolerances could be implemented to directly print respirators that provide the requisite 95% filtration efficiency, AM processes are not sufficiently reliable for widespread distribution and local production of N95-type respiratory protection without commensurate quality assurance processes in place. Certain design/printer/material combinations may provide sufficient protection for specific users, but the respirators should not be trusted without quantitative filtration efficiency testing. It is currently not advised to expect printed respirators originating from distributed designs to replicate performance across different printers and materials.

Within the micro and nano world, tiny membrane-enclosed bits of material are more or less free to move and act as communication tools within cells, between cells, between different tissues and between organisms in global environment. Based on the mechanism of membrane budding and vesiculation that includes all types of cells, in this review, we attempted to present a review on SARS-CoV-2 virus actions in compartments of different scales (cells and their surroundings, tissues, organisms and society). Interactions of the virus with cells on a molecular level, with neural system, endothelium, hematopoietic system, gastrointestinal system and genitourinary system. Transmission route between organisms and between mother and fetus are considered. Also, transmission of virus through contact with materials and with environment, the suggested measures to prevent contamination with the virus and to support the organism against the disease are given.

This study investigates the impact of global financial crisis and the present COVID-19 pandemic on daily and weekly Crude oil futures using four variants of ARMA-GARCH models: ARMA-sGARCH, ARMA-eGARCH, ARMA-TGARCH and ARMA- aPARCH with dummy variables We also investigated the persistence, half-life and backtesting of the models. This study therefore seeks to contribute to the body of literature on the impact of global financial crisis and the present COVID-19 pandemic on crude oil futures market. This investigation of the impact of global financial crisis and the COVID-19 on crude oil futures has not been much studied at present. We obtained and analyzed the daily and weekly crude oil futures from secondary sources. Daily crude oil futures used in this study covers the period from the 4th January 2000 to 27th April 2020 while the weekly crude oil futures covered from 2ndJanuary 2000 to 26th April 2020 . The global financial crisis period covered from 2nd July 2007 to 31st March 2009 and the current COVID-19 pandemic covered from 1st January 2020 to 27th April, 2020. The study used both student t and skewed student t innovations with AIC, goodness-of-test fit and backtesting to select the best model. Most of the estimated ARMA-GARCH models are supported by skewed student t distribution while most of the ARMA-GARCH models exhibited high persistence values in the presence of global financial crisis and the COVID-19 pandemic. In the overall, the estimated ARMA(1,0)-eGARCH(2,1) and ARMA(1,0)-eGARCH(2,2) model for daily crude oil futures and weekly crude oil futures respectively have been significantly impacted by the global financial crisis and the Present COVID-19 pandemic while the preferred estimated models also passed the goodness-of-test fit and backtesting.This study recommends shareholders and investors should think outside the box as crude oil futures tend to be affected by global financial crisis and COVID-19 pandemic while countries also that depend mostly on crude oil are encouraged to diversify their economy in other to survive and be sustained during financial and health crisis.

Over the course of the pandemic due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), multiple new clinical manifestations, as the consequence of the tropism of the virus, have been recognized. That includes now the neurological manifestations and conditions, such as headache, encephalitis, as well as olfactory and taste disorders. We present a series of ten cases of RT-PCR confirmed SARS-CoV-2 infected patients diagnosed with viral-associated olfactory and taste loss from four different countries.

The Coronavirus pandemic has created complex challenges and adverse circumstances. This research discovers public sentiment amidst problematic socioeconomic consequences of the lockdown, and explores ensuing four potential sentiment associated scenarios. The severity and brutality of COVID-19 have led to the development of extreme feelings, and emotional and mental healthcare challenges. This research identifies emotional consequences - the presence of extreme fear, confusion and volatile sentiments, mixed along with trust and anticipation. It is necessary to gauge dominant public sentiment trends for effective decisions and policies. This study analyzes public sentiment using Twitter Data, time-aligned to COVID-19, to identify dominant sentiment trends associated with the push to 'reopen' the economy. Present research uses textual analytics methodologies to analyze public sentiment support for two potential divergent scenarios - an early opening and a delayed opening, and consequences of each. Present research concludes on the basis of exploratory textual analytics and textual data visualization, that Tweets data from American Twitter users shows more trust sentiment support, than fear, for reopening the US economy. With additional validation, this could present a valuable time sensitive opportunity for state governments, the federal government, corporations and societal leaders to guide the nation into a successful new normal future.

Within the past several decades, the emergence of new viral diseases with severe health complications and mortality is evidence of an age-dependent, compromised bodily response to abrupt stress with concomitantly reduced immunity. The new severe acute respiratory syndrome coronavirus 2, SARS-CoV-2, causes coronavirus disease 2019 (COVID-19). It has increased morbidity and mortality in persons with underlying chronic diseases and those with a compromised immune system regardless of age and in older adults who are more likely to have these conditions. While SARS-CoV-2 is highly virulent, there is variability in the severity of the disease and its complications in humans. Severe pneumonia, acute respiratory distress syndrome, lung fibrosis, cardiovascular events, acute kidney injury, stroke, hospitalization, and mortality have been reported that result from pathogen–host interactions. Hallmarks of aging, interacting with one another, have been proposed to influence health span in older adults, possibly via mechanisms regulating the immune system. Here, we review the potential roles of the hallmarks of aging coupled with host–coronavirus interactions. Of these hallmarks, we focused on those that directly or indirectly interact with viral infections, including immunosenescence, inflammation and inflammasomes, adaptive immunosenescence, genomic instability, mitochondrial dysfunction, telomere attrition, epigenetic alterations, and impaired autophagy. These hallmarks likely contribute to the increased pathophysiological responses to SARS-CoV-2 among older adults and may play roles as an additive risk of accelerated biological aging even after recovery. We also briefly discuss the role of anti-aging drug candidates that require paramount attention in COVID-19 research.

Currently, with a large number of fatality rates, coronavirus disease-2019 (COVID-19) has emerged as a potential threat to human health worldwide. It has been well-known that severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) is responsible for COVID-19 and World Health Organization (WHO) proclaimed the contagious disease as a global pandemic. Researchers from different parts of the world amalgamate together inquest of remedies for this deadly virus. Recently, it has been demonstrated that the spike glycoprotein (SGP) of SARS-CoV-2 is the mediator behind the entrance into the host cells. Our group has comprehensibly analyzed the SGP of SARS-CoV-2 through multiple sequence analysis along with the phylogenetic analysis. Further, this research work predicted the most immunogenic epitopes for both B-cell and T-cell. Notably, we focused mainly on major histocompatibility complex (MHC) class I potential peptides and predicted two epitopes; WTAGAAAYY and GAAAYYVGY, that bind with the MHC class I alleles which are further validated by molecular docking analysis. Furthermore, this study also proposed that the selected epitopes were shown availability in a greater range of the population. Hence, our study comes up with a strong base for the implementation of designing novel vaccine candidates against SARS-CoV-2, however adequate laboratory works will need to be conducted for the appropriate application.

This study presents a prediction model based on Logistic Growth Curve to evaluate the effectiveness of Movement Control Order (MCO) on COVID-19 pandemic spread. The evaluation assesses and predicts the growth models. The estimated model is a forecast-based model that depended on partial data from the COVID-19 cases in Malaysia. The model is then studied together with the effectiveness of the three phases of MCO implemented in Malaysia. Evidence from this study suggests that results of the LGC prediction model match with the progress and effectiveness of the MCO to flatten the curve, thus helped to control the spike in number of active COVID-19 cases and spread of COVID-19 infection growth.

Background: Flattening the curve refers to community isolation measures that keep the daily number of disease cases at a manageable level for medical providers. Efforts to completely contain the COVID – 19 have failed. As there is currently no vaccine or specific medication to treat COVID-19, the only way to flatten the curve is through collective action of mitigation efforts. Objectives: The study was carried out with aim to study the effect of mitigation efforts in reducing the overall COVID -19 attack rate and flattening the curve of COVID-19 in Egypt. Methods: Secondary data in the situation reports of WHO, Worldometer and Egyptian MoHP Report about the COVID-19 epidemic in Egypt were analyzed till June 27, 2020. Survival analysis was carried out to determine the cumulative proportional survival of COVID-19. The Susceptible Infected Recovered (SIR) model was used to study the epidemic dynamics of COVID-19 pandemic. Results: In Egypt in the fourth week after exposure β was 0.17 and γ = 0.07. The fraction of infectious individuals will grow exponentially as the exponential growth rate was 0.10, with an epidemic time of 7 days. R in 22 ^nd June was 0.80 (less than one person infected) where β=0.21 and γ =0.26. There was reduction in the actual overall attack rate at 22^nd June of 96 % of its value without intervention with a cumulative proportional survival of 0.89. There was flattening of the curve. Conclusion and Recommendation: Mitigation efforts of Egypt had succeeded in flattening the curve of COVID-19 Pandemic. Even though, strengthening all the mitigation efforts to keep the exposure probability, as well as the transmission rate as low as possible is mandatory for containment of the epidemic.

Background: Outbreak of the Covid-19 is now an ongoing global health emergency. At the end of December 2019, the first infection was reported in Wuhan and the world did not pay attention to this extremely contaminated disease and plucked to react rapidly. The World is in an vulnerable state in disease spreading, facing a great loss of lives and socio-economic aspects also. That is why we have proposed a potential mathematical model with data analysis to predict and control the outcome of this pandemic. Methods: The model presented the epidemic dynamics of multiple compartments. We collected available online data of Spain. In primary step, we estimated the parameters using either the data analysis or reference papers. Then we did the data fitting analysis in comparison with the outcome of our mathematical results. The results of the system depended not only the parameters also on social consciousness. Results: It is found that disease progression in this model is determined by the basic reproductive ratio, $R_0$, the actual epidemic of $R_0$ and effective $R(t)$ of each day. If $R_0>1$, the number of latently infected individuals grows exponentially; endemic solution is stable while infection rate decays if $R_0<1$. The optimal control theory stated that vaccination and treatment strategies are highly effective for reducing both susceptible and infected population and to increase the recover rate high. In Spain, after state of alarm (quarantine) on 14 March 2020, reported cases increasing for 13 days only and from the 14th day, daily reported cases started to decline albeit with small fluctuation. Our proposed model approximates that the disease in Spain could be fully under control by after July 2020. Conclusion: Outbreak will be in control of health care system, reduce the death rate and will ensure social-economic stability.

This case study investigates the heart rate (HR) and heart rate variability (HRV) in a patient with coronavirus disease 2019 (COVID-19). We report the case of a 58-year old male who contracted COVID-19. During his disease, 24-hour Holter electrocardiography (ECG) was performed continuously. For comparison, his 24-hour Holter ECGs from the previous 10 years were available. In this patient, COVID-19 was associated with a decrease in HR and a paradoxical decline in HRV. An abrupt decline in HRV and a decrease in HR may signal the onset of COVID-19 before common symptoms such as dry cough or fever appear. In addition, HRV and HR measurements may help to evaluate the course of the disease.

According to the changed operative conditions due to lockdown and successive reopening a number of facts can be analysed. The main effects have been detected on: mobility, environment, social media and people flows. While in this first report only mobility, transport and environment are reported. The analysis performed identified a strong reduction of the mobility and transport activities, and in the pollutants. The mobility reduction has been assessed to be quite coherent with respect to what has been described by Google Global mobility report. On the other hand, in this paper a number of additional aspects have been put in evidence providing detailed aspects on mobility and parking that allowed us to better analyze the impact of the reopening on an eventual revamping of the infection. To this end, the collected data from the field have been compared from those of google and some considerations with respect to the Imperial college Report 20 have been derived. For the pollutant aspects, a relevant reduction on most of them has been measured and rationales are reported.

