The ongoing emergence of SARS-CoV-2 virus variants remains a source of concern because it is accompanied by the potential for increased virulence as well as evasion of immunity. Here we show that, although having an almost identical spike gene sequence as another Omicron variant (BA.5.2.1), a BA.4 isolate lacked all the typical disease characteristics of other isolates seen in the Golden Syrian hamster model despite replicating almost as effectively. Animals infected with BA.4 had similar viral shedding profiles to that seen with BA.5.2.1 (up to day 6 post infection) but they all failed to lose weight or present with any other significant clinical signs. We hypothesize that this lack of detectable signs of disease during infection with BA.4 was due to a small (nine nucleotide) deletion (∆686-694) in the viral genome (ORF1ab) responsible for production of non-structural protein 1 which resulted in the loss of three amino acids (aa 141-143).

Monitored infection and vaccination rates during past past Corona waves are used to infer a posteriori two key parameter of the SIRV-epidemic model, namely the real time variation of the (i) ratio of recovery to infection rate and (ii) ratio of vaccination to infection rate. We demonstrate that using the classical SIR model the ratio between recovery and infection rates tends to overestimate the true ratio, that is of relevance in predicting the dynamics of an epidemics in the presence of vaccinations.

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.

Nowadays, the presence of pathogen-specific antibodies in the blood is widely controlled by a serodiagnostic technique based on the lateral flow immunoassay (LFIA). However, its common one-stage format with an antigen immobilized in the binding zone of a test strip and a nanodis-persed label conjugated with immunoglobulin-binding proteins is associated with risks of very low analytical signals. It is caused by the presence of non-specific immunoglobulins in very large excess to the target antibodies in the tested samples thus decreasing their binding with the detected labels. In this study, the first stage of the immunochromatographic serodiagnosis was carried out in its traditional format using a conjugate of gold nanoparticles with staphylococcal immunoglobulin-binding protein A and an antigen immobilized on a working membrane. At the second stage, a labeled immunoglobulin-binding protein was added, which enhanced the coloration of the bound immune complexes. The use of two separated steps, binding of specific antibodies, and further coloration of the formed complexes allowed a significant reducing the influence of non-specific immunoglobulins on the assay results. The proposed approach was ap-plied for the serodiagnosis using a recombinant RBD protein of SARS-CoV-2. As a result, an in-crease in the intensity of test zone coloration by more than two orders of magnitude was demonstrated, which enabled to significantly reduce false-negative results. When testing a panel of 16 positive and 8 negative serum samples, the diagnostic sensitivity of the LFIA was 62.5% for the common format and 100% for the enhanced format; the diagnostic specificity of both variants was 100%.

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

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

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

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

Coronavirus Disease 2019 (COVID-19) is the pandemic challenge of the last year. Cardiovascular involvement is one of the main characteristics of this disease. Due to endothelial damage, consequent phlogosis may increase a thrombosis risk. Cardiac injury may occur in different ways. However, an ischemic involvement of the cardiovascular system is rarely implied. In this regard, direct and indirect effects of COVID-19 are described. Nonetheless, the possible evaluation of the cardiovascular system may require different modalities. The cardiovascular evaluation may be different in emergency compared to critical care, requiring different tools for each setting. The aim of this review is to explore these modalities according to the different involvement of the cardiovascular system..

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

With the now available vaccination against Covid-19 it is quantitatively explored how vaccination campaigns influence the mathematical modeling of epidemics. The standard susceptible-infectious-recovered/removed (SIR) epidemic model is extended to the fourth compartment V of vaccinated persons and the vaccination rate v(t) that regulates the relation between susceptible and vaccinated persons. The vaccination rate v(t) competes with the infection (a(t)) and recovery (\mu(t)) rates in determining the time evolution of epidemics. In order for a pandemic outburst with rising rates of new infections it is required that k+b<1-2\eta, where k=\mu_0/a_0 and b=v_0/a_0 denote the initial ratios of the three rates, respectively, and \eta << 1 is the initial fraction of infected persons. Exact analytical inverse solutions t(Q) for all relevant quantities Q=[S,I,R,V] of the resulting SIRV-model in terms of Lambert functions are derived for the semi-time case with time-independent ratios k and b between the recovery and vaccination rates to the infection rate, respectively. These inverse solutions can be approximated with high accuracy yielding the explicit time-dependences Q(t) by inverting the Lambert functions. The values of the three parameters k, b and \eta completely determine the reduced time evolution the SIRV-quantities Q(\tau). The influence of vaccinations on the total cumulative number and the maximum rate of new infections in different countries is calculated by comparing with monitored real time Covid-19 data. The reduction in the final cumulative fraction of infected persons and in the maximum daily rate of new infections is quantitatively determined by using the actual pandemic parameters in different countries. Moreover, a new criterion is developed that decides on the occurrence of future Covid-19 waves in these countries. Apart from Israel this can happen in all countries considered.

The widespread deployment of social media has helped researchers access an enormous amount of data in various domains, including the pandemic caused by the COVID-19 spread. This study presents a heuristic approach to classify Commercial Instagram Posts (CIPs) and explores how the businesses around the Holy Shrine – a sacred complex in Mashhad, Iran, surrounded by numerous shopping centers – were impacted by the pandemic. Two datasets of Instagram posts (one gathered data from March 14th to April 10th, 2020, when Holy Shrine and nearby shops were closed, and one extracted data from the same period in 2019), two word embedding models – aimed at vectorizing associated caption of each post, and two neural networks – multi-layer perceptron and convolutional neural network – were employed to classify CIPs in 2019. Among the scenarios defined for the 2019 CIPs classification, the results revealed that the combination of MLP and CBoW achieved the best performance, which was then used for the 2020 CIPs classification. It is found out that the fraction of CIPs to total Instagram posts has increased from 5.58% in 2019 to 8.08% in 2020, meaning that business owners were using Instagram to increase their sales and continue their commercial activities to compensate for the closure of their stores during the pandemic. Moreover, the portion of non-commercial Instagram posts (NCIPs) in total posts has decreased from 94.42% in 2019 to 91.92% in 2020, implying the fact that since the Holy Shrine was closed, Mashhad citizens and tourists could not visit it and take photos to post on their Instagram accounts.

We start out by deriving simple analytic expressions for all measurable amounts of cases and fatalities during a pandemic evolution exhibiting multiple waves, described by the semi-time SIR model. The approximant shares all relevant features with the exact solution, including time and position of the peak of daily new infections, as well as the asymptotic behaviors at small and large times. We derive exact analytic expressions for the early doubling time, late half decay time, and a half-early peak law, characterizing the dynamical evolution. We show, in particular, how the asymmetry of the first epidemic wave and its exponential tails are affected by the initial conditions; a feature that has no analogue in the all-time SIR model. We apply the approach to available data from different continents. Our analysis reveals that the immunity is very strongly increasing during the 2nd wave, while it was still at a very moderate level of a few percent in several countries at the end of the first wave. The wave-specific SIR parameters describing the infection and recovery rates we find to behave in a similar fashion, while their ratio k was decreasing only by a about 5% for most countries. Still, an apparently moderate change of k can have significant consequences for the relevant numbers like the final amount of infected or deceased population. As we show, the probability for an additional wave is however low in several countries due to the fraction of immune inhabitants at the end of the 2nd wave, irrespective the currently ongoing vaccination efforts. We compare with alternate approaches.

