Since the worldwide spread of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), treating taste and saliva secretory disorders associated with coronavirus disease 2019 (COVID-19) has become one of the most critical issues in the COVID-19 era. The aim of the present study was to update information on treatments being applicable to such oral symptoms and discuss their pathogenic mechanisms. Promising treatments include different types of methods using tetracycline, corticosteroid, zinc, stellate ganglion block, phytochemical curcumin, traditional herbal medicine, nutraceutical vitamin D, photobiomodulation, antiviral drug, malic acid sialagogue, chewing gum, acupuncture, and/or moxibustion. At present, however, fully validated treatments are still lacking for COVID-19-associated ageusia/dysgeusia/hypogeusia and xerostomia/dry mouth/hyposalivation. An appropriately selected treatment and oral healthcare should be provided to COVID-19 patients and survivors suffering from taste and saliva secretory disorders. Understanding of currently available treatment options is required for dental profes-sionals because they not only experience patients who were infected with SARS-CoV-2 or recov-ered from COVID-19 but first become aware of their abnormal taste and salivary secretion. By doing so, dentists and dental hygienists can play a crucial role in managing COVID-19-associated oral symptoms and contribute to improving the oral health-related quality of life of the relevant dental patients.

Acute appendicitis is the most common surgical emergency worldwide with peak incidence in the age range of 10 – 19 years, and the standard treatment procedure is the surgical removal of the appendix to avoid complications such as its rupture, peritonitis, and sepsis. The COVID-19 pandemic required the global population to stay indoors to stop the spread of virus, which led to a decline in the number of patients visiting the hospital for non- COVID -19 related emergencies. This is a case of a 9-year-old girl who tested positive for COVID -19 and developed acute appendicitis and benefited from individualised classical homeopathy. Further scientific investigation is necessary to establish the relevance of individualised classical homeopathy in treating serious acute conditions such as acute appendicitis.

COVID-19, the fear it engendered, and the policy measures to manage its spread have disproportionately impacted the wellbeing of children and adolescents (CAs). We present an intensive critical realist case study of the impact of COVID-19 on the health and wellbeing of CAs in Rwanda, seeing it as much a social and political crisis as a medical and public health one. To do this, we carried out interviews with a purposive sample of 25 leaders with a working knowledge of children and young people; they were more likely than the CAs themselves to observe changes across the CA population within their remit and more likely to be looking for general explanations rather than individual experiences. The findings show that CAs' responses to the changes wrought on their lives by Covid-19 were conditioned by their age, gender, social class and if they lived in urban or rural areas. However, Covid19 has not just revealed the structural weakness of the Rwandan health system but of education, social protection, child protection, employment, family, and financial systems. The pathway to (adverse) impacts of COVID-19 on CAs is conditioned by these institutions and their interactions together with structural socioeconomic inequalities both within Rwanda and globally.

The research objects are the tax and budgetary policies of the Russian Federation. In this research, financial (budgetary) risks are understood as a decrease in the balance of the state (national) budget resulting from a reduction in revenues or an increase in expenditures. This research considers production in the main sectors of the economy as a key factor of financial risk in the COVID-19 pandemic. The research aims to analyze the main directions of the budgetary and tax policy of the Russian Federation aiming at supporting the economy and the population during the spread of COVID-19, which is especially relevant in connection with the expected recession in a number of sectors of the economy and a decrease in the level of employment and, accordingly, the well-being of citizens. In these conditions, it is necessary to adjust the budgetary and tax policy to preserve the state’s social obligations and expand social and economic support for businesses and citizens to smooth out the negative consequences of the impact of restrictive measures. The authors applied systemic and institutional approaches and statistical methods. The main results of the research reflect the need to (1) implement support measures (tax and budgetary incentives) for small and medium-sized enterprises, on which the crisis provoked by the COVID-19 pandemic has had the most destructive impact, and (2) to expand the volume of budgetary financing of social programs for financial risk management of the Russian economy during the COVID-19 pandemics.

The alterations in sleep among undergraduate students have been a burden to their mental health and academic studies. We used the Pittsburgh Sleep Quality Index scale in this study conducted among Georgian and International students. The respondents participated in this study through the University intranet as their responses remained anonymous. The survey comprised the demographic characteristics and sleep health deteriorating wake patterns such as subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. A total of 500 students completed this study, 72% were Georgian students, and 28% were international students. 50.8% of Georgian students were under the age of 20 years, and 74.3% of international students were between 21 and 30 years of age. Most Georgian students reported poor subjective sleep quality, short sleep duration, fewer sleep disturbances, and daytime dysfunction. However, sleep latency was higher among international students. Both categories of students reported using sleeping pills as the statistical significance was observed between global score and gender, subjective sleep quality, and age grade of Georgian students (p<0.05). This study aimed to evaluate the sleep-wake health quality among international and Georgian undergraduate students at the University of Georgia.

COVID-19 is a pandemic triggered by the coronavirus SARS-CoV-2 whose peak occurred in the years 2020 and 2021. The main target of the virus is the lung and infection is associated to an accentuated inflammatory process involving mainly the innate arm of the immune system. Here, we described the induction of a pulmonary inflammatory process triggered by the intranasal (IN) instillation of UV-inactivated SARS-CoV-2 in C57BL/6 mice and then the evaluation of vitamin D (VitD) ability to control this process. The assays used to estimate the severity of lung involvement included total and differential number of cells in the BALF, histopathological analysis, quantification of T cell subsets and inflammatory mediators by RT-PCR, cytokine quantification in lung homogenates and flow cytometric analysis of cells recovered from lung parenchyma. IN instillation of inactivated SARS-CoV-2 triggered a pulmonary inflammatory process, consisting of various cell types and mediators, resembling the typical inflammation found in COVID-19 patients. This inflammatory process was significantly decreased by IN delivery of vitD, but not by its IP administration, suggesting that this hormone has therapeutic potential in COVID-19 if locally applied.

SARS-CoV-2 resembles the ancient mythical creature Hydra. Just like with the Hydra, when one head is cut, it is followed by appearance of two more heads, suppression of one SARS-CoV-2 variant causes appearance of newer variants. Unlike Hydra that grows identical heads, newer SARS-CoV-2 variants are usually more infective, which can be observed as time evolution of the virus at hand, which occurs through acquisition of mutations during time. The appearance of new variants is followed by appearance of new COVID-19 pandemic waves. With the appearance of new pandemic waves and determining of sequences, in the scientific community and general public the question is always raised of whether the new variant will be more virulent and more pathogenic. The two variants characterized in this paper, BA.5.2 and BF.7, have caused a pandemic wave during the late 2022. This paper gives full chemical and thermodynamic characterization of the BA.5.2 and BF.7 variants of SARS-CoV-2. Having in mind that Gibbs energy of binding and biosynthesis represent the driving forces for the viral life cycle, based on the calculated thermodynamic properties we can conclude that the newer variants are more infective than earlier ones, but that their pathogenicity has not changed.

Coronavirus disease 2019 (COVID-19) was declared a pandemic in March 2020, which led to the implementation of non-pharmaceutical interventions that had inadvertent physical, mental and social effects. The purpose of this study was to examine the experiences and responses of Canadians to these interventions on Twitter using the Kübler-Ross Change Curve (KRCC) during the first six months of the pandemic. Tweets were analyzed using sentiment analysis, thematic content analysis and KRCC. The findings highlight that many Canadians attempted to adapt to the changes but had a predominantly negative outlook on policies due to the financial and social repercussions

Since the beginning of 2020, tetracycline (TC), such as minocycline (MINO), has been used to inhibit coronavirus disease 2019 (COVID-19). Traditional Japanese Kampo medicine, such as Saiko-keishi-to (SKT), has recently received a lot of attention for its anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) effects. We describe a COVID-19 patient treated with MINO and SKT in anticipation of their anti-SARS-CoV-2 properties. A 90-year-old male patient with Alzheimer’s disease was referred to a medical clinic due to fever, appetite loss, and general malaise. Based on positive SARS-CoV-2 rapid antigen tests, he was diagnosed with COVID-19. He did not have COVID-19 pneumonia, but he had difficulty in eating on his own. As a result, he was referred to a hospital for admission. After admission, he was treated with molnupiravir to avoid aggravation. Seven days after his admission, he was discharged. After his discharge, he was referred to our hospital as an outpatient due to a prolonged mild fever and general malaise. As a precaution, a real-time reverse transcription-polymerase chain reaction (RT-PCR) test was performed, which yielded a positive result. Therefore, the aforementioned symptoms were thought to be caused by prolonged COVID-19. He was treated with MINO and SKT due to the anti-viral properties of these two drugs. The RT-PCR test became negative 7 days after receiving this treatment, and the fever and general malaise subsided.

COVID-19 is the first known coronavirus pandemic. Nevertheless, the seasonal circulation of the four milder coronaviruses of humans – OC43, NL63, 229E and HKU1 – raises the possibility that these viruses are the descendants of more ancient coronavirus pandemics. This proposal arises by analogy to the observed descent of seasonal influenza subtypes H2N2 (now extinct), H3N2 and H1H1 from the pandemic strains of 1957, 1968 and 2009, respectively. Recent historical revisionist speculation has focussed on the influenza pandemic of 1889-1892, based on molecular phylogenetic reconstructions that show the emergence of human coronavirus OC43 around that time, probably by zoonosis from cattle. If the “Russian influenza”, as The Times named it in early 1890, was not influenza but caused by a coronavirus, the origins of the other three milder human coronaviruses may also have left a residue of clinical evidence in the 19th century medical literature and popular press. In this paper, we search digitised 19th century British newspapers for evidence of previously unsuspected coronavirus pandemics. We conclude that there is little or no corpus linguistic signal in the UK national press for large-scale outbreaks of unidentified respiratory disease for the period 1785 to 1890.

Introduction. The outbreak of the COVID pandemic was a period of uncer-tainty and tension for healthcare managers, resulting from the lack of knowledge, i.e. about the transmission of the virus, but also from the lack of uniform organisational and treatment procedures. It was the period where the ability to prepare to a crisis situation, to adapt to the existing conditions and to draw conclusion from the situa-tion were critical to keep ICUs operating. The aim of this study was to show the prep-aration of an ICU in Poland to ensure resilience, and also the methods of reacting dur-ing the COVID-19 pandemic on both central and local level. Methods. Based on the EC and WHO guidelines on resilience a matrix of 6 elements and 13 standards as-signed to them was created, with a series of questions from a survey questionnaire. Results. Good management in resilient systems is free access to any resource. A free and transparent flow of information and also well motivated human resources in an appropriate number. Conclusion. Appropriate preparation, adaptation to the existing situation and effective management of crisis situations is an important element of ICU resilience.

The goal of this study is to develop a global analysis, based on data from 2015 to 2022, that clarifies the impact of containment policies (e.g., lockdown and quarantine) for Coronavirus Disease-2019 (COVID-19) on the air pollution between countries of different continents. In this context, average changes of CO, NO2, SO2, O3, PM2.5, and PM10 concentrations based on measurements at ground level in January, February, and March for 2019, 2020, 2021, and 2022 are compared with average values of 2015-2018 period between 300 cities of 19 countries in 5 continents. Results show that the maximum reduction in pollutant concentrations during this period is given by: CO (-4,367.5%) in France, NO2 (-150.5%) in China and Australia, SO2 (-154.1%) in Israel, O3 (-94.1%) in China, PM2.5 (-41.4%) in Germany and PM10 (-157.4%) in Turkey. Findings reveal that the effects of containment policies on air quality vary significantly between countries depending on different geographical characteristics of regions. This study has main environmental policy implications because it clarifies the critical role of severe control measure to reduce air pollution and support sustainable environment and development.

COVID-19 had a significant impact on construction projects due to labor shortages and COVID-19 restrictions, yet little is known about the impact it had on construction safety. To address this gap, an Australian construction project was selected to study the impact of COVID-19 on safety performance, safety climate and safety leadership. The study collected data from safety climate surveys, leading and lagging safety indicators and used linear regression to compare safety performance pre and post the onset of COVID-19. Our results showed after the onset of COVID-19 there was a significant reduction (Pr>F at 0.05%) in incident rate, an improvement in supervisor safety leadership and safety climate, and satisfaction with organisational communication. The study identified the increase level of safety awareness due to COVID-19 did not result in an increase in the level of engagement in safety leadership. Interestingly, participation in the safety leadership activities did not improve until a change of Project Manager occurred. The study determined leaders who establish a positive safety climate within a project could negate the safety performance impact of COVID-19. The study confirms the importance of site safety leadership in maintaining engagement in risk management and the value of focused safety communication.

Abstract: Introduction: Nurses, at the forefront of the fight against the Covid-19 pandemic, have a significant responsibility. Thus, it is substantial to examine the factors behind the job stress, job satisfaction, and the care nurses provide in this process. To examine the correlation between nurses' job stress, satisfaction, and caring behavior perceptions during the Covid-19 pandemic. Method: A descriptive and correlational study. It was conducted with 261 nurses working in a hospital between 2020-2021. Introductory information form, Job Satisfaction Scale for Nurses, Swedish Demand-Control-Support Questionnaire (Job Stress Scale) and Caring Behaviors Inventory-24 were used as data collection tools. Factors behind the perception of caring behaviors were analyzed by linear regression analysis. Results: Caring behavior was found negatively correlated with job stress and positively correlates with job satisfaction. The regression analysis showed that the evaluation of the pre-pandemic work environment and the sub-dimensions of the scales, job control, support from superiors, and perceived significance in the workplace affected the caring behavior. Conclusion: The nurses have low job stress, high job satisfaction, and a high perception of caring behavior in the fight against Covid-19.

Background: The COVID-19 pandemic has seen a considerable expansion in the way work settings are structured with a continuum emerging between working fully in-person and from home. The pandemic has also exacerbated many risk factors for poor mental health in the workplace, especially in public-facing jobs. Therefore, we sought to test the potential relationship between work setting and self-rated mental health. Methods: We modeled the association of work setting (only working from home, only in-person, hybrid) on self-rated mental health (Excellent/Very Good/Good vs. Fair/Poor) in an online survey of Canadian workers during the 3rd wave of COVID-19. Mediating effects of vaccination, masking, and distancing were explored due to the potential effect of COVID-19 related worries on mental health among those working in-person. Results: Among 1,576 workers, most reported hybrid work (77.2%). Most also reported good self-rated mental health (80.7%). Exclusive work from home (aOR: 2.79, 95%CI:1.90,4.07) and exclusive in-person work (aOR: 2.79, 95%CI: 1.83,4.26) were associated with poorer self-rated mental health than hybrid work. Vaccine status mediated only a small proportion of this relationship (7%), while masking and physical distancing were not mediators. Conclusion: Hybrid work arrangements were associated with positive self-rated mental health. Compliance to vaccination, masking, and distancing did not meaningfully mediate this relationship.

In the present study we introduce a deterministic mathematical model in order to study the interaction between the human immune system and a virus, like COVID 19. The mathematical analysis is based on the tools of dynamical systems theory, by modeling the interactions between the immune system and the virus, using a predator-prey method and following the ideas of G. Moza, from \cite{TGV}. It will be obtained some conclusions with medical relevance and the main three of them are the followings: 1) A deficiency of a single type of immunity in the early stages of virus proliferation, may lead to a large virus multiplication and the human body can loses the fight against this virus; 2) If the level of all components of the immunity system are at the normal threshold from the first moment of the infection and the immune system kill the virus at higher rate than the rate of virus reproduction, then the human body has the ability to stop the multiplication of the virus and liquidate it, that means the virus will be destroyed; 3) If the level of at least one type of immunity can be increased beyond the normal threshold, by medical interventions (like vaccination) in the early stages of virus infection, then the immune system has a better chance to win the fight with the virus.

Since the origin of COVID-19, everyone is getting accustomed to the new rules and regulations, travel restrictions and new lifestyle. Constant changes in the government advisories and the COVID-19 guidelines poses a real challenge for children to adapt to causing stress, anxiety and other mental health issues. Therefore, it is imperative to raise awareness about the challenges that Indian children are dealing with to help them better cope with this stressful and frantic time. The focus of this review is on various child-related problems that the Indian government is trying to tackle such as stress, depression, malnutrition, school closures, digital divide, child labor, child trafficking in context of mental health issues caused by them during COVID-19. Highlights:The reader will come to appreciate that: Digital-divide caused by shifting offline learning to online mode. Strategies implemented by Indian government to combat malnutrition Effect of COVID-19 lockdown on children suffering from mental disorders Child labor and trafficking and the strategies that aim to decrease child labor during the pandemic Educating the children appropriately regarding COVID protocols

The aims of the study are: a) Describe the reactogenicity of WHO-approved two mRNA (Pfizer-BioNTech, Moderna) and two non-RNA vaccines (Oxford-AstraZeneca, Sinovac) among lactating mother and baby pairs; and b) compare and contrast the reactogenicity between mRNA and non-mRNA vaccines. A cross-sectional, self-reported survey was conducted amongst 1784 lactating women who received COVID-19 vaccinations. The most common maternal adverse reaction was a local reaction at the injection site; the largest minority of respondents, 43.7% (780/1784), reported experiencing worse symptoms when receiving the second dose compared to the first dose. There were no major reported adverse effects or behavioural changes in the breastfed infants. Among the respondents who received non-mRNA COVID-19 vaccinations, a majority reported no change in lactation but those who did more commonly reported an increase in milk supply, decrease in milk supply and pain in the breast. The more commonly reported lactation changes (fluctuations in breastmilk supply and pain in the breast) for the non-mRNA vaccines were similar to that of respondents who received mRNA vaccines. Our study, with a large cohort and wide geographical and racial mix, further augments earlier reported findings that COVID-19 vaccines are safe for breastfeeding mothers and her children.