In the end of April nearly 100 cases of children aged between 6 month and 9 years with Kawasaki like disease were reported (mostly in Europe) probably linked to COVID-19. With the increasing awareness of this condition the number of cases reported is increasing worldwide. We aim to sum up the known data about this new entity based on published data (in a case report, a series of 8 cases and in newspapers and society statement) and using our knowledge of classical Kawasaki disease. It seems to be a post infectious disease with an onset between 2-4 weeks after the infection, probably in genetically predisposed children aged between 6 month to 17 years. A very rough estimation of incidence based on current data from Bergamo, Italy, and New York State and a lot assumption is between 0.016% (95% CI:0.013-0.02%) - 0.31% (95% CI: 0.2-0.47%) of infected children. Clinical signs overlaps with Kawasaki disease in some children, but another feature is prominent gastrointestinal manifestations. For the 9 detailed patients most had incomplete presentation for Kawasaki disease (with a mean 1.7 (+/-1.2) criteria per patient for the 5 non fever criterion) and only one had a classical form. In some cases, presentation is closer to toxic shock syndrome or isolated myocarditis. Persistent fever seems to be constant and biological exploration are consistent with inflammation (elevated CRP, ferritin and D-Dimers). Management is described as supportive and children seem to improve rapidly, but can require cardiac or respiratory support. In date of 11 may 2020 there is 4 deaths confirmed linked to these new entities (1 in UK and 3 in New York). Paediatricians and general practitioners need to be aware of these possible evolution following COVID-19 infection. However it seems to be rare and children are probably still spared from most morbidities and mortality linked to COVID-19 infection .There are need of published detailed cohorts to better delineate these entities.

The sudden pervasive of severe acute respiratory syndrome Covid-19 has been leading the universe into a prominent crisis. It has influenced each zone, for example, industrial area, horticultural zone, Public transportation, economic zone, and so on. So as to see how Covid-19 affected the globe, we conducted an investigation characterizing the effects of the pandemic over the world using Machine Learning (ML) method. Prediction is a typical data science exercise that helps the administration with function planning, objective setting, and anomaly detection. We propose an additive regression model with interpretable parameters that can be naturally balanced by experts with domain intuition about the time series. We focus on global data beginning from 22^nd January 2020, till 26^th April 2020 and performed dynamic map visualization of Covid-19 expansion globally by date wise and predicting the spread of virus on all countries and continents. The major advantages of this work include accurate analysis of country-wise as well as province/state-wise confirmed cases, recovered cases, deaths, prediction of pandemic viral attack and how far it is expanding globally.

Several articles have reported that the low number of COVID-19 cases in Japan is attributed to the small number of diagnostic RT-PCR tests performed. The criticism is based on the low number of the tests performed, and they suspected there would be more potential cases in Japan. The use of pre-test probability among tested subjects is proposed in order to evaluate of the sufficiency of test availability instead of the number of the tests. The pre-test probability means the average probability, i.e., ‘suspicion level’, of having coronavirus among the tested subject in a country. The higher pre-test probability is regarded as less sufficient opportunity of the tests, and the test availability could be evaluated by the pre-test probability. Thus, potential problems of underestimation of COVID-19 cases by insufficient amount of the test would be clear by using pre-test probability. The comparison of the pre-test probability could be replaced with that of the positive rate of the test because of the linear relationship between them under the assumption of common sensitivity and specificity. Japan shows the third lowest rate (8.6%), and is considered that the considerably sufficient number of the tests have been performed. In conclusion, the positive rate of the test as a surrogate index of the pre-test probability is useful to evaluate the sufficiency of test amount instead of the number of the tests performed. In present, the potential problem of underestimation by insufficient test availability would be less serious in Japan.

We hypothesize that the reason severe COVID-19 is closely linked to a limited number of conditions such as obesity, hypertension, older age and diabetes is that these conditions are characterized by a pro-inflammatory state in general and an angiotensin converting enzyme-1-bias in particular. We review recent evidence that this pro-inflammatory state can be reversed via regular exercise and a healthy diet. Studies are suggested that could test this hypothesis.

The new pandemic coronavirus disease 2019 (COVID-19) is a worldwide threatening health issue. Early progression of this disease starts in the lung airways with an exaggerated inflammation, triggered by the viral infection and characterized by a “cytokine storm” that can lead to lethal lung injuries. In the absence of an effective anti-viral molecule and until the formulation of a successful vaccine, anti-inflammatory drugs might offer a complementary tool for controlling the associated complications and thus decreasing the subsequent fatalities. Drug repurposing for several molecules has emerged as a rapid temporary solution for COVID-19. Among these drugs, Thalidomide, a historically emblematic controversial molecule that harbors an FDA approval for treating Erythema Nodosum Leprosum (ENL) and multiple myeloma (MM). Based on only one-case report of positive outcomes in a patient treated amongst others with Thalidomide, two clinical trials on the efficacy and safety of Thalidomide in treating severe respiratory complications in COVID-19 patients were registered. Conversely, the absence of any substantial, promising evidence on Thalidomide usage in that context along with the discontinued studies on the efficiency of this drug in similar pulmonary diseases might cause a significant obstacle for carrying on clinical studies. In this review, we will discuss the theoretical effectiveness of this drug in attenuating inflammatory complications that are encountered in patients with COVID-19 while pinpointing the lack of evidence that is needed to move forward with this drug.

Background: COVID-19 is a disease of the elderly as 95% of deaths related to COVID-19 occur in people over 60 years of age. Despite the urgent need for a preventive treatment there are currently no serious leads, other than the vaccination. Objective: To find a preventive treatment of COVID-19 in elderly patients. Design: Retrospective case-control study. Setting: Robertsau Geriatric Hospital of the University Hospitals of Strasbourg, France. Patients: 179 elderly patients who had been in contact with the SARS-CoV-2, of whom 89 had tested RT-PCR-positive (COVID-pos) for the virus and 90 had tested RT-PCR-negative (COVID-neg). Measurements: Treatments within 15 days prior to RT-PCR (including antihypertensive drugs, antipsychotics, antibiotics, nonsteroidal anti-inflammatory drugs, proton pump inhibitors (PPIs), paracetamol, anticoagulant, oral antidiabetics (OADs), corticosteroids, immunosuppressants), comorbidities, symptoms, laboratory values, and clinical outcome were all collected using the electronic patient record. Results: COVID-pos patients more frequently had a history of diabetes (P=.016) and alcoholism (P=.023), a lower leukocyte count (P=.014) and a higher mortality rate– 29.2% versus 14.4% – (P=.014) when compared to COVID-neg patients. Patients on PPIs were 2.3 times less likely (odds ratio [OR] = 0.4381, 95% confidence interval [CI] [0.2331, 0.8175], P=.0053) to develop COVID-19 infection, compared to those not on PPIs. No other treatment decreased or increased this risk. COVID-19 patients on antipsychotics (P=.0013) and OADs (P=.0166) were less likely to die. Limitations: retrospective study. Conclusion: PPIs treatment lowered the risk of development of COVID-19 infection, and antipsychotics and OADs decreased the risk of mortality in geriatric patients. If further studies confirm this finding, PPIs could be used preventatively in the elderly in this pandemic context. Moreover, OADS and antipsychotics should be tested in clinical trials.

Along with the Coronavirus pandemic, another crisis has manifested itself in the form of mass fear and panic phenomena, fuelled by incomplete and often inaccurate information. There is therefore a tremendous need to address and better understand COVID-19's informational crisis and gauge public sentiment, so that appropriate messaging and policy decisions can be implemented. In this research article, we identify public sentiment associated with the pandemic using Coronavirus specific Tweets and R statistical software, along with its sentiment analysis packages. We demonstrate insights into the progress of fear-sentiment over time as COVID-19 approached peak levels in the United States, using descriptive textual analytics supported by necessary textual data visualizations. Furthermore, we provide a methodological overview of two essential machine learning classification methods, in the context of textual analytics, and compare their effectiveness in classifying Coronavirus Tweets of varying lengths. We observe a strong classification accuracy of 91% for short Tweets, with the Naive Bayes method. We also observe that the logistic regression classification method provides a reasonable accuracy of 74% with shorter Tweets, and both methods showed relatively weaker performance for longer Tweets. This research provides insights into Coronavirus fear sentiment progression, and outlines associated methods, implications, limitations and opportunities.

Many governments particularly in Europe are designing social interventions for the first post COVID-19 emergency phase. Definition of a ‘best practice’ for restriction release is urgent. Although data uncertainty generate difficulties, we believe near term analysis must shift from attempting to understand the numerous ‘unknowns’ to the clarification and interpretation of the few ‘knowns’, to create stepping stones towards rapid evidence-based decision making.Here, open access data on COVID-19 severity in three European countries were analyzed. Spain’s data were more comprehensive than those from Italy and Germany. Overall, COVID-19 severity shows a remarkable nonlinear growth with age that is significantly higher in adult males. Hence, age-adaptive and gender-balanced social interventions might represent efficient repopulation options for public health policymakers. Furthermore, we urge wider governmental effort for open access to relevant data. Their analysis will allow consolidation of existing trends, validation of key observations and thus facilitation of timely decisions.

There is an urgent need to identify effective therapies for COVID-19. The SARS-CoV-2 host factor protease TMPRSS2 is required for viral entry and thus an attractive target for therapeutic intervention. In mouse, knockout of tmprss2 led to protection against SARS-CoV-1 with no deleterious phenotypes, and in human populations genetic loss of TMPRSS2 does not appear to be selected against. Here, we mined publicly available gene expression data to identify several compounds that down-regulate TMPRSS2. Recognizing the need for immediately available treatment options, we focused on FDA-approved drugs. We found 20 independent studies that implicate estrogenic and androgenic compounds as transcriptional modulators of TMPRSS2, suggesting these classes of drugs may be promising therapeutic candidates for clinical testing and observational studies of COVID-19. We also note that expression of TMPRSS2 is highly variable and skewed in humans, with a minority of individuals having extremely high expression. Combined with literature showing that inhibition of TMPRSS2 protease activity reduces SARS-CoV-2 viral entry in human cells, our results raise the hypothesis that modulation of TMPRSS2 expression is a promising therapeutic avenue for COVID-19.

After the increasing number of SARS-CoV-2 infections all over the world, researchers and clinicians are struggling to find a vaccine or innovative therapeutic strategies to treat this viral infection. The SARS-CoV infection that occurred in 2002, MERS and other more common infectious diseases such as HCV, led to the discovery of many RNA-based drugs. Among them, siRNAs and antisense LNAs have been demonstrated to have effective antiviral effects both in animal models and humans. Owing to the high genomic homology of SARS-CoV-2 and SARS-CoV (80-82%) the use of these molecules could be employed successfully also to target this emerging coronavirus. Trying to translate this approach to treat COVID-19, we analyzed the common structural features of viral 5’UTR regions that can be targeted by non-coding RNAs and we also identified miRNAs binding sites suitable for designing RNA-based drugs to be employed successfully against SARS-CoV-2.

The emergence of new type of viral pneumonia cases in China, on December 31, 2019; identified as the cause of human coronavirus, labeled as "COVID-19," took a heavy toll of death and reported cases of infected people all over the world, with the potential to spread widely and rapidly, achieved worldwide prominence but arose without the procurement guidance. There is an immediate need for active intervention and fast drug discovery against the 2019-nCoV outbreak. Herein, the study provides numerous candidates of drugs (either alone or integrated with another drugs) which could prove to be effective against 2019-nCoV, are under different stages of clinical trials. This review will offer rapid identification of a number of repurposable drugs and potential drug combinations targeting 2019-nCoV and preferentially allow the international research community to evaluate the findings, to validate the efficacy of the proposed drugs in prospective trials and to lead potential clinical practices.

The Bacillus Calmette-Guerin vaccine (BCG vaccine) designed to prevent tuberculosis in children has been shown to induce a trained immune response in the body to fight against bacteria as well as other parasites and viruses. This knowledge has been reciprocated to generate the idea that this vaccine can also offer protection against severe acute respiratory syndrome coronavirus-2 (SARS-COV-2). Some recent pre-print articles have highlighted that countries with mass BCG immunizations seems to have a lower incidence of coronavirus disease 2019 (COVID-19) compared to those without BCG immunization. There are yet no experimental proof of any such association and the world health organisation (WHO) is currently testing the theory with clinical trials on selected cohorts. Epidemiologists and other scientific experts has expressed both their hope and concern simultaneously regarding the success theory of BCG vaccination to prevent COVID-19. Though its still not verified in any way whether the BCG vaccination can actually prevent COVID-19 or not but we believe a thorough analytical research in this regard is indeed worth a shot.

Coronavirus disease 2019 (COVID-19) can lead to systemic coagulation activation and thrombotic complications. We investigated the incidence of objectively confirmed venous thromboembolism (VTE) in 198 hospitalized patients with COVID-19 in a single-center cohort study. Seventy-four patients (37%) were admitted to the intensive care unit (ICU). At time of data collection, 58 (29%) were still hospitalized and 14% had died. During a median follow-up of 5 days (IQR, 3-9), 33 patients (17%) were diagnosed with VTE of whom 22 (11%) had symptomatic VTE, despite routine thrombosis prophylaxis. The cumulative incidences of VTE at 7 and 14 days were 15% (95% CI, 9.3-22) and 34% (95% CI, 23-46), respectively. For symptomatic VTE, these were 11% (95% CI, 5.8-17) and 23% (95% CI, 14-33). VTE appeared to be associated with death (adjusted HR, 2.9; 95% CI, 1.02-8.0). The cumulative incidence of VTE was higher in the ICU (25% at 7 days 95% CI, 15-36, and 48% at 14 days, 95% CI, 33-61) than on the wards (any VTE and symptomatic VTE 6.5 % at 7 days (95% CI, 1.5-17) and 10% at 14 days (95% CI, 2.9-24)).The observed risk for VTE in COVID-19 is high, particularly in ICU patients, which should lead to a high level of clinical suspicion and low threshold for diagnostic imaging for DVT or PE. Future research should focus on optimal diagnostic and prophylactic strategies to prevent VTE and potentially improve survival.

SARS-CoV-2, the novel coronavirus behind COVID-19 pandemic is acquiring new mutations in its genome. Although some mutations provide benefits to the virus against human immune response, a number of them may result in their reduced pathogenicity and virulence. By analyzing more than 3000 high-coverage, complete genome sequences deposited in the GISAID database, here I report a unique 28881-28883:GGG>AAC trinucleotide-bloc mutation in the SARS-CoV-2 genome that results in two sub-strains, described here as SARS-CoV-2g (28881-28883:GGG genotype) and SARS-CoV-2a (28881-28883:AAC genotype). Computational analysis and literature review suggest that this bloc mutation would bring 203-204:RG(arginine-glycine)>KR(lysine-arginine) amino acid changes in the nucleocapsid (N) protein affecting the SR (serine-arginine)-rich motif of the protein, a critical region for the transcription of viral RNA and replication of the virus. Thus, 28881-28883:GGG>AAC bloc-mutation is expected to modulate the pathogenicity of the SARS-CoV-2. Remarkably, SARS-CoV-2g and SARS-CoV-2a strains can be linked with the heterogeneity of COVID-19 cases across different regions within and between countries by analyzing existing data. Sequence analysis suggests that severely affected cities, such as Milan, Lombardy, New York, Paris have the predominant presence of SARS-CoV-2g strains, whereas less affected places like Abruzzo, Lyon, Valencia have a relatively higher presence of SARS-CoV-2a, an indication that the latter strain may contribute to the reduced cases of COVID-19. A similar relationship is observed when Netherlands, Portugal are compared with Spain, France and Germany. These analyses suggest that the SARS-CoV-2 has already evolved into a less infective SARS-CoV-2a affecting COVID-19 cases in different regions. The time a country or region needs to acquire SARS-CoV-2a strains may be indicative to the time it would need to overcome the peak of the COVID-19 cases. To confirm these assumptions, prompt retrospective and prospective epidemiological studies should be conducted in different countries to understand the course of pathogenicity of the SARS-CoV-2a and SARS-CoV-2g. Potential drugs can be designed targeting 28881-28883 region of the N protein to modulate virus pathogenicity.

The Corona Virus Disease 2019 (COVID-19) outbreak is becoming pandemic with the highest mortality in people with associated comorbidities. These RNA viruses containing four structural proteins usually use spike protein to enter the host cell. It has been demonstrated that Angiotensin Converting Enzyme 2 (ACE2) ,as a part of renin-angiotensin-aldosterone system (RAAS), acts as a host receptor for the virus which is the main target of therapeutic approaches. However, medications acting on RAAS can lead to serious complications especially in people with diabetes and hypertension. To avoid this, other potential treatment modalities should be used in COVID-19 patients with associated comorbidities.

A novel and highly pathogenic coronavirus (2019-nCoV)-induced pneumonia spread worldwide in a short time. However, studies on the effects of 2019-nCoV on the male reproductive system are limited. The aim of this study is to describe the clinical characteristics of the male reproductive system of COVID-19 patients and to explore the presence of 2019-nCoV in semen. Retrospective, single-center case series of 112 male patients with confirmed COVID-19 who were admitted to Renmin Hospital of Wuhan University from January 2 to March 7, 2020. Demographic data, symptoms and signs related to the male reproductive system, throat swabs and semen samples were collected and analyzed. 2019-nCoV RNA measured in throat swab and semen samples. The organ distribution of ACE2 mRNA and protein in human tissue on The Human Protein Atlas portal and investigated immunohistochemistry (IHC) images of the testis. The HPA dataset revealed relatively high levels of ACE2 protein and RNA expression in the testis. A total of 3 severe COVID-19 patients (2.7%) presented with orchidoptosis, while no patients experienced other symptoms or signs related to the male reproductive system. The analysis of 2019-nCoV RNA in semen included 17 patients with fertility needs. Among these patients, 9 (52.9%) remained positive for 2019-nCoV according to throat swab analysis, and 8 (47.1%) became negative. In the semen 2019-nCoV analysis, all 17 patients were negative for the N gene and ORF1ab gene. In view of the potential impairment, long-term follow-up for male COVID-19 patients with fertility needs is of great significance.

Background: On Dec 19, 2019, the public health department of China reported that an outbreak of pneumonia was caused by a novel Coronavirus. The virulence of the new virus COVID-19 was much greater than either the SARs and MERSs viruses and on March 11, 2020, the World Health Department (WHO) declared a worldwide pandemic. Understanding the pathophysiology of virulence of the SARS-COV-2 virus is absolutely necessary for understanding the transmission, virulence factors, reduce risk factors, clinical presentation, predict outcomes of the disease and provide guidance for any current or future treatment protocols. Methodology: A comprehensive PubMed search was performed during December 20, 2019 and April 03, 2020, utilizing the words: Wuhan Virus, COVID-19, SARs coronavirus, ACE2, S-protein, virulence, clinical presentation, epidemiology, genome, treatment, structure, MERs, pathogenesis and/or pathology alone and in combination with other terms. Each paper was evaluated by three content experts for quality, reproducibility, credibility and reputation of the journal. Results: The SARS-COV-2 virus is much more virulent than either the SAR’s or MER’s virus and its ability to cause serious disease inversely corresponds to the person’s ability to produce T-cells which declines linearly with age. The ACE2 receptor binding site does not vary among different ethnic groups but do in ACE-2 expression levels. This variance in expression level may explain for different infectivity rates among men and women and predict and explain different susceptibilities to infection by different ethnic groups. Furthermore, by understanding the underlying pathophysiology one can explain and provide guidance to the clinical effectiveness of any treatment. Conclusions: The underlying pathophysiology of COVID-19 explains not only the virulence, and clinical presentation, but, explains at a molecular level the comorbidity risk factors such as hypertension, sex, and age. Ethnic and anatomic expression patterns of ACE-2 and associated pathophysiology suggests that Native Americans and Asians may be particularly susceptible to this disease.

COVID 19, a pandemic spread without any solid anti-viral antidote. Researchers worldwide are currently giving their best to make antidote for this virus with all available literatures and knowledge. Research carried out indicates sulfated polysaccharides (carrageenan) are selective inhibitors of several enveloped and non-enveloped viruses and act predominantly by inhibiting the binding or internalization of virus into the host cells. Polysaccharides produced from Porphyridium sp. are sulfated polysaccharides which are promising antiviral agents against respiratory viruses from the family of coronavirus. These biocompatible compounds can be used as a coating material on the sanitary items for COVID-19 prevention.

More than 1,000,000 confirmed cases of COVID-19 have been registered worldwide since the beginning of the pandemic in Wuhan on December 2019. The high mortality rate of COVID-19 is associated with age, gender and the presence of comorbidities. Biochemical data have shown that COVID-19 patients develop a local and systemic hyper-inflammatory response associated with poor outcome. Therefore, the understanding of the biological mechanisms underlying SARS-CoV-2-induced inflammation is a compelling need. Following this reasoning, here we will focus on the importance of the progressive age-related development of a pro-inflammatory state (aka inflamm-aging) in the understanding of the unbalanced inflammatory response against SARS-CoV-2 in aged people. In particular, we underpin the role of mitochondrial DNA and genomic DNA telomeric sequences in local and systemic mechanisms of inflammation. Indeed, the leakage of mtDNA out of its natural compartment (i.e. the mitochondrion), into the cytoplasm and in the extracellular environment is a powerful trigger of innate immunity and inflammation, as part of an evolutionary-conserved signaling mechanism of cellular damage (e.g. viral infection). High levels of circulating mtDNA are increased in aged people and set up as inflammatory markers of poor prognosis in intensive care unit patients. In turn, telomeric DNA, which can be released into the cytoplasm and in the extracellular environment upon cell damage, has been proven to exert potent anti-inflammatory activity. Since that aged people (particularly those affected by co-morbidity) are equipped with shortened telomeres, we posit that, in aged people affected by COVID-19 the release of mtDNA, coupled with insufficient telomeric DNA favors the onset of a detrimental inflammatory response. In this regard, we highlight that the mechanism of action of some currently used drugs, as well as potential new ones may be better understood under the light of the above-depicted theoretical framework thus explaining how studies on inflamm-aging may help to understand and combat COVID-19 pandemic.