Coronaviruses are pathogens recognized for having an animal origin, commonly associated with terrestrial environments. However, although in a few cases, there are reports of their presence in aquatic organisms like fish, frogs, waterfowls and marine mammals. None of these cases has led to human health effects when contact with these infected organisms has taken place, whether they are alive or dead. Aquatic birds seem to be the main group carrying and circulating these types of viruses among healthy bird populations. Although the route of infection for CoVID-19 by water or aquatic organisms has not yet been observed in the wild, the relevance of its study is highlighted because there are cases of other viral infections known to have been transferred to humans by aquatic biota. It is encouraging to know that aquatic species, such as fish, marine mammals, and amphibians, shows very few cases of coronaviruses and that some other aquatic animals may also be a possible source of cure or treatment against then, as some evidence with algae and marine sponges suggest.

All countries are facing decisions about which groups to prioritise for COVID-19 vaccination after the first vaccine product has been licensed, at which time supply shortages are inevitable. Here we define the key target populations and their size in China for a phased introduction of COVID-19 vaccination with evolving goals, accounting for the risk of illness and transmission. Essential workers (47.2 million) like healthcare workers could be prioritized for vaccination to maintain essential services. Subsequently, older adults, individuals with underlying health conditions and pregnant women (616.0 million) could be targeted to reduce severe COVID-19 outcomes. Then it could be further extended to target adults without underlying health conditions and children (738.7 million) to reduce symptomatic infections and/or to stop virus transmission. The proposed framework could assist Chinese policy-makers in the design of a vaccination program, and could be generalized to inform other national and regional COVID-19 vaccination strategies.

We revisit the Susceptible-Infectious-Recovered/Removed (SIR) model which is one of the simplest compartmental models. Many epidemological models are derivatives of this basic form. While an analytic solution to the SIR model is known in parametric form for the case of a time-independent infection rate, we derive an analytic solution for the more general case of a time-dependent infection rate, that is not limited to a certain range of parameter values. Our approach allows us to derive several exact analytic results characterizing all quantities, and moreover explicit, non-parametric, and accurate analytic approximants for the solution of the SIR model for time-independent infection rates. We relate all parameters of the SIR model to a measurable, usually reported quantity, namely the cumulated number of infected population and its first and second derivatives at an initial time t=0, where data is assumed to be available. We address the question on how well the differential rate of infections is captured by the Gauss model (GM). To this end we calculate the peak height, width, and position of the bell-shaped rate analytically. We find that the SIR is captured by the GM within a range of times, which we discuss in detail. We prove that the SIR model exhibits an asymptotic behavior at large times that is different from the logistic model, while the difference between the two models still decreases with increasing reproduction factor. This part A of our work treats the original SIR model to hold at all times, while this assumption will be released in part B. Releasing this assumption allows to formulate initial conditions incompatible with the original SIR model.

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

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

Recycled wastewater is considered as a sustainable source of irrigation water. Despite commendable safety records, viral contamination of agricultural products has occurred the past causing disease outbreaks. This review examines the apprehension that the novel coronavirus (SARS-CoV-2) may also spread through recycled wastewater irrigation (RWI) industry. The novel SARS-CoV-2 is now perceived as an enteric pathogen, and has been found to remain stable in the wastewater for days. Mounting evidences also suggest that viral particles shed by infected individuals through sewage, and greywater is much higher (up to 10 Log₁₀) than the amount typically removed (6-7 Log₁₀) through the recycled water disinfection processes. Such gap indicated an increased risk of infection through fecal-oral transmission route. This study also identified greywater irrigation schemes posing a higher risk of transmission of SARS-CoV-2. It was recommended that countries putting greywater in the ‘low risk’ category may rewrite the safety guidelines in post COVID-19 times. This review also suggest that the choice of irrigation method could be critical in protecting the farmers, and the consumers from possible infections during the pandemic. In this regard, irrigation methods (i.e. sprinkler) that generate airborne droplet (leading to aerosols) may be operated with caution when public spaces are in the vicinity. The study also indicated that the developing countries should regulate surface irrigation practice that pump water from polluted rivers during the pandemic.

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.

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

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.

The Coronavirus disease due to SARS-CoV-2 emerged in Wuhan city, China in December 2019 and rapidly spread more than 200 countries as a global health pandemic. There are more 3 million confirmed cases and around 207,000 fatalities. The primary manifestation is respiratory and cardiac but neurological manifestations are being reported in the literature as case reports and case series. The most common reported symptoms to include headache and dizziness followed by encephalopathy and delirium. Among the complications noted are Cerebrovascular accident, Guillian barre syndrome, acute transverse myelitis, and acute encephalitis. The most common peripheral manifestation was hyposmia. It is further noted that sometimes the neurological manifestations can precede the typical features like fever and cough and later on typical manifestations develop in these patients. Hence a high index of suspicion is required for timely diagnosis and isolation of cases to prevent the spread in neurology wards. We present a narrative review of the neurological manifestations and complications of COVID-19. Our aim is to update the neurologists and physicians working with suspected cases of COVID-19 about the possible neurological presentations and the probable neurological complications resulting from this novel virus infection.

The severity of the global COVID-19 pandemic, with a high transmission rate, 2.6-4.7% lethality and a huge economic impact, poses an urgent need for efficient medical treatments and vaccines. Currently, there are only non-specific treatments to assist the patients in acute respiratory distress during the inflammatory step following the preliminary infection by SARS-CoV-2. Clinical trials of drug repurposing were quickly launched at the international level. Specific treatments such as the transfusion of plasma from patients who have recovered into infected patients or the use of specific inhibitors of the viral RNA-polymerase complex are promising strategies to block infection. To complete the therapeutic arsenal, we believe that the opportunity of targeting the SARS-CoV-2 genome by RNA therapy should be deeply investigated. In the present paper, we propose to design specific antisense oligonucleotides targeting transcripts encoding viral proteins associated to replication and transcription of SARS-CoV-2, aiming to block infection. We designed antisense oligonucleotides targeting the genomic 5’ untranslated region (5’-UTR), open reading frames 1a and 1b (ORF1a and ORF1b) governing expression of the replicase/transcriptase complex, and the gene N encoding the nucleoprotein that is genome-associated. To maximize the probability of efficiency, we predicted the antisense oligonucleotides by using two design methods: i) conventional antisense oligonucleotides with 100% phosphorothioate modifications (ASO); ii) antisense locked nucleic acids GapmeR. After binding the viral RNA target, the hetero-duplexes antisense oligonucleotide-RNA are cleaved by RNAse H1. Nine potent ASO candidates were found and we selected five of them targeting ORF1a (3), ORF1b (1) and N (1). Nine GapmeR candidates were predicted with excellent properties and we retained four of them targeting 5’-UTR (1), ORF1a (3), ORF1b (1) and N (1). The most potent GapmeR candidate targets the 5’-UTR, a key genomic domain with multiple functions in the viral cycle. By this open publication, we are pleased to share these in silico results with the scientific community in hopes of stimulating innovation in translational research in order to fight the unprecedented COVID-19 pandemic. These antisense oligonucleotide candidates should be now experimentally evaluated.

The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2, has been declared by the World Health Organization (WHO) as a pandemic. Unfortunately, finding a vaccine or developing drugs from the scratch is a time-consuming luxury given the widespread and high fatality rates of the virus. In the short term, repurposing of drugs already in use seem to be the most rational step to quickly and effectively curb the virus. Several antiviral agents had been proposed as possible remedies, but the 4-aminoquinolines, Chloroquine (CHQ) and hydroxychloroquine (HCHQ) appear to be generating more interest. They are generic, cheaply available and have proven efficacy against malaria parasites in Africa. The human immunodeficiency virus (HIV), on the other hand, targets the immune system thereby reducing the patient’s ability to fight infections. Sadly, 68% of the global HIV burden occur in Africa. It is therefore anticipated that incidence of severe forms of COVID-19 could occur in Africa because of associated endemic conditions that compromise the immune system. With CHQ and HCHQ being considered for clinical use against COVID-19, there is a need to highlight their potential merits and confounding variables in the subgroup of patients with or without HIV.

The Gauss model for the time evolution of the first corona pandemic wave allows to draw conclusions on the dark number of infections, the amount of heard immunization, the used maximum capacity of breathing apparati and the effectiveness of various non-pharmaceutical interventions in different countries. In Germany, Switzerland and Sweden the dark numbers are 7.4 +/- 6.1, 11.1 +/- 8.5 and 25 +/- 25, respectively. Our method of estimating dark numbers from modeling both, infection and death rates simultaneously spares these countries the laborious, time-consuming and costly medical testing for antibodies of large portions of the population. In Germany the total number of infected persons, including the dark number of infections by the first wave is estimated to be 1.06 +/- 0.60 million, corresponding to 1.28 +/- 0.72 percent of the German population. We work out direct implications from these predictions for managing the 2nd and further corona waves.

The recent outbreak and spread of the COVID-19 virus infection across the world has seen a massive global system-wide shutdown of human social and economic activity. Both developed and developing nations have been forced to contain and isolate their citizens as much as possible. However, the continuous rising cases in both categories of nations, especially those with poor or nonexistent testing facilities and healthcare systems pose a hidden danger. The seemingly lack of and access to a truly global concerted research effort in both temporary but effective symptom mitigation may lead to more deaths in infected cases. We propose that a fusion of both technological and home-grown solutions can be utilized effectively to manage symptoms. This would add to the preventive methods of social distancing, isolation, quarantine and frequent handwashing to halt the impact of the disease. We also hope to spur further research in such drug/non-drug combination therapy-based methods with emphasis on effectiveness based on quality of nutrient sources.

Social distancing, washing hands and good hygiene are essential and currently the most potent methods available to curb down the unprecedented speed by which the new coronavirus is spreading across the globe. Even under lockdown, which is necessary to significantly reduce the number of people that get infected by an ill person, are there additional measures that each of us can embrace to even further reduce the risk of infection and the severity of the COVID-19 disease? Given the lack of licensed drugs that target SARS-CoV-2 specifically, we have to look into additional non-specific defense mechanisms that animals and humans evolved to protect themselves from pathogen invasions. The goal of this article is to describe how various of our non-specific defense mechanisms work, which actually precede the inflammatory response, and to discuss whether we can exploit the unique features of the coronavirus envelope and the self-cleaning machinery of the human respiratory tract to strengthen our self-defense. The challenge is to actively interfere with supportive measures during the short time window between getting exposed and before an inflammatory response gets initiated.

Novel coronavirus infection is a recent infective agent that causes severe potentially fatal pneumonia. The clinical presentation includes asymptomatic infection, severe pneumonia, and acute respiratory failure. Data pertaining to the clinical presentation of solid organ transplant recipients are scarce. Two cases of novel coronavirus infection in two recipients of renal transplant with variable clinical presentations and outcomes are reported. The first patient presented with progressive respiratory symptoms, acute renal failure, and passed away, whereas the second one, although presented with respiratory tract symptoms and hypoxemia remained stable and exhibited an excellent clinical recovery despite recent reception of thymoglobulin induction. This paper reports rare cases of novel coronavirus infection in renal transplant recipients. For an enhanced insight of the novel coronavirus infection and acute kidney injury on the clinical presentation, severity, and outcome in solid organ transplant recipients, further investigations are required.

There is currently a lack of pathologic data on the novel coronavirus (SARS-CoV-2) pneumonia, or COVID-19, from autopsy or biopsy. Two patients who recently underwent lung lobectomies for adenocarcinoma were retrospectively found to have had COVID-19 at the time of surgery. These two cases thus provide important first opportunities to study the pathology of COVID-19. Pathologic examinations revealed that, apart from the tumors, the lungs of both patients exhibited edema, proteinaceous exudate, focal reactive hyperplasia of pneumocytes with patchy inflammatory cellular infiltration, and multinucleated giant cells. Hyaline membranes were not prominent. Since both patients did not exhibit symptoms of pneumonia at the time of surgery, these changes likely represent an early phase of the lung pathology of COVID-19 pneumonia.

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

SARS-CoV-2 is a novel betacoronavirus and the aetiological agent of the current COVID-19 outbreak that originated in Hubei Province, China. While polymerase chain reaction is the front-line tool for SARS-CoV-2 surveillance, application of amplification-free and culture-free methods for isolation of SARS-CoV-2 RNA, partnered with next-generation sequencing, would provide a useful tool for both surveillance and research of SARS-CoV-2. We here release into the public domain a set of bait capture hybridization probe sequences for enrichment of SARS-CoV-2 RNA from complex biological samples. These probe sequences have been designed using rigorous bioinformatics methods to provide sensitivity, accuracy, and minimal off-target hybridization. Probe design was based on existing, validated approaches for detecting antimicrobial resistance genes in complex samples and it is our hope that this SARS-CoV-2 bait capture platform, once validated by those with samples in hand, will be of aid in combating the current outbreak.

Introduction: On March 11, 2020, the World Health Organization (WHO) declared Coronavirus disease 2019 (COVID-19) as a pandemic. The spread of the Delta variant of coronavirus started in June 2021 and accounted for the fifth peak of COVID-19 in Iran in July 2021. According to reports from other countries, vaccination protects against severe diseases caused by COVID-19, including the Delta variant. Studies have also shown that vaccination provides strong protection against SARS-CoV-2 infection, COVID-19-related hospitalization, and mortality. This retrospective cohort study was designed based on the medical care monitoring center (MCMC) database of Sayyad Shirazi Hospital.Methods: The following patient data were extracted for this study: demographic characteristics, signs and symptoms, ICU admission, need for aggressive oxygen therapy, including intubation, mortality, and vaccination status. Results: Being vaccinated was associated with a 4.14-fold increase in survival (adjusted OR=4.14; 95% CI: 2.22 to 7.69; P<0.01), and individuals in a younger age group demonstrated a 5.58-fold higher likelihood of surviving (adjusted OR=5.58; 95% CI: 4.25 to 8.14; P<0.01). The risk of severe COVID-19 was significantly lower in vaccinated individuals, showing a 3.12-fold decrease in risk (adjusted OR=3.12; 95% CI: 2.06 to 4.72; P<0.01), and in younger age groups, the risk exhibited a 3.28-fold decrease (adjusted OR=3.28; 95% CI: 2.66 to 4.04; P<0.01).Conclusion: The present results suggest that receiving at least one dose of COVID-19 vaccine had a significant relationship with decreased COVID-19 severity and mortality in vaccinated patients compared to unvaccinated patients.

Antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are multi-targeted and variable over time. Multiplex quantitative serological assays are needed to provide accurate and robust seropositivity data for establishment of serological signatures during vaccination and or infection. We describe here, validation and evaluation of an electro-chemiluminescence (ECL) based Mesoscale Discovery assays (MSD), for estimation of total and functional IgG to SARS-CoV-2 spike, nucleocapsid, and receptor binding (RBD) proteins in human serum samples to establish serological signatures of SARS-CoV-2 natural infection and breakthrough cases. The 9-PLEX assay was validated as per ICH, EMA and US FDA guidelines using a panel of sera samples including the NIBSC/WHO international reference panel (20/268). Assay demonstrated high specificity and selectivity in inhibition assays, wherein the homologous inhibition was more than 85% and heterologous inhibition was below 10 %. Assay also met predetermined acceptance criteria for precision (CV < 30 %), accuracy (70-130 %) and dilutional linearity. Method applicability to serological signatures was demonstrated using sera samples (N=45) representing vaccinated, infected and breakthrough cases. The method was able to establish distinct serological signatures and thus provide potential tool for seroprevalence of SARS-COV-2 during vaccination or infection.

The dynamical equations of the susceptible-infected-recovered/removed (SIR) epidemics model play an important role to predict and/or analyze the temporal evolution of epidemics outbreaks. Crucial input quantities are the time-dependent infection ($a(t)$) and recovery ($\mu (t)$) rates regulating the transitions between the compartments $S\to I$ and $I\to R$, respectively. Accurate analytical approximations for the temporal dependence of the rate of new infections $\dot{J}(t)=a(t)S(t)I(t)$ and the corresponding cumulative fraction of new infections $J(t)=J(t_0)+\int_{t_0}^tdx\dot{J}(x)$ are available in the literature for either stationary infection and recovery rates and for a stationary value of the ratio $k(t)=\mu (t)/a(t)$. Here a new and original accurate analytical approximation is derived for general, arbitrary and different temporal dependencies of the infection and recovery rates which is valid for not too late times after the start of the infection when the cumulative fraction $J(t)\ll 1$ is much less than unity. The comparison of the analytical approximation with the exact numerical solution of the SIR-equations for different illustrative examples proves the accuracy of the analytical approach.

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.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the COVID-19 pandemic still able to infect the population in many countries. The Omicron strain is the most mutated variant of SARS-CoV-2. The high transmissibility of the strain and the ability to evade immunity require a priority study of its properties in order to quickly create effective means of preventing it. The present work is devoted to the study of in silico interaction of piRNAs with the genome of the SARS-CoV-2 (gRNA) in order to identify endogenous piRNAs and propose synthetic piRNAs with high antiviral activity for drug development. The studies were carried out using proven bioinformatic methods of interaction of the entire SARS-CoV-2 genome with more than eight million piRNAs. Binding sites (BSs) of piRNAs in the 5'UTR were located with overlapping nucleotide sequences called clusters of BSs. Several clusters of BSs were found in the nsp3, nsp7, RNA-dependent RNA polymerase, endoRNAse, S surface glycoprotein, ORF7a and nucleocapsid. 16 synthetic piRNAs have been proposed that interact with gRNA with free binding energy from -170 kJ/mol to -175 kJ/mol, which can be used to create drugs that suppress the reproduction of SARS-CoV-2.

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 onset of the Coronavirus 2019 (COVID-19) pandemic has challenged the worldwide healthcare sector, including dentistry. The highly infectious nature of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and risk of transmission through aerosol generating procedures has profoundly impacted the delivery of dental care services globally for months causing prioritization of critical dental needs and suspension of routine dental procedures. As dental practices with strengthened infection control strategies and preventive measures are re-opening in the “new normal” period, it is the responsibility of healthcare professionals to constantly analyze new data and limit the spread of COVID-19 in dental care settings. With the new variants of SARS-CoV-2 rapidly emerging in different geographic locations, a definite need to comply more than ever with the rigorous public health measures to mitigate COVID -19 transmission exists. The aim of this article is to provide dental clinicians with essential information regarding both the spread of SARS-CoV-2 virus and protective measures against COVID-19 transmission in dental facilities. By compiling guidance and standard protocols recommended by credible national and international organizations, this article serves as an aid to navigating through this unprecedented time with ease. Much to learn about COVID-19 exists and because of constant ongoing research, we are not aware of all of the newly found information. However, in this paper, we reviewed the available literature recommended for the best current practices that must be taken for a dental office to function safely and successfully.

The negative effect of COVID-19 pandemic has reach world economy due to absence from work for SARS-CoV-2 infection in workers, among other things. However, some economic areas are essential to society and people must continue working outside home, to support economic reactivation; their serological profile could be different from global population. Cross-sectional study. Workers from health, construction, public transportation, public force, bike delivery messengers, independent or informal commerce areas, and residents of Bucaramanga or its metropolitan area were invited to participate. All participants self-completed a virtual survey and a blood test was taken to assess IgG and IgM with ARC COV2 test. Seroprevalence was estimated considering a complex survey design, correcting for finite population effect and adjusting for test performance. 7.045 workers were enrolled; 59.9% were women, most were residents of Bucaramanga and working in health occupations. Global adjusted seroprevalence was 19.5% (IC95% 18.6 - 20.4), being higher for Girón [27.9% (CI95% 24.5 - 31.30]). Workers with multiple contact with people during working hours or using public transportation to go to work had higher frequency of seropositivity for SARS-CoV-2. Seroprevalence among workers living in these four municipalities from the Colombian northeast area is still low.

To date, viruses closely related to SARS-CoV-2 have been reported in four bat species: Rhinolophus acuminatus, Rhinolophus affinis, Rhinolophus malayanus, and Rhinolophus shameli. Here, we analysed 343 sequences of the mitochondrial cytochrome c oxidase subunit 1 gene (CO1) from georeferenced bats of the four Rhinolophus species identified as reservoirs of SARS-CoV-2-like viruses. Haplotype networks were constructed in order to investigate patterns of genetic diversity among bat populations of Southeast Asia. No strong geographic structure was found for the four Rhinolophus species, suggesting high dispersal capacity. The ecological niche of SARS-CoV-2 like viruses was predicted using the four localities of bat SARS-CoV-2-like viruses and the localities where bats showed identical or very similar CO1 haplotypes than virus-positive bats. The ecological niche of SARS-CoV-like viruses was deduced from the localities where bat SARS-CoV-like viruses were previously detected. The results show that the ecological niche of SARS-CoV2-like viruses includes several regions of mainland Southeast Asia whereas that of SARS-CoV-like viruses is mainly restricted to China. In agreement with these results, human populations in Laos, Vietnam, Cambodia, and Thailand appear to be much less affected by the Covid-19 pandemic than other countries of Southeast Asia. In the climatic transitional zone between the two ecological niches (southern Yunnan, northern Laos, northern Vietnam, and possibly Hainan and Taiwan), genomic recombination between highly divergent viruses is more likely to occur. Since recombinant viruses can threaten the benefit of vaccination campaigns, these regions should be under surveillance.

Over two years (2012-2014), 719 nasopharyngeal samples were collected from 6 weeks to 12 months old infants presenting at emergency department with moderate to severe acute bronchiolitis. Viral testing was performed and we found 98% positive samples including 90% Respiratory Syncytial Virus, 34% Human Rhino Virus, and 55% viral co-detections with predominance of RSV/HRV co-infections (30%). Interestingly, we found that the risk of being infected by HRV is higher in the absence of RSV, suggesting interferences or exclusion mechanisms between these two viruses. Conversely, Coronavirus infection had no impact on the likelihood of co-infection involving HRV and RSV. Bronchiolitis is the leading cause of hospitalizations in infants before 12 months of age, and many questions about its role in the later chronic respiratory diseases (asthma and chronic obstructive pulmonary disease) do exist. Role of virus detection and burden of viral codetections need to be further explored, in order to understand the physiopathology of chronic respiratory diseases, a major public health issue.

SARS-CoV-2 continues to widely circulate in populations globally. Underdetection is acknowledged and is problematic when attempting to capture the true prevalence. Seroprevalence studies, where blood samples from a population sample are tested for SARS-CoV-2 antibodies that react to the SARS-CoV-2 virus, are a common method for estimating the proportion of people previously infected with the virus in a given population. However, obtaining reliable estimates from seroprevalence studies is challenging for a number of reasons, and the uncertainty in the results is often overlooked by scientists, policy makers and the media. This paper reviews the methodological issues that arise in designing these studies, and the main sources of uncertainty that affect the results. We discuss the choice of study population, recruitment of subjects, uncertainty surrounding the accuracy of antibody tests themselves, and the relationship between antibodies and infection over time. Understanding these issues can help the reader to interpret and critically evaluate the results of seroprevalence studies.

Knowing the “point of view” of the immune system is essential to understand the characteristic of a pandemic, such as that generated by the Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV)-2, responsible for the Coronavirus Disease (COVID)-19. In this review, we will discuss the general host/pathogen interactions dictating protective immune response or immunopathology, addressing the role of immunity or immunopathology in influencing the clinical infection outcome, and debate the potential immunoprophylactic and immunotherapy strategies required to fight the virus infection.

In humans, coronaviruses can cause infections of the respiratory system, with damage of varying severity depending on the virus examined: ranging from mild or moderate upper respiratory tract diseases, such as the common cold, to pneumonia, severe acute respiratory syndrome, kidney failure and even death. Human coronaviruses known to date, common throughout the world, are seven. The most common - and least harmful - ones were discovered in the 1960s and cause a common cold. Others, more dangerous, were identified in the early 2000s and cause more severe respiratory tract infections. Among these the SARS-CoV, isolated in 2003 and responsible for the Severe Acute Respiratory Syndrome (the so-called SARS), which appeared in China in November 2002, the Coronavirus 2012 (2012-nCoV) cause of the Middle Eastern Respiratory Syndrome from Coronavirus (MERS), which exploded in June 2012 in Saudi Arabia, and actually SARS-CoV-2. On December 31, 2019, a new Coronavirus strain was reported in Wuhan, China, identified as a new Coronavirus beta strain ß-CoV from Group 2B, with a genetic similarity of approximately 70% to SARS-CoV, the virus responsible. of SARS. In the first half of February, the International Committee on Taxonomy of Viruses (ICTV), in charge of the designation and naming of the viruses (i.e., species, genus, family, etc.), thus definitively named the new coronavirus as SARS-CoV-2. This article highlights the main knowledge we have about the biomolecular and pathophysiologic mechanisms of SARS-CoV-2.

The COVID-19 pandemic caused by the novel coronavirus emerged in Wuhan City, Hubei province of China at the end of 2019, has radically transformed the lives of people around the world. Due to its fast spreading, it is currently considered as a worldwide health, social and economic concern. The lack of knowledge on this area has encouraged academic sphere for extensive research, which is reflected in exponentially growing scientific literature in this area. However, current state of COVID-19 research reveals only early development of knowledge, while a comprehensive and in-depth overview remains neglected. Accordingly, the main aim of this paper is to fill the aforementioned gap in the literature and provide an extensive bibliometric analysis of COVID-19 research across science and social science research landscape, using innovative and sophisticated bibliometric approaches (e.g. Venn diagram, Biblioshiny descriptive statistics, VOSviewer co-occurrence network analysis, Jaccard distance cluster analysis, text mining based on logistic regression). The bibliometric analysis is based on the Scopus database including all relevant and latest information on COVID-19 related publications (n=16,866) in the first half of 2020. The empirical results indicate that there is still a lack of publications of COVID-19 and its implications in less-explored (non-health) sciences, especially in social sciences. Accordingly, the findings emphasize an importance of a comprehensive and in-depth approach considering different scientific disciplines in COVID-19 research. The understanding of the evolution of emerging scientific knowledge on COVID-19 is beneficial not only for scientific community but also for evidence-based policymaking in order to prevent and address the COVID-19 pandemic.

Coronaviruses are positive sense RNA virus belonging to the Coronaviridae family, which are further subdivided into four genera: Alpha, Beta, Gamma, and Delta Coronaviruses. Infectious bronchitis virus and SARS-CoV belong to Beta Coronaviridae family. Infectious bronchitis virus causes respiratory and nephritic signs that includes tracheal rales, urate crystals, lethargy and nasal discharge. In livestock and pets, the Coronavirus infection causes mostly gastrointestinal lesions, which may be prevented through vaccination and biosecurity. Recent infections of SARS-CoV-2 (also known as COVID-19) on farm and pet animals were summarized in this study. Besides, zoo animals were reported with infections in some countries/regions. Although the damage of COVID-19 has not been reported as serious as highly pathogenic avian influenza (HPAI) and African Swine Fever (ASF) on farm animals so far, the transmission mechanism of COVID-19 among group animals/farms and its long-term impacts are still not clear. The impact of Coronavirus on animals and potential prevention strategies, such as vaccine development and farm biosecurity measures, were discussed. Prior to the development of the effective vaccine, the biosecurity measures (e.g., conventional disinfection strategies and innovated technologies) may play roles in preventing potential spread of diseases/viruses.

The pandemic outbreak of COVID-19 had begun in March of 2020 on a global scale. This outbreak has originated numerous questions for society and many challenges for public managers. The disease is worrying because it has a high propagation velocity, high lethality levels, and there is no cure. Some groups are considered more vulnerable due to pre-existing disease conditions, age-range, and living conditions. In Latin American countries, people live in different conditions than those who live in countries located in the North hemisphere, such as climatic conditions, less favorable socioeconomic conditions, different educational levels, inequality, precarious urban infrastructure, etc. These factors generate even more concern and uncertainty about the pandemic than in developed countries. This study aimed, although preliminarily, to identify areas of great socio-spatial vulnerability and susceptibility of infection of people over 60 years old of COVID-19 in Brasília, Brazil. In this research, publicly available data and information about the population characteristics and social aspects were used, all connected directly to the census sectors. With the support of Geographic Information System (GIS), a matrix was used to cross-check the data and, thereby, achieve the objective of identifying the most vulnerable sectors for people aged over 60 years old. The results point out to more than 400 census sectors classified as Extremely Vulnerable in Brasília and it should be the object of special attention for public managers to do specific health care actions.

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.

This study estimates the negative impacts of the COVID-19 on poverty and unemployment in Indonesia. In doing so, this study develops and uses the SD model that reproduced similar patterns in terms of GDP, poverty, and unemployment. Estimated unemployment and estimated poverty under the COVID-19 are calculated for three different economic scenarios: the optimistic, the mid, and the pessimistic scenarios. This study concludes that Indonesia will experience rising unemployment and poverty in ranges (9-10) and (25-26) million people respectively by the end of this year – depending on projected economy growths. This study suggests that existing financial aids are sufficient to support rising unemployment and rising poverty level. However, if the Indonesia government cannot carefully slow the COVID-19 flow, higher financial supports are required to curb the negative impacts of the COVID-19.

An outbreak of winter disease, complicated by severe respiratory syndrome, occurred in January 2020 in a high production dairy cow herd located in a hilly area of the Calabria region. Of the 52 animals belonging to the farm, 5 (9.6%) died with severe respiratory distress, death occurring 3-4 days after the appearance of the respiratory signs (caught and gasping breath). Microbiological analysis revealed absence of pathogenic bacteria whilst Real-time PCR identified the presence of RNA from Bovine Coronavirus (BCoV) in several organs: lungs, small intestine (jejunum), mediastinal lymph nodes, liver and placenta. Since being the only pathogen identified, BCoV was hypothesized to be the cause of the lethal pulmonary infection. Like the other CoVs, BCoV is able to cause different syndromes. Its role in calfhood diarrhoea and in mild respiratory disease is well known: we report instead the involvement of this virus in a severe and fatal respiratory disorder, with symptoms and disease evolution resembling that of Severe Acute Respiratory Syndromes (SARS).

The present study investigates the relationship between the transmission of COVID-19 infections and climate indicators in Dhaka City, Bangladesh, using coronavirus infections data available from the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh. The Spearman-ranked correlation test was carried out to study the association of seven climate indicators, including humidity, air quality, minimum temperature, precipitation, maximum temperature, mean temperature and wind speed with the COVID-19 outbreak in Dhaka City, Bangladesh. The study found that, among the seven indicators, only three indicators (air quality, minimum temperature and average temperature) have a significant relationship with new COVID-19 cases. The results of this paper will give health regulators and policymakers valuable information to lessen the COVID-19 infection in Dhaka and other countries around the world.

With confirmed COVID-19 cases surpassing the 8.5 million mark around the globe, there is an imperative need to deepen the efforts from the international scientific community to gain comprehensive understanding of SARS-CoV-2. Although the main clinical manifestations are associated with respiratory or intestinal symptoms, reports of specific and non-specific neurological signs and symptoms, both at presentation or during the course of the acute phase, are increasing. Approximately 25-40% of the patients present neurological symptoms. The etiology of these neurological manifestations remains obscure, and probably involves several direct pathways, not excluding the direct entry of the virus to the Central Nervous System (CNS) through the olfactory epithelium, circumventricular organs, or disrupted blood-brain barrier (BBB). Furthermore, neuroinflammation might occur in response to the strong systemic cytokine storm described for COVID-19, or due to dysregulation of the CNS angiotensin system. Descriptions of neurological manifestations in patients in the previous coronavirus (CoV) outbreaks have been numerous for the SARS-CoV and lesser for MERS-CoV. Strong evidence from patients and experimental models suggests that some human variants of CoV have the ability to reach the CNS and that neurons, astrocytes and/or microglia can be target cells for CoV. A growing body of evidence shows that astrocytes and microglia have a major role in neuroinflammation, responding to local CNS inflammation and/or to dysbalanced peripheral inflammation. This is another potential mechanism for SARS-CoV-2 damage to the CNS. In this work we will summarize the known neurological manifestations of SARS-CoV-2, SARS-CoV and MERS-CoV, explore the potential role for astrocytes and microglia in the infection and neuroinflammation, and compare them with the previously described human and animal CoV that showed neurotropism. We also propose possible underlying mechanisms by focusing on our knowledge of glia, neurons, and their dynamic intricate communication with the immune system.

The novel coronavirus disease (COVID-19) pandemic has impacted health and wellbeing globally. To strengthen preventive and clinical care amid this pandemic, technological innovations like artificial intelligence (AI) are increasingly used in different contexts. This bibliometric study aimed to assess the current scholarly development and prominent research domains in applications of AI technologies in COVID-19 research. A total of 105 articles were retrieved from MEDLINE database that emphasized on the use of AI in the context of COVID-19. Most articles had multiple authors with a collaboration index of 7.18. Moreover, most of the articles were produced from the USA (22.86%) and China (21.9%), whereas developing countries were underrepresented among the contributing nations. Furthermore, several research domains were identified, including prevention and control, diagnostics, epidemiological characteristics, therapeutics, psychological conditions, and different areas of data sciences related to COVID-19. The current bibliometric evidence shows the early stage of development in this field, which necessitates equitable applications of AI in COVID-19 research emphasizing on health disparities, socio-legal issues, vaccine development, and applied public health research in this pandemic.

Severe acute respiratory syndrome novel coronavirus 2 (SARS-CoV-2) has caused the global pandemic as COVID-19, which is the most notorious global public health crisis in the last 100 years. SARS-CoV-2 is composed of four structural proteins and several non-structured proteins. The multi-facet nucleocapsid (N) protein is the major component of structural proteins of CoVs, However, there are no dedicated genomic, sequences and structural analyses focusing on potential roles of N protein. Hence, there is an urgent requirement of a detailed study on N protein of SARS-CoV-2. Herein, we are presenting a comprehensive study on N protein from SARS-CoV-2. We have identified seven motifs conserved in the three major domains namely N-terminal domain, linker regions and the C-terminal domains. Out of seven motifs, six motifs are conserved across different members of coronaviridae, while motif4 is specific for SARS CoVs with potential amyloidogenic properties. Additionally, we report this protein has large patches of disordered regions flanking with these seven motifs. These motifs are hubs of epitopes with 67 experimentally verified epitopes from related viruses. We report the presence of three nuclear localization signals (NLS1-NLS3 mapped to 36-41, 256-26, and 363-389 residues, respectively) and two nuclear export signals (NES1-NLS2 from 151-161 and 217-230 residues, respectively) in the N protein of SARS-CoV-2. These deciphered two Q-patches as Q-patch1 and Q-patch2, mapped in the regions of 266-306, and 361-418 residues, which potentially help in the aggregation of the viral proteins along with ²¹⁹LALLLLDR²²⁶ patch. Additionally, we have identified 14 antiviral drugs potentially binding to seven motifs of N-proteins using docking-based drug discovery methods.

During the period of health emergency linked to the current COVID-19 pandemic, the management of children's oral health presents specific problems related to the infectious spread of the disease. These problems must be faced on the one hand by acting on the oral health prevention methods, and on the other by implementing specific protocols relating both to the conditions of oral pathologies that normally do not represent an emergency, and to those clinical situations that fall into the category of pediatric dental emergencies. In this perspective, in addition to defining rigorous and highly effective infection control protocols in the dental settings, it is of fundamental importance to work on remote communication and education aimed at maintaining the oral health of the children. This article, after an analysis of the risk factors from COVID-19 associated with pediatric dental treatment, presents a series of considerations on potential oral prevention strategies and on the management of emergency and non-emergency dental procedures in a context of disease transmission control, proposing new approaches and models of treatment based also on remote interaction techniques which will then retain their usefulness even at the end of the current emergency period.

The spread of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already taken on pandemic proportions, affecting over 150 countries in a matter of months. Even though containment measures in China have reduced new cases by more than 90%, this reduction is not the case elsewhere, as the US, Spain and Italy have come off worse-off by the spread of the virus, and there is serious concern regarding the national health systems' capacity around the world and Africa, in particular, to effectively respond to the needs of infected patients who require intensive care for the COVID-19 illness. As a result, authorities around the world have resorted to the lockdown strategy to curb the spread of the virus. Therefore, the study aimed at investigating the effect of the lockdown strategy in curbing the spread of the COVID-19 virus in Nigeria. Consequently, the study found daily relative risk increase in cases, and daily relative risk increase in mortality. Also observed is the growth in cases in areas where active measures were not taken. Further, halt in business activities has rendered many penniless and unable to provide for themselves basic amenities. The study recommends that there is need to implement community-level measures of social distancing which may include closing schools, need for individuals with COVID-19 case or respiratory symptoms be properly taken care of, trace and quarantine those who must have come in contact with affected persons and introducing stay at home palliatives for the general public.

As more cases of COVID-19 are studied and treated world-wide, it had become apparent that lethal and most severe cases of pneumonia are due to an out-of-control inflammatory response to the SARS-CoV2 virus. I explored the putative causes of this specific feature through a detailed genomic comparison with the closest SARS-CoV-2 relatives isolated from bats, as well as previous coronavirus strains responsible for the previous epidemics (SARS-CoV, and MERS-CoV). The high variability region of the nsp3 protein was confirmed to exhibit the most variations between closest strains. It was then studied in the context of physiological and molecular data available in the literature. A number of convergent findings point out de-mono-ADP-ribosylation (de-MARylation) of STAT1 by the SARS-CoV-2 nsp3 as a likely cause of the cytokine storm observed in the most severe cases of COVID-19. This may suggest new therapeutic approaches and an assay to predict the virulence of naturally circulating SARS-like animal coronaviruses.

The ongoing COVID-19 pandemic is shaking the foundations of public health governance all over the world. Researchers are challenged by informing and supporting authorities on acquired knowledge and practical implications. This commentary applies established theories of risk perception research to COVID-19 and reflects on the role of risk perceptions in these unprecedented times. Moreover, it calls for utilizing the knowledge on risk perception to improve health risk communication, build trust and contribute to a collaborating governance.

The outbreak of coronavirus 2 (SARS-CoV-2) has already taken on pandemic proportions and has affected more than 100 countries in recent weeks. It is imperative that global healthcare systems are prepared. Containment initiatives in Jordan, on the other hand, have decreased new cases by over 63%. The Jordanian national health system has been very pleased with its ability to adequately meet the needs of the patients diagnosed with SARS-CoV-2 pneumonia, and includes intensive care. From 2 March to 14 April 2020, between 4% and 8% of active infected patients in Jordan registered daily in intensive care. The percentage is very low.

The world is facing a major health crisis, the global pandemic of COVID-19 caused by the SARS-CoV-2 coronavirus, for which no approved antiviral agents or vaccines are currently available. Here we describe a collection of codon-optimized coding sequences for SARS-CoV-2 cloned into Gateway-compatible entry vectors, which enable rapid transfer into a variety of expression and tagging vectors. The collection is freely available via Addgene. We hope that widespread availability of this SARS-CoV-2 resource will enable many subsequent molecular studies to better understand the viral life cycle and how to block it.

SARS-CoV-2 is a novel and highly pathogenic coronavirus, which was first diagnosed in Wuhan city, China, in 2019, and spread to 185 countries and territories, and as of April 29, 2020, more than 3.11 million cases were recorded, and more than 217,000 people were killed. Despite all worldwide efforts, there is currently no vaccine, any drugs available to protect people against deadly SARS-CoV-2 coronavirus. The world urgently needs a SARS-CoV-2 coronavirus vaccine or effective antiviral drugs to relieve the human suffering associated with the pandemic that kills thousands of people every day. The SARS-CoV-2 genome encode a non-structural proteins named as ORF1a/b, and structural proteins such as spike (S) glycoprotein, nucleocapsid protein (N), small envelop protein (E) and matrix protein (M). A number of studies have been shown that CoV spike (S) glycoprotein and nucleocapsid protein (N) could be promising targets for vaccine, antibodies and therapeutic drug development to combat with deadly, pandemic SARS-CoV-2. Purposes of the present paper is the sequence analysis and amino acid variations of structural proteins deduced from novel coronavirus SARS-CoV-2 strains, isolated in different countries. Multiple sequence alignment of S, N and E proteins from four different coronavirus species, are also described. It is expected that the data from these studies will be very useful for the the designing and development of vaccines, antibodies and therapeutic agents that can be used to combat with the highly pathogenic SARS-CoV-2 coronavirus worldwide.

We describe a 90-year-old male presenting with disequilibrium, loss of balance and difficulty walking for three days prior to initial presentation. Interestingly, he denied cough, fever or dyspnea prior to arrival. Over the course of 48 hours, the patient developed acute respiratory distress syndrome (ARDS) requiring intubation, diagnosed with COVID-19 infection and was treated in the intensive care unit where he died. Since the initial cases in Wuhan China in Dec 2019, the medical and epidemiological communities have learned much about the presenting features, symptomatology, epidemiology, transmission and common physical, laboratory and radiological findings of this disease. Although common symptoms are already established, it is very important to learn and record atypical symptoms or presentations of this highly contagious disease. By doing so, we will be able to recognize earlier atypical symptoms and prevent the environmental exposure to Health care workers and future patients as well. We report that Central disequilibrium may be such as initial presenting sign and symptom of impending respiratory failure from SARS-CoV-2 virus. These atypical findings such as presyncope may precede common respiratory complications of SARS-CoV-2.

This document outlines best practice recommendations for an acute care physiotherapy for patients with COVID-19, with an emphasis on critical care rehabilitation including the patients in extra corporeal membrane Oxygenation (ECMO) support, developed for practice in Qatar but adaptable within any settings. This recommendation is the result of a combination of systematic evidence search, subsequent critical evaluation of retrieved evidence and consensus process. The agreed recommendations were integrated into a physiotherapy clinical reasoning algorithm. It includes recommendations on physiotherapy referral, screening, management categories and best practice recommendations. It is intended for use by physiotherapists and other relevant stakeholders in the acute care setting caring for adult patients with suspected and/or confirmed COVID-19.

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.

On March 11^th 2020, the World Health Organization (WHO) declared the coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus (SARS-CoV2) as a pandemic. Until an effective treatment or a vaccine is developed, the current recommendations are to contain the disease, and control its transmission. It is now clear that the primary mode of SARS-CoV2 transmission is aerosol/droplet spread, and by contacting virus contaminated surfaces acting as fomites (inanimate vectors). Furthermore, recent data indicate that the live virus particles are present in saliva, and, more alarmingly, asymptomatic individuals may transmit the infection. By virtue of the nature of the practice of dentistry where intrinsically, a high volume of aerosols are produced, as well as the close proximity of dentists and patients during treatment, dentists and allied dental staff are considered the highest risk health professional group for acquiring SARS-CoV2 during patient management. Therefore, several organizations and specialty associations have proposed guidelines and recommendations for limiting the transmission of SARS-COV2 from carriers to dentists and vice versa. This paper aims to provide a review of these guidelines, and concludes with a brief look at how the practice of dentistry may be impacted by COVID-19, in the post-pandemic era.

The proposal of novel drugs and approaches for effective treatment of the novel coronavirus is a necessity after the quick outbreak of the disease. Since the commencement of the coronavirus spread, enormous efforts have been made to protect, alleviate and cure the disease, though no specific treatment has been approved. While there have been convincing results in the use of chemical drugs and interferon therapy, such therapeutic approaches have various drawbacks and lack the required performance for the treatment of the new coronavirus. Medicinal plant species can provide a solution as a source of natural antiviral compounds by the accumulation of secondary metabolites and lectins as well as acting as a platform to express the viral immunogenic proteins. This study reviews the advantages and the results of previous research for the treatment of the novel coronavirus disease and previous generations of similar coronaviruses. Several plant-derived anti coronavirus compounds have been nominated that could be targeted for further research due to the similarity of the coronavirus disease in 2003 and the current coronavirus. This review regards plant species such as Scutellaria baicalensis (Baikal skullcap), and Utrica dioica (Stinging nettle) as suitable candidates for the new coronavirus antiviral research. Furthermore, the use of plants such as Nicotiana tabacum (Tobacco) for the expression of the coronavirus viral antigens can be a target for the future vaccinal research of the new coronavirus due to the efficiency of expression and intrinsic antiviral properties.

In December 2019, outbreak of novel coronavirus (COVID-19) occurred in Wuhan, Hubei Province, China and exported across the world leading to thousands of deaths and millions of suspected cases. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection into the host undergoes a huge number of complex replicative machineries which still remains unclear. Understanding the mechanism (s) of replication and mode of infection of SARS-CoV2 to human cells will help us in the development of novel vaccines or drugs for the eradication and prevention of the disease. This review compiles the knowledge of SARS-CoV2 replicative machinery, mode of infection to the human cells and the development of drugs and vaccines which are currently under clinical trials.

Background: The world, now in an emergency of preventing the drastic spread of COVID-19. After the infection was first reported in December 2019, almost every country did not pay attention to this highly contaminated disease and failed to react swiftly. Now the whole universe is in an vulnerable state, loosing a great loss of lives and facing difficulties in all socio-economic aspects. That is why we have the urge to develop an efficient mathematical model (quarantine) based on social consciousness to control the epidemic. Methods: This is a quarantine mathematical model. The outcome of the system is dependent on social consciousness. We have calculated the awareness level by considering various socio-economic factor of each country. In our model, the parameters are Education Index, GDP per capita, population density, high literacy and stable economy. To maximize the efficiency of the model, it has to be implemented in initial stage. However, strict application of the method in vigorous stage of epidemic will also bring a satisfactory outcome. Results: Higher social consciousness will decrease the number of infected population dramatically while minimal or lower awareness will do a outburst. Conclusion: Outbreak will be in control of health care system, lower the death rate and will ensure social and economic stability.

Increasing evidence points to host Th17 inflammatory responses as contributing to the severe lung pathology and mortality of lower respiratory tract infections from coronaviruses. This includes host inflammatory and cytokine responses to COVID-19 caused by the SARS-2 coronavirus (SARS CoV2). From studies conducted in laboratory animals, there are additional concerns about immune enhancement and the role of potential host immunopathology resulting from experimental human COVID-19 vaccines. Here we summarize evidence suggesting there may be partial overlap between the underlying immunopathologic processes linked to both coronavirus infection and vaccination, and a role for Th17 in immune enhancement and eosinophilic pulmonary immunopathology. Such findings help explain the link between viral-vectored coronavirus vaccines and immune enhancement and its reduction through alum adjuvants. Additional research may also clarify links between COVID-19 pulmonary immunopathology and heart disease.

The SARS-CoV-2 is a recently identified positive sense single stranded RNA virus and member of the coronavirus family of viruses. It is thought to be the etiological factor for the ongoing COVID-19 pandemic. This virus is thought to have originated from bats and acquired ability of human-to-human transmission. While SARS-CoV-2 is relatively benign, it has infected more than half a million people (as of March 29^th 2020) worldwide and the number of infected people continues to rise. More than 170 countries have reported COVID-19 positive cases. With a mortality rate of less than both the previous coronavirus outbreaks, COVID-19 has (conversely) caused the death of over 33,980 (as of 29^th March, 2020 at 22.00 hours EDT) people worldwide and the number is increasing. Given the enormous impact of this virus on human health and wellbeing and consequent devastating impacts on world trade, economics and quality of life, it is important to understand this virus better and get insight into its pathogenic mechanisms which will aid in devising effective measure to curb its spread and predict future pattern of its interaction with humans. Though very little is known about this SARS-CoV-2 but its mechanisms and patterns of spread can be speculated (with caution, nevertheless) from what we know about its closest relatives SARS-CoV-1 (responsible for SARS-2002 epidemic) and MERS-CoV (responsible for MERS-2012 epidemic). In the present review, we aim at bringing together the coherent and peer reviewed literature about the SARS-CoV-2 and its close relatives and try to understand its infection patterns and reconstruct its pathogenic mechanisms with anecdotes on diagnosis and future directions. We hope that this paper will serve the purpose of being a reliable source of information to scientists, clinicians and general public.

The COVID-19 pandemic is due to infection caused by the novel SARS-CoV-2 that impacts the lower respiratory tract. The spectrum of symptoms ranges from asymptomatic infections to mild respiratory symptoms to the lethal form of COVID-19 which is associated with severe pneumonia, acute respiratory distress and fatality. At present, the global case fatality rate of COVID-19 laboratory confirmed cases is ~4.7% ranging from ~0.3-0.4% in Chile and Israel to ~10.8% in Italy. To address this global crisis, up-to-date information on the viral genomics and transcriptomics is crucial for understanding the origins and global dispersal of the virus, providing insight into viral pathogenicity, transmission and epidemiology, and enabling strategies for therapeutic interventions, drug discovery and vaccine development. Therefore, this review provides a comprehensive overview of COVID-19 epidemiology, genomic etiology, findings from recent transcriptomic map analysis, viral-human protein interactions, molecular diagnostics, and the current status of vaccine and novel therapeutic intervention development. Moreover, we provide an extensive list of resources that will help the scientific community access numerous types of databases related to SARS-CoV-2 OMICs and approaches to therapeutics related to COVID-19 treatment.

The recent outbreak of novel coronavirus (SARS-CoV-2 or 2019-nCoV) and its spread to the whole world is currently posing one of the major threats to human health and the world economy. It has been suggested that SARS-CoV-2 is similar to SARS-CoV based on the genome sequence comparison. Despite the genomic similarity between SARS-CoV and SARS-CoV-2, the spike glycoprotein and receptor binding domain in SARS-CoV-2 shows considerable difference compared to SARS-CoV, due to the presence of several point mutations. We analyzed the receptor binding domain (RBD) from recently published 3D structure of spike glycoprotein of SARS-CoV-2 and compared with RBD of SARS-CoV. The observations highlight few important features of RBD in the light of the recently published findings from the 3D structures of spike glycoprotein and its complex with human angiotensