Several epidemiological models are being used around the world to project the number of infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate prediction models is of utmost importance to take proper actions. Due to a high level of uncertainty or even lack of essential data, the standard epidemiological models have been challenged regarding the delivery of higher accuracy for long-term prediction. As an alternative to the susceptible-infected-resistant (SIR)-based models, this study proposes a hybrid machine learning approach to predict the COVID-19 and we exemplify its potential using data from Hungary. The hybrid machine learning methods of adaptive network-based fuzzy inference system (ANFIS) and multi-layered perceptron-imperialist competitive algorithm (MLP-ICA) are used to predict time series of infected individuals and mortality rate. The models predict that by late May, the outbreak and the total morality will drop substantially. The validation is performed for nine days with promising results, which confirms the model accuracy. It is expected that the model maintains its accuracy as long as no significant interruption occurs. Based on the results reported here, and due to the complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research.

The Coronavirus disease 2019 (COVID-19) pandemic is clearly taking a firmer grip on South Africa and more podiatrists will face the potential transmission of SARS-CoV-2. Government response was swift with the implementation of a travel ban, strict national lockdown as well as social distancing and hygiene protocols in line with international health regulations. Co-morbidities such as tuberculosis and HIV/AIDS, endemic to South Africa, are considered a dangerous combination with COVID-19, making many South Africans vulnerable to contracting the COVID-19. Patients with diabetes as well as the aged are vulnerable, both in terms of potential combined complications and challenges in continuity in foot care. The demands of the pandemic may outstrip the ability of the health systems to cope. Should this time arrive, all healthcare practitioners, including podiatrists, would have to step in and take on a role beyond their scope of practice in order to ensure that the healthcare system does not get overwhelmed. It is important for podiatrists to keep abreast with the developments around the COVID-19, in order that they may institute appropriate clinical practice which will ensure maximum protection for themselves, staff and patients as well as providing quality foot health care.

This study aims to identify benefits and barriers to distance education, particularly from the perspective of teachers in Saudi Arabia. As the applied data collection tool, a questionnaire was distributed to the general education teachers in three districts. The sample size of the study was 1076 teachers. The results revealed that despite several benefits gained from distance learning, there are also some barriers. Teachers found that the most important advantage in distance learning is the acquisition of technical skills during the online teaching processes, they learn more and use digital education platforms, they have sufficient time to prepare the scientific content, they were able to provide adequate technical solutions for their courses, and they have the opportunity to use multiple media to deliver their courses. With the introduction of distance learning, teachers have explored new ways to deliver course contents to students. It has fostered better ways to provide more interactive real-time and on-demand teaching and learning using modern technology, thus, helping teachers become familiar with the use of electronic resources. It seems that teachers invest in technical methods to enhance students’ performance. Also, teachers reported some obstacles that they face during remote teaching. Most of these problems are connection problems applied with devices and the internet, lack of students’ motivation to learn in distance, problems associated with urban learners.

In December 2019, an animal human coronavirus transmission occurred in Wuhan, China. A state of global pandemic was shortly declared, among a very rapid contagious spread of the virus. The causative virus was identified as SARS CoV 2 virus and is genetically related to the previous SARS outbreak in 2003. The virus causes wide clinical spectrum from mild flu like symptoms to adult respiratory distress syndrome. Kidney involvement has been reported in several reports in patients with various degrees of severity of SARS CoV2 infection. As knowledge is evolving, the accurate incidence of AKI is not known. Many questions are yet to be answered as regards the effect of epidemiological variables and comorbidities on the occurrence of AKI. Some reports have observed the occurrence of hematuria and proteinuria in a percentage of infected patients. Moreover, chronic kidney disease has not been found in some reports to add to the adverse outcomes, an aspect that merits further exploration. Patients on regular hemodialysis may be vulnerable to contagion due to lower status of immunity and need for frequent attendance to healthcare facilities. Due to the previous factors, prevention and mitigation of SARS CoV2 virus in this vulnerable population constitutes a major challenge.

This article investigated whether the atmospheric temperature had any role in the spread and vulnerability to COVID-19 worldwide and how that knowledge can be utilized to contain the fast-spreading disease. It highlighted that temperature was an important factor in transmitting the virus, and a moderately cool environment was the most favourable state for its susceptibility. In fact, the risk from the virus is reduced significantly in high temperature environment. Warm countries and places were likely to be less vulnerable. We identified various degrees of vulnerability based on temperature and specified countries for March and April. The maximum reported case, as well as death, was noted when the temperature was in the range of around 275°K (2°C) to 290°K (17°C). Countries like the USA, UK, Italy and Spain belonged to this category. The vulnerability was moderate when the temperature was less than around 275°K (2°C) and countries in that category were Russia, parts of Canada and few Scandinavian countries. For temperature 300°K (27°C) and above, a significantly lesser degree of vulnerability was noted. Countries from SAARC, South East Asia, the African continent and Australia fell in that category. In fact, when the temperature was more than 305°K (32°C), there was a unusually low number of reported cases and deaths. For warm countries, further analyses on the degree of vulnerability were conducted for the group of countries from SAARC and South East Asia and individual countries were compared. We also showed countries can switch from one vulnerability state to another based on the variability of temperature. We provided maps of temperature to identify countries of different vulnerability states in different months of the year. That influence of temperature on the virus and previous results of clinical trials with similar viruses gave us a useful insight that regulating the level of temperature can provide remarkable results to arrest and stop the outbreak. Based on that knowledge, some urgent solutions are proposed, which are practically without side effects and very cost-effective too.

The COVID-19 pandemic is placing unprecedented stress on healthcare systems around the world. Although Radiation Oncology Departments are not at the frontline of fighting this infectious disease, it is important to implement COVID-19 policies to reduce risk of staff and patient exposure, and to limit the risk of department shutdown or downtime. This brief report describes the policy implemented at George Washington University Radiation Oncology to manage the risks of COVID-19. This includes a General Statement related to the priorities of the Radiation Oncology department, a screening procedure for new and follow-up patients, management policies for critical and non-critical patients with COVID-19 or under quarantine, a policy for the management of patients currently under treatment who are diagnosed or placed in quarantine, a clinical escalation action plan, guidelines for staff meetings and travel, and procedure management. This policy was implemented at George Washington University Radiation Oncology after the first case of COVID-19 was reported in Washington DC on March 7, 2020.

The current Coronavirus Disease 19 (COVID-19) pandemic, caused by the SARS-CoV-2 virus, is unprecedented in recent history and threatens the lives and livelihoods of billions worldwide. The rapid spread and lack of modern parallels have left governments, health agencies, and the public racing to understand how to best mitigate and ultimately suppress the pandemic, but we are still working to understand the strengths and weaknesses of various interventions at our disposal. Few issues have been as contentious as the public use of face masks to control the pandemic’s spread. There is ongoing debate about their effectiveness, but an increasing body of evidence suggests that masks could be a useful in preventing the spread of coronavirus, leading several governments and health agencies to review and revise their policies. Here, we review the theory and evidence behind use of masks. The theory behind masks is that they prevent the spread of viral particles by infected persons, and inhalation of viral particles by uninfected persons. Even assuming masks are not 100% effective in preventing infection, they may reduce severity of infection by reducing viral dosing. Laboratory studies suggest masks may be effective in stopping both exhalation and inhalation of viral particles. However, real-world studies provided limited evidence for the use of masks in controlling influenza transmission and highlight potential problems associated with their misuse, such as poor compliance or improper use. Evidence for efficacy of face masks against the first SARS virus, SARS-CoV-1, implies that they may be effective against the current outbreak of SARS-Cov-2 virus. This is important as mathematical modeling suggests that even small reductions of in transmission rates can make a large difference over time, potentially slowing the pace of viral pandemics and limiting their spread. Perhaps the strongest argument for the use of masks is that countries with early adoption of masks have tended to see flatter pandemic curves, even without strict nationwide lockdowns. There is little evidence that respirators are more effective than surgical masks, but this may be due to misuse or poor compliance. Studies suggest some non-medical masks perform on par with medical masks. Improvised masks are less effective than medical masks, but may provide better protection than nothing at all. While many governments now encourage the use of improvised face coverings, more will need to be known about material, design, and who needs to wear masks, and when, to ensure effectiveness. Proper use of masks will also be important; if masks are used improperly or infrequently they may provide limited protection. It is important that public health policy makers consider the debate and the potential of masks as part of multi-faceted coronavirus control strategies.

The outbreak of COVID-19 started in mainland China and has rapidly spread to more than 200 countries and territories around the world (WHO, 2020). The new coronavirus is a respiratory virus and its transmission is known to occur by upper respiratory secretions, including airborne droplets after coughing or sneezing. There is no evidence to support the role of food in the transmission of COVID-19. However, sharing food in public places is not encouraged. Furthermore, standard operating procedures of food safety like thorough washing, avoid cross contamination, keeping raw and cooked foods separated, refrigeration and heating are highly suggested. The pandemic has dramatically increased food insecurity across the countries and threatens the food security and nutrition of millions of people. The review presents information about SARS-CoV-2 with respect to food, including a brief history of coronavirus, its classification and transmission. It further presents the role of food as a carrier of the virus, which looks unlikely so far but cannot be fully ruled out, food contamination and handling followed by prevention and safety measures as per the standard guidelines, and conclusive remarks.

The recently emerged coronavirus named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS- CoV-2) is the newest threat to human health. It has already infected more than half a million people worldwide, leading to a lot of deaths. Although it causes mild flu-like disease in most patients, lethality may increase to more than 20% in elderly subjects, especially those with comorbidities, like hypertension, diabetes or lung and cardiac disease, and the mechanisms are still elusive. Common symptoms at the onset of illness are fever, cough, myalgia or fatigue, headache, and diarrhea or constipation. Interestingly, respiratory viruses have also placed themselves as relevant agents for CNS pathologies. Here we discuss several CNS related features, referred by several patients, especially at the beginning of the disease. Thus, we also discuss the possibility by which SARS-CoV-2 may affect the olfactive system of patients, either directly or indirectly.

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

The Gauss model for the time evolution of the first corona pandemic wave rendered useful in the estimation of peak times, amount of required equipment, and the forecasting of fade out times. At the same time it is probably the simplest analytically tractable model that allows to quantitatively forecast the time evolution of infections and fatalities during a pandemic wave. In light of the various descriptors such as doubling times and reproduction factors currently in use to judge about lock-downs and other measures that aim to prevent spreading of the virus, we hereby provide both exact, and simple approximate relationships between the two relevant parameters of the Gauss model (peak time and width), and the transient behavior of two versions of doubling times, and three variants of reproduction factors including basic reproduction numbers.

Background: The COVID-19 pandemic is the global public health emergency concern and had an impact on the day to day life of individuals. Its effect on an individual’s mental health is significant to the extent of suicide. Objective: This study aimed to assess the magnitude of psychological problems and their associated factor among communities living in Dilla town in response to the pandemic. Methods: From Apr 1- Apr 15, 2020, a community-based cross-sectional study was conducted using multi-stage sampling techniques. Self-administered the questioner, Depression, Anxiety and Stress Scale (DASS-21), and logistic regression analysis (95% CI, p-value <0.05) was used. Results: This study included 445 respondents with a 94% non- response rate who was living in Dilla town. In total, 34.4% of respondents had a psychological problem (11.4 % mild and 23% moderate level of the psychological problem). Female, Greater secondary level of education, monthly income below 500 ETB, more than three family size, and wearing face mask were variables associated with the outcome variable (p < 0.05). Conclusions: Nearly one-third of the respondents had mild to moderate psychological among communities living in Dilla town. There is a need for mental health support on those identified groups of peoples to enhance their resilience in response to the pandemic.

Coronaviruse disease (COVID-19) outbreak has created an emergency globally, and social distancing and isolation is the only solution to prevent its spread. Several countries have announced fully locked on to tackle this pandemic. The recent COVID-2019 has shaken the globe with incidence cases of more than half-million cases, and a mortality toll of more than twenty thousand to date. The coronavirus family is inclusive of pathogen of both – animal species and humans, encapsulating the isolated severe acute respiratory syndrome coronavirus (SARS-CoV). Researchers round the globe have been dexterously working to decode this lethal virus. Many mathematical frameworks have also been depicted which have helped to understand the dynamics of the COVID-19. Research on coronaviruses continues to explore various aspects of viral replication and pathogenesis to understanding the predilection of these viruses to switch between species, to develop an infection in a new host, and to identify significant reservoirs of coronaviruses will dramatically aid in our potential to prophesize when and where potential epidemics may occur. Many of the non-structural and accessory proteins encoded by the viruses remain unclear and unknown. This systematic review highlights the current situation of the pandemic, virus genomic composition, pathogenesis, symptomatology, diagnosis, and prognosis along with mathematical models of disease transmission and dynamics.