Corona Virus Infectious Disease-2019 (COVID-19) outbreak originated recently at Wuhan, China in December 2019. It has already spread rapidly to more than 200 countries and has been declared a pandemic by WHO. It is caused by a beta-coronavirus named as SARS-CoV-2. There is no definitive cure, either drug or vaccine, to treat or prevent this viral disease. Recently, the crystal structure of the main protease M^pro has been determined. M^pro is responsible for the proteolytic maturation of the polyprotein essential for the viral replication and transcription, which makes it an important drug target. The discovery of new drug molecules may take years before getting to the clinics. So, considering urgency we performed molecular docking studies using FDA approved drugs to identify molecules that could potentially bind to the substrate-binding site and inhibit SARS-CoV-2 main protease (M^pro). We used the Glide module in Schrodinger software suite to perform molecular docking studies followed by MM-GBSA based energy calculations to score the hit molecules. Molecular docking and manual analysis suggest that several drugs may bind and potentially inhibit M^pro. We also performed molecular simulations studies for selected compounds to evaluate protein-drug interactions. Interestingly, we observed only one antiviral compound, Adefovir, in the top50 list of compounds. Considering bioavailability, lesser toxicity, route of administration some of the top-ranked drugs including lumefantrine (antimalarial), dipyridamole (coronary vasodilator), dihydroergotamine (used for treating migraine), hexoprenaline (anti- asthmatic), riboflavin (vitamin B2) and pantethine (vitamin B5) may be taken forward for further in vitro and in vivo experiments to investigate their therapeutic potential.

The new coronavirus is very likely to already exist in the complex system of human society, including the population and the surrounding environments. Therefore, the research focus of the origin of COVID-19 should be shifted from how wild animals spread it to humans to how it was triggered by complex natural, social, and living systems. We advocate three levels of attribution (i.e., the source of the virus), inducement (i.e., the incentive factors triggering the outbreak), and cause (i.e., the birth of the virus) to reveal the origin of COVID-19 from the shallower to the deeper. It not only meets the urgent needs of short-term prevention and control, but also provides technical weapons for the long-term fight against emerging viruses.

At the time of reception of this article (April 2, 2020), efforts to develop a specific vaccine against SARS-Cov-2, the causative agent of the coronavirus disease 2019 (COVID-19), had just begun trial phase 1, but full validation of this and other current developments is likely to take many more months to reach completion. The ongoing pandemic constitutes a major health burden of world proportions that is also having a devastating impact on whole economies worldwide, the knock-on effects of which could be catastrophic especially in poorer countries. Alternative measures to ameliorate the impact and hamper or minimally slow down disease progression are urgently called for. This review discusses past and currently evolving data on the etiological agent of the current pandemic, SARS-CoV-2, and its host cell receptors with a view to disclosing alternative drugs for palliative or therapeutic approaches. Firstly, SARS-CoV-2 exhibits marked tropism for cells that harbor the membrane-bound metalloprotease angiotensin-converting enzyme 2 (ACE2) at their plasmalemma, predominantly in cells lining the oral cavity, upper respiratory tract, and bronchoalveolar cells, making these epithelial mucosae the most likely viral receptor cell targets and entry routes. Secondly, the crystal structures of several coronavirus spike proteins in complex with their cell host target receptors, and of SARS-Cov-2 in complex with an inhibitor, are now available at atomic resolution through X-ray diffraction and cryo-electron microscopy studies. Thirdly, viral entry of other viruses has been successfully blocked by inhibiting viral endogenous proteases or clathrin/dynamin-dependent endocytosis, the same internalization pathway followed by ACE2 and some viruses. Fourthly, the target cell-surface receptor molecules and SARS-CoV-2 possess other putative sites for drugs potentially modulating receptor activity or virus processing. A multi-pronged pharmacological approach attacking more than one flank of the viral-receptor interactions is worth considering as a front-line strategy.

Aims: In late December 2019, early reports predicted the onset of a potential Coronavirus outbreak in china, given the estimate of a reproduction number for the 2019 Novel Coronavirus (COVID-19). Because of high ability of transmission and widespread prevalence, the mortality of COVID-19 infection is growing fast worldwide. Absent of an anti-COVID-19 has put scientists on the urge to repurpose already approved therapeutics or to find new active compounds against coronavirus. Here in this study, a set of computational approaches were performed in order to repurpose antivirals for dual inhibition of the frontier proteases involved in virus replication, papain-like protease (PLpro; corresponding to nsp3) and a main protease (Mpro), 3C‑like protease (3CLpro; corresponding to nsp5). Materials and Methods: In this regard, a rational virtual screening procedure including exhaustive docking techniques was performed for a database of 160 antiviral agents over 3CLpro and PLpro active sites of SARS-CoV-2. The compounds binding energies and interaction modes over 3CLpro and PLpro active sites were analyzed and ranked with the aid of free Gibbs binding energy. The most potent compounds, based on our filtering process, are then proposed as dual inhibitors of SARSC-CoV-2 proteases. Key findings: Accordingly, seven antiviral agents including two FDA approved (Nelfinavir, Valaganciclovir) and five investigational compounds (Merimepodib, Inarigivir, Remdesivir, Taribavirine and TAS106-106) are proposed as potential dual inhibitors of the enzymes necessary for RNA replication in which Remdesivir as well as Inagrivir have the highest binding affinity for both of the active sites. Significance: The mentioned drug proposed to inhibit both PLpro and 3CLpro enzymes with the aim of finding dual inhibitors of SARSC-CoV-2 proteases.

The 2019 novel coronavirus (previously 2019-nCoV) or coronavirus infectious disease 2019 (COVID-19) outbreak has been summarized as on March 29, 2020. COVID-19 is a highly transmittable and pathogenic viral infection caused by severe acute respiratory syndrome coronavirus 2 (SERS-CoV-2). The disease was first seen during an outbreak in Wuhan, China and continuous spreading from human to human around the sphere. The disease is uncontrolled and increasing the death toll through. The world is facing a global challenge to protect human lives caused by coronavirus outbreak. The number of infected patients is increasing day by day due to COVID-19 as a pandemic. The world health organization (WHO) has declared global public health emergency on January 30, 2020. The disease has been spread around 201 countries with total confirmed cases 634835 and death cases 29891 as on March 29, 2020. The goal of this review to summaries and update the clinical/medical features and suggestions for diagnosis of the COVID-19 as a pandemic. The discussion of the various therapeutic algorithms, risk, prevention and control based on the latest reports has been provided.

The spread of the global COVID-19 pandemic, the lack of specific treatment and the urgent situation requires use of all resources to remedy this scourge. In the present study, using molecular docking, we identify new probable inhibitors of COVID-19 by molecules from Nigella sativa L, which is highly reputed healing herb in North African societies and both Islamic and Christian traditions. The discovery of the M^pro protease structure in COVID-19 provides a great opportunity to identify potential drug candidates for treatment. Focusing on the main proteases in CoVs (3CL^pro/M^pro) (PDB ID 6LU7 and 2GTB); docking of compounds from Nigella Sativa and drugs under clinical test was performed using Molecular Operating Environment software (MOE). Nigelledine docked into 6LU7 active site gives energy complex about -6.29734373 Kcal/mol which is close to the energy score given by chloroquine (-6.2930522 Kcal/mol) and better than energy score given by hydroxychloroquine (-5.57386112 Kcal/mol) and favipiravir (-4.23310471 kcal/mol). Docking into 2GTB active site showed that α- Hederin gives energy score about-6.50204802 kcal/mol whcih is better energy score given by chloroquine (-6.20844936 kcal/mol), hydroxychloroquine (-5.51465893 kcal/mol)) and favipiravir (-4.12183571kcal/mol). Nigellidine and α- Hederin appeared to have the best potential to act as COVID-19 treatment. Further, researches are necessary to testify medicinal use of identified and to encourage preventive use of Nigella Sativa against coronavirus infection.

Introduction: The COVID-19 pandemic is a global crisis, the number of cases and deaths are on a steep incline. This article reviews the possible immunological mechanisms which underlie the disease pathogenesis by looking at the behaviour of previous coronaviruses not only in humans but also other mammals which possibly act as reservoir hosts. Observations: A key aspect of this coronavirus as well as the previous SARS CoV seems to be the importance of host immune response in the pathology and clinical severity of illness caused by them. A hyperactive innate immune state in combination with an exhausted adaptive immune response are possible determinants of severe illness. Conclusion: There is a possibility that the current SARS CoV 2 has immune evasive tactics similar to SARS CoV in its repertoire, since they share a 76% homology. These might have been learnt behaviour from long periods of persistence in their reservoir hosts and they may be the reason behind the dysregulated immune response evoked in humans. That in turn is highly likely to be one of the factors which govern disease severity. With this in mind we want to bring the medical community’s attention to a ‘hit early, hit hard’ intervention as a possible strategy to modify the course of the disease and bring down the numbers of severe sufferers.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known to cause 2019-coronavirus disease (COVID-19) pandemic is a zoonotic coronavirus and crosses species to infect human populations, where an efficient transmission of virus occurs human-to-human. Nationwide lockdown is being adopted to stop public transport, keep people at their homes and out of their work, and maintain social distancing. In turn, large geographic areas in the world (including China, Italy, Spain, and USA) has been almost halted. This temporary halt is significantly slashing down the air pollution (air pollutants and warming gases) in most cities across the world. This paper: (i) introduces both COVID-19 and air pollution; (ii) overviews the relation of air pollution with respiratory/lung diseases; (iii) compiles and highlights major data appeared in media and journals reporting lowering of air pollution in major cities those have been highly impacted by the COVID-19; and also (iv) lists the way forward in the present context. Because COVID-19 is an ongoing pandemic and currently far from over, strong conclusions could not be drawn with very limited data at present. The temporary slashed down global air pollution as a result of COVID-19 restrictions are expected to stimulate the researchers, policy makers and governments for the judicious use of resources; thereby minimise the global emissions, and maintain their economies once the pandemic eases. On the other, lifting of the nationwide lockdown and eventual normalisation of the temporarily halted sectors may also reverse the currently COVID-19 pandemic-led significantly slashed down global air pollution that could make the future respiratory health crisis grimmer.

As of 26 March 2020, Pakistan had 1179 cases of COVID-19, with most 421 cases from Sindh, 394 cases, 131 cases, 123 cases, 84 cases, 25 cases and 01 cases from Punjab, Balochistan, Khyber Pakhtunkhwa, Gilgit-Baltistan, Islamabad Capital Territory, and Azad Jammu and Kashmir respectively. Travel-related cases were the main source of SARS-CoV-2 infection during the early phase of the pandemic in Pakistan. Nevertheless, cases of local virus transmission are increasing day by day. As of 26 March 2020, nine deaths have been reported from COVID-19. The case fatality rate is 0.8%, which is less compare to China, Italy, USA, and Iran. The SIR (Susceptible-Infected-Recovered) model of epidemiological analysis predicts that almost 90 million population will be infected in the coming days with 5% critical cases that need health care facilities. However, the Pakistan health care system cannot provide services to this much population. Hence, we need to act timely to reduce this number by restricting local transmission of the disease. This can be done by mass testing, quarantine, isolation and social distancing of the active coronavirus cases in Pakistan. Moreover, better communication between the authorities is very much required to control disease transmission.

The coronavirus pandemic will deeply affect the tourism and travel sector. It is already clear now that its economic impact would be more severe that in the case of the Severe Acute Respiratory Syndrome (SARS) in 2002-2003. Although not as deadly as SARS, coronavirus infection has a longer incubation period and leaves about 85% of the infected without any (or with just mild) symptoms which makes it more difficult to track and to contain. Moreover, it appears to be much more contagious than its predecessor. The goods news is that most people recover from the disease and develop antibodies that can protect them from getting infected again (natural vaccination). Those cured might become the key element for the post-virus recovery strategies of tourism organisations. People with the acquired immunity to the virus would be capable of travelling freely without spreading the disease. Airlines, hotels and gastronomy should aim at this group offering them discounts and special offers. However, the problem is how to effectively ensure that everyone who claims to be cured from COVID-19 is telling the truth. Health tracking bracelets, apps, and other advanced technological solutions should be put in place. Recent best practices from Hong Kong, mainland China, or India might be applied.