There are two contrary opinions regarding the risk if mainland China (MC) moves away from its zero-COVID policy. Some experts think the risk shall be much lower than influenza as per MC’s own COVID-19 case fatality rate (CFR), while some other experts think the risk shall be much higher than influenza as per the COVID-19 CFRs of other regions. We elucidate here that this and multiple other striking differences in the CFR between various scenarios all support and substantially resulted from the view that good IDM is highly powerful to mitigate COVID-19, where IDM (isolation-disinfection-maintenance) means isolation of COVID-19 cases from other people, disinfection of their living environments, and health maintenance (e.g., rest, nutrition, breathing). The high effect of good IDM is also supported by the theoretic functions of IDM in minimizing co-infections and maintaining body functions, and the fact that all the 505 COVID-19 deaths reported in MC in 2022 before May 5 died directly of severe underlying diseases with COVID-19. Although it is tough for people in poverty to obtain good IDM, good IDM can be feasible at home for the most mild cases and in hospitals for the most severe cases. Therefore, good IDM can be crucial to mitigating COVID-19 worldwide. It also suggests that the risk for China to end its zero-COVID policy depends on China’s control policies or measures. Based on the effect of IDM, the cautious co-existence policy was proposed for COVID-19 control. This policy could reduce the whole death toll in MC because good IDM is non-specific and can reduce deaths of various other diseases. The cautious co-existence policy (non-specific) and the vaccination policy (specific) aid each other to mitigate COVID-19, and they cannot replace each other. Those who are qualified in health for vaccination should be vaccinated against COVID-19 timely.

The COVID-19 has dramatically affected mental health and work environment of many labor sectors, including the educational sector. Our primary aim was to investigate preschool teachers’ psychological distress and work engagement during the early stages of the COVID-19 outbreak, while examining the possible protective role of participating in mindfulness-based intervention (C2C-IT) and emotion regulation. Emotional distress, work engagement and COVID-19 concerns’ prevalence were evaluated among 165 preschool teachers in the early stages of the COVID-19 outbreak in Israel, using self-report questionnaires. Findings show that preschool teachers have experienced increased emotional distress. Teachers who had participated in the C2C-IT intervention six month before the pandemic outbreak (N=41) reported lower emotional distress, higher use of adaptive emotion regulation strategies and higher work engagement, compared to their counterparts that had not participated in the mindfulness training (N = 124). Emotion regulation strategies mediated the link between participating in the CTC-IT intervention and emotional distress and work engagement. Teaching is a highly demanding occupation, especially during a pandemic, therefore it is important to invest resources in empowering this population. According to the findings of the current study, implementation of mindfulness-based intervention during the school year, may benefit teachers’ well-being, even during stressful events such as the COVID-19 pandemic.

During the COVID-19 pandemic, conducting face-to-face medical residency interviews was challenging due to infection prevention precautions, social distancing and travel restrictions. Virtual interviews were implemented by the Saudi Commission for Health Specialties (SCFHS) as an alternative process for residency matching while striving to maintain the same quality standards. This national survey was conducted to assess the satisfaction and perceptions of faculty members’ virtual interviews performance in the assessment for the medical training residency programs. Among the participating 173 faculty members (34.1%) did not have previous experience with video-conferencing. Zoom application was the most commonly used platform (65.9%). Most (89.6%) of the faculty perceived virtual interviews as “adequate” for the candidates to express themselves, while almost half of the faculty (53.8%) agreed that virtual interviews allowed them to accurately reach an impression about the candidates. Overall, 73.4% of faculty felt comfortable ranking the virtually interviewed candidates. We conclude that the acceptance of participating faculty members in the first Saudi medical residency training matching cycle virtual interviewing event was well perceived. This study provides evidence for future application and research of virtual interviews in residency candidates' assessment, especially after the pandemic crisis resolves.

Background: Psychological sufferings are observed among dental students during their academic years, which had been intensified during the COVID-19 pandemic. Objectives: This study assessed the levels and identified factors associated with psychological distress, fear and coping experienced by dental undergraduate students in Bangladesh. Methods: A cross sectional online survey was conducted during October-November, 2021. The Kessler Psychological Distress Scale (K-10), Fear of COVID-19 Scale (FCV-19S) and Brief Resilient Coping Scale (BRCS) were used in order to assess psychological distress, fear and coping strategies respectively. Results: A total of 327 students participated; the majority (72%) were 19-23 years old and females (75%). One in five participants were infected with COVID-19 and 15% reported contact with COVID-19 cases. Negative financial impact (AOR 3.72, 95%CIs 1.28-10.8), recent or past COVID-19 infection, contact with COVID-19 cases were associated with higher levels of psychological distress; but being a 3rd year student (0.14, 0.04-0.55) and being satisfied about current social life (0.11, 0.03-0.33) were associated with lower levels of psychological distress. Being a 3rd year (0.17, 0.08-0.39) and a 4th year student (0.29, 0.12-0.71) were associated with lower levels of fear. Health care service use and feeling positive about life were associated with medium to high resilience coping. Conclusions: This study iden-tified dental students in Bangladesh who were at higher risk of psychological distress, fear and coping during the ongoing pandemic. Development of mental health support system within dental institution should be considered in addition to the academic and clinical teaching.

COVID-19 has become a part of everyone's day-to-day life, since the outbreak in 2019 the novel coronavirus disease (COVID-19) has caused more than 4.5 million deaths with over 200 million cases reported globally. Currently, the number of infections and deaths are gradually lowering in different countries however the underlying challenges still exist. COVID-19 threatens human life, social functioning and development. Although numerous studies have been carried out in the past to highlight the key challenges very limited studies have been conducted from an ordinary person's viewpoint. In the fight against COVID-19, humanity has been pushed to a level which cannot be accepted where establishing that balance is a priority. This study focuses on highlighting the common issues faced by the ordinary public in the current era. Five key areas were identified to be the most essential; education, technological adaptation, transportation, mental health and gender-based violence (GBV).

The coronavirus disease 2019 (COVID-19) pandemic has caused considerable global disruption to clinical practice. This article will review the impact that the pandemic has had on oncology clinical trials. It will assess the effect of the COVID-19 situation on the initial presentation and investigation of patients with suspected cancer. It will also discuss the impact of the pandemic on the subsequent management of cancer patients and how clinical trial approval, recruitment and conduct were affected during the pandemic. An intriguing aspect of the pandemic is that clinical trials investigating treatments for COVID-19 and vaccinations against the causative virus, SARS-CoV-2, have been approved and conducted at unprecedented speed. In light of this, this re-view will also discuss the potential that this enhanced regulatory environment could have on the running of oncology clinical trials in the future.

The reverse transcription quantitative polymerase chain reaction (RT-qPCR) is an established tool for the diagnosis of RNA pathogens. Its potential for automation has caused it to be used as a presence/absence diagnostic tool even when RNA quantification is not required. This technology has been pushed to the forefront of public awareness by the COVID-19 pandemic, as its global application has enabled rapid and analytically sensitive mass testing, with the first test targeting three viral genes published within days of the publication of the SARS-CoV-2 genomic sequence. One of those, targeting the RNA-dependent RNA polymerase gene, has been heavily criticised for supposed scientific flaws at the molecular and methodological level and this criticism has been extrapolated to doubts about the validity of RT-qPCR for COVID-19 testing in general. We have analysed this assay in detail and our findings reveal some limitations, but also highlight the robustness of the RT-qPCR methodology for SARS-CoV-2 detection. Whilst our data show that some errors can be tolerated, it is always prudent to confirm that primer and probe sequences complement their intended target, since when errors do occur, they may result in a reduction in the analytical sensitivity. However, in this case it is unlikely that a mismatch will result in poor specificity or significant number of false positive SARS-CoV-2 diagnoses, especially as this is routinely checked by diagnostic laboratories as part of their quality assurance.