It is no news that the COVID–19 pandemic has affected many persons in different ways. As the number of reported cases rises across the globe, efforts are geared towards production and administration of effective vaccines for the disease. However, many developing countries are faced with the dilemma of how to slow the spread and flatten the curves of the disease as the available vaccines are not enough. Interestingly, the dynamics of the disease can be analysed to get useful insights to enhance the making of suitable preventive policies that will slow the spread, ultimately flatten the curves of the disease and also help in managing any future occurrence. In this work, the aim is to analyse the dynamics, and estimate the basic reproduction number of the second wave of the pandemic in Nigeria using a Susceptible-Infected-Recovered-Deceased (SIRD) compartmental–based model. The dynamics of the disease is described by a system of nonlinear ordinary differential equations. The model takes into consideration the current control policies in place - social distancing, mask usage, personal hygiene and quarantine. Available data provided by Nigeria Centre for Disease Control (NCDC), World Health Organization (WHO) and Wolfram Data Repository were used for the computations. The Quasi–Newton algorithm was implemented in fitting the proposed model to the available data and a sensitivity analysis was presented. Major parameters - effective contact rate, average recovery time, average mortality rate, and overall effectiveness of the control policies - influencing the dynamics of the disease, and the basic reproduction numbers were estimated. The turning points of the disease during the second wave were also obtained. The proposed model gave estimated values for the parameters influencing the spread of the disease. Also, the measure of the overall effectiveness of the current control policies gave insight into how effective the measures are.

COVID-19 Pandemic management has become the top priority of Government Institutions globally, which is justifiable seeing the high mortality of the disease. In India, Lockdowns by National, State and Local level administrations have greatly reduced the spread of the SARS COV-2 Virus. Some areas with a greater proportion of COVID-19 patients have been declared hotspots with increased restrictions on public activities through law enforcement. But quite often delay in identification of these hotspots leads to community transmission of the Virus thus aggravating the problem. A method to identify the areas which are at risk of becoming the next hotspot for the disease is the need of the hour[1]. In this Research document we will find the probable risk factors and make an appropriate scale to measure the vulnerability of an area, identified by its Postal code. To help with this a Pan India survey by the title of “Survey on General Indian population on the level of preparedness for COVID-19 pandemic” was launched and received around 1250 submissions, with the acquired data we will evaluate the risk factors and make appropriate scale to identify ‘pre-hotspots’.

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

Background We intend to examine whether the COVID-19 outbreak influences medical decision-making (MDM) among Non-COVID patients. Method We recruit 287 patients who admit to ER department due to cardiovascular complaints. Anxiety level was measured using three questionnaires (GAD-7, Beck Inventory, and the cardiac anxiety questionnaire). A fourth survey was designed to assess MDM considerations. Results 64% of patients were male (median age 54). Almost half of the patients were found to have moderate to severe levels of anxiety.79.3% of patients reported that the outbreak influenced their MDM. 44.5% of patients sought medical care 2-3 from the onset of symptoms. Coronary artery disease was found in only 26 patients (9.1%). Almost half of the patients stated that they would have gone earlier if not for the current pandemic. Conclusion Non-COVID patients seeking medical care had a high anxiety level that directly affected decision-making and put them at unnecessary risk.

The COVID-19 outbreak and the sudden lockdown of society in March 2020 had a large impact on people’s daily life and gave rise to concerns for the mental health in the general population. The aim of the study was to examine post-traumatic stress reactions related to the COVID-19 pandemic, the prevalence of symptom-defined post-traumatic stress disorder (PTSD), and factors associated with post-traumatic stress in the Norwegian population during the early stages of the COVID-19 outbreak. A survey was administered via social media channels, to which a sample of 4527 adults (≥18 years) responded. Symptom-defined PTSD was measured with the PTSD Checklist for the DSM-5. The items were specifically linked to the COVID-19 pandemic. We used the DSM-5 diagnostic guidelines to categorize participants as fulfilling the PTSD symptom criteria or not. Associations with PTSD were examined with single and multiple logistic regression analyses. The prevalence of symptom-defined PTSD was 12.5% for men and 19.5% for women. PTSD was associated with lower age, female gender, lack of social support, and a range of pandemic-related variables such as economic concerns, expecting economic loss, having been in quarantine or isolation, being at high-risk for complications from COVID-19 infection, and having concern for family and close friends. In conclusion, posttraumatic stress reactions were common in the Norwegian population in the early stages of the COVID-19 outbreak. Concerns about finances, health, and family and friends seem to matter.

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

There are many types of coronavirus on the bases of important hosts including human, rat, turkey, rabbit, etc. The virus looks like a crown or corona of the sun with its round projection, spike. Now a day, newly emerged coronavirus disease (COVID 19) was first detected at Wuhan, China in December 2019 and it became a public health emergency international concern. Although a couple of researches has been conducting, much secretes of the virus and disease is still not understood and not reached a common understanding yet. However, sharing basic information is crucial based on the existing published research articles and updated information. Therefore, this review aimed to draw attention to the COVID 19 pandemic facts, opportunities, and challenges based on up to date information on cases in Ethiopia. Accordingly, the coronavirus is a single-stranded, non-segmented RNA genome virus. Two third of the genome (5'end) consists of two genes that code nonstructural proteins and the other 2-7 genes (3' end) code structural proteins including spike, envelope, membrane, and nucleocapsid. The virus transmits from animal to human and suggested as it might be originated from a bat and/or seafood. Coronavirus transmit human to human by direct contact and droplets during coughing and sneezing and common symptoms like fever, dry cough, and tiredness, short breathing, etc. can be seen from the patient. So that stay at home and social distancing are the most practicing pre-prevention methods. The disease causes high economic loss, face to face education closure, community cultural practice, and mass gathering activities are prohibited. However, various charity associations and creativities found increase than before. To this end, peoples should accept and follow governmental advice and instructions to escape from the pandemic.

The coronavirus (COVID-19) pandemic limitations may negatively affect children and youth in terms of health behaviors, and it might be especially challenging for children who are diagnosed with neurodevelopmental disorders such as children and youth diagnosed with Autism Spectrum Disorder (ASD). The present study assessed alterations in physical activity, screen time, and sleep duration of ASD children and the prevalence of meeting the 24-hour movement guidelines during the COVID-19 outbreak. Forty-six Arab Israeli mothers of children with ASD were surveyed by an online cross-sectional survey. As reported by the mothers, the results show a significant decrease in physical activity, a significant increase in screen time, and a significant increase in sleep duration during the COVID-19 pandemic. Moreover, the proportion of the sample who gained the physical activity and screen time recommendations lessened while the percentage of children who met the sleep duration guidelines increased. The prevalence of ASD children who achieved the overall 24-hour movement guidelines was very small during the COVID-19 outbreak. The outcomes extend the body of knowledge regarding the negative effects of the COVID-19 pandemic on children diagnosed with neurodevelopmental disorders and highlight the need for instant healthcare and interventions and programs for children with ASD.

After the appearance of first cases of ‘pneumonia of unknown origin’ in the Wuhan city, China, during late 2019, the disease progressed fast. Its cause was identified as a novel coronavirus, named provisionally 2019-nCoV. Subsequently, an official name was given as SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) by the International Committee on Taxonomy of Viruses (ICTV) study group. The World Health Organization (WHO) named the Coronavirus disease-2019 as COVID-19. The epidemics of COVID-2019 have been recorded over 113 countries/territories/areas apart from China and filched more than 4292 humans, affecting severely around 1,18,326 cases in a short span. The status of COVID-2019 emergency revised by the WHO within 42 days from Public Health International Emergency (January 30, 2020) to a pandemic (March 11, 2020). Nonetheless, the case fatality rate (CFR) of the current epidemic is on the rise (between 2-4%), relatively is lower than the previous SARS-CoV (2002/2003) and MERS-CoV (2012) outbreaks. Even though investigations are on its way, the researchers across the globe have assumptions of animal-origin of current SARS-CoV-2. A recent case report provides evidence of mild COVID-2019 infection in a pet dog that acquired COVID-2019 infection from his owner in Hong Kong. The news on travellers associated spread across the globe have also put many countries on alert with the cancellation of tourist visa to all affected countries and postponement of events where international visits were required. A few diagnostic approaches, including quantitative and differential real-time polymerase chain reaction assays, have been recommended for the screening of the individuals at risk. In the absence of any selective vaccine against SARS-CoV-2, re-purposed drugs are advocated in many studies. This article discourse the current worldwide situation of COVID-2019 with information on virus, epidemiology, host, the role of animals, effective diagnosis, therapeutics, preventive and control approaches making people aware on the disease outcomes.

Loneliness was one of the most prominent emotional experiences during social distancing due to the COVID-19 pandemic. This article aims to shed light on the experiences of loneliness and its relationship with mental health of adolescents in the Da Nang City during the COVID-19 pandemic. Data were collected online in early 2023 after 18 months Da Nang lifted its lockdown. The Strength and Difficulties Questionaire, the Multidimensional Scale of Perceived Social Support and the Negative Experience Scale were used to investigate loneliness among adolescents and effects of protective social factors. A total of 1,262 grade 6 to 12 students responded to the surveys. Results indicated that (1) loneliness was a more prominent emotion experienced by these adolescents during the COVID-19 lockdown; (2) factors contributing to loneliness were related to illness, social distancing, and a lack of care and attention from parents; (3) loneliness reported mostly was short in duration and mild at level, while there was a significant proportion of prolonged loneliness; and (4) Support from family and friends, however, could reduce the risk of mental health problems for the youngsters.

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.

With the rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that results in coronavirus disease 2019 (COVID-19), corporate entities, federal, state, county and city governments, universities, school districts, places of worship, prisons, health care facilities, assisted living organizations, daycares, homeowners, and other building owners and occupants have an opportunity to reduce the potential for transmission through built environment (BE) mediated pathways. Over the last decade, substantial research into the presence, abundance, diversity, function, and transmission of microbes in the BE has taken place and revealed common pathogen exchange pathways and mechanisms. In this paper, we synthesize this microbiology of the BE research and the known information about SARS-CoV-2 to provide actionable and achievable guidance to BE decision makers, building operators, and all indoor occupants attempting to minimize infectious disease transmission through environmentally mediated pathways. We believe this information is useful to corporate and public administrators and individuals responsible for building operations and environmental services in their decision-making process about the degree and duration of social-distancing measures during viral epidemics and pandemics.

In the context of the COVID-19 pandemic, countries around the world varied in the strength and timeliness of their responses. In Romania, specific challenges were faced with regards to managing the spread and limiting the impact of the disease, ranging from healthcare infrastructure to demographic and sociocultural aspects. As the country has a sizeable diaspora, major difficulties were faced when large numbers of individuals from highly affected areas returned to Romania. However, the fast implementation of control measures successfully averted a surge in the number of COVID-19 cases. This delayed the overburdening of an already challenged healthcare system during the initial phases of the epidemic. Furthermore, early control was facilitated by the exploitation of communication channels that penetrated all layers of society, from ordinary citizens to governmental authorities and high-ranking religious figures. The management of the COVID-19 crisis in Romania illustrates the importance of a fast initial response which takes into account the role played by sociocultural aspects in the context of an epidemic. As the challenges faced by Romania are not unique, these results could inform future public health strategies worldwide.

COVID-19 pandemic instigated a digital revolution in academia and higher education. Social distancing, months-long quarantine, as economic shutdown will help the majority of people working in academia and higher education not only to complete their personal transition to the fully functional and operational online tuition, but also to understand that online defences, online entrance and final exams, as well as online academic jobs are as effective and meaningful as those conducted “in real life”. Due to the crisis induced by the coronavirus epidemic, innovations in academia and higher education that would have normally taken several years due to the various contradictory administrative regulations are now introduced promptly in a matter of days. This is a clear example of the Schumpeterian ‘creative destruction’ in making that will forever change the status quo in academia and higher education.

In this article, the evolution in space and in time of the coronavirus pandemic is studied by utilizing a neural network with a self-organizing nature for the spatial analysis of data, and a fuzzy fractal method for capturing the temporal trends of the time series of the countries. Self-organizing neural networks possess the capability for clustering countries in the space domain based on their similar characteristics with respect to their coronavirus cases. In this form enabling finding the countries that are having similar behavior and thus can benefit from utilizing the same methods in fighting the virus propagation. To validate the approach, publicly available datasets of coronavirus cases worldwide have been used. In addition, a fuzzy fractal approach is utilized for the temporal analysis of time series of the countries. Then, a hybrid combination of both the self-organizing maps and the fuzzy fractal approach is proposed for efficient COVID-19 forecasting of the countries. Relevant conclusions have emerged from this study, that may be of great help in putting forward the best possible strategies in fighting the virus pandemic. A lot of the existing works concerned with the Coronavirus have look at the problem mostly from the temporal viewpoint that is of course relevant, but we strongly believe that the combination of both aspects of the problem is relevant to improve the forecasting ability. The most relevant contribution of this article is the proposal of combining neural networks with a self-organizing nature for clustering countries with high similarity and the fuzzy fractal approach for being able to forecast the times series and help in planning control actions for the Coronavirus pandemic.

The current COVID-19 pandemic is one of the most devastating events in recent history. The virus causes relatively minor damage to young, healthy populations, imposing life-threatening danger to the elderly and people with diseases of chronic inflammation. Therefore, if we could reduce the risk for vulnerable populations, it would make the COVID-19 pandemic more similar to other typical outbreaks. Children don’t suffer from COVID-19 as much as their grandparents and have a much higher melatonin level. Bats are nocturnal animals possessing high levels of melatonin, which may contribute to their high anti-viral resistance. Viruses induce an explosion of inflammatory cytokines and reactive oxygen species, and melatonin is the best natural antioxidant that is lost with age. The programmed cell death coronaviruses cause, which can result in significant lung damage, is also inhibited by melatonin. Coronavirus causes inflammation in the lungs which requires inflammasome activity. Melatonin blocks these inflammasomes. General immunity is impaired by anxiety and sleep deprivation. Melatonin improves sleep habits, reduces anxiety and stimulates immunity. Fibrosis may be the most dangerous complication after COVID-19. Melatonin is known to prevent fibrosis. Mechanical ventilation may be necessary but yet imposes risks due to oxidative stress, which can be reduced by melatonin. Thus, by using the safe over-the-counter drug melatonin, we may be immediately able to prevent the development of severe disease symptoms in coronavirus patients, reduce the severity of their symptoms, and/or reduce the immuno-pathology of coronavirus infection on patients’ health after the active phase of the infection is over.

This paper presents multidisciplinary and innovative research concerning fighting against coronavirus through wastewater collection and treatment. Studies suggest that coronavirus exists in the wastewaters. Untreated wastewater is proved to spread the virus. Coronavirus is attacking people globally and shrinking the economy. This paper highlights the idea that the coronavirus shall be defeated with the help of wastewater collection and treatment as well. The question addressed by this paper is will communities defeat the coronavirus without well-collected and treated wastewaters? This research aims to display the role of wastewaters in the spread of coronavirus in cities and to require their collection. The methods to achieve the goals are theoretical surveys, case study strategy, mathematical modeling, statistical procedures, forecasting of future, and dialectical discussions. The findings of this research demonstrate the need for carefully collected and treated wastewaters to overcome the coronavirus. This paper gives suitable techniques to collect and treat wastewater such as wastewater stabilization ponds, bacterial reactors, and anaerobic ponds. The innovative idea of this paper, its suggested indicators to select a certain wastewater treatment technique in every city, and its outcome will assist the global community to fight the coronavirus more effectively.

Background: Previous studies have found variable impact of the coronavirus disease 2019 (COVID-19) pandem-ic on the consumption of antimicrobial drugs in human medicine, with trends in several European countries differing between community and inpatient prescribing. Aim: This study analysed changes in the volumes and use density of antibacterial and antifungal drugs dis-pensed in acute care hospitals in Germany between 2019 and 2022. Methods: Surveillance data for the four years available from 279 hospitals, among them 272 for antifungals, were expressed as the total volumes of daily doses or as use density (daily doses per 100 patient/occupied bed days) per year and analysed descriptively, using recommended hospital-adapted daily dose definitions (RDD) and (as sensitivity analysis) WHO/ATC-defined daily dose definitions (DDD). Hospitals were stratified according to size (number of beds) and university affiliation, and location (East, West, South). Results: There were significant decreases both in the total number of patient days and antibacterial drug vol-umes in 2020 through 2022 compared with 2019. The relative changes between 2019 and 2020, 2021 and 2022 were -12.8%, -13.5%, and -13.3% for patient days, and -9.7%, -11.0%, and -10.1% for antibacterial RDD, respec-tively. Broad-spectrum betalactams, notably piperacillin-tazobactam and carbapenems, increased in volume unlike most other drug classes. The resulting antibacterial drug use density was slightly but significantly increas-ing with pooled means (and medians) of 43.3 (40.0) RDD/100 in 2019 compared to 44.8 (41.7), 44.5 (40.80), and 44.9 (41.7) RDD/100 in the years 2020 through 2022, respectively. Antifungal drug volumes and use density increased after 2019 and peaked 2021 (differences between 2019 and 2021 for total volumes +6.4%, and for pooled mean use density values +22.9%, respectively). These trends were similar in the different hospital strata and comparable when DDD instead of RDD were used. Conclusions: Similar to what has been observed in a majority of European countries the total volume of antibac-terial drug use in German acute care hospitals decreased with the pandemic without a rebound phenomenon in 2022. In association with restricted hospital capacities and presumably more immunocompromised general medi-cine patients, however, inpatient prescribing of (primarily broad-spectrum) antibacterials and of antifungal drugs increased.

Isolation, quarantine, and contact tracing were some of the most critical and commonly employed non-pharmaceutical interventions to control the COVID-19 pandemic. However, the effectiveness of these strategies after their implementation depends upon many factors such as the country's population, availability of sufficient resources to diagnose and effectively isolate the infected individuals, and feasibility, and acceptability of isolation and quarantine policy by the public. This narrative review aims to appraise the current evidence on the correct implementation strategies and shortcomings made in the isolation and quarantine strategies during the COVID-19 pandemic. PubMed, SCOPUS, EMBASE, and Web of Science citation index with the following keywords were searched: Pandemic, COVID-19, Coronavirus, Quarantine, and Isolation. The results showed that quarantine and isolation of COVID-19 patients were more effective than late adoption (5-fold versus 2.6-fold)’. Around 90% of outbreaks could have been managed if 80% of contacts were monitored, traced, and isolated within 4 days. For each new case of COVID-19, around thirty-six individuals should have been traced. When the percentage of individuals without symptoms is greater than 30%, isolation and contact tracing alone cannot contain the infection. The delay between the onset of symptoms and isolation is the most important factor determining whether an outbreak is controllable. The ideal day for testing should start on the 6th of the quarantine. However, this evidence is mostly based on mathematical modeling studies, and evidence for its effectiveness in real scenarios is required. Symptom-based isolation strategy should not be considered the sole criterion for considering isolation.

The ongoing COVID-19 global pandemic is affecting every facet of human lives (e.g., public health, education, economy, transportation, and the environment). This novel pandemic and citywide implemented lockdown measures are affecting virus transmission, people’s travel patterns, and air quality. Many studies have been conducted to predict the COVID-19 diffusion, assess the impacts of the pandemic on human mobility and air quality, and assess the impacts of lockdown measures on viral spread with a range of Machine Learning (ML) techniques. This review study aims to analyze results from past research to understand the interactions among the COVID-19 pandemic, lockdown measures, human mobility, and air quality. The critical review of prior studies indicates that urban form, people's socioeconomic and physical conditions, social cohesion, and social distancing measures significantly affect human mobility and COVID-19 transmission. During the COVID-19 pandemic, many people are inclined to use private transportation for necessary travel purposes to mitigate coronavirus-related health problems. This review study also noticed that COVID-19 related lockdown measures significantly improve air quality by reducing the concentration of air pollutants, which in turn improves the COVID-19 situation by reducing respiratory-related sickness and deaths of the people. It is argued that ML is a powerful, effective, and robust analytic paradigm to handle complex and wicked problems such as a global pandemic. This study also discusses policy implications, which will be helpful for policymakers to take prompt actions to moderate the severity of the pandemic and improve urban environments by adopting data-driven analytic methods.

Individuals from rural areas are increasingly using social media as a means of communication, receiving information, or actively complaining of inequalities and injustices. This study captured 57 days’ worth of Twitter data from June to August 2021 related to rural health using English language keywords. The study utilised social network analysis and natural language processing to analyse the data. It was found that Twitter served as a fruitful platform to raise awareness of problems faced by those living in rural areas. Overall, Twitter was utilised in rural areas to express complaints, to debate, and share information. Twitter could be leveraged as a powerful social listening tool for individuals and organisations who want to gain insight into popular narratives around rural health.

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.

The technology-driven world of the 21^st century is currently confronted with a major threat to humankind in the form of the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). As of April 22, 2020, COVID-19 has claimed 169, 006 human lives and had spread to over 200 countries with more than 2,471,136 confirmed cases. The perpetually increasing figures associated with COVID-19 are disrupting the social and economic systems globally. The losses are unmatched and significantly higher compared to those from previously encountered pathogenic infections. Previously, two CoVs (SARS-CoV and Middle East respiratory syndrome-CoV) affected the human population in 2002 and 2012 in China and Saudi Arabia, respectively. Based on genomic similarities, animal-origin CoVs, primarily those infecting bats, civet cats, and pangolins, were presumed to be the source of emerging human CoVs, including the SARS-CoV-2. The cohesive approach amongst virologists, bioinformaticians, big data analysts, epidemiologists, and public health researchers across the globe has delivered high-end viral diagnostics. Similarly, vaccines and therapeutics against COVID-19 are currently in the pipeline for clinical trials. The rapidly evolving and popular technology of artificial intelligence played a major role in confirming and countering the COVID-19 pandemic using digital technologies and mathematical algorithms. In this review, we discuss the noteworthy advancements in the mitigation of the COVID-19 pandemic, focusing on the etiological viral agent, comparative genomic analysis, population susceptibility, disease epidemiology, animal reservoirs, laboratory animal models, disease transmission, diagnosis using artificial intelligence interventions, therapeutics and vaccines, and disease mitigation measures to combat disease dissemination.

In late December 2019 a novel RNA beta-coronavirus was recognized as the causative agent of previously pneumonia cases of unknown origin. The virus was successively named Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) as well as the respiratory illness that it causes Coronavirus disease 19 (COVID-19) (1, 2). The global spread of SARS-CoV-2 and the thousands of deaths caused by COVID-19 led the World Health Organization (WHO) to declare a pandemic on 11 March 2020. To date, the world has paid a high toll in this pandemic in terms of human lives lost, economic repercussions and increased poverty. Indeed, even if most patients with COVID-19 are asymptomatic or experience mild self-limiting disease, 14% of them progress to severe disease and 5% to critical illness with complications, such as interstitial pneumonia, respiratory failure with acute respiratory distress syndrome (ARDS) and multiple organ dysfunction syndromes (MODS) (3). It is accepted that SARS-CoV-2 primarily affects the respiratory system, although other organs are also involved (4). The virus enters host cells by attaching its Spike like surface projections to the angiotensin-converting enzyme-2 (ACE2) receptor which is mainly expressed on alveolar epithelial cells and in nearly all human organs in varying degrees. Thus, although the central target of SARS-CoV-2 infection is the lung, the wide distribution of ACE2 receptors in other organs may lead to cardiovascular, gastrointestinal, kidney, liver, central nervous system and ocular damages that have to be closely monitored during the disease (5, 6). The virus then activates the innate and adaptive immune system resulting in a large number of cytokines release, known as “cytokine storm”, that is directly correlated with tissue injury and unfavourable prognosis of severe lung disease (7). In particular, interleukin (IL)-6 seems to plays an important role in driving this cytokine release so that its increased levels have been recognized as a hallmark inflammatory signature in sera of COVID-19 patients (8). IL-6 is a polyfunctional cytokine with both anti-inflammatory and pro-inflammatory properties which exerts its several functions through two main signal transduction pathways (9). In the classical signal transduction pathway, IL-6 binds to IL-6-trans membrane receptor (IL-6R) to form a complex that, then, binds to the trans membrane glycoprotein gp130, inducing its homo-dimerization and initiating intracellular signal transduction. This kind of signaling is limited to cells (hepatocytes, macrophages, neutrophils, T cells, etc.) that express IL-6R on their cell surface (10). Nevertheless, cells do not express IL- 6R, as stromal and epithelial cells, are able to still respond to IL-6 because the soluble form of the receptor (sIL-6R) binds to IL-6 in circle and then anchors to membrane gp130 receptor, initiating the trans-signaling pathway. For this reason, sIL-6R is able to increase the function of IL-6 and is considered the agonist form of its receptor. When the level of IL-6 increases, its effects are widely expressed because gp130 molecules are ubiquitous and, therefore, also present in cells without IL-6R in the membrane form. On the contrary, a soluble form of the glycoprotein 130 (sgp130) can complex with sIL-6R to prevent the sIL-6R from binding to the membrane-bound gp130. In this case sgp130 is able to decrease the function of IL-6 and is considered the antagonist form of IL-6 receptor system (11). Based on the central role of IL-6 in the inflammatory pathology of COVID-19 and the consistent association between elevated levels of the cytokine and severe disease outcomes found in the first phase of infection, we sought to analysis IL-6 and its soluble receptor complex behavior during the different waves of COVID-19 pandemic, in order to evaluate the possible differences which occur among them and to hypothesize if they might be used as prognostic markers of disease severity.

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.