We present the AI-discovered aetiology of COVID-19, based on a precise disease model of COVID-19 built under five weeks that best matches the epidemiological characteristics, transmission dynamics, clinical features, and biological properties of COVID-19 and consistently explains the rapidly expanding COVID-19 literature. We present that SARS-CoV-2 implements a unique unbiased survival strategy of balancing viral replication with viral spread by increasing its dependence on (i) ACE2-expressing cells for viral entry and spread, (ii) PI3K signaling in ACE2-expressing cells for viral replication and egress, and (iii) viral-non-structural-and-accessory-protein-dependent immunomodulation to balance viral spread and viral replication. We further propose the combination of irinotecan (an in-market topoisomerase I inhibitor) and etoposide (an in-market topoisomerase IIinhibitor) could potentially be an exceptionally effective treatment to protect critically ill patients from death caused by COVID-19-specific cytokine storms triggered by sepsis, ARDS, and other fatal comorbidities.

Coronavirus disease 2019 (COVID-19) was recently appeared all over the world. The viral main protease (3-chymotrypsin-like cysteine enzyme) controls COVID-19 duplication and manages its life cycle, making it a drug discovery target. Therefore, herein, we analyzed the theoretical approaches of 10 structurally different hydrolysable tannins as natural anti-COVID-19 through binding with the main protease of 2019-nCoV using molecular docking modelling via Molecular Operating Environment (MOE v2009) software. Our results revealed that there are top three hits may serve as potential anti-COVID-19 lead molecules for further optimization and drug development to control COVID-19. Pedunculagin, tercatain, and punicalin were found to faithfully interact with the receptor binding site and catalytic dyad (Cys145 and His41) of COVID-19 main protease, showing their successfully inhibit the protease enzyme of 2019-nCoV. We anticipated that this study would pave way for tannins based novel small molecules as more efficacious and selective anti-COVID-19 therapeutic compounds.

The emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) linked with coronavirus disease 2019 (COVID-19) poses a serious threat to public health worldwide. Firstly, the SARS-CoV-2 was reported in Wuhan, Hubei Province, China in December 2019. Initially, the major proportion of virus-infected cases (i.e. about 99%) was reported in China and now it is being reported in other counties as well. Humans begin to be infected within their communities and transmittance of the viral epidemic increased rapidly due to lack of understanding of its transmission routes and precautionary measures. The existence of SARS-CoV-2 in China threatened the population greatly due to the high incidence of fatal respiratory infections. Current investigations speculated that this virus transferred into a human from viral-infected bats. However, the process of interspecies viral transmission is an important scientific question to be addressed. Due to the continuous increase in the patients infected with COVID-19 associated pneumonia, the World Health Organization (WHO) has included this viral epidemic to the priority list of diseases. Therefore, accelerated research developments are required to control the spread of this outbreak, as it is declared as a public health emergency by WHO especially in the absence of efficacious drugs and vaccines. Our review encompasses the recent status of disease severity in China, a particular replication mechanism of SARS-CoV-2 and potential risks and precautionary measures required to avoid contact with this fatal viral infection.

Ethnopharmacological relevance: Novel coronavirus disease (COVID-19) outbroke in Wuhan has imposed a huge influence onto the society in term of the public heath and economy. However, so far, no effective drugs or vaccines have been developed. Whereas, the Traditional Chinese Medicine (TCM) has been considered as a promising supplementary treatment for the disease owing to its clinically proven performance on many diseases even like severe acute respiratory syndrome (SARS). Meanwhile, many side-effect (SE) reports suggest the SE of the TCM prescriptions cannot be ignored in curing the COVID-19, especially because COVID-19 always simultaneously leads to dramatic degradation of the patients’ physical condition. How to evaluate the TCM regarding to their latent SE is a urgent challenge. Aim of the study: In this study, we use an ontology-based side-effect prediction framework (OSPF) developed in our previous work and Artificial Neural Network (ANN)-based deep learning to evaluate the TCM prescriptions that are officially recommended in China for novel coronavirus (COVID-19). Materials and methods: Firstly, we adopted the OSPF developed in our previous work, where an ontology-based model separate all the ingredients in a TCM prescription into two categories: hot and cold. Then, we established a database by converting each TCM prescription into a vector containing the ingredient dosage and the according hot/cold attribution as well as the safe/unsafe label. And, we trained the ANN model using this database, after which a safety indicator (SI), as the complementary percentage of side-effect (SE) possibility, is then given for each TCM prescription. According to the proposed SI from high to low, we re-organize the recommended prescription list. Secondly, by using this method, we also evaluate the safety indicators of some other famous TCM prescriptions that are not in the recommended list but are used traditionally to cure flu-like diseases for extending the potential treatments. Results: Based on the SI generated in the ANN model, FTS, PMSP, and SF are the safest ones in recommended list, which all own a more-than-0.8 SI. Whereas, JHQG, LHQW, SFJD, XBJ, and SHL are the prescriptions that are most likely unsafe, where the indicators are all below 0.2. In the extra list, the indicators of XC, XQRS, CC, and CHBX are all above 0.8, and at the meantime, XZXS, SJ, QW, and KBD’s indicators are all below 0.2. Conclusions: In total, there are seven TCM prescriptions which own the indicators more than 0.8, suggesting these prescriptions should be considered firstly in curing COVID-19, if suitable. We believe this work will provide a reasonable suggestion for the society to choose proper TCM as the supplementary treatment for COVID-19. Besides, this work also introduces a pilot and enlightening method for creating a more reasonable recommendation list of TCM to other diseases.

Background: COVID-19 vaccines have been linked to myocarditis which in some circumstances can be fatal. This systematic review aims to investigate potential causal links between COVID-19 vaccines and death from myocarditis using post-mortem analysis. Methods: We performed a systematic review of all published autopsy reports involving COVID-19 vaccination-related myocarditis through July 3^rd, 2023. All autopsy studies that include COVID-19 vaccine-induced myocarditis as a possible cause of death were included, without imposing any additional restrictions. Causality in each case was determined by three independent reviewers with cardiac pathology experience and expertise. Results: We initially identified 1,691 studies and, after screening for our inclusion criteria, included 14 papers that contained 28 autopsy cases. The cardiovascular system was the only organ system affected in 26 cases. In 2 cases, myocarditis was characterized as a consequence from multisystem inflammatory syndrome (MIS). The mean and median number of days from last COVID-19 vaccination until death was 6.2 and 3 days, respectively. Most of the deaths occurred within a week from the last injection. We established that all 28 deaths were causally linked to COVID-19 vaccination by independent adjudication. Conclusions: The temporal relationship, internal and external consistency seen among cases in this review with known COVID-19 vaccine-induced myocarditis, its pathobiological mechanisms and related excess death, complemented with autopsy confirmation, independent adjudication, and application of the Bradford Hill criteria to the overall epidemiology of vaccine myocarditis, suggests there is a high likelihood of a causal link between COVID-19 vaccines and death from suspected myocarditis in cases where sudden, unexpected death has occurred in a vaccinated person. Urgent investigation is required for the purpose of risk stratification and mitigation in order to reduce the population occurrence of fatal COVID-19 vaccine-induced myocarditis.

The knowledge of COVID-19 impact on the human body has increased rapidly. Although many people recover from COVID-19, some continue to experience persistent symptoms that have been identified as Long COVID. This condition can have a severe impact on quality of life, and it remains a significant concern for medical professionals and researchers. One of the key components of the SARS-CoV-2 virus that enables it to enter human cells is the spike (S) protein. Recent studies have revealed a complex network of interactions between G proteins, spike (S) protein, and the Renin-Angiotensin System (RAS) may be responsible, at least in part, for long COVID. SARS-CoV-2 can also affect the brain, leading to neurological symptoms such as confusion, memory loss, and fatigue. Increasing evidence suggests that COVID-19 is not just a respiratory illness since it is likely that the virus could influence signal transduction pathways such as G-protein-coupled receptor (GPCR), among others, in the brain, either directly or indirectly, affecting neural functions. These interactions with the spike (S) protein and RAS, alongside the brain, are complex and require deep research to understand their implications for Long COVID-19 manifestation fully. While recent research has shed light on the complex interactions between G proteins, spike (S) protein, the brain, and the angiotensin system, this article explores these interconnected pathways and their implications for long COVID-19 manifestations. The present review summarises current research on different molecular mechanisms in Long COVID pathophysiology and may help identify possible targets or new strategies for the diagnosis and treatment.

Aging induces numerous physiological alterations, with immunosenescence emerging as a pivotal factor. This phenomenon has attracted both researchers and clinicians, prompting pro-found questions about its implications for health and disease. Among the contributing factors, one intriguing actor in this complex interplay is human cytomegalovirus (CMV), a member of the herpesvirus family. Latent CMV infection exerts a profound influence on the aging immune system, potentially contributing to age-related diseases. This review delves into the intricate relationship between immunosenescence and CMV, revealing how chronic viral infection im-pacts the aging immune landscape. We explore the mechanisms through which CMV can im-pact both the composition and functionality of immune cell populations and induce shifts in in-flammatory profiles with aging. Moreover, we examine potential role of CMV in such pathol-ogies as cardiovascular diseases, cancer, neurodegenerative disorders, COVID-19, and Long COVID. This review underlines the importance of understanding the complex interplay be-tween immunosenescence and CMV. It offers insights into the pathophysiology of aging and age-associated diseases, as well as COVID-19 outcomes among the elderly. By unraveling the connections between immunosenescence and CMV, we gain a deeper understanding of aging's remarkable journey and the profound role that viral infections play in transforming the human immune system.

We evaluated epidemiological evolution and economic impact of COVID-19 pandemic in the European Union (EU) and worldwide, and the effects of control strategies on them. We collected incidence, mortality, and gross domestic product (GDP) data between the first quarter of 2020 and of 2023. Then, we reviewed the effectiveness of the mitigation and zero-COVID control strategies. The statistical analysis was done calculating the incidence rate ratio (IRR) of two rates and its 95% confidence interval (CI). In the EU, COVID-19 presented six epidemic waves. The sixth one at the beginning of 2022 was the biggest. Globally, the biggest wave occurred at the beginning of 2023. Highest mortality rates were observed in the EU during 2020-2021 and globally at the beginning of 2021. In mitigation countries, mortality was much higher than in zero-COVID countries (IRR= 6.82; CI:6.14-7.60; p<0.001). A GDP reduction was observed worldwide, except in Asia. None of the eight zero-COVID countries presented a GDP growth percentage lower than the EU percentage in 2020, and 3/8 in 2022 (p=0.054). COVID-19 pandemic caused epidemic waves with high mortality rates and a negative impact on GDP. The zero-COVID strategy was more effective in avoiding mortality and potentially had less impact on GDP.

Approximately 10–20% of individuals suffering from COVID-19 develop prolonged symptoms known as long COVID or post-COVID condition (LC). This review aimed to assess healthcare resource use (HCRU) and healthcare costs associated with LC. Because LC is not clearly defined and often remains undiagnosed, studies reporting on long-term follow-up of individuals with a COVID-19 diagnosis were also included. Among the 41 publications included, 36 reported on HCRU and 16 on costs. Individuals with LC had significantly elevated HCRU and healthcare cost vs controls without a COVID-19 diagnosis over ≥15 months, with a 7.6%–13.1% increase in total healthcare costs per person per month as assessed by difference-in-difference analysis. Among studies that did not specifically refer to LC, having a COVID-19 diagnosis was associated with a significant 4–10% increase in long-term total HCRU over 6–8 months and a 1.3- to 2.9-fold relative increase in total healthcare costs over 6 months. Due to the heterogeneity of included studies, high-quality evidence is needed to better understand the economic burden of LC. In the absence of effective treatments, prioritizing prevention of acute COVID-19, e.g., through vaccination, may be crucial for preventing LC and the associated long-term HCRU and medical spending.