The worldwide pandemic of coronavirus disease 2019 (COVID-19) has become an unprecedented challenge to global public health. With the intensification of the COVID-19 epidemic, the development of vaccines and therapeutic drugs against the etiological agent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are also widespread. To prove the effectiveness and safety of these preventive vaccines and therapeutic drugs, available animal models that faithfully recapitulate clinical hallmarks of COVID-19 are urgently needed. Currently, animal models including mice, golden hamsters, ferrets, nonhuman primates and other susceptible animals have been involved in the study of COVID-19. 92 vaccine candidates have entered clinical trials after the primary evaluation in animal models, of which inactivated vaccines, subunit vaccines, virus-vectored vaccines and mRNA vaccines are promising vaccine candidates. In this review, we summarize the landscape of animal models and advanced vaccines with efficacy range from about 50% to more than 95%. In addition, we point out future directions for animal models and vaccine development, aiming at providing valuable information and accelerating the breakthroughs confronting SARS-CoV-2.

In the first year of its appearance, the 2019 coronavirus disease (COVID-19) has affected more than 150 million individuals and killed 3 million people worldwide. The pandemic has also triggered numerous global initiatives to tackle the newly emerging disease, including the development of SARS-CoV-2 vaccines and the attempt to discover potential pharmacological therapies. Nonetheless, despite the success of SARS-CoV-2 vaccines development, COVID-19 therapy remains challenging. Several repurposed drugs that were documented to be useful in small clinical trials have been shown to be ineffective in larger studies. Additionally, the pathophysiology of SARS-CoV-2 infection displayed the predominance of hyperinflammation and immune dysregulation in inducing multiorgan damage. Therefore, the potential benefits of both immune modulation and suppression in COVID-19 have been extensively discussed. Here, we reviewed the roles of immunomodulation as potential COVID-19 pharmacological modalities based on the existing data and proposed several new immunologic targets to be tested in the foreseeable future.

The spread of the Coronavirus pandemic has been accompanied by an infodemic. The false information that is embedded in the infodemic affects people’s ability to have access to safety information and follow proper procedures to mitigate the risks. This research aims to target the falsehood part of the infodemic, which prominently proliferates in news articles and false medical publications. Here, we present NeoNet, a novel supervised machine learning text mining algorithm that analyzes the content of a document (news article, a medical publication) and assigns a label to it. The algorithm is trained by TFIDF bigram features which contribute a network training model. The algorithm is tested on two different real-world datasets from the CBC news network and Covid-19 publications. In five different fold comparisons, the algorithm predicted a label of an article with a precision of 97-99 %. When compared with prominent algorithms such as Neural Networks, SVM, and Random Forests NeoNet surpassed them. The analysis highlighted the promise of NeoNet in detecting disputed online contents which may contribute negatively to the COVID-19 pandemic.

Background: COVID-19 is associated with neuropsychiatric symptoms including increased depressive, anxiety and chronic fatigue-syndrome (CFS)-like physiosomatic (previously known as psychosomatic) symptoms.Aims: To delineate the associations between affective and CFS-like symptoms in COVID-19 and chest CT-scan anomalies (CCTAs), oxygen saturation (SpO₂), interleukin (IL)-6, IL-10, C-Reactive Protein (CRP), albumin, calcium, magnesium, soluble angiotensin converting enzyme (ACE2) and soluble advanced glycation products (sRAGEs).Method: The above biomarkers were assessed in 60 COVID-19 patients and 30 heathy controls who had measurements of the Hamilton Depression (HDRS) and Anxiety (HAM-A) and the Fibromyalgia and Chronic Fatigue (FF) Rating Scales. Results: Partial Least Squares-SEM analysis showed that reliable latent vectors could be extracted from a) key depressive and anxiety and physiosomatic symptoms (the physio-affective or PA-core), b) IL-6, IL-10, CRP, albumin, calcium, and sRAGEs (the immune response core); and c) different CCTAs (including ground glass opacities, consolidation, and crazy paving) and lowered SpO2% (lung lesions). PLS showed that 70.0% of the variance in the PA-core was explained by the regression on the immune response and lung lesions latent vectors. Moreover, one common “infection-immune-inflammatory (III) core” underpins pneumonia-associated CCTAs, lowered SpO2 and immune activation, and this III core explains 70% of the variance in the PA core, and a relevant part of the variance in melancholia, insomnia, and neurocognitive symptoms.Discussion: Acute SARS-CoV-2 infection is accompanied by lung lesions and lowered SpO2 which both may cause activated immune-inflammatory pathways, which mediate the effects of the former on the PA-core and other neuropsychiatric symptoms due to SARS-CoV-2 infection.

The COVID-19 pandemic affected the whole world, but not all countries were impacted equally. This opens the question of what factors can explain the initial faster spread in some countries compared to others. Many such factors are overshadowed by the effect of the countermeasures, so we studied the early phases of the infection when countermeasures have not yet taken place. We collected the most diverse dataset of potentially relevant factors and infection metrics to date for this task. Using it, we show the importance of different factors and factor categories as determined by both statistical methods and machine learning (ML) feature selection (FS) approaches. Factors related to culture (e.g., individualism, openness), development, and travel proved the most important. A more thorough factor analysis was then made using a novel rule discovery algorithm. We also show how interconnected these factors are and caution against relying on ML analysis in isolation. Importantly, we explore potential pitfalls found in the methodology of similar work and demonstrate their impact on COVID-19 data analysis. Our best models using the decision tree classifier can predict the infection class with roughly 80% accuracy.

Part of philosophy is to subject assertions to critical scrutiny, clarifying exactly what the assertion is saying, its implications, and thus its direct plausibility. The goal is to ensure clarity, logical consistency, and rational argumentation in order to arrive at reasoned conclusions. A common problem is that arguments have missing implied premises that, unless explicitly stated, are mistakenly assumed to be true. Here we subject conclusions made regarding the SARS-CoV-2 pandemic to critical scrutiny, revealing their implied premises so that these premises can be explicitly examined and refuted. Specifically, we refute the conclusions that “no one is protected until everyone is protected” and “population lockdowns are required to protect those at high risk of adverse outcomes.” In the end, we argue for the conclusion that “an Emergency Management principles based response to the pandemic, compared to population-wide lockdowns, offers a way to prevent more adverse outcomes from COVID-19, better prevent overwhelmed healthcare, and prevent most of the collateral damage to the wellbeing of the population that has resulted from the lockdowns.”

The GFPMX projects forest area and stock, consumption, production, imports, exports, and prices of industrial roundwood, fuelwood, sawnwood, wood-based panels, wood-pulp, and paper and paperboard, in 180 countries, and currently from 2018 to 2070. The core principle of the model is the Cobweb theorem, according to which markets are not necessarily in equilibrium, but take some time to adjust to shocks, such as demand shifts, leading to oscillatory dynamics of prices and quantities. The paper presents the model structure and the estimation of its parameters from international statistics on production, trade, forest area, and forest stock. This is followed by an application of the GFPMX to the impact on the global forest sector of the economic recession caused by the COVID-19 pandemic.

: The purpose of this research was to verify the importance and performance of crisis management in Korean fitness center using Importance-Performance Analysis (IPA). For this study, 304 fitness center executives and managers in Seoul and Gyeonggi region were selected as from March 21 to May 17, 2020. Frequency analysis was performed using SPSS 24.0 and exploratory factor analysis was conducted to verify the validity and reliability. Priority analysis and IPA analysis were performed to compare the mean values, and the following results were obtained. First, in the first quadrant, there were 6 attributes besides keep social distancing between employees and customers. Second, in the second quadrant, there were four attributes in addition to regular disinfection of the gymnasium. Third, in the third quadrant, there were 6 attributes besides maintain furniture clean. Third, there were 6 attributes other than maintaining furniture clean in the third quadrant. Fourth, in the fourth quadrant, there are three attributes in addition to the restriction of face-to-face meetings. The conclusion is as follows. First, equip supplies for prevention of covid19, keep social distance, and check government support policies. Second, analyze of economic support policies, and research on their application methods. Third, Prepare various non-face-to-face communication methods and Untact(non-contact) marketing strategies. Fourth, make a checklist for factors with relatively little importance.

Background: Flow-through dot-blot assay (FT-DBA) for SARS-CoV-2 specific IgG detection will provide a reliable and affordable immunoassay for the rapid serosurveillance against COVID-19. Method: SARS-CoV-2 antigens were immobilized on nitrocellulose membrane to capture IgG immunoglobulins, which were then detected with AuNP anti-human IgG. A total of 181 samples were characterized with in-house and commercial immunoassay. The positive panel consisted of RT-PCR positive samples from patients with both <14 days and >14 days from the onset of symptoms, while the negative panel contained samples collected either from the pre-pandemic era dengue patients from healthy donors during the pandemic period. Results: In-house ELISA selected a total of 79 true seropositive and 100 seronegative samples. The sensitivity of samples with <14 days using FT-DBA was 94.7% which increased to 100% for samples >14 days. The overall detection sensitivity and specificity were 98.8% and 98%, respectively, whereas the overall PPV and NPV were 97.6% and 99%. Moreover, comparative analysis between ELISA and FT-DBA revealed clinical agreement of Cohen’s Kappa value of 0.944. Conclusion: The assay can confirm past SARS-CoV-2 infection with high accuracy within 2 minutes compared to ELISA. It can help track SARS-CoV-2 disease progression, population screening, and vaccination response.

A global event such as the COVID-19 crisis presents new, often unexpected responses that are fascinating to investigate from both, scientific and social standpoints. Despite several documented similarities, the Coronavirus pandemic is clearly distinct from the 1918 flu pandemic in terms of our exponentially increased, almost instantaneous ability to access/share information, offering an unprecedented opportunity to visualise rippling effects of global events across space and time. Personal devices provide “big data” on people’s movement, the environment and economic trends, while access to the unprecedented flurry in scientific publications and media posts provides a measure of the response of the educated world to the crisis. Most bibliometric (co-authorship, co-citation, or bibliographic coupling) analyses ignore the time dimension, but COVID-19 has made it possible to perform a detailed temporal investigation into the pandemic. Here, we report a comprehensive network analysis based on more than 20000 published documents on viral epidemics, authored by over 75,000 individuals from 140 nations in the past one year of the crisis. In contrast to the 1918 flu pandemic, access to published data over the past two decades enabled a comparison of publishing trends between the ongoing COVID-19 pandemic and those of the 2003 SARS epidemic, to study changes in thematic foci and societal pressures dictating research over the course of a crisis.

Purpose: The ongoing COVID-19 crisis has created the need for social distancing between medical staff and patients, therefore, healthcare robotics is increasingly important as regards infectious control. The purpose of this study was to design and fabricate a remote controlled transport robot that could provide an optimum technology base for developing countries, having dual functions of telepresence and delivery operations inside or outside buildings, is easy to assemble and also easily able to be cleaned using standard chemical agents.Methods: This machine was designed and fabricated to incorporate two main functions; delivery and telepresence. The robot consists of a base frame, DC motors for driving and steering systems, actuator motor for driving wheel elevation, Wi-Fi AP/Repeater, network camera, and a necessary a back-up power system.Results: This robot can be used both indoors and outdoors. It can carry loads of more than 80 kg. The machine can cross obstacles greater than 3 cm. It can be cleaned by disinfectant agents. An actuator motor can lift the driving wheels above the surface to prevent gear damage. Conclusion: This article demonstrates the concept of a healthcare telepresence and delivery robot that can provide distancing during the present COVID-19 crisis, using optimum technology for low and middle-income countries. In the future, the researcher should consider development of the delivery controls, combined with the telepresence system using the internet of things, to improve the navigation system, the manipulator system for supporting multi-floor transportation, and also other multi-functional purposes.

This study analyzes the relationship between the spread of the SARS-CoV-2 virus (COVID-19) and the mobility patterns of the Portuguese population. By reducing mobility, the idea is that contacts are reduced, countering the spread of the virus in the community. As an indicator of the spread of the virus, the reproduction number (Rt) was used. Data from Google's Community Mobility Reports was used to evaluate changes in mobility patterns. This report uses location data from Android mobile phone users. The locations are divided into retail and recreation, grocery and pharmacy, parks, transit stations, workplaces and residential. In this year of the COVID-19 crisis in Portugal, population mobility patterns have changed over the various phases of the pandemic. At first, all mobility was affected uniformly, with the population avoiding much of the activity outside the home. In a second phase, there was some adaptation, and the areas considered to be of lower risk had less impact, emphasizing the changes in the relationship between daily life and the workplace.

The worldwide spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has ubiquitously impacted many aspects of life. As vaccines continue to be manufactured and administered, limiting the spread of SARS-CoV-2 will rely more heavily on the early identification of contagious individuals occupying reopened and increasingly populated indoor environments. In this study, we investigated the utility of an impaction-based aerosol sampling system with multiple nucleic acid collection media. Heat-inactivated SARS-CoV-2 was utilized to perform bench-scale, short-range aerosol, and room-scale aerosol experiments. Through bench-scale experiments, AerosolSense Capture Media (ACM) and nylon flocked swabs were identified as the highest utility media. In room-scale aerosol experiments, consistent detection of aerosol SARS-CoV-2 was achieved at a concentration equal to or greater than 0.089 genome copies per liter of room air (gc/L) when air was sampled for eight hours or more at less than one air change per hour (ACH). Shorter sampling periods (~75 minutes) yielded consistent detection at ~31.8 gc/L of room air and intermittent detection down to ~0.318 gc/L at (1 and 6+ ACH respectively). These results support further exploration in real-world testing scenarios and suggest the utility of indoor aerosol surveillance as an effective risk mitigation strategy in occupied buildings.

Being a combination of the conference call, talkback radio, audio podcast, and an online video chat, Clubhouse is a new social networking app that gained over 10 million users and over $100 in valuation in just 8 months. Unlike other social networks, it offers a real-time streaming audio chat that does not ask users to share any unnecessary information like exchanging text messages, conducting video calls, or sharing photos. Instead, Clubhouse users can listen to real-time conversations, contribute to these conversations and create their own conversations for the others to listen and to interact with. Often nicknamed a “Silicon Valley’s hottest start-up”, Clubhouse positions itself as an “exclusive” and “alternative” social network that attracts various celebrities and people who just want to talk to each other. Launched in March 2020, amidst the COVID-19 pandemic with its social distancing and lockdowns, Clubhouse offered its users a space for the digital group psychotherapy where people could solve their problems by talking them through with strangers. However, it is unclear what is going to happen to this new social network in the post-pandemic world after all of its hype eventually evaporates. This paper discusses the possible underlying motives for the Clubhouse creation and its real purposes. Moreover, it looks at the three possible scenarios of its further development.

The first attempt to control and mitigate an epidemic outbreak caused by a previously unknown virus occurs primarily via non-pharmaceutical interventions (NPIs). In case of the SARS-CoV-2 virus, which since the early days of 2020 caused the COVID-19 pandemic, NPIs aimed at reducing transmission enabling contacts between individuals. The effectiveness of contact reduction measures directly correlates with the number of individuals adhering to such measures. Here, we illustrate by means of a very simple compartmental model how partial noncompliance with NPIs can prevent these from stopping the spread of an epidemic.

This study aims to understand the global environment of COVID-19 management and guide future policy directions after the pandemic crisis. To this end, we analyzed a series of the World Economic Forum’s COVID-19 response reports through text mining and network analysis. These reports, written by experts in diverse fields, discuss multidimensional changes in socioeconomic situations, various problems created by those changes, and strategies to respond to national crises. Based on 3,897 refined words drawn from a morphological analysis of 26 reports (as of the end of 2020), this study analyzes the frequency of words, the relationships among words, the importance of specific documents, and the connection centrality through text mining. In addition, network analysis helps develop strategies for sustainable response to and management of national crises through identifying clusters of words with a similar structural equivalence.

We report on the design, characterization and validation of a spherical irradiation system for inactivating SARS-CoV-2, based on UV-C 275 nm LEDs. The system is designed to maximize ir-radiation intensity and uniformity, and can be used for irradiating a volume of 18 liters. To this aim: (i) several commercially available LEDs have been acquired and analyzed; (ii) a complete optical study has been carried out in order to optimize the efficacy of the system. (iii) The re-sulting prototype has been characterized optically, and tested for the inactivation of SARS-CoV-2 for different exposure times, doses and surface types. Results indicate that a 99.9% inactivation can be reached after 1 minute of treatment with a dose of 83.1 J/m2.

During 2019, the number of patients suffering from cough, fever and reduction of WBC’s count increased. At the beginning, this mysterious illness was called “fever with unknown origin”. At the present time, the cause of this pneumonia is known as the 2019 novel coronavirus (2019-nCoV) or the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). The SARS-CoV-2 is one member of great family of coronaviruses. Coronaviruses can cause different kind of illnesses including respiratory, enteric, hepatic, and neurological diseases in animals like cat and bat. Coronaviruses are enveloped positive-stranded RNA viruses. The SARS-CoV-2 has some particular structures for binding to host cells, reproducing itself in cells and damaging human cells. The SARS-CoV-2 can bind angiotensin-converting enzyme 2 (ACE‐2) receptors and cause various difficulties for human. The SARS-CoV-2 can cause either not-serious issues like fever and cough or serious concerns such as multi-organ failure. Source(s) of SARS-CoV-2 is under debate. Malayan pangolin and bat are the most suspicious candidate for being sources of the SARS-CoV-2. The SARS-CoV-2 can be transmitted by various ways such as transmitting from infected human to healthy human and can make severe pneumonia, which can lead to death. The SARS-CoV-2 can infect different kind of people with different ages, races, and social and economic levels. The SARS‐CoV‐2 infection can cause various sorts of clinical manifestations like cough and fever and intensity of signs and symptoms depends on sufferer conditions. Clinicians use all of available documents and tests like laboratory, histopathological and radiological findings for diagnosing new cases and curing patients with high accuracy. At the present time, there is no particular way for treating SARS-CoV-2 infection; neither antiviral drugs nor palliative agents. It seems that the best way for standing against the SARS-CoV-2 infection is preventing from it by social distancing and vaccination. This review tries to prepare an essential brief update about SARS-CoV-2 infection for clinicians.

Based on comprehensible non-parametric methods, estimates of crucial parameters that characterise the COVID-19 pandemic with a focus on the German epidemic are presented. Where appropriate, the estimates for Germany are compared with the results for seven other countries (FR, IT, US, UK, ES, CH, BR) to get an idea of the breadth of applicability and a relational understanding. Thereby, only prevalence data of daily reported new counts of diagnosed cases and fatalities provided by the Johns Hopkins University are used. Drawing on uncertain a priori knowledge is avoided. Specifically, we present estimates resulting from delay-time correlations for the duration from diagnosis to death being 13 days for Germany and Switzerland. The delay-time correlation applied to time series from other countries exhibit less pronounced peaks suggesting high variabilities for the corresponding time-to-death durations. With respect to the German data, the two time series of new cases and fatalities exhibit a strong coherence within the frequency range of interest, which backs our findings. Furthermore, based on the knowledge of this time lag between diagnoses and deaths, properly delayed asymptotic as well as instantaneous fatality-case ratios are calculated having superiority compared to the commonly published case-fatality rate. The temporal median of the instantaneous fatality-case ratio with proper delay of 13-days between cases and deaths for Germany turns out to be 0.02. Time courses of asymptotic fatality-case ratios are presented for other countries which substantially differ during the first half of the pandemic, however, converge to a narrow range with standard deviation 0.57% and mean 2.4%. Additionally, the time courses of instantaneous fatality-case ratios with optimal delay for the 8 exemplarily chosen countries are calculated and compared by means of the temporal medians. Similarly to the asymptotic fatality-case ratios, the differences are much smaller than expected from mass media reports. The basic reproduction number, R₀, for Germany is estimated to be between 2.4 and 3.4. The uncertainty stems from uncertain knowledge of the generation time. A delay autocorrelation shows resonances at about 4 days and 7 days, where the latter resonance is at least partially attributable to the sampling process with weekly periodicity. The calculation of the basic reproduction number is based on an evaluation of cumulative numbers of cases yielding time-dependent doubling times as an intermediate step. This allows to infer to the reproduction number during the early phase of onset of the epidemic. In a second approach, the instantaneous reproduction number is derived from the incident (counts of new) cases and allows, in contrast to the first version, to infer to the temporal behaviour of the reproduction number during the later epidemic course. The time course of the reproduction number is compared to an alternative control measure given by the per capita growth, which largely confirms the conclusions drawn from the reproduction number. To conclude, by avoiding complicated parametric models we provide insights into basic features of the COVID-19 epidemic in an utmost transparent and comprehensible way. The perhaps most striking insight is that the fatality-case ratios do not differ between countries as much as previously suspected.

When all countries are battling Covid-19 by adopting different policies, it could help address the issue of government response policy efficiency. This study examines the efficiency of government intervention policies in 19 countries, the efficiency of preventing the spread, and also the mortality caused by the virus. The policies are categorized based on the Oxford COVID-19 Government Response Tracker, which combines various indicators, including Containment and closure, Economic response, and Health systems. Given that the governments apply a top-down approach to design these policies, the current research evaluates the efficiency of policies based on the same approach. Here, two different models have been used to calculate the efficiency of policies. We designed a combined index in both models and applied Window DEA method to determine the output quantities in the efficiency ratio. The results of our study show that in both models, Japan, Finland and Thailand had the highest level of government response efficiency. The countries with the lowest government response efficiency were the United States, Spain, and Russia in the first model, and China, Italy, and Spain in the second.

The aim of the present cross-sectional study was to analyze the differential impact of the first COVID-19 lockdown (3rd April 2020) on stress, health practices, and self-care activities across different Hispanic countries, age range and gender groups. 1082 participants from Spain, Chile, Colombia, and Ecuador took part in this study. Irrespective of the country, and controlling for income level, young people, especially females, suffered a greater level of stress, perceived the situation as more severe, showed less adherence to health guidelines and reported lower levels of health consciousness, in comparison to their male peers and older groups. However, in the case of self-care, it seems that older and female groups are generally more involved in self-care activities and adopt more healthy daily routines. These results are mostly similar between Colombia, Ecuador, and Spain. However, Chile showed some different tendencies, as males reported higher levels of healthy daily routines and better adherence to health guidelines compared to females and people over the age of 60. Differences between countries, genders and age ranges should be considered in order to improve health recommendations and adherence to guidelines. It would also be crucial to identify vulnerable groups to promote the adoption of health behaviors that may help in the development of effective public health strategies. Future studies should be addressed to explore the possible causations of such differences in more cultural-distant samples and at later stages of the current outbreak.

Before COVID-19, post-secondary learning was dominated by in-person, institution-organized meetings. With the March 12, 2020 lockdown, learning became virtual, largely dependent on commercial online platforms. Already more likely to experience anxiety and depression in re-lation to their research work, perhaps no students have endured more regarding the limitations imposed by COVID-19 on their mentorship and supervision than graduate students. The in-crease in mental health issues facing graduate students has come to the attention of their post-secondary institutions. Programs have been devised with the aim of reducing these chal-lenges. However, the additional attention and funds to combat depression and anxiety have not shown anticipated results. A new approach to mitigate anxiety and depression in graduate students through mentorship and supervision is warranted. Offered here is an award-winning model featuring self-directed learning in a community based on consensus decision-making where consensus represents the adding together of different points of view rather than agreement. The approach is non-hierarchical in structure, based in narrative research. The proposed model and approach are presented and limitations considered. This model and approach are offered as a likely solution to ebb the increase in anxiety and depression in graduate stu-dents—particularly in response to COVID-19.

With the arrival of SARS-CoV-2 vaccines, a new stage of the pandemic commenced, with new challenges ahead. During the coming months, countries will be implementing their COVID-19 vaccination programs depending on their implementation of vaccine availability and its prescription on risk stratification. Although children will not benefit from active immunization programs, now, with the beginning of the era of the anti-COVID19 vaccines, the suffering of children can no longer be ethically tolerated or neglected. The time has come to provide specific lasting strategies for children living in the COVID-19 era. Here we propose a child-focused indirect COVID-19 vaccination strategy.For better or worse, children depend on their natural caregivers (adults) and the rest of society for their well-being and achieving their full potential. We believe that including in the priority categories also those adults in close contact with children could ensure a safety net of child protection.A child-focused vaccination strategy would allow the faster return to "normality" for children and their families. Such an approach would not only enable the reopening and continuity of essential services for children but also would allow adults to return to their routine economic/productive activities.

The increasingly rapid flow of technological development is now a tool to improve backwardness, renew the system, as well as a means of improvement in various aspects of life. For companies, the development of information and communication technology is a new innovation or breakthrough to improve service quality. Various benefits provided by technology and information. However, if not handled properly, technology and information will become a boomerang for an organization. HRIS is the application of HRM functions in the application of information and communication technology. The concept of HRIS as a digital form of HRM is increasing along with the outbreak of the Covid-19 pandemic which has caused a large loss impact on all lines of life. The limitation of social interaction in an effort to prevent the wider spread of covid-19 and the higher number of casualties causes business activities to stall. This research uses quantitative methods with a study sample of 100 randomly selected. This study aims to see how clarity of high-tech goals in human resources management, perceived benefits, perceived ease of use, company conditions that can influence attitudes towards HRIS.

The outbreak of COVID-19 has had a major impact on people’s daily life. This study aimed to examine use of alcohol and addictive drugs during the COVID-19 outbreak and examine their association with mental health problems and problems related to the pandemic. A sample of 4527 persons responded to the survey. Use of alcohol and addictive drugs were cross-tabulated with sociodemographic variables, mental health problems and problems related to COVID-19. Logistic regression analyses were used to examine the strength of the associations. Daily use of alcohol was associated with depression and expecting financial loss in relation to the COVID-19 outbreak. Use of cannabis was associated with expecting financial loss in relation to COVID-19. Use of sedatives was associated with anxiety, depression, and insomnia. Use of painkillers was associated with insomnia and self-reported risk of complications if contracting the coronavirus. We conclude that the occurrence of mental health problems is more important for an understanding of the use of alcohol and addictive drugs during the COVID-19 outbreak compared to specific pandemic-related worries.

Taking advantage of tourists’ intensive flow, the SARS-CoV-2 virus rapidly spread causing thousands of deaths globally. Trying to contain the already pandemic virus, government travel restrictions were suddenly imposed. Consequently, the tourism industry, which at that moment employed one in ten workers globally, suddenly collapsed. Hundreds of thousands of workers immediately lost their income. Flights were cancelled, and thousands of tourists were stuck abroad with no means to return to their home countries. The gravity of the situation raised the question of whether there was scholarly knowledge that could have helped manage tourism during the current pandemic. To answer this question, a methodical literature review was performed, allowing for up to 900 publications to be analysed. Keywords used were pandemic, tourism, tourist and travel. Based on this process, 63 publications were selected for further analysis. Among these, less than 5% were focused on the tourism side of the problem. As such, this research concludes that, by the time the novel coronavirus emerged, there was, virtually, no scholarly knowledge on how to manage tourism during pandemic times so as to avoid chaos, and that the scholarly community studying related issues is very small. Moving forward, this article recommends that research funding agencies and universities encourage the sound development of this area of knowledge. Aspects that should be investigated include when, how and by whom should tourism be halted, as well as the feasibility of a Tourism World Fund for supporting related costs.

As consequence of COVID-19, millions of households suffered mobility restrictions and changes in their lifestyle during several months. The aim of this study was to evaluate the effects of COVID-19 home confinement in food habits, lifestyle and emotional balance of the Spanish population. This cross-sectional study used data collected via an anonymous online questionnaire during the last month before lockdown finished in Spain in a total of 675 participants. 38.8% of the respondents experienced weight gain while 31.1% lost weight during confinement. The increase in body weight was positively correlated with the age (Rs = 0.14, p &lt;0.05) and BMI (Rs = 0.20, p &lt;0.05). We also identified that 39.7% reported poorer quality sleep, it was positively correlated with BMI (Rs = -0.18, p &lt;0.05) and with age (Rs = -0.21, p &lt;0.05). 44.7% of the participants had not performed physical exercise during confinement with differences by sex (p &lt;0.05), by age (p &lt;0.05), by BMI (p &lt;0.05) and sleep quality (p &lt;0.05). According to emotional-eater questionnaire, 21.8% and 11% were classified as emotional eater and very emotional eater, respectively. We emphasize the importance of adopting a healthy lifestyle, as the COVID-19 pandemic nowadays is ongoing.

Background: Forecasting nonlinear stochastic systems most often is quite difficult, without giving in to temptations to simply simplify models for the sake of permitting simple computations. Objective: Here, two basic algorithms, Adaptive Simulated Annealing (ASA) and path-integral codes PATHINT/PATHTREE (and their quantum generalizations qPATHINT/qPATHTREE) are offered to detail such systems. Method: ASA and PATHINT/PATHTREE have been effective to forecast properties in three disparate disciplines in neuroscience, financial markets, and combat analysis. Applications are described for COVID-19. Results: Results of detailed calculations have led to new results and insights not previously obtained. Conclusion: These 3 applications give strong support to a quite generic application of these tools to stochastic nonlinear systems.

Rainwater harvesting could be an optional water source to fulfil the emergency water demand in different setups. The aim was to assess if the rainwater harvesting potential for households and selected institutions were sufficient to satisfy the emergency water demand for the prevention of COVID-19 in Dilla town, Southern, Ethiopia. Rain water harvesting potential for households and selected institutions were quantified using 17 years’ worth of rainfall data from Ethiopian Metrology Agency. With an average annual rainfall of 1464 mm, households with 40 and 100 m2 roof sizes have a potential to harvest between 15.71-31.15 m3 and 41.73-82.73 m3 of water using Maximum Error Estimate. Meanwhile 7.2-39.7 m3 and 19.11-105.35 m3 of water can be harvested from the same roof sizes using Coefficient of Variation for calculation. Considering mean monthly rainfall, the health centres and Dilla University can attain 45.7% and 77% of their emergency water demand, while the rest of the selected institutions in Dilla Town can attain more than 100 % of their demand using only rainwater. Rain water can be an alternative water source for the town in the fight against COVID-19.

As the number of infections and deaths caused by the recent COVID-19 pandemic is increasing dramatically day-by-day, scientists are rushing towards developing possible counter-measures to fight the deadly virus, SARS-CoV-2. Although many efforts have already been put forward for designing and developing potential vaccines, however, most of them are proved to possess negative consequences. Therefore, in this study, the methods of immunoinformatics were exploited to design novel epitope-based subunit vaccine against the SARS-CoV-2, targeting four essential proteins of the virus i.e., spike glycoprotein, nucleocapsid phosphoprotein, membrane glycoprotein, and envelope protein. The highly antigenic, non-allergenic, non-toxic, non-human homolog and 100% conserved (across other isolates from different regions of the world) epitopes were used for constructing the vaccine. In total, fourteen CTL epitopes and eighteen HTL epitopes were used to construct the vaccine. Thereafter, several in silico validations i.e., the molecular docking, molecular dynamics simulation (including the RMSF and RMSD studies), and immune simulation studies were also performed which predicted that the designed vaccine should be quite safe, effective, and stable within the biological environment. Finally, in silico cloning and codon adaptation studies were also conducted to design an effective mass production strategy of the vaccine. However, more in vivo and in vitro studies are required on the predicted vaccine to finally validate its safety and efficacy.

COVID-19 and new concept, lockdown, change social life of all classes of humans. Children partially feel the changes of daily life and this situation has been children’s free mind. Children are under a new type of restriction imposed on them by their parents. Normally they prefer play with their their friends than study and always waiting for holidays. They heard a new jargon i.e. lockdown where everything stands still. Very often they see peoples in the roads and few vehicles are moving in the roads. However, a peculiar thing happens now that they sit in front of computer to hear the virtual classes that are taken by the teachers. This also happens when there is no lockdown since COVID-19 still affects people. The environment is totally changed and they do not find any proper answers from the parents about the scenario.This study has been made an attempt to carry out the mental affairs of children in West Bengal, India. Several families are surveyed for collecting responses mostly from rural areas as well as urban areas for the time-period from April, 2020 to July, 2020. An effort has been given in this paper to predict the stress, depression and anxiety faced by children during the COVID-19. A Deep Learning Neural Network (DLNN) based method is applied to understand the stress level, depression level and anxiety level amongst the children. A hybrid DLNN has been presented in this research that combines both Convolutional Layer and Gated-Recurrent Unit (GRU) for obtaining the prediction of the mental health of children. The model obtains an accuracy of 89.57% for defeminizing mental anxiety of children.

A probe of a patient, seeking help in an emergency ward of a French hospital in late December 2019 because of Influenza like symptoms, was retrospectively tested positive to COVID-19. Despite the early appearance of the virus in Europe, the prevalence and virulence appeared to be low for several weeks, before the spread and severity of symptoms increased exponentially, yet with marked spatial and temporal differences. Here, we compare the possible linkages between peaks of fine particulate matter (PM2.5) and the sudden, explosive increase of hospitalizations and mortality rates in the Swiss Canton of Ticino, and the Greater Paris and London regions. We also discuss the influence of Saharan dust intrusions on the COVID-19 outbreak observed in early 2020 on the Canary Islands. We find that high PM2.5 concentrations – possibly favored by air temperature inversions or Saharan dust intrusions – are not only modulating but even more so boosting severe outbreaks of COVID-19. We conclude that the overburdening of the health services and hospitals as well as the high over-mortality observed in various regions of Europe in spring 2020 can be linked to peaks of PM2.5 and likely particular weather situations that have favored the spread and enhanced the virulence of the virus. In the future, we recommend to monitor not only the prevalence of the virus, but also to consider the occurrence of weather situations that can lead to sudden, very explosive COVID-19 outbreaks.

The pandemic of coronavirus disease (COVID-19), a disease caused by severe acute respiratory syndrome coronavirus 2 (SARSCoV-2), is causing substantial morbidity and mortality. Older age and presence of diabetes mellitus, hypertension and obesity significantly increases the risk for hospitalization and death in COVID-19 patients. In this Perspective, informed by the studies on SARS-CoV-2, Middle East respiratory syndrome (MERS-CoV), and the current literature on SARS-CoV-2, we discuss potential mechanisms by which diabetes modulates the host-viral interactions and host-immune responses. We hope to highlight gaps in knowledge that require further studies pertinent to COVID-19 in patients with diabetes mellitus, hypertension and obesity.

A patient will visit physicians when he/she feels ill. This illness is not for COVID-19 but it is a general tendency of human being to visit doctor probably it can not be controlled by general drug. When a patient comes to a doctor, the doctor examines him/her after knowing his/her problem. The physician always asks him/her about some questions related to him/her daily life. For example, if a young male patient comes to a doctor with a symptom of fever and cough, the first question doctor asked him that he has a habit of smoking. Then doctor asks him whether this type of symptom appeared often to him previously or not. If the answers of both questions are yes, then the first one is habit and the second one is that he may suffering from some serious disease or a disease due to the weather. The aim of this paper is to consider habit of the patient as well as he/she has been affected by a critical disease. This information is used to build a model that will predict whether there is any possibility of his/her being affected by COVID-19. This research work contributes to tackle the pandemic situation occurred due to Corona Virus Infectious Disease, 2019 (Covid-19). Outbreak of this disease happens based on numerous factors such as past health records and habits of patients. Health records include diabetes tendency, cardiovascular disease existence, pregnancy, asthma, hypertension, pneumonia; chronic renal disease may contribute to this disease occurrence. Past lifestyles such as tobacco, alcohol consumption may be analyzed. A deep learning based framework is investigated to verify the relationship between past health records, habits of patients and covid-19 occurrence. A stacked Gated Recurrent Unit (GRU) based model is proposed in this paper that identifies whether a patient can be infected by this disease or not. The proposed predictive system is compared against existing benchmark Machine Learning classifiers such as Support Vector Machine (SVM) and Decision Tree (DT).

COVID-19 pandemic event requires a rapid response from various organizations at the international and national levels. One important response is the provision of information sharing facilities and monitoring of the spread of cases around the world, JHU CSSE developed the Dashboard in January 2020 and followed by WHO the same month for the WHO COVID-19 dashboard. Both dashboards have distributed information as expected by the user with their respective pros and cons. JHU CSSE Dashboard provides faster information with good access to mobile device users even though the display and color selection are less attractive. Information on the WHO COVID-19 Dashboard is often late but more data appearances and variations and comparisons between countries can be made. In the Indonesian context, ESSC for COVID-19 Geoportal as Esri Indonesia initiative has been developed with the support of data and information from various parties and developed with the principles of big data management which are fully supported by adequate spatial portal developer software from Esri. Particularly in Indonesia, there is not yet an adequate system to support spatial based decision making at the local level, therefore the development of a GIS dashboard to support provincial and district governments is highly recommended.

Seven human coronaviruses (hCoVs) are known to infect humans. The most recent one, SARS-CoV-2, was isolated and identified in January 2020 from a patient presenting with severe respiratory illness in Wuhan, China. Even though viral coinfections have the potential to influence the resultant disease pattern in the host, very few studies have looked at the disease outcomes in patients infected with both HIV and hCoVs. Groups are now reporting that even though HIV-positive patients can be infected with hCoVs, the likelihood of developing severe CoV-related diseases in these patients is often similar to what is seen in the general population. This review aimed to summarize the current knowledge of coinfections reported for HIV and hCoVs. Moreover, based on the available data, this review aimed to theorize why HIV-positive patients do not frequently develop severe CoV-related diseases.

COVID-19 disease, caused by the SARS-CoV2 virus, is a potentially fatal disease that represents a serious public health and economic problem worldwide. The SARS-CoV2 virus infects the lower respiratory tract and can cause pneumonia in humans. ARDS is the leading cause of death in COVID-19 disease. One of the main characteristics of ARDS is the cytokine storm, an uncontrolled systemic inflammatory response resulting from the release of pro-inflammatory cytokines and chemokines and growth factors, by immune cells. The other important aspect of the disease is represented by the involvement of the vascular organ that undergoes endothelitis. Hyperinflammation and endothelitis contribute in various ways to trigger coagulation disorders with diffuse micro thrombotic and thromboembolic phenomena. Lastly, multiple organ failure may occur (MOF). Since so far there is no approved treatment, there is an urgent need to reposition known treatments, considered safe, to be included in trials. Naturally produced interferons represent the body's first line of defense against viruses. Pharmacological forms, obtained by means of genetic recombination techniques, have long been approved and used to treat numerous pathologies. Interferons are divided into three families, within which some subfamilies are distinguishable. Only IFN-II comprises a single isoform which has completely different aspects and functions. The IFN I and III, however, each comprise different subfamilies (17 subfamilies the IFN-I and 4 subfamilies the IFN-III), share many aspects, representing the body's first antiviral response, but play different roles. The use of IFNs has been studied in two severe hCoV (Human Coronavirus) diseases, closely related to COVID-19 disease, such as SARS and MERS. Numerous in vitro and in vivo studies have been conducted, often in combination with other antivirals. The results have been controversial. The positive results in vitro and in experimental animals were often not replicable in humans. The possible positioning of these molecules in the right window of therapeutic opportunity requires that the complex dialogue between IFN, inflammasome, cytokines, pro-inflammatory chemokines, growth factors and barrier function be shed light.

SARS-CoV-2 virus infections in humans were first reported in December 2019, the boreal winter. The resulting COVID-19 pandemic was declared by the WHO in March 2020. By July 2020 COVID-19 is present in 213 countries and territories, with over 12 million confirmed cases and over half a million attributed deaths. Knowledge of other viral respiratory diseases suggests that the transmission of SARS-CoV-2 could be modulated by seasonally-varying environmental factors such as temperature and humidity. Many studies on the environmental sensitivity of COVID-19 are appearing online, and some have been published in peer-reviewed journals. Initially, these studies raised the hypothesis that climatic conditions would subdue the viral transmission rate in places entering the boreal summer and that southern hemisphere countries would experience enhanced disease. For the latter, the COVID-19 peak would coincide with the peak of the influenza season, increasing misdiagnosis and placing an additional burden on health systems. In this review, we assess the evidence that environmental drivers are a significant factor in the trajectory of the COVID-19 pandemic, globally and regionally. We critically assessed 42 peer-reviewed and 80 preprint publications that met qualifying criteria. Since the disease has been prevalent for only half a year in the northern, and a quarter of a year in the southern hemisphere, datasets capturing a full seasonal cycle in one locality are not yet available. Analyses based on space-for-time substitutions, i.e. using data from climatically distinct locations as a surrogate for seasonal progression, have been inconclusive. The reported studies present a strong northern bias. Socio-economic conditions peculiar to the ‘Global South’ have been omitted as confounding variables, thereby weakening evidence of environmental signals. We explore why research to date has failed to show convincing evidence for environmental modulation of COVID-19, and discuss directions for future research. We conclude that the evidence thus far suggests a weak modulation effect, currently overwhelmed by the scale and rate of the spread of COVID-19. Seasonally-modulated transmission, if it exists, will be more evident in 2021 and subsequent years.

Background: The antimalarial drug chloroquine and antimicrobial drug azithromycin have received significant attention during the current COVID-19 pandemic. Both drugs can alter cardiac electrophysiology and have been associated with drug-induced arrhythmias. Meanwhile, sympathetic activation is commonly observed during systemic inflammation and oxidative stress (e.g., in SARS-CoV-2 infection), and may influence the electrophysiological effects of chloroquine and azithromycin. Here, we investigated the effect of beta-adrenergic stimulation on proarrhythmic properties of chloroquine and azithromycin using a detailed in silico model of ventricular electrophysiology. Methods: Concentration-dependent chloroquine and azithromycin-induced alterations in ion-channel function were incorporated into the Heijman canine ventricular cardiomyocyte model. Single and combined drug effects on action-potential (AP) properties were analyzed using a population of 592 models accommodating inter-individual variability. Sympathetic stimulation was simulated by an increase in pacing rate and experimentally validated isoproterenol-induced changes in ion-channel function. Results: At 1 Hz pacing, therapeutic doses of chloroquine and azithromycin (5 and 20 µM, respectively) individually prolonged AP duration (APD) by 33% and 13%. Their combination produced synergistic APD prolongation (+161%) with incidence of proarrhythmic early afterdepolarizations in 53.5% of models. Increasing the pacing frequency to 2 Hz shortened APD and together with 1 µM isoproterenol corrected the drug-induced APD prolongation. No afterdepolarizations occurred following increased rate and simulated application of 0.1-1 µM isoproterenol. Conclusion: Sympathetic stimulation limits chloroquine- and azithromycin-induced proarrhythmia by reducing their APD-prolonging effect, suggesting the importance of heart rate and autonomic status monitoring in particular conditions (e.g., COVID-19).

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.

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.

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.

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 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.

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.

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: 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.

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.

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.

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.

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.

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.