COVID-19 has created anxiety not only in individuals but also in health organizations, and countries worldwide. Not a single industry is left un-influenced and loss is being estimated in billions of dollars. The widespread of this pandemic disease has challenged researchers all over the world. Some of the researchers are working to invent its cure while, others are applying computing technologies to stop its spread, by analyzing and identifying patterns for prediction and forecasting. This is by no doubt the hottest area of research for the last 100 years. This survey has targeted the research published in computing sub-domains to combat the pandemic. The survey has clustered the scientific efforts into logical groups: surveillance, metrological effects, social media analytics, image processing and business and economy, analysis and modeling. It will serve as a leading source for the followings: researchers who want to identify what has been achieved in different computing sub-domains, those who need fresh authenticated datasets openly accessible for different research contexts and what are future directions in this area of research. The findings of analysis and modeling can be also useful for government agencies who want to set priorities and formulate policies.

This paper examines interlinkages and hedging opportunities between nine major cryptocurrencies for the period between 30 September 2015 and 4 June 2020, which notably includes the coronavirus disease 2019 (COVID-19) outbreak lasting from early 2020 through the end of the sample period. The results of dynamic conditional correlation (DCC) analysis using a minimum connectedness approach show a high degree of correlation between cryptocurrencies throughout the sample period. However, the correlations reach their minimum values during the COVID-19 pandemic, which indicates that cryptocurrencies acted as a hedge or safe haven during the stressful period of the COVID-19 pandemic. The weight of cryptocurrencies was significantly reduced and their hedging effectiveness varied greatly during the pandemic, which indicates that investors’ preferences changed during the COVID-19 period.

The COVID-19 pandemic has brought about unprecedented changes to human lifestyles across the world. The virus and associated social restriction measures have been linked to an increase in mental health conditions. A considerable body of evidence shows that spending time in and engaging with nature can improve human health and wellbeing. Our study explores nature’s role in supporting health during the COVID-19 pandemic. We created web-based questionnaires with validated health instruments and conducted spatial analyses in a geographic information system (GIS). We collected data on people’s patterns of nature exposure, associated health and wellbeing responses, and potential socioecological drivers such as relative deprivation, access to greenspaces, and land-cover greenness. We applied a range of statistical analyses including bootstrap resampled correlations and binomial regression models, adjusting for several potential confounding factors. We found that respondents significantly changed their patterns of visiting nature as a result of the COVID-19 pandemic. People spent more time in nature and visited nature more often during the pandemic. People generally visited nature for a health and wellbeing benefit and felt that nature helped them cope during the pandemic. Greater land-cover greenness within a 250 m radius around a respondent’s postcode was important in predicting higher levels of mental wellbeing. There were significantly more food-growing allotments within 100 m and 250 m of respondents with high mental wellbeing scores. The need for a mutually-advantageous relationship between humans and the wider biotic community has never been more important. We must conserve, restore and design nature-centric environments to maintain resilient societies and planetary health.

This paper aims to quantify the effect of the deadly novel coronavirus (COVID-19) pandemic outbreak on Chinese stock market performance. Shanghai Stock Exchange Composite Index and its component sector indices are examined in this study. The pandemic is represented by a lockdown dummy, new COVID-19 cases and a dummy for 3 February 2020. First, descriptive analysis is performed on these indices to compare their performances before and during the lockdown period. Next, regression analysis with Exponential Generalized Autoregressive Conditional Heteroscedasticity specification is estimated to quantify the pandemic effect on the Chinese stock market. This paper finds that health care, information technology and telecommunication services sectors were relatively more pandemic-resistant, while other sectors were more severely hurt by the pandemic outbreak. The extent to which each sector was affected by pandemic and sentiments in other financial and commodity markets were reported in details in this paper. The findings of this paper are resourceful for investors to avoid huge loss amid pandemic outburst and the China Securities Regulatory Commission in handling future pandemic occurrence to cool down excessive market sentiments.

Monitored differential infection rates of past Corona waves are used to infer, a posteriori, the real time variation of the ratio of recovery to infection rate as key parameter of the SIR-epidemic model. From monitored Corona waves in five different countries it is found that this ratio exhibits a linear increase at early times below the first maximum of the differential infection rate before the ratios approach a nearly constant value close to unity at the time of the first maximum with small amplitude oscillations at later times. The observed time dependencies at early times and at times near the first maximum agree favorably well with the behavior of the calculated ratio for the Gaussian temporal evolution of the rate of new infections, although the predicted linear increase of the Gauss ratio at late times is not observed.

The 2019 Coronavirus pandemic which was initially referred to as 2019-nCoV, was first identified in Wuhan, China. Early response from the Chinese government included quarantine of infected persons, isolation and total lockdown of Wuhan province to prevent further spread. With the spread of the disease across national borders and declaration of the disease as a global pandemic, there has been a robust response by the international community to contain this deadly virus and prevent its further spread worldwide. Africa is not left out of this rampaging pandemic with documented cases in over 40 countries and still rising. Although extensive studies have been carried out on the novel SARS-CoV-2 on its pathogenesis, mode of infection and virulence but much is still unknown. However, potentially infectious samples are received routinely in the medical laboratory for analysis. This technical note reviews good laboratory practice (GLP) and processes across the different specialities of Medical Laboratory practice that should minimize the risk of infection to laboratory staff especially in resource-limited settings.

The COVID-19 pandemic has great adverse impacts on personal life, the U.S. economy, and the world economy. Freezing all human activities is not a sustainable measure. Thus we want to develop a public intervention framework that allows people to resume personal and economic activities. In this article, we examined transmission routes, disease severity, personal vulnerability, available treatments, and person-person interactions to establish a general public intervention framework. We divide people into risk groups, non-risk group and group that may serve as viral transmitters, explore interactions between individual persons within each group and between different groups, and propose interaction behavior modifications to mitigate viral exposures. For the non-risk groups, we identified preventive measures that can help them avoid the most serious exposures and infections that pose higher death risks. The invention measures for the vulnerable groups include prior-exposure measures, heightened protective measures, interaction behavior changes, post-exposure remedial measures, and multiple factors treatments to reduce death and disability risks. The multiple interventions and two-ways defensive behavior modifications are expected to result in reduced rate of detectable infections and lowered disease severity for the vulnerable groups. In this framework, most human activities and economic activities can continue as normal. With time passing, the population acquires population immunity against the COVID-19 virus. Implementation of this intervention framework requires considerable resources and governmental effects while the multiple factors treatment protocol requires the support of health care professionals.

The very first infected novel coronavirus case (COVID-19) was found in Hubei, China in Dec. 2019. The COVID-19 pandemic has spread over 215 countries and areas in the world, and has significantly affected every aspect of our daily lives. At the time of writing this article, the numbers of infected cases and deaths still increase significantly and have no sign of a well-controlled situation, e.g., as of 14 April 2020, a cumulative total of 1,853,265 (118,854) infected (dead) COVID-19 cases were reported in the world. Motivated by recent advances and applications of artificial intelligence (AI) and big data in various areas, this paper aims at emphasizing their importance in responding to the COVID-19 outbreak and preventing the severe effects of the COVID-19 pandemic. We firstly present an overview of AI and big data, then identify their applications in fighting against COVID-19, next highlight challenges and issues associated with state-of-the-art solutions, and finally come up with recommendations for the communications to effectively control the COVID-19 situation. It is expected that this paper provides researchers and communities with new insights into the ways AI and big data improve the COVID-19 situation, and drives further studies in stopping the COVID-19 outbreak.

Various symptoms have been reported to persist beyond acute phase of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which is referred as long coronavirus disease 19 (long COVID-19). Over 65 million individuals suffer from long COVID-19. However, the causes of long COVID-19 have been largely unknown. Since long COVID-19 symptoms are observed throughout the body, vascular endothelial dysfunction may be a strong candidate to induce long COVID-19. The angioten-sin-converting enzyme 2 (ACE2), the entry receptor of SARS-CoV-2, is ubiquitously expressed in endothelial cells. We previously found that the risk factors for athero-sclerotic cardiovascular disease (ASCVD) and the history of ASCVD can be the risk for severe COVID-19, suggesting a contribution of pre-existing endothelial dysfunction to severe COVID-19. Here, we show a significant association of endothelial dysfunction with development of long COVID-19 and show that biomarkers for endothelial dysfunction in patients with long COVID-19 are also crucial players in development of ASCVD. We consider the influence of long COVID-19 on development of chronic kidney disease (CKD) and ASCVD. Furthermore, we suggest the therapeutic interventions for long COVID-19 by considering endothelial dysfunction as the treatment tar-gets for long COVID-19. Such interventions may prevent pandemic of CKD and ASCVD in post COVID-19 era.

In the face of the newly emergent COVID-19 pandemic, researchers around the world are racing to identify efficacious drugs capable of preventing or treating its infection. They are doing that by testing already available and approved antimicrobials for their rapid repurposing against COVID-19. Using the data emerging on the comparable efficacy of various compounds having different mechanisms of action and indications, I suggest in this report, their potential mechanistic convergence. Specifically, I highlight the lysosome as a key possible therapeutic target for COVID-19, proposing one of the lysosomal storage disorders, Niemann-Pick type C disease (NPC), as a prototypical condition with inherent resistance or an “unfavorable” host cell environment for viral propagation. The included reasoning evolves from previously generated data in NPC, along with the emerging data on COVID-19. The aim of this report is to suggest that pharmacological induction of a “transient” NPC-like lysosomal dysfunction, could hold answers for targeting the ongoing COVID-19 pandemic.

Coronavirus Disease 2019 (COVID-19) is a respiratory illness caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). It is considered to be first reported from Wuhan, Hubei Province, China in December 2019. As of present, there are over 3.7 million identified cases worldwide and more than 259,000 deaths have been reported. This disease, its incubation period, course, complications, and the basis of spread remains a potential question due to variation in the pattern of spread around the globe and relatively fewer number of large-scale studies at present. This literature review aims to study the available data on its spread and incubation period. A literature search using PubMed with regular keywords ‘coronavirus’ and ‘COVID-19’, and Medical Subject Headings (MeSH) search for their etiology and pathogenicity was done with the search builder. The literature search revealed 26,689 studies among which 14 studies were selected for review. Studies were selected after the application of inclusion criteria and exclusion criteria with the removal of duplicates, and careful review for the outcome of interest ‘incubation period’. Among the 14 studies selected for review, there were eight review articles, five case reports, and one comparative study. The current literature review concludes that the mean incubation period for most of the literature falls between five days to 12 days with minimum reported time from known exposure to the onset of a symptom being one day and the maximum reported time from exposure to the onset of a symptom being 18 days.

To understand great disparities in disease outcomes between CIVID-19 patients, we explore infection and host responses in kinetics. From existing data, we deduced a model that the lungs are damaged by rapidly rising flow resistance as a result of retaining white blood cells in lung tissues. The retention of white blood cells is initially triggered by viral infection but aggravated by injuries caused by low temperature. Lungs are initially damaged by fluid leakage, rapidly followed by extruding blood into alveolar spaces. The step of blood extruding is predicted to take place in a very short time. Our simulations show that as little as 0.1% retention of white blood cells in the lungs can lead to their failure in 5 to 10 days. The small degrees of imbalance implies that this imbalance could be corrected by a large number of factors that are known to reduce flow resistance. The model implies that the top priority is maintaining blood micro-circulation and preserving organ functions in the entire disease course, especially after the virus has spread the whole lungs. From exploring a large number of hypothetical infection modes, we propose preventive, mitigating and treatment strategies for ultimately ending the pandemic. The first strategy is avoiding exposures that could result in widespread damages to lungs and taking post exposure mitigating measures that would reduce disease severity. The second strategy is reducing death rate and disability rate from the current levels to one tenth for infected patients by using multiple factors health optimization method. The double reduction strategies are expected to generate a series of chain reactions that favor mitigating or ending the pandemic. Some reactions include a big reduction of the amount of viral discharges from infected patients into the air, the avoidance of panic, chronic stress and emotional distress, and cross-infections which are expected in quarantines. The double reductions would have a final effect of ending the pandemic.

The objective of the present study is to analyze COVID-19 transmission in specific dampest regions with excess rainfall and recurring fogs. The working hypothesis is that widespread transmission of SARS CoV 2 (leading to COVID-19) and similar viral agents can be explained by specific climate factors having high air humidity. The main case study of the Turkish Black Sea region is investigated. Results reveal that the provinces in region under study have some climate factors and geographical features that foster the accelerated transmission of viral agents, such as SARS-CoV-2, and consequential negative impact on society. In particular, Spearman's Correlation Coefficient shows a statistically significant positive association between the average atmospheric pressure and the spread of the COVID-19 confirmed cases in Samsun province (Spearman’s correlation coefficient rs =0.86, p-value 0.05). A statistically significant positive association between the average precipitation and the spread of COVID-19 confirmed cases in Sinop province (Spearman’s correlation coefficient rs =0.79, p-value 0.05), and finally, a statistically significant negative association between the average sun hour and the spread of the COVID-19 confirmed cases in Samsun province (Spearman’s correlation coefficient rs = 0.89, p-value 0.01). These findings suggest that regions' geographical characteristics, demographic structure, climate and environmental parameters must be considered in the national scale epidemic management plans to design effective anti-pandemic health policies to cope with future waves of the COVID-19 and new airborne diseases and to reduce negative effects on health, social and economic systems.

Telehealth is the delivery of many health care services and technologies to individuals at different geographical areas and is categorized as asynchronously or synchronously. The coronavirus disease 2019 (COVID-19) pandemic has caused major disruptions in health care delivery to breast cancer (BCa) patients and there is increasing demand for telehealth services. Globally, telehealth has become an essential means of communication between patient and health care provider. The application of telehealth to the treatment of BCa patients is evolving and increasingly research has demonstrated its feasibility and effectiveness in improving clinical, psychological and social outcomes. Two areas of telehealth that have significantly grown in the past decade and particularly since the beginning of the COVID-19 pandemic are telerehabilitation and teleoncology. There two technological systems provides opportunities at every stage of the cancer care continuum for BCa patients. We conducted a systematic literature review that examined the use of telehealth services via its various modes of delivery among BCa patients particularly in areas of screening, diagnosis, treatment modalities, as well as satisfaction among patients and health care professionals. The advantages of telehealth models of service and delivery challenges in delivery to patients in remote arears are discussed.

The epidemic of Coronavirus Disease 2019 (COVID-19) have affected all the regions of the world, nevertheless, in some countries there is a lack of studies on its main clinical and epidemiological features. We analyzed the incidence, incidence rates, and evolution of COVID-19 cases in Honduras from February 18-April 24, 2020.Methods: Using daily epidemiological data from surveillance about COVID-19 in Honduras, we calculated the rates of incidence (cases/100,000 population), and developed at national, departmental, and municipal levels GIS-based maps.Results: February 18 - April 24, 2020, a sum of 3,169 suspected COVID-19 cases have been assessed by RT-PCR, 533 (16.8%) of them were positive, for an incidence rate of 5.73 cases/100,000 pop. The highest peak was reached on March 31 (48 cases). The department with the highest number of cases and incidence rate was Cortes (383 cases, 71.9% of the total, 21.45 cases/100,000 pop). Discussion: The pattern and evolution of COVID-19 epidemic in Honduras has been particularly focused in the major urban areas, San Pedro Sula and Tegucigalpa, the capital city. Studies using geographical information systems linked with clinical disease characteristics are necessary to attain accurate epidemiological data for public health systems. Such information is also useful for assessment of the evolution of the pandemic and monitoring interventions.

The coronavirus disease 2019 (COVID-19) pandemic is the defining global health and socioeconomic crisis of our time and represents the greatest challenge faced by the world since the end of the Second World War. The academic literature indicates that climatic features, specifically the temperature and absolute humidity, are very important factors affecting infectious pulmonary disease epidemics (e.g., SARS, MERS); however, the influence of climatic parameters on COVID-19 remains extremely controversial. The goal of this study is to quantify the existing relationship between several daily climate parameters (temperature, relative humidity, accumulated precipitation, solar radiation, wind direction and intensity, and evaporation), local morphological parameters, and new daily positive swabs for COVID-19, which represents the only parameter that can be statistically used to quantify the pandemic. The daily deaths parameter was not considered because it is not reliable due to frequent administrative errors. Daily data on meteorological conditions and new cases of COVID-19 were collected for the Lombardy area from March 1, 2020, to April 20, 2020. This region in Italy exhibited the largest number of official deaths in the world per million inhabitants, with a value of approximately 1700 per million on june 30, 2020. Moreover, the apparent lethality was approximately 17% in this area, mainly due to the considerable housing density and the extensive presence of industrial and craft areas. The Mann-Kendall test and multivariate statistical analysis showed that none of the considered climatic variables exhibited statistically significant relationships with the epidemiological evolution of COVID-19, at least in the spring months in temperate subcontinental climate areas, with the exception of solar radiation, which was directly related and showed an otherwise low explained variability of approximately 20%. Furthermore, the average temperatures of two highly representative meteorological stations of Molise and Lucania, the most weakly affected by the pandemic. The temperatures at these stations were approximately 1.5°C lower than that in the cities in Lombardy of Bergamo and Brescia, again confirming that a significant relationship between the increase in temperature and decrease in virology from COVID-19 was not evident, at least in the Italian peninsula.

SARS-CoV-2 is a newly emerging, highly transmissible, and pathogenic coronavirus in humans, which has caused global public health emergency and economic crisis. To date, millions of infections and thousands of deaths have been reported worldwide, and the numbers continue to rise. Currently, there is no specific drug or vaccine against this deadly virus; therefore, there is a pressing need to understand the mechanism through which this virus enters the host cell. Viral entry into the host cell is a multistep process in which SARS-CoV-2 utilizes the receptor binding domain of the spike glycoprotein (S) to recognize ACE2 receptors on the human cells; this initiates host cell entry by promoting viral-host cell membrane fusion through large scale conformational changes in the S protein. Receptor recognition and fusion are critical and essential steps of viral infections and are key determinants of the viral host range and cross-species transmission. In this review, we summarize the current knowledge on the origin and evolution of SARS-CoV-2 and the roles of key viral factors. We discuss the RNA dependent RNA polymerase structure of SARS-CoV-2, its significance in drug discovery, and explain the receptor recognition mechanisms of coronaviruses. We provide a comparative analysis of the SARS-CoV and SARS-CoV-2 S proteins, receptor-binding specificity, and discuss the differences in their antigenicity based on biophysical and structural characteristics.

We previously proposed a public intervention framework concept that would allow people to resume personal and economic activities. We showed that intervention measures are used in a quantitative scale to reduce transmission probabilities and disease severity. In this article, we systematically examine the origin, assumptions, performance and limitations of epidemiological models from different views used in past review. We found that nearly all model assumptions fail to hold or are remote from reality; R0 does not exit or has no utility in guiding treatment options; personalized intervention measures are vitally important to COVID-19 due to its transmission characteristic; and current epidemiological models are unable to accurately assess the true benefits of personalized intervention measures. We suggest that poor performance of the models are attributed to flawed assumption that health/disease properties can be treated as transferable properties. The flaw creates a fiction that disease properties such as infection probabilities and death risks can be transferred from any vulnerable persons to anyone in the population and thus severely limit societal ability to fight the pandemic. We finally show that the benefits of personalized mitigation measures could be determined directly by using variable Ri values for infected persons (or nodes) together assessment of death rate and disability rate; the attempt of avoiding the disease by defeating all potential transmission probabilities is unrealistic; but mitigating disease severity for specific persons is more feasible and reliable. A most reliable strategy for reviving economy is using personalized protective measures and improving person health before effective vaccine is available.

As the world endures the coronavirus disease 2019 (COVID-19) pandemic, conditions of 35 million vulnerable individuals struggling with substance use disorders (SUDs) worldwide have not received sufficient attention for their special health and medical needs. Many of these individuals are complicated by underlying health conditions, such as cardiovascular and lung diseases and undermined immune systems. During the pandemic, access to the healthcare systems and support groups is greatly diminished. Current research on COVID-19 has not addressed the unique challenges facing individuals with SUDs, including the heightened vulnerability and susceptibility to the disease. In this systematic review, we will discuss the pathogenesis and pathology of COVID-19, and highlight potential risk factors and complications to these individuals. We will also provide insights and considerations for COVID-19 treatment and prevention in patients with SUDs.

Coronavirus Disease 2019 (COVID-19), caused by SARS-CoV-2 (Severe Acute Respiratory Syndrome - Coronavirus-2) of the family Coronaviridae, appeared in Wuhan, Hubei province, China being its epicenter in December 2019. This disease was declared as posing Public Health International Emergency by World Health Organization on January 30, 2020, attained the status of a very high-risk category on February 29, and now having a pandemic status (March 11, 2020). COVID-19 has presently spread to more than 195 countries/territories while killing nearly 19,600 humans out of cumulative confirmed cases accounting to more than 430,000 within a short period of just a few weeks. The majority of deaths have been reported in Italy and China. Researchers worldwide are pacing with high efforts to counter the spread of this virus and to design effective vaccines and therapeutics/drugs. Few of the studies have shown the potential of animal-human interface and zoonotic links in the origin of SARS-CoV-2. Exploring the possible zoonosis and revealing the factors responsible for its initial transmission from animals to humans will pave ways to design and implement effective preventive and control strategies to counter COVID-19. The present review presents an overview of COVID-19 and the causative virus SARS-CoV-2, with particular emphasis on the role of animals and their jumping the cross-species barriers, experiences learned from SARS- and MERS-CoVs, zoonotic links, and spillover events, transmission to humans and rapid spread., highlighting in very brief the preventive and control measures along with a few of the recent research developments to counter this pandemic virus/disease.

We aimed to explore university students’ perceptions and experiences of SARS-CoV-2 mass asymptomatic testing, social distancing and self-isolation during the COVID-19 pandemic. This qualitative study comprised of four rapid online focus groups conducted at a higher education institution in England during high alert (tier 2) national COVID-19 restrictions. Data were analysed thematically. Participants were purposively sampled university students (n = 25) representing a range of gender, age, living circumstances (on/off campus) and SARS-CoV-2 testing/self-isolation experiences. Six themes with 16 sub-themes emerged from the analysis of the qualitative data: ‘Term-time Experiences’, ‘Risk Perception and Worry’, ‘Engagement in Protective Behaviours’, ‘Openness to Testing’, ‘Barriers to Testing’ and ‘General Wellbeing’. Students described feeling safe on campus, believed most of their peers are adherent to protective behaviours and were positive towards asymptomatic testing in university settings. University communications about COVID-19 testing and social behaviours need to be timely and presented in a more inclusive way to reach groups of students who currently feel marginalised. Barriers to engagement with SARS-CoV-2 testing, social distancing and self-isolation were primarily associated with fear of the mental health impacts of self-isolation, including worry about how they will cope, high anxiety, low mood, guilt relating to impact on others and loneliness. Loneliness in students could be mitigated through increased intra-university communications and a focus on establishment of low COVID-risk social activities to help students build and enhance their social support networks. These findings are particularly pertinent in the context of mass asymptomatic testing programmes being implemented in educational settings and high numbers of students being required to self-isolate. Universities need to determine the support needs of students during self-isolation and prepare for the long-term impacts of the pandemic on student mental health and welfare support services.

Background: Only few studies have studied the link between risk perception and sleep in the context of the COVID-19 pandemic. This study investigates the effect of two distinct risk appraisals—risk perception and perception of collective coordinated defense (PCCD) on Chinese adults’ sleep quality during the COVID-19 pandemic, and tested COVID-19-related fear and rumination as potential mediators of the relationships. Methods: Data were collected using a self-report online questionnaire from a sample of 224 Chinese adults during the fourth wave of the COVID-19 pandemic in Hong Kong. Results: COVID-19 risk perception and PCCD were related to poor sleep quality. Mediation analysis showed that both fear and rumination mediated the relationship between risk perception and sleep quality, whereas only fear mediated the relationship between PCCD and sleep quality. The model showed an excellent fit to the data and accounted for 44% of the variance in sleep quality in Chinese adults. Conclusions: This study demonstrates the distinct perceptual processes—risk appraisals in particular—contributed to poor sleep quality in Chinese adults during the COVID-19 public emergencies. These findings would be helpful for policy makers to address the sleep problems induced by psychological consequences of the pandemic.

The aim of this study is to describe a research protocol of a multi-country randomized controlled trial to investigate the effect of a smartphone CBT stress management program on improving depression and other health- and work-related outcomes among hospital nurses in Vietnam and Thailand during the COVID-19 epidemic as a part of the COCONATS project. The study is a two-arm, parallel randomized control trial. Hospital nurses (N = 1,500) will be recruited in Vietnam and Thailand, and those who meet the criteria will be randomly allocated to the intervention or control (treatment as usual) group. A seven-week, seven-module smartphone-based stress management program will be developed to teach CBT skills. The intervention group will participate in the program for 10 weeks. Depression as the primary outcome will be measured using the DASS21 at baseline and in 3- and 6-month follow-up surveys. A mixed model repeated measures analysis will be used to test the intervention effect in the total combined sample, on an intention-to-treat basis. This is the first study to investigate the effectiveness of a self-guided smartphone CBT program on improving depression among hospital nurses using a RCT design in South-East Asian middle-income countries during the COVID-19 pandemic.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the etiological agent of the current pandemic worldwide. The pathological condition induced by this pathogen is known as COVID-19 disease. SARS-CoV-2 associated pandemic has been defined as a “public health emergency of international concern” by the International Health Regulation Emergency Committee of the World Health Organization. To date, considerable efforts are in progress to develop more advanced strategies against SARS-CoV-2. Despite the numerous scientific studies published, our knowledge regarding this pathogen is still incomplete, as this virus has been identified only recently. Therefore, scientific investigation of the SARS-CoV-2 has been possible only for a short period of time and effective management of the serious forms of this disease is still lacking. Considerable efforts are in progress worldwide with the purpose to develop more advanced strategies against this pathogen. In this review, we have analyzed the structural and the biological SARS-CoV-2 characteristics and those of other well-known RNA viruses, with the aim to identify possible similarities and analogies between all these pathogens, may be a very useful approach. These infectious agents have been widely studied since several years ago and, a large series of scientific reports are available in the literature regarding this topic. Therefore, focusing on the Human Immunodeficiency Virus (HIV), Hepatitis C Virus (HCV) and Influenza viruses (IVs), we have collected their historical data, clinical manifestations, pathogenetic mechanisms and related infections. Taking advantage of the results of our research, we have assembled this narrative review, with the aim to get useful insights and lessons from HIV, HCV and IVs characteristics and, consequently, to transfer the obtained knowledge to the study of SARS-CoV-2 biology. There are well known differences between all these pathogens. In particular, they present a distinct mode of transmission, as SARS-CoV-2 and Influenza viruses are airborne pathogens, whereas HIV and HCV are bloodborne infectious agents. However, these viruses exhibit some potential common clinical manifestations and pathogenetic mechanisms and their understanding may contribute to establishing preventive measures and new therapies against SARS-CoV-2. Accordingly, we have analysed and discussed the following points: 1) the biology, the pathogenesis and the clinical manifestations of SARS-CoV-2, HIV, HCV and IVs in mankind; 2) the onset and spreading of pandemics caused by respiratory viruses according to a perspective historical point of view; 3) the possible development of a persistent SARS-CoV-2 reservoir worldwide; 4) the possibility of SARS-CoV-2 reinfection/reactivation; 5) the possible involvement and impact of climatic factors in increasing the risk of SARS-CoV-2 spreading.

Coronaviruses (CoVs) are enveloped positive-sense single-stranded RNA viruses with a genome 27-31kbases in length. Critical genes include the spike (S), envelope (E), membrane (M), nucleocapsid (N) and 9 accessory open reading frames encoding for non-structural proteins (NSPs) that have multiple roles in the replication cycle and immune evasion (1). There are 7 known human CoVs that most likely appeared after zoonotic transfer, the most recent being SARS-CoV-2 responsible for the Covid-19 pandemic. Antivirals that have been approved by the FDA for use against Covid-19 such as Paxlovid can potentially target and successfully inhibit the main protease (MPro) activity of multiple human CoVs, however alternative proteomes encoded by CoV genomes have a closer genetic similarity to each other, suggesting that antivirals could be developed now that target future CoVs. New zoonotic introductions of CoVs to humans are inevitable and unpredictable. Therefore, new antivirals are required to control not only the next human CoV outbreak, but also the 4 common human CoVs (229E, OC43, NL63, HKU1) that circulate frequently and to contain sporadic outbreaks of the severe human CoVs (SARS-CoV, MERS and SARS-CoV-2). The current study found that emerging antiviral drugs, such as Paxlovid, have only been proven to target SARS-CoV-2. Other drugs which have the potential to target other human CoVs, are still within clinical trial and are not yet available for public use. Monoclonal antibody (mAb) treatment and vaccines for SARS-CoV-2 can reduce mortality and hospitalisation rates, however they target the Spike protein whose sequence mutates frequently and drifts. Spike also is not applicable for targeting other HCoVs as these are not well conserved sequences among human CoVs. Thus, there is a need for readily available treatments globally that target all 7 human CoVs and improve the preparedness for inevitable future outbreaks. Here we discuss antiviral research contributing to the control of common and severe CoV replication and transmission, including the current SARS-CoV-2 outbreak. The aim was to identify common features of CoVs for antivirals, biologics and vaccines that could reduce the scientific, political, economic and public health strain caused by CoV outbreaks now and in the future.

The induction of acoustic-mechanical oscillations to virus particles by illuminating them with microwave signals is analyzed theoretically. Assuming the virus particle being of spherical shape, its capsid consisting primarily of glycoproteins, a viscous fluid model is adopted while the outside medium of the sphere is taken to be ideal fluid. The electrical charge distribution of virus particle is assumed to be spherically symmetric with a variation along the radius. The generated acoustic-mechanical oscillations are computed by solving a boundary value problem analytically, making use of the Green’s function approach. Resonance conditions to achieve maximum energy transfer from microwave radiation to acoustic oscillation to the particle is investigated. Estimation of the feasibility of the technique to compete virus epidemics either for sterilization of spaces and/or use for future therapeutic applications is examined briefly.

Beginning in December 2019, a novel coronavirus known as SARS-CoV-2 has caused an international outbreak of respiratory illness termed COVID-19. This disease may cause mild to moderate respiratory illness. However, older individuals and those with underlying medical conditions like diabetes, cancer, and cardiovascular disease are more likely to develop serious illnesses (progressive pneumonia, multi-organ failure, and even death) (1). The main target for antiviral therapy for COVID-19 is the 3CL protease (3CLpro, Main protease, Mpro, Nsp5). The 3CL protease plays an integral role in viral replication and is often known as the “Achilles heel” of the SARS-CoV-2 virus (2). Thus, NLC Pharma utilized a unique and novel technology termed Quantum Core Technology (QCT) to design a mechanism-based potent inhibitor against the SARS-Cov-2 3CL protease. 3CL Pharma has designed an oral anti-viral for COVID-19 called Tollovir. Biochemical assays have revealed that 40uM of Tollovir in PBS can achieve 90% maximum inhibition of 3CL protease. Furthermore, the oral anti-viral has completed clinical trial phase 2b/3. Tollovir has proven to be safe and significantly decreases mortality rates of hospitalized patients with COVID-19 infection.

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

As the outbreak of COVID-19 has accelerated, an urgent need for finding strategies to combat the virus is growing. Thus, gaining more knowledge on the pathogenicity mechanisms of SARS-CoV-2, the causing agent of COVID-19, and its interaction with the immune system is of utmost importance. Although this novel virus is not well known yet, its structural and genetic similarity with SARS-CoV as well as the comparable pattern of age-mortality relations suggest that the previous findings on SARS can be applicable for COVID-19. Therefore, a systems biology study was conducted to investigate the most important signaling pathways activated by the virus. The results were then validated through a literature review on COVID-19 and the other closely related viruses, SARS and MERS. Interferons have shown to play a crucial role in the defense against coronavirus diseases. CoV can impede the interferon induction in humans. Moreover, STAT1, a key protein in the interferon-mediated immune response, is antagonized by the virus. This could explain the increased response threshold of immune cells to IFNs during CoV infections. A vivid correlation between the innate immune response threshold and the fatality rates in COVID-19 can be found. Differences in the dynamics of the interferon-related innate immune responses in children, adults, and elderly may explain the reported fatality rates. The increased mortality rates in the elderly can be explained by the higher threshold of interferon-mediated immune responses. Earlier induction of interferons in children and their less developed immune system could contribute to their near to zero fatality rate. Administration of interferon-inducing agents, such as poly (ICLC), could reduce the mortality of SARS at the very early stages of the disease. Interferon-γ combination with an interferon-I might induce synergistic effects and maximize the benefits. However, in-depth research is needed to validate it and determine the optimum dosage and timing to prevent unwanted results. Such interventions can act as a double-edged sword and aid the imbalance of the immune reactions, which may occur at the later stages of the disease. With the advancement of the disease and the virus overload, the responses would shift toward immnopathogenic over-reactions and probably cytokine storm. Moderating the activity of the immune system and supportive care in such conditions might be the optimum approach.

Background: The information on the difference in clinical characteristics between severe and non-severe cases is limited in some countries including Iran. The objective of this case series is to compare the clinical characteristics, radiologic features, and laboratory findings between COVID-19 severe cases who received the intensive care unit (ICU) care with non-severe cases who did not receive ICU care. Methods: In this retrospective cohort study, 186 laboratory-confirmed patients with COVID-19 diagnosed from 1 March 2020 to 30 March 2020 were investigated. Results: This study population included 186 hospitalized patients with confirmed COVID-19. The median age was 47 years, and 88 (47.31%) were female. Of these patients, 48 were admitted and transferred to ICU. Of 186 patients, 44.62% had medical comorbidities including hypertension and diabetes. The most common clinical manifestation were shortness of breath 86.56%, myalgia 74.19%, and headache. Higher neutrophil counts, CRP, and LDH as well as the lower levels of lymphocytes were the most important laboratory finding among COVID-19 patients. As of April 15, 2020, 33 were still hospitalized. A total of 116 patients (62.70 %) had been discharged, and 36 patients (19.94 %) had died. Of the 48 patients admitted to the ICU, 33.33% have died. Conclusion: In the present study, shortness of breath was the most common clinical symptom, and the mortality rate in patients admitted to the ICU was about 33%, indicating that about one-third of patients with severe illness who admitted to the ICU section died.

Introduction: Adverse events related to vaccines are reactions that can lead to serious complications, in the present that we live at the publication of this article with the need to generate high rates of vaccination have been presented in the case of vaccine agents against COVID-19 adverse events, with thrombotic events being the most important. Case Presentation: This is a 37-year-old female patient who presents 11 days after ChAdOx1-S vaccination against COVID-19 presents with intense headache associated with symptoms of intracranial hypertension, she was initially taken to simple cranial tomography showing presence of cerebral edema and indirect signs of cerebral venous thrombosis, it is proposed to carry out cerebral angiography which showed the presence of thrombosis of both transverse venous sinuses, no hypercoagulability states were found in the laboratories, the immunological tests carried out for antiphospholipid syndrome were negative, the thrombotic event was associated with the ChAdOx1-S vaccine, later the patient was taken to thrombectomy by Neuroradiology, achieving complete channeling of both transverse venous sinuses. Conclusions: Adverse events associated with vaccination have been described with multiple vaccine agents, this component against COVID-19 is also an event to consider, knowing the pathophysiology of these events is essential to be able to reduce these risks and select the least risky agent. Despite this risk, vaccination remains the only cost-effective measure to reduce the morbidity and mortality associated with COVID-19.

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models need to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak.

The 2019 Novel Coronavirus (COVID-19) has caused an acute reduction in world supplies of personal protective equipment (PPE) due to increased demand. To combat the impending shortage of equipment including N95 masks, the George Washington University Hospital (GWUH) developed a 3D printed reusable N95 comparable respirator that can be used with multiple filtration units. We evaluated several candidate prototype respirator models, 3D printer filaments, and filtration units detailed here. Our most recent working model was based on a respirator found on an open source maker website and was developed with PLA (printer filament), a removable cap, a removable filtration unit consisting of two layers of MERV 16 sandwiched between MERV 13, and removable elastic bands to secure the mask. Our candidate mask passed our own suction test protocol to evaluate leakage and passed a qualitative Bitrix N95 fit test at employee health at GWUH. Further efforts are directed at improving the current model for seal against face, comfort, and sizing. The 3D model is available upon request and in the supplement of this paper. We welcome collaboration with other institutions and suggest other facilities consider mask fit for their own population when exploring this concept.

Introduction: The 2019 novel coronavirus (COVID-19) is very contagious, and can be transmitted to other people by droplet, aerosol, sneezing, infected surface, and cough. There is no vaccine or effective treatment at this time. Therefore, the prevention of COVID-19 and the rapid diagnosis of infected patients is crucial. Method: We searched all relevant literature published up to February 28, 2020, from Embase, Scopus, PubMed, Web of Science, and the Cochrane library to collect the studies that reported clinical and laboratory characteristics of COVID-19 infected patients. The study quality was assessed with the Critical Appraisal Checklist. Depending on the heterogeneity test, we used either random or fixed-effect models to analyze the appropriateness of the pooled results. Result: Twenty studies were included in the meta-analysis, including a total of 52,251 patients with confirmed COVID-19 infection. 69.5% (95% CI 54.5-81, p < 0.001) of patients had a history of recent travel to Wuhan, contact with people from Wuhan, or lived in Wuhan. The most common symptoms among COVID-19 infected patients were fever 85.6 % (95% CI 73 -93, p < 0.001), and cough 63 % (95% CI 55.5-70, p < 0.001), respectively. The laboratory analysis showed that thrombocytosis was present in 91% (95% CI 81-98, p < 0.001) CRP was elevated in 81% (95% CI 65-91, p < 0.001), and lymphopenia in 62.5% of cases (95% CI 42-79, p < 0.001). The most common radiographic signs were bilateral involvement in 76.8% (95% CI 62.5-87, p < 0.001) and consolidation in 75.5% (95% CI 50.5-91, p < 0.001) of patients. Most patients (85.4%) were hospitalized, 20.6% of patients were admitted to the ICU in critical condition, and the mortality rate was 5.6%. Conclusions: Fever and cough are the most common symptoms of COVID-19 infection in the literature published to date. Thombocytosis, lymphopenia, and increased CRP were common lab findings although most patients included in the overall analysis did not have laboratory values reported. The most common radiographic sign was bilateral involvement in and consolidation. Among Chinese patients with COVID-19, rates of hospitalization, critical condition, and hospitalization were high in this study, but these findings may be biased by reporting only confirmed cases.

Coronaviruses are highly transmissible and pathogenic viruses for humans and animals. The vast quantity of information collected about SARS-CoV-2 during the pandemic helped to unveil details on the mechanisms behind the infection, which are still largely elusive. Recent research demonstrated that different class I/II human leukocyte antigen (HLA) alleles might define an individual susceptibility to SARS-CoV-2 spreading, contributing to the differences in the distribution of the infection through different populations; additional studies suggested that the homolog of the HLA in cats, the Feline Leukocyte Antigen (FLA), plays a pivotal role in the transmission of viruses. With these premises, this study aimed to exploit a bioinformatic approach for the prediction of the transmissibility potential of two distinct Feline Coronaviruses (FCoVs) in domestic cats (Feline enteric Coronavirus, FeCV and Feline Infectious Peritonitis Virus, FIPV) using SARS-CoV-2 as the reference model. We performed an epitope mapping of nonapeptides deriving from SARS-CoV-2, FeCV and FIPV glycoproteins and predicted their affinities for different alleles included in the three main loci in class I FLAs (E, H and K). The predicted complexes with the most promising affinities were then subjected to molecular docking and molecular dynamics simulations to provide insights into the stability and binding energies in the cleft. Results showed the FLA proteins encoded by alleles in FLA-I H (H*00501 and H*00401) and E (E*01001 and E*07001) loci are largely responsive to several epitopes deriving from replicase and spike proteins of the analyzed coronaviruses. The analysis of the most affine epitope sequences resulting from the prediction can stimulate the development of anti-FCoV immunomodulatory strategies based on peptide drugs.

Porcine epidemic diarrhea (PED) is a swine wasting disease caused by coronavirus infection. It causes great economic damage to the swine industry worldwide. Despite the continued use of vaccines, PED outbreaks continue, highlighting the need to review the effectiveness of current vaccines and develop additional vaccines based on new platforms. Here, we review existing vaccine technologies for preventing PED and highlight promising technologies that may help control PED virus in the future.

Ferret Systemic Coronaviral Disease (FSCD) is a systemic disease, caused by ferret systemic coronavirus, that is considered lethal in most of the ferrets that are affected by it. To our knowledge, no treatment has been shown effective against FSCD, and most of the ferrets are euthanized or die after development of clinical disease. GS-441524 has been shown effective for successfully treating cats with Feline Infectious Peritonitis (FIP), a disease that shares similarities with FSCD. However, to our knowledge treatment with GS-441524 has not been reported for treatment of FSCD in ferrets. Here we describe three cases of ferrets diagnosed with FSCD successfully cured utilizing oral GS-441524. FSCD may be effectively treated following similar protocols utilized for feline infectious peritonitis in cats

We present a modification of the logistic model of epidemics that takes into account the possibility that an epidemic can develop from multiple physically-distinct hot spots with a range of starting times. This produces an improved understanding of the time evolution of the COVID-19 epidemic taking place in the United States in the spring of 2020.

There is a lot of discussion underway with conflicting opinions examining the airborne nature of the SARS-CoV2 virus. Surprisingly, important phenomena prevalent with respect to aerosols (suspended droplets) have not been considered. In this Technical Note, we propose a methodology for the coupling of aerosol phenomena (such as evaporation, particle transport accounting for drag) to accurately establish the lifetimes of the droplets. A characteristic time analysis illustrates the time scales for evaporation and settling: for example, the characteristic time for evaporation of a 10 µm droplet is 0.036 s at a relative humidity of 25%; compared to a settling time of about 500 s. For any particle smaller than ~ 100 µm, the evaporation of the emitted or exhaled droplet has to be considered. Coupling evaporation of the droplet as it settles, we estimate the horizontal distance traversed. Trajectories of a 10 µm and 100 µm particle emitted with a typical initial velocity of release associated with coughing and sneezing indicates the greater spread in the horizontal direction when evaporation is accounted for. The life time of the 10 µm particle increases from 8.3 min to 12 hours (will be intercepted prior and the actual airborne time will then be shorter); and for a 100 µm particle from 4.9 s to 39.4 s.

There is an urgent need to advance safe and affordable COVID-19 vaccines for low- and middle-income countries of Asia, Africa and Latin America. Such vaccines rely on proven technologies such as recombinant protein-based vaccines to facilitate its transfer for emerging market vaccine manufacturers. Our group is developing a two-pronged approach to advance recombinant protein-based vaccines to prevent COVID-19 caused by SARS CoV2 and other coronavirus infections. One vaccine is based on a yeast-derived (Pichia pastoris) recombinant protein comprised of the receptor binding domain (RBD) of the SARS-CoV formulated on alum and referred to as the CoV RBD219-N1 Vaccine. Potentially this vaccine could be used as a heterologous vaccine against COVID-19. A second vaccine specific for COVID-19 is also being advanced using the corresponding RBD of SARS-CoV-2. The first antigen has already undergone cGMP manufacture and is therefore “shovel ready” for advancing into clinical trials, following vialing and required GLP toxicology testing. Evidence for its potential efficacy to cross-protect against SARS-CoV-2 includes cross-neutralization and binding studies using polyclonal and monoclonal antibodies. Evidence in support of its safety profile include our internal assessments in a mouse challenge model using a lethal mouse adapted SARS strain, which show that SARS-CoV RBD 291N1 (when adsorbed to Alhydrogel®) does not elicit eosinophilic lung pathology. Together these findings suggest that recombinant protein-based vaccines based on the RBD warrant further development to prevent SARS, COVID-19 or other coronaviruses of pandemic potential.

This was a retrospective cohort study, which aimed to investigate the factors associated with hesitancy to receive the third dose of coronavirus disease 2019 (COVID-19) vaccine. A paper-based questionnaire survey was administered to all participants. Accordingly, the study included participants who provided answer in the questionnaire whether they have an intent to receive the third dose of vaccine. Data on sex, age, area of residence, adverse reactions after the second vaccination, whether the third vaccination was desired, and reasons to accept or hesitate booster vaccination were retrieved. Among the 2439 participants with mean (±SD) age of 52.6±18.9 years, and median IgG-S antibody titer of 324.9 (AU/mL), 97.9% of participants indicated their intent to accept a third vaccination dose. The logistic regression revealed that younger age (OR=0.98; 95% CI: 0.96-1.00) and higher antibody level (OR=2.52; 95% CI: 1.27-4.99) are positively associated with the third vaccine hesitancy. The efficacy of the COVID-19 vaccine and concerns about adverse reactions had significant impact on the third vaccination behavior. A rapid increase in the booster dose rate is needed to control the pandemic, and specific approaches should be taken in these groups that are likely to hesitate the third vaccine, subsequently increasing booster contact rate.

Coronaviruses cause infections in humans and diverse species of animals and birds with a global distribution. Bovine coronavirus (BCoV) produces predominantly two forms of disease in cattle, a respiratory form, and a gastrointestinal form. All age groups of cattle are affected by the respiratory form of coronavirus whereas the gastroenteric form causes neonatal diarrhea or calf scour in young cattle and winter dysentery in adult cattle. The tremendous impacts of bovine respiratory disease and the associated losses are well-documented and underscores the importance of this pathogen. Beyond this, studies have demonstrated significant impacts on milk production associated with outbreaks of winter dysentery, with up to a 30% decrease in milk yield. Research data so far have shown that the viral structure or strain is not a determinant of tissue tropism and clinical form of the disease. In North America, BCoV was identified for the first time in 1972, and it continues to be a significant economic concern for the cattle industry. The virus is classified under Coronaviridae family, Betacoronavirus genus and Betacorovirus 1 species. A number of conventional and molecular diagnostic assays are available for the detection of BCoV from clinical samples. Conventional assays for BCoV detection include virus isolation, which is challenging from clinical samples, electron microscopy, fluorescent antibody assays, and various immunoassays. Molecular tests are mainly based on nucleic acid detection and predominantly include conventional and real-time polymerase chain reaction (PCR) assays. Isothermal amplification assays and genome sequencing have also been used increasingly in recent years for the detection and identification of BCoV. Loop-mediated isothermal amplification, helicase-dependent amplification, recombinase polymerase amplification, and multienzyme isothermal rapid amplification are some examples of the isothermal amplification assays for used BCoV. Point-of-care testing has gained some popularity recently as they can offer user-friendly testing on the farm (barn-side). The present study reviewed literature on coronavirus infections in cattle from the last three and a half decades and presents information mainly on the current and advancing diagnostics in addition to epidemiology, clinical presentations, and the impact of the disease on the cattle industry.

At the beginning of December 2019, a new type of coronavirus emerged, SARS-CoV-2. This virus causes COVID-19, a highly contagious disease that can initially present asymptomatically and can also lead to death. Our ecological study goal was to evaluate the incidence, mortality, and lethality rates for COVID-19 between the states of Espírito Santo and Minas Gerais, with time series analysis using secondary and public databases on COVID-19 from January 2020 to July 2022. Prais-Winsten linear regression was used for trend analyses. In 2020, the rate in Espírito Santo was 2.19 times greater than Minas Gerais. This trend continued in 2021, with Espírito Santo's rate being 1.29 times greater. In 2022, Espírito Santo's rate remained 2.65 times higher than Minas Gerais. Furthermore, Espírito Santo had the highest mortality, with the exception of 2021. In turn, Minas Gerais had the highest fatality rate throughout the analyzed pandemic period. The state of Espírito Santo had a higher incidence of COVID-19, as well as higher mortality, when compared to the state of Minas Gerais. In turn, Minas Gerais had a higher fatality rate. Furthermore, both states showed similar trends for mortality, lethality, and incidence in the years 2020 and 2021.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known globally as COVID-19, originated in December 2019 in Wuhan, Hubei province in China and has rapidly spread across the globe ever since. The first recorded case in sub-Saharan Africa was in Nigeria, on the 25th February, 2020. The virus continues to spread, and new variants of the disease have emerged, the number of deaths and new infections in the countries of sub-Saharan Africa has been relatively low compared to predictive models. This could be due to several factors, such as slower transmission dynamics of the virus, a lower-case fatality rate, or a lack of testing or reliable data. Whilst this may also, in part, be due to the robustness of the nations' public health responses, there is scarce reporting on the specifics of this. However, emerging research has demonstrated that various environmental factors could influence virus transmission. The study adopted collected meteorological data that was critically analysed and discussed. The impact of three factors in the context of sub-Saharan African nations: temperature, ultraviolet (UV) exposure and pre-existing infection with Plasmodium (malaria) were discussed. These factors were discussed critically in light of the reduced rates of transmission and mortality observed.

The interleukin 6 (IL-6) receptor blocking antibody tocilizumab was repurposed in the coronavirus pandemic with the intention of blocking the excess inflammatory activation associated with severe disease. We retrospectively evaluated the response to tocilizumab based on measured levels of IL-6 as well as other inflammatory markers. In the sample of 41 patients with measured levels, 16 received tocilizumab. In patients who received tocilizumab, there was a statistically significant relationship between both higher IL-6 levels and measured acute phase reactants with mortality, but not in those who did not. Additionally, an improved mortality after tocilizumab was suggested with those with higher IL-6 measurements, but not in those with lower levels, but this finding failed to achieve statistical significance (p=0.14). Though this study is limited by a small sample size and retrospective design, an association is suggested between higher IL-6 levels and improved mortality after tocilizumab.

The Novel Coronavirus Disease (nCOVID) has grabed the whole world recently since its origin in Wuhan city of China. There is very dire consequences the whole world is going through because of nCOVID. The unprecedented nCOVID and associated consequences pushed the public health system in the crisis. Undoubtedly, it has affected almost all countries of the world. Nevertheless, hardly a few country it has spared from its dire consequences in terms social and economical losses. However, it is worth of observing that some of the positive consequences are also results of this pandemic. Consequently, this paper discusses the pros and cons of the pandemic from various perspective such as social and economical impacts on human lives and livelihoods.

Our perspective article covers major findings concerning Feline Infectious Peritonitis (FIP) - a fatal coronaviral disease of cats. In the context of FIP pathogenesis, we outline disease signalment and focus on the challenges and promises of FIP invoking coronavirus RNA detection. In particular, we outline critical aspects of coronavirus RNA replication and biogenesis. We infer the replicative intermediates of feline coronavirus may constitute an underappreciated factor triggering the progression of the maladaptive immune response underlying FIP pathogenesis.

Each sport has its specific rules, which determine what is allowed (or not) impacting directly on the sport demands. Studies involving physiological and time-motion measurements have shown that soccer is a highly demanding sport. The new coronavirus disease 2019 (COVID-19) has been a world health crisis. Soccer seasons were interrupted worldwide to avoid spreading the virus. Leagues resumed the season (no fans at the arenas) after several weeks of interruption, causing overlay of schedule. This overlay (e.g., games every Sunday and Wednesday) will cause accumulated fatigue on players, raising the risk of injuries. Considering this condensed calendar, the Fédération Internationale de Football Association (FIFA) has changed (temporarily) up to five substitutions during elite games (instead of three as the regular rule allows). Considering the already published scientific evidence, clearly, the change in the soccer substitution rule due to COVID-19 is insufficient. Implementing unlimited substitutions may benefit soccer players' health, coaches’ jobs, more entertainment for fans and sponsors (e.g., keeping intensity during all game, including on the second half) and eventually prolonging the useful life of the players. A real game-changer!

The soccer injury rate is distinctly higher during matches than the training sessions. Rules determine how to play, generating specific kinds of fatigue which is associated with the injury incidence. No research has evaluated the impact of potential rule-induced physical demands in soccer or comparing sports. Understanding the differences might be useful for enhancing rules (e.g., safer sport). Therefore, the aims of this study were: a) to described the differences in the rule-induced physical demands of soccer, futsal, basketball, and handball; and b) to evaluate whether soccer rule-induced physical demands are different than the other invasion intermittent team sports, focusing the impact of the substitutions rules. Data were collected from different sports rules (i.e., soccer, futsal, basketball, and handball), and performed hypothetical corrections to equate the other team sports to the soccer (i.e., court dimensions/number of players). The data showed that soccer has higher rule-induced physical demands: lower substitutions, higher dimensions in absolute (eight to 15 times), and relative (four to eight times) values. Hypothetical corrections showed that soccer has remarkably large differences. Therefore, we conclude that soccer has remarkably higher rule-induced physical demands than other team sports, and allowing unlimited substitutions in soccer is a must.

The world is suffering from the Coronavirus pandemic and is undergoing some drastic changes in day to day lives. The survey was conducted to analyze the situation of Pharmacy students in India. What are the types of challenges being faced by them during this lockdown due to the Pandemic COVID-19 and how are they getting adapted to the situations? A cross sectional survey was conducted via snowball sampling technique in which 226 participants submitted their response. The chief issue of concern to students was the change in the study pattern which has made the process much difficult for both the faculties and students. Online examination was also be reported as a point of concern. The normal life that we used to have is not acceptable in today’s scenario, hence, the institutions have to make the students more comfortable and adaptable towards the online studies and make the most out of it.

There is a current pandemic of a new type of coronavirus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The number of confirmed infected cases has been rapidly increasing. This paper analyzes the characteristics of SARS-CoV-2 in comparison with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and influenza. COVID-19 is similar to the diseases caused by SARS-CoV and MERS-CoV virologically and etiologically, but closer to influenza in epidemiology and virulence. The comparison provides a new perspective for the future of the disease control, and offers some ideas in the prevention and control management strategy. The large number of infectious people from the origin, and the highly infectious and occult nature have been two major problems, making the virus difficult to eradicate. We thus need to contemplate the possibility of long-term co-existence with COVID-19.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging infectious disease with currently a pandemic state. Cardiac function can be involved, affecting prognosis, in addition with lung feature severity, particularly in patients with comorbidities. Since the renin angiotensin aldosterone (RAA) system may interact with SARS-Cov-2, researches are still ongoing to assess the prognostic value of RAA blockers in cardiology.

OBJECTIVE: Recent worldwide outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of respiratory coronavirus disease 2019 (COVID-19), is a current, ongoing life-threatening crisis and international public health emergency. The early diagnosis and management of the disease remains a major challenge. In this review, we aim to summarize the updated epidemiology, causes, clinical manifestation and diagnosis, as well as prevention and control of the novel coronavirus SARS-CoV-2.MATERIALS AND METHODS: A broad search of the literature was performed in “PubMed” “Medline” “Web of knowledge”, and “Google Scholar” World Health Organization-WHO” using the keywords “severe acute respiratory syndrome coronavirus”, “2019-nCoV”, “COVID-19, “SARS”, “SARS-CoV-2” “Epidemiology” “Transmission” “Pathogenesis” “Clinical Characteristics”. We reviewed and documented the information obtained from literature on epidemiology, pathogenesis and clinical appearances of SARS-CoV-2 infection.RESULTS: The global cases of COVID-19 as of April 2, 2020 have risen to more than 900,000 and morbidity has reached more than 47,000. The incidence rate for COVID-19 has been predicted to be higher than the previous outbreaks of other coronavirus family members, including those of SARS-CoV and the Middle East Respiratory Syndrome Coronavirus (MERS-CoV). The main clinical presentation of SARS-CoV-2 infection ranges from asymptomatic stages to severe lower respiratory infection in the form of pneumonia. Most of the patients also presented with fever, cough, sore throat, headache, fatigue, myalgia and breathlessness.Individuals at higher risk for severe illness include elderly people and patients with a weakened immune system or that are suffering from a underlying chronic medical condition like hypertension, diabetes, cancer, respiratory illness or cardiovascular diseases.CONCLUSIONS: SARS-Cov-2 has emerged as a worldwide threat, currently affecting 170 countries and territories across the globe. There is still much to be understood regarding SARS-CoV-2 about its virology, epidemiology and clinical management strategies; this knowledge will be essential to both manage the current pandemic and to conceive comprehensive measures to prevent such outbreaks in the future.

During December 2019, a novel coronavirus named as 2019-nCoV, has emerged in Wuhan, China. The human to human transmission of this virus has also been established. Untill now the virus has infected more than seven thousand people and has spread to fifteen countries. The World Health Organization (WHO) has declared 2019-nCoV as global health emergency due to its outburst well beyond China. There is need to develop some vaccines or therapeutics to control or prevent 2019-nCoV infections. The bottleneck with current conventional approaches is that these require longer time for vaccine development. However, computer assisted approaches help us to produce effective vaccine in short time compared with conventional methods. In this study, bioinformatics analysis was used to predict B cell and T cell epitopes of surface glycoprotein of 2019-nCoV that could be suitable to trigger significant immune response. The sequence of surface glycoprotein was collected from the database and analyzed to identify the immunogenic epitope. Both B cell and T cell epitopes were analyzed so the predicted epitopes can stimulate both cellular and humoral immune responses. We predicted 13 B cell and 05 T cell epitopes that later on were joined with GPGPG linker to make a single peptide. This computational approach to design a multi epitope peptide vaccine against emerging 2019-nCoV allows us to find novel immunogenic epitopes against the antigen targets of surface 2019-nCoV surface glycoprotein. This multi epitope peptide vaccine may prove effective to combat 2019-nCoV infections.

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

Ongoing outbreak of pneumonia caused by novel coronavirus (2019-nCoV) began in December 2019 in Wuhan, China, and the number of new patients continues to increase. On the contrary to ongoing outbreak in China, however, there are limited secondary outbreaks caused by exported case outside the country. We here conducted simulations to estimate the impact of potential secondary outbreaks at a community outside China. Simulations using stochastic SEIR model was conducted, assuming one patient was imported to a community. Among 45 possible scenarios we prepared, the worst scenario resulted in total number of persons recovered or removed to be 997 (95% CrI 990-1,000) at day 100 and maximum number of symptomatic infectious patients per day of 335 (95% CrI 232-478). Calculated mean basic reproductive number (R0) was 6.5 (Interquartile range, IQR 5.6-7.2). However, with good case scenarios with different parameter led to no secondary case. Altering parameters, especially time to hospital visit could change the impact of secondary outbreak. With this multiple scenarios with different parameters, healthcare professionals might be able to prepare for this viral infection better.

A recent manuscript (Zhou, P. et al. “A pneumonia outbreak associated with a new coronavirus of probable bat origin”, Nature 579, 270–273 (2020). https://doi.org/10.1038/s41586-020-2012-7) from Wuhan Institute of Virology claimed the identification of a bat coronavirus, RaTG13, which showed 96.2% genome homology with SARS-CoV-2. In this paper, we raise the puzzling observations surrounding the identification, characterization, unique genome features of this RaTG13 strain, as well as its 100% nucleotide identity in partial RdRp gene with another bat coronavirus strain BtCoV/4991. And the paper presented premature hypothesis of potential bat origin of SARS-CoV-2 while RaTG13 strain was not successfully isolated. We also present the concerns on the methodology, data quality and experiment procedures described in this paper. We call for the authors to provide additional data, to share related samples to be verified and further characterized by other scientists.

A short review of the important studies was conducted to evaluate the potential of aerosol transmission of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The minimum size of droplets potentially carrying the SARS-CoV-2 was newly estimated and discussed in this review.

Background: Vaccinating children against COVID-19 is an essential public health strategy in order to reach herd immunity and prevent illness among children and adults. Parents are facing tremendous stress in relation to the COVID-19 pandemic and the effectiveness of the COVID-19 vaccination program for children. In this study, we aimed to investigate parents’ willingness to vaccinate their children against COVID-19 in North Kivu province (DRC). Methods: A cross-sectional survey between December 01, 2021 to January 20, 2022 in 6 health zones (Goma, Karisimbi, Butembo, Beni, Kamango and Katwa) was conducted in the province of North Kivu. In each health zone, we selected 5 clusters (Health area) using the method of probabilistic selection proportional to population size. In total, 522 parents participated in our study. Results: Overall, 32.8% of parents intended to vaccinate their children. In the multivariate analysis, younger age of parents (aOR : 2.40, CI : [1.50-3.83]), higher level of fear that “a member of my family” could contract COVID-19 (aOR : 2.35, CI : [1.38-4.02]), higher level of perceived vulnerability to COVID-19 within the family (aOR : 1.70, CI : [1.005-2.2881]), higher level of perceived susceptibility to COVID-19 within the family (aOR : 3.07, CI : [1.80-5.23]), and history of vaccination against COVID-19 among parents (aOR : 16.47, CI : [8.39-32.33]), were significantly associated with the intention to have their children or adolescents vaccinated. Conclusion: Willingness of parents to vaccinate their children against the COVID-19 vaccination was low in North Kivu. There is undeniably in this region a need to reinsure the populations about vaccine safety for both children and adults. Public health authorities should also address widespread misinformation about vaccines in a timely manner.

The National Examination in Indonesia has been abolished since 2020. Hence, the Indonesian junior high schools makes its final examination items for the 9th-grade, and from the results, the school determines students' graduation. The final examination has an important role and significant value in making decisions about students' graduation. Therefore, this study is aimed to analyze the Online Final Examination items in one of the public junior high schools in Bandung. The sample was 234 students in grade 9 using their mathematics examination tests, comprising 20 multiple-choice items with 4 options, while the data processing used Winsteps software with the Rasch modeling technique. Subsequently, the Rasch model results showed an acceptable person separation statistic of 1.54 and sufficient person reliability at 0.74. The item separation statistics was in a good category at 4.59, while the item reliability at 0.95 was excellent. Although four online final examination items were in the fit category, 16 were good and capable of dividing students according to their abilities. The result also provided very detailed data about the quality of the items and the ability of each grade 9 student. Since each test item is included in the fit category, this study contributes information on preparing and analyzing the Online Final Examination to teachers..

Background: The aim of our study was to analyze the effect of socioeconomic inequalities, both at the individual and area of residence levels, on the probability of COVID-19 confirmed infection, and its variations across three pandemic waves. Methods: Retrospective cohort study. We included data from all individuals tested by COVID-19 during the three waves of the pandemic, from March to December 2020 (357,989 individuals). We studied the effect of inequalities on the risk of having a COVID-19 confirmed diagnosis after being tested using multilevel analyses with two levels of aggregation: individuals and basic healthcare area (BHA) of residence (deprivation level and type of zone). Results: Patient profile changed through the pandemic, with a predominance of low-paid employees living in deprived BHA. Workers with low salaries, unemployed and people on minimum integration income or who no longer receive the unemployment allowance, had a higher probability of COVID-19 infection than workers with salaries ≥€18,000 per year. Inequalities were higher in women and in the second wave. The deprivation level of BHA of residence influenced the risk of COVID-19 infection, especially in the second wave. Conclusions: There are inequalities in the risk of COVID-19 confirmed infection, both at individual and area level. It is necessary to develop individual and area coordinated measures in the control, diagnosis and treatment of the epidemic, in order to avoid an increase in the already existing inequalities.

The aim of the study was to examine the prevalence of suicide thoughts and -attempts during the early stage of the COVID-19 outbreak and examine factors associated with suicide thoughts in the general Norwegian population. A sample of 4527 adults living in Norway were recruited via social media. Data related to suicide thoughts and attempts, mental health variables, pandemic-related concerns and sociodemographic variables were collected. Associations with suicide thoughts were analyzed with logistic regression analysis. In the sample, 3.6 % reported suicide thoughts during the last month, while 0.2 % had attempted to commit suicide during the same period. Lower age (OR: 0.66, p < 0.001), daily alcohol use (OR: 3.29, p < 0.001), being in the risk group for COVID-19 complications (OR: 2.38, p < 0.01), and having economic concerns related to the pandemic (OR: 2.51, p < 0.001) were associated with having suicide thoughts. In addition to known risk factors, the study suggests that aspects specific to COVID-19 may be important for suicidal behaviors during the pandemic.