Coronavirus disease 2019 (COVID-19), can manifest with ocular symptoms. These symptoms can be divided into isolated events attributed to COVID-19 and those occurring in multisystem inflammatory syndrome in children (MIS-C), a newly diagnosed disease entity associated with COVID-19 infection. Currently, the literature lacks specific guidelines and treatment regimens for COVID-19 ocular symptoms, especially in children.

We aimed to estimate the proportion of the population infected with SARS-CoV-2 in the first year of the pandemic. The study population consisted of outpatient adults with mild or no COVID-19 symptoms, and was divided into subpopulations with different levels of exposures. Of the subpopulation without known previous COVID-19 contacts 4143, of the subpopulation with known COVID-19 contacts 594 persons were investigated. IgG- and IgA-seroprevalence and RT-PCR positivity were determined in context with COVID-19 symptoms. We hope to have contributed to the understanding of the significance of the asymptomatic and mild infections in the long persistence of the pandemic.

Coronavirus disease 2019 (COVID-19), an infectious disease pandemic, affected millions of people globally, resulting in high morbidity and mortality. Causing further concern, significant proportions of COVID-19 survivors suffer from the lingering health effects of severe acute respiratory syndrome virus 2 (SARS-CoV-2), the pathogen that causes COVID-19. One of the diseases manifesting as a post-acute sequela of COVID-19 is new-onset diabetes. This systematic review and meta-analysis will perform a comprehensive and systematic literature search to estimate the burden of new-onset diabetes after COVID-19. Specifically, this study will estimate the magnitude of the incidence, risk, and population-attributable fraction of new-onset diabetes. The study will also explore and summarize the data on the natural history or clinical course of the new-onset diabetes cases. Five bibliographic databases, including PubMed, MEDLINE, Embase, Scopus, and Web of Science, will be searched for eligible studies. The World Health Organization COVID-19 Research Database, preprint servers, and conference abstracts will also be searched. Cohort studies of COVID-19 patients of all ages providing data on new cases of diabetes in the post-acute phase of the illness will be included. The comparators to estimate the pooled risk ratio will be those with no diagnosis of COVID-19 or those infected with other respiratory tract infections. The findings of this study will likely inform clinical practice, public health guidelines, and policies for early detection and treatment of new-onset diabetes cases in the long-COVID phase. This protocol has been registered in the International Prospective Register of Systematic Reviews (PROSPERO: No.CRD42020200432).

The COVID-19 Omicron variant, reported to be the most immune evasive variant of COVID-19, is resulting in a surge of COVID-19 cases globally. This has caused schools, colleges, and universities in different parts of the world to transition to online learning. As a result, social media platforms such as Twitter are seeing an increase in conversations related to online learning. Mining such conversations, such as Tweets, to develop a dataset can serve as a data resource for interdisciplinary research related to the analysis of interest, views, opinions, perspectives, attitudes, and feedback towards online learning during the current surge of COVID-19 cases caused by the Omicron variant. Therefore this work presents a large-scale public Twitter dataset of conversations about online learning since the first detected case of the COVID-19 Omicron variant in November 2021. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter, as well as with the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management. The paper also briefly outlines some potential applications in the fields of Big Data, Data Mining, Natural Language Processing, and their related disciplines, with a specific focus on online learning during this Omicron wave that may be studied, explored, and investigated by using this dataset.

Background: COVID-19 mainly affects the respiratory system, although its manifestations are multisystemic. Increasingly, complications presented after the acute phase are still being rec-ognized and are associated with impaired functional status and health-related quality of life (HRQoL). The objective was assess the functional status and HRQoL of patients with post-COVID-19. Methods: This was a cross-sectional study involving individuals affected by COVID-19 who had persistent symptoms for one month after the acute phase of the disease. HRQoL was verified through the Short Form Health Survey 36 (SF-36) and, functional status was assessed using the six-minute walk test (6MWT), the Fatigue Severity Scale (FSS), the Med-ical Research Council (MRC) Dyspnea Scale and, the Post-COVID-19 Functional Status Scale (PCFS). Results: Were included 123 patients, 73 (59.35%) were male, with a mean age of 49.17±13.48 years and a body mass index of 31.02±6.56 stratified into three groups, not recov-ered group (NRG=23), ward recovered group (WHG=60), and intensive care unit group (ICUG=40). The main symptoms were muscle weakness (74.17%) and dyspnea (68.33%). In rela-tion to the distance covered in the 6MWT, the GNR group walked 12.83% below the predicted values, GNR 20.21% and the UGCI 28.82%, respectively. The MRC dyspnea scale had a mean value of less than 3 and the FSS scale had a mean value over 4, indicating considerable fatigue. In the PCFS scale, a significant difference was observed (p>0.0005); while in the SF-36, all HRQoL domains were compromised. Conclusion: Post-COVID-19 patients involved in this study showed a significant decline in functional status and an impairment of HRQoL.

Introduction: Rural areas face additional challenges in preventing, preparing for, responding to, and recovering from disasters. This study aimed to understand how rural General Practitioners PHCPs perceive their roles, involvement, and capacity in disaster health management. Methods: For this qualitative descriptive research, semi-structured interviews were carried out with convenience and purposive samples of rural PHCPs before and during the COVID pandemic. Open, axial, and selective coding were employed to analyse the data inductively. Results: five interviews were conducted pre-COVID and ten interviews during the second and third waves of COVID. Identified themes were similar between the two periods. Rural PHCPs were underutilised due to a lack of awareness of their capacity and a lack of infrastructure and support for greater involvement. Conclusion: Rural PHCPs can be better integrated and supported in readiness for a whole of system response to future disasters.

Introduction – Coronavirus Disease of 2019 (Covid-19) is arguably the greatest global health threat of our time. Immediately the pandemic was declared by WHO, countries around the world took broad public health and social measures (PHSM), including closure of schools, to prevent the spread of the SARS-CoV-2 virus, which causes COVID-19. [1] The COVID-19 pandemic posed an enormous risk to the health and safety of learners, teachers, parents, school administrators, education practitioners, and the wider community. Schools provide not just learning and social support for students but also, crucially, childcare, without which many parents cannot return to work. However, reopening schools carried the public health risk of viral resurgence. Parents and teachers are understandably wary as the students and staff are affected by the disease and the false information surrounding the disease. As the COVID-19 crisis becomes more protracted, there is a growing need to ensure that concerned stakeholders have appropriate mechanisms and capabilities to cope with their evolving local situations. Aim – It assessed the compliance to COVID-19 preventive measures among secondary schools in Nnewi North LGA of Anambra state, Nigeria using WHO checklist. Setting and design – This was a facility-based cross-sectional observational survey. It involved day schools, boarding schools, all boys schools, all girls schools, mixed schools, government schools, private schools, missionary schools, urban schools, and rural schools. A total area population study was done and involved all thirty-one (31) secondary schools within Nnewi North local government area of Anambra state. Data was collected through school surveys and observations of compliance measures, both done during the same school visit. Informed consent was obtained from the principal of each school or their representative before carrying out the study in their facilities. Observations and NCDC guidelines based on WHO guidelines was used to measure compliance in secondary schools. The assessment was based on the concept of indications (i.e. moments in a staff-student / student-student/ staff-staff interaction) that present an infection. Results – Out of the schools sampled, 12 schools (38.71%) had good compliance, 9 schools (29.03%) had moderate compliance, and 10 schools (32.26%) had poor compliance. The finding of this study thus revealed that the overall compliance level toward COVID-19 preventive and control measures among secondary schools in Nnewi-North LGA of Anambra state was 38.71%. This is a very poor compliance level because strict high-level compliance is required to prevent and control the COVID-19 pandemic. The possible reason for this low compliance level may be due to fatigue and reluctance from the establishments’ side and inadequate enforcement of the COVID-19 preventive and control measures from the concerned government authorities’ side. Conclusions – The common restraining factors against compliance to standard COVID-19 preventive measures included the fact that the students are children and thus wouldn’t always wear their masks at all times, school ownership, attitude towards, and risk perception of COVID-19 and these factors significantly influenced the adherence of each school towards COVID-19 mitigation measures.

This study aimed to test the hypothesis that the use of theories in open access resources during the COVID-19 pandemic would be greater than in copyrighted resources. Using the Scopus database from August 18-28, 2023, the search terms “COVID-19,” “Coronavirus,” “SARS-CoV-2,” and “2019-nCoV” retrieved 511,920 results, of which 17,487 were selected. After filtering, 8,254 studies were analyzed. These were categorized as "Both Theory and Model," "Only Theory," and "Only Model." Using MS Excel, the researchers sorted studies based on titles, abstracts, and keywords to assess the magnitude of theory and model use. The study found that theories and models were employed across various disciplines and indexed accordingly. Further analysis included term categories, year-wise distribution, and citation patterns in relation to access categories. The study recommended future research to explore the connection between theories/models and factors such as publication trends, geography, and funding. The study concluded that, journals should encourage authors to include theories/models used in their studies in titles, especially during health emergencies, to provide early insights into handling pandemics.

In the frame of the I-MOVE-COVID-19 project, a cohort of 2050 patients admitted in two Spanish reference hospitals between March 2020 and December 2021 was selected, and a range of clinical factors data were collected at admission to assess their impact on the risk COVID-19 severity outcomes through a multivariate adjusted analysis and nomograms. The need for ventilation and ICU admission were found directly associated with a higher mortality risk (OR 6.9 and 3.2, respectively). The clinical predictors of mortality were need for ventilation and ICU, advanced age, neuromuscular disorders, thrombocytopenia, hypoalbuminaemia, dementia, cancer, elevated CPK and neutrophilia (OR between 1.8 and 3.5), whilst the presence of vomiting, sore throat and cough diminished risk of death (OR 0.5, 0.2 and 0.1 respectively). Admission to ICU was predicted by the need for ventilation, abdominal pain and elevated LDH (OR 371.0, 3.6 and 2.2, respectively) as risk factors; otherwise, it was prevented by advanced age (OR 0.5). In turn, the need for ventilation was predicted by low oxygen saturation, elevated LDH and CPK, diabetes, neutrophilia, obesity and elevated GGT (OR between 1.7 and 5.2), whilst prevented by hypertension (OR 0.5). These findings could enhance patient management and strategic interventions to combat COVID-19.

Objectives: This study aimed to evaluate the risk of hepatitis B virus reactivation (HBVr) in COVID-19 patients receiving immunosuppressive treatment, which has been insufficiently studied to date. Secondarily, we aimed to evaluate the seroprevalence of HBV infection in COVID-19 patients. Methods: We performed an HBV screening in all Romanian adults hospitalized in 4 COVID-19 wards between October 2021 and September 2022. We enrolled patients with positive hepatitis B core antibody (anti-HBc) without protective hepatitis B surface antibody (anti-HBs), HBV treatment or immunosuppressive conditions, whom we followed virologically at 3 months. Results: We identified 333/835 (39.9%) anti-HBc-positive patients. Follow-up was performed in 13 patients with positive hepatitis B surface antigen (HbsAg) and 19 HBsAg-negative/anti-HBc-positive patients. Among those who received immunosuppressants, 4/23 (17.4%) patients experienced HBVr: 1 out of 8 (12.5%) HBsAg-positive patients (with 1.99 log increase in HBV DNA level) and 3 out of 15 (20%) HBsAg-negative/anti-HBc-positive patients (with de novo detectable HBV DNA level). Conclusions: Administration of COVID-19 immunosuppressants may result in a significant risk of HBVr in co-infected patients. We recommend performing an HBV triple screen panel (HBsAg, anti-HBs, anti-HBc) in all COVID-19 patients receiving immunosuppressive treatment. HBV prophylaxis may be indicated in certain patients. Larger studies are needed in order to establish an appropriate and cost-effective management in these patients.

Well-annotated gene and genomic sequences serve as a foundation for making inferences in molecular biology and evolution, and can directly impact public health. The first SARS-CoV-2 genome was submitted to GenBank and used to develop the two successful vaccines. Conserved protein domains are often chosen as targets for developing antiviral medicines or vaccines. Mutation and substitution patterns provide crucial information not only on functional motifs and genome/protein interactions but also for characterizing phylogenetic relationships among viral strains. These patterns, together with the collection time of viral samples, serve as the basis for addressing the question of when and where the host-switching event occurred. Unfortunately, viral genomic sequences submitted to GenBank undergo little quality control, and critical information in the annotation is frequently changed without being recorded. Researchers often have no choice but to hold blind faith in the accuracy of the sequences. There have been reports of incorrect genome annotation but no report that casts doubt on the genomic sequences themselves because it seems theoretically impossible to identify genomic sequences that may not be authentic. This paper takes an innovative approach to show that some SARS-CoV-2 genomes submitted to GenBank cannot be possibly authentic. Specifically, some SARS-CoV-2 genomic sequences deposited in GenBank with collection time in 2023 and 2024, isolated from saliva, nasopharyngeal, sewage, and stool are identical to the reference genome of SARS-CoV-2 (NC_045512). The probability for such occurrence is effectively 0. I also compile SARS-CoV-2 genomes with changed sample collection time. One may led astray in bioinformatic analysis without being aware of errors in sequences and sequence annotation.

Because we observed a reduced humoral immune response to the COVID-19 vaccine and subsequently discovered a lower susceptibility to COVID-19 in individuals carrying the ALDH2 rs671 variant, we hypothesized that rs671 is beneficial for cellular immunity against COVID-19. Using the IFN-γ enzyme-linked immunospot (ELISPOT) assay, we evaluated cellular immunity before and after COVID-19 vaccination in two subcohorts of a previously reported cohort. Subcohort 1 (26 participants) had six repeated observations at baseline and after one to three doses, whereas subcohort 2 (19 participants) had two observations, before and after the third dose. ELISPOT counts at six months after the second dose increased from baseline in carriers of the rs671 variant, but not in non-carriers. A positive effect of rs671 on ELISPOT counts was estimated using a mixed model, including the random effect of subcohort, repeated measures, and fixed effects of vaccine type, age, sex, height, lifestyle, steroid use, and allergic disease. There was no association between ELISPOT counts and specific IgG levels, suggesting a limitation in estimating protective potential by humoral response. There is lower humoral and higher cellular immunity against SARS-CoV-2 in rs671 variant carriers compared to non-carriers, providing a potential basis for optimizing preventive measures and drug discovery.

Unheralded cardiac arrest among previously healthy young people without antecedent illness, months or years after COVID-19 vaccination, highlights the urgent need for risk stratification. The most likely underlying pathophysiology is subclinical myopericarditis and reentrant ventricular tachycardia or spontaneous ventricular fibrillation that is commonly precipitated after a surge in catecholamines during exercise or the waking hours of terminal sleep. Small patches of inflammation and/or edema can be missed on cardiac imaging and autopsy, and the heart can appear grossly normal. This paper reviews evidence linking COVID-19 vaccines to cardiac arrest where unfortunately the majority of victims have had no antecedent clinical evaluation. We propose a comprehensive strategy for evaluating cardiovascular risk post-vaccination, incorporating detailed patient history, antibody testing, and cardiac diagnostics in the best attempt to detect abnormalities before sudden cardiac death. This approach aims to identify individuals at higher risk of cardiac events after COVID-19 vaccination and guide appropriate clinical management. It is prudent for each primary care physician to have a pre-established plan when addressing this issue in their practice.

We were tasked by Canada’s COVID-19 Immunity Task Force to describe severe adverse events (SAE) associated with emergency department (ED) visits and/or hospitalizations in immune-mediated inflammatory diseases (IMID). At 8 Canadian centres, data were collected from adults with rheumatoid arthritis (RA), axial spondyloarthritis (AxS), systemic lupus (SLE), psoriatic arthritis (PsA) and inflammatory bowel disease (IBD). We administered questionnaires, analyzing SAEs experienced within 31 days following SARS-CoV-2 vaccination. About two-thirds (63%) of 1556 participants were female; mean age was 52.5 years. BNT162b2 (Pfizer) vaccine was the most common, with mRNA-1273 (Moderna) being second. Forty-nine percent of participants had IBD, 27.4% RA, 14.3% PsA, 5.3% SpA, and 4% SLE. Twelve SAEs leading to ED visit or hospitalization were self-reported, occurring in 11 participants. SAEs included 6 ED visits (including one Bell’s Palsy 31 days after first vaccination) and 6 hospitalizations (including one Guillain-Barré syndrome 15 days after the first vaccination). Two SAEs involved pericarditis, one in SLE (considered a serious disease flare) and one in RA. Thus, in the 31 days after SARS-CoV-2 vaccination in IMID, though several serious AEs occurred, these were relatively few. As SARS-CoV2 continues to be a common cause of death, our findings may help optimize vaccination acceptance.

Seroprevalence of anti-severe acute respiratory syndrome coronavirus 2 (anti-SARS-CoV-2) antibodies in the postvaccination period in Kenya remains to be elucidated. This study aimed to determine the seroprevalence of anti-SARS-CoV-2 IgM and IgG and evaluate vaccination uptake in Nairobi, Kenya. This was a cross-sectional study conducted in a university setting. Serum anti-SARS-CoV-2 IgM and IgG levels were assayed using enzyme-linked immunosorbent assays. Mann–Whitney U test was used for binary comparisons and Kruskal–Wallis Test for multigroup comparisons. Statistical significance was set at p &lt; 0.05. A total of 189 participants were enrolled (median age, 21 years; female, 50.8%). The seroprevalence of anti-SARS-CoV-2 was 12.7% for IgM and 87.8% for IgG. Anti-SARS-CoV-2 IgG titers were higher among the vaccinated vs. non-vaccinated individuals (p &lt; 0.001, U = 2817.5), females vs. males (p = 0.024, U = 3616), and those vaccinated &lt; 6 months before the study vs. those vaccinated &gt;1 year earlier (p = 0.002, H = 12.359). The vaccination hesitancy rate was 43.4% and the underlying reasons included mistrust (22.4%), health concerns (19.7%), and lack of information (18.4%). Despite the high seroprevalence of anti-SARS-CoV-2 IgG, the high vaccine hesitancy rate necessitates community engagement and education prior to vaccines roll out.

Human existence and development ever demanded suitable shelter, the dual direc-tion relationship of human-residence have always been a material dealt with to enhance residential living conditions. The emersion of COVID-19 pandemic had introduced ab-rupt and dramatic changes in human life protocols, that exerted clear pressure on differ-ent sectors within the built environment. Housing beard great impact due to needs of so-cial distancing and quarantine obligations to increase chances of human existence. In order to measure human adaptation and residence alterations following new residential requirements, Quality of life investigations to promotse better built environment for oc-cupants had been facilitated using theory of residential dissatisfaction already been adopted in current study. Residents’ responses had been extracted regarding their dissat-isfaction applying Likert scale for measurement and evaluation. The study focused on homogenous housing estates in Erbil City precisely apartments have been selected with different plans and building layouts for their widespread use in the city and have been occupied during the three stages of study to go beyond investigating direct impact of the pandemic towards permanence of alterations and adaptation even after pandemic. Rea-sons causing changed dissatisfaction levels have been investigated for better reliability towards formulating final conclusions and recommendations. Findings showed in-creased dissatisfaction during pandemic in most of spaces, apartment layout and space design significantly affected responses and demands. Levels of dissatisfaction after pan-demic were different from stability to slight decline in dissatisfaction. The effect of limited external spaces in apartments had limited the possibility to manage the pressure, a case that might be less demanding in single family housing due to availability of private gar-dens.

Purpose: To explore how race and residential zip codes' socioeconomic index (SES) influenced COVID-19 testing rates in St. Louis during the early and peak phases of the pandemic. Method: An ecological study was conducted using COVID-19 testing data from March to November 2020 in St. Louis City. The study included 16,915 individual tests from 30 residential zip codes. Results: The overall testing rate in St. Louis was 303.97 per 10,000 population. Testing rates among Blacks, Whites, American Indian/Alaskan Natives, and Asians were 374.26, 247.77, 360.63, and 242.41 per 10,000, respectively. Higher testing rates were observed in low and middle SES zip codes compared to high SES zip codes. Adjusted for SES, testing rates were 1.68% higher among Blacks and 0.43% higher among American Indian/Alaskan Natives compared to Whites, and 0.033% lower among Asians. Geographical mapping showed higher testing rates in the inner core and lower rates in the periphery of St. Louis. Conclusion: Race and SES influence testing rates. Areas with low testing rates should be targeted for intervention in St. Louis.

Knowing the number of cases of an epidemic is the first function of epidemiological surveillance. An important underreporting of cases was observed in many places during the first wave of COVID-19 pandemic. To estimate this underreporting in the COVID-19 outbreak of Borriana (Valencia Community, Spain), during “Falles” mass gathering events in March 2020, a cross-sectional study was performed in June 2020 querying public health register. Logistic regression models were used. From a total of 468 symptomatic COVID-19 cases diagnosed in the outbreak by anti-SARS-CoV-2 serology, 36 cases were reported (7.7%), thus an underreporting of 92.3% (95% Confidence Interval [CI] 89.5%-94.6%), 13 unreported cases for every reported case. Only positive SARS-CoV-2 polymerase chain reaction cases were predominantly reported due to a limited testing capacity and following a national protocol. Significant factors associated with underreporting were no medical assistance for COVID-19 disease, adjusted odds ratio [aOR] 10.83 (95% CI 2.49-47.11), no chronic illness, aOR=2.81 (95% CI 1.28-6.17), middle and lower social classes, aOR=3.12 (95% CI 1.42-6.85), younger age, aOR=0.97 (95% CI 0.94-0.99), shorter duration of illness, aOR=0.98 (95% CI 0.97-0.99). To improve surveillance, studies of representative population samples are necessary to estimate the magnitude of future epidemics, and novel approaches are recommended.

Introduction: This population-based retrospective cohort study assesses rates of adverse events (AEs) involving cerebral thromboembolism (CTE) after COVID-19 vaccines. Methods: Data were collected from the U.S. Centers for Disease Control and Prevention (CDC) and Food and Drug Administration (FDA) Vaccine Adverse Event Reporting System (VAERS) database from January 1, 1990 to December 31, 2023. CTE AEs after COVID-19 vaccines were compared to those after influenza vaccines and after all other vaccines using proportional reporting ratio (PRR) analysis by time. Results: There are 5137 cerebral thromboembolism AEs reported in the 3 years (36 months) after COVID-19 vaccines compared to 52 AEs for the influenza vaccines over the past 34 years (408 months) and 282 AEs for all other vaccines (excluding COVID-19) over the past 34 years (408 months). The PRR’s are significant when comparing AEs by time from COVID-19 vaccines to that of the influenza vaccines (p < 0.0001) or to that of all other vaccines (p < 0.0001). The CTE AEs PRR by time (95% confidence intervals) for the COVID-19 vaccine AEs vs influenza AEs is 1120 (95% confidence interval (723-1730), p < 0.0001) and for COVID-19 vaccines vs all others is 207 (95% confidence interval (144-296), p < 0.0001). Cerebral venous thromboembolism AEs are female predominant with a female/male odds ratio of 1.63 (95% confidence interval (1.52-1.74), p < 0.0001). Conversely, cerebral arterial thromboembolism has a nonsignificant male preponderance. Cerebral venous thromboembolism is far more common than cerebral arterial thromboembolism over 36 months with an odds ratio (OR) of 14.8 (95% confidence interval 14.0-15.5, p < 0.0001). Atrial fibrillation, the most common identifiable cause of cerebral arterial thromboembolism, occurs far more commonly after the COVID-19 as compared to all other vaccines with a PRR of 123 (95% CI 88.3-172, p < 0.0001) Conclusions: There is an alarming breach in the safety signal threshold concerning cerebral thrombosis AEs after COVID-19 vaccines compared to that of the influenza vaccines and even when compared to that of all other vaccines. An immediate global moratorium on the use of COVID-19 vaccines is necessary with an absolute contraindication in women of reproductive age.

Apart from their obvious educational mission, public schools provide health, psychological, emotional, and social development grounding for students. Thus, the educational system is special in that it combines multiple integrated responsibilities and duties beyond the scope of any other social welfare program. As such, social workers are a very important constituent of this system, and they ostensibly serve to attend to the wellbeing of students while ensuring educational system performance. In light of this extremely steep set of demands, this work assesses and compares social workers’ authentic roles in UAE schools during and after the COVID-19 pandemic so that we may contribute to the improvement of educational systems worldwide. The results are nuanced and will better illuminate the important capabilities of social workers in the continually changing educational system, as well as the challenges they face and ameliorate during emergency scenarios.

Seroconversion surveys of anti-SARS-CoV-2 antibodies provide accurate estimates of the SARS-CoV-2 infection. This nationwide population-based cross-sectional serosurvey aimed to evaluate the prevalence of SARS-CoV-2 antibodies among residents in Gabon and compare the estimated cumulative number of COVID-19 cases with the officially registered number of laboratory-confirmed cases up to December 2021. Households in each province were randomly selected. Twenty-eight localities including 16 urban and 12 rural, were randomly selected to participate in the study. Whole blood samples were collected in dry tubes from all study participants around the country within 15 days. Serum samples were used to measure the total Immunoglobulin antibodies. Overall, data of 1672 households were analyzed. Out of the 3659 participants, 3175 were found positive for SARS-CoV-2 antibodies, resulting in a crude seroprevalence of 86.77%. Stratification of study participants by age group has shown highest seroprevalences in 20–29 and 40-49 age groups with 91.78% (95% CI:89.5–93.6) and 91.42% (95% CI:88.7–93.5), respectively. Nyanga province had the lowest prevalence (72,8%), and Estuaire and Ogoué-Lolo provinces had the highest prevalence (90 and 92%, respectively). Our results suggest a high transmission rate in the Gabonese population, 21 months after the first SARS-CoV-2 case in the country. This high seroprevalence estimate could indicate that the applied infection control measures may not have been adequately implemented or appropriately adhered to by the population.

Immunosuppressed individuals, such as people living with HIV (PLWH), remain vulnerable to severe COVID-19. We analyzed the persistence of specific SARS-CoV-2 humoral and cellular immune responses in a retrospective, cross-sectional study in PLWH on antiretroviral therapy. Among 104 participants, 70.2% had anti-S IgG antibodies and 55.8% had significant neutralizing activity against the Omicron variant in a surrogate virus neutralization test. Only 38.5% were vaccinated (8.76 ± 4.1 months prior), all displaying anti-S IgG, 75% with neutralizing antibodies and anti-S IgA. 29.8% had no SARS-CoV-2 serologic markers and displayed significantly lower CD4 counts and HIV viral load. Severe immunosuppression (present in 12.5% of participants) was linked to lower levels of detectable anti-S IgG (0.0003), anti-S IgA (p &lt; 0.0001) and lack of neutralizing activity against Omicron variant (p &lt; 0.0001). T-cell responses were present in 86.7% of tested participants, even in those lacking serological markers. In PLWH without severe immunosuppression, neutralizing antibodies and T-cell responses persisted for up to 9 months post-infection or vaccination. Advanced immunosuppression led to diminished humoral immunity, but retained cellular immune.

Background Community infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have increased rapidly since the emergence of the Omicron strain. During the eighth and ninth pandemic waves—when movement restrictions in the community were eased—the all-case registration system was changed, and the actual status of infection became uncertain. Methods We conducted regular rapid antigen tests (R-RAT) once or twice a week to examine the actual state of coronavirus disease (COVID-19) diagnosis among healthcare employees. Results Overall, 320 (1.42/day) and 299 (1.76/day) employees were infected in the eighth and ninth pandemic waves. During both periods, 59/263 doctors (22.4%), 335/806 nurses (41.6%), 92/194 administrative employees (47.4%), and 129/218 clinical laboratory technicians (59.2%) were infected. In the eighth wave, 56 of 195 employees were infected through close contact; in the ninth wave, 26 of 62 employees were infected. No significant difference was observed in the number of vaccinations between infected and non-infected employees. The positivity rate of R-RAT was 0.41% and 0.45% in the eighth and ninth waves. R-RAT detected infection in 212 and 229 employees during the eighth and ninth waves, respectively; the ratio of R-RAT-detected positive employees to those who reported infection was significantly higher during the ninth wave (odds ratio: 1.67, 95% confidence interval: 1.17–2.37, p

COVID-19, caused by the SARS-CoV-2 virus, has spread around the world and killed around 6.9 million people. Rapid and accurate diagnosis is essential for preventing and controlling the disease, reducing transmission and consequently saving lives. RT-PCR is the gold standard test used to detect the disease. However, the test is expensive and the result is time-consuming, which makes mass testing difficult, especially in countries with limited resources. In addition, the test has high analytical specificity and low diagnostic sensitivity, which leads to false-negative results. Several studies in the literature report the presence of hematological and biochemical alterations in infected patients and use these alterations with machine learning algorithms to help diagnose the disease. Therefore, this article presents the results obtained by different neural network architectures based on Adaptive Resonance Theory (ART) for the diagnosis of COVID-19. The study was conducted in two distinct stages: the first consisted of selecting the best ART network among several, using three open-access datasets and comparing the results with the literature. In the second stage, the chosen model was tested on a dataset containing patients from various hospitals in four countries. In addition, the model was subjected to external validation, including data from a country not present during the training and adjustment of the model, in order to validate the robustness and generalization capacity of the model. The results obtained by the ART networks in this study are promising, outperforming not only classical models, but also the deep learning models often used in the literature. Validation on data from different countries strengthens the model’s reliability and effectiveness.

This research uses a gravity model method to investigate the factors determining the number of tourists visiting Australia. Understanding the variables that draw visitors to specific locations is essential for policymakers and other stakeholders in the tourism sector since tourism continues to play a significant role in the economy of many countries worldwide. Despite the widespread use of gravity models in the analysis of international tourism flows, only a tiny amount of attention has been paid to particularly researching the flow of tourists to Australia. This research addresses this knowledge gap by analyzing the variables influencing travel patterns to Australia. The gravity model framework is used, and it considers factors like gross domestic product, gross domestic product per capita, migratory stocks, distance, population size, cost of living, and cultural similarities. The purpose of this research is to aid in developing focused marketing strategies by providing insights into the factors that influence the flow of tourists to Australia via the analysis of these variables. The results are anticipated to add to the current literature on gravity modeling in tourist research and give practical implications for industry stakeholders and policymakers. The discussion of the findings, their ramifications, and possible directions for further study serves as the conclusion of the work.

The COVID-19 pandemic has shown varying effects on adolescents’ mental health, psychosocial functioning, risk behaviours, and victimisation. This study aims to examine the changes reported by a sample of Swedish adolescents (N=1607) at the end of the first year of the pandemic in relation to these factors. Data was collected with an electronic survey between September 2020 and February 2021, targeting upper-secondary high school students (aged 15-19 years). The results indicate a relatively low overall impact of the pandemic on Swedish upper-secondary school students, with notable gender differences. Compared to females, a higher percentage of male adolescents reported experiencing elevated levels of anxiety, depression, sleep disturbances, anger, and increased illicit drug use as consequences of the pandemic. In contrast, females demonstrated an increase in several salutogenic behaviours. Victimisation rates generally decreased during this period. These findings underscore the importance of heightened awareness among professionals within schools, social services, and healthcare settings regarding the distinct challenges encountered by a larger portion of male adolescents during the COVID-19 pandemic in Sweden.

Introduction: The emergency of the SARS-CoV-2 virus spread and its subsequent global pan-demic have raised significant concerns regarding its impact on pregnancy outcomes. This review aims to summarize the emerging data on the risk of preterm delivery in pregnant women infected with SARS-CoV-2. Materials and Methods: A systematic search was conducted from March 2020 to December 2023 using PubMed, following PRISMA guidelines. Studies correlating maternal COVID-19 infection with preterm birth were included. Results: Thirteen studies were analyzed, indicating a higher incidence of preterm birth in SARS-CoV-2 positive pregnant women compared to controls. The average incidence rate of pre-term birth in infected patients was 18.5%, with a median of 12.75%, while non infected women showed an average incidence of preterm birth of 10% with a median of 8.2%. Discussion: Studies suggest an association between SARS-CoV-2 infection during pregnancy and increased risk of preterm birth and cesarean section. Severity of symptoms and underlying comorbidities further elevate this risk. Notably, infections during the third trimester pose the highest risk of preterm birth. Conclusion: Preventing SARS-CoV-2 infection during pregnancy is crucial to mitigate adverse obstetric outcomes. Close monitoring and tailored interventions for infected pregnant women, particularly those in later trimesters and with comorbidities, are imperative to reduce the risk of preterm birth and improve maternal-fetal outcomes.

Artificial Intelligence (AI) and Machine Learning (ML) approaches that could learn from large data sources have been identified as useful tools to support clinicians in their decisional process; AI and ML implementations have had a rapid acceleration during the recent COVID-19 pandemic. However, many ML classifiers are “black box” to the final user, since their underlying reasoning process is often obscure. Additionally, the performance of such models suffer from poor generalization ability in presence of dataset shift. Here, we present a comparison between an explainable-by-design (“white box”) model (Bayesian Network (BN)) versus a black-box model (Random Forest), both studied with the aim to support clinicians of Policlinico San Matteo University Hospital in Pavia (Italy) during the triage of COVID-19 patients. Our aim is to evaluate whether the BN predictive performances are comparable with those of a widely used but less explainable ML model such as Random Forest and to test the generalization ability of the ML models across different waves of the pandemic.

Background: Coronavirus disease 2019 (COVID-19) caused several cardiovascular complications, including acute myocardial infarction(AMI) in infected patients. Our study aims to understand the overall trends of AMI among COVID-19 patients during the first two years of the pandemic and the disparities and outcomes between the first and second years. Methods: Our retrospective analysis via the 2020 and 2021 National Inpatient Sample(NIS) for hospitalizations between April 2020 and December 2021 analyzed adults with a primary diagnosis of COVID-19 who experienced events of AMI. We compared month-to-month events of AMI and mortality of AMI patients with COVID-19, patient characteristics, and outcomes between the 2020 and 2021 AMI samples. Results: There were 2,541,992 COVID-19 patients, with 3.55% experiencing AMI. The highest rate of AMI was in December 2021 (4.35%). No statistical differences in trends of AMI mortality were noted over the 21 months. AMI cases in 2021 had higher odds of undergoing PCI (aOR 1.627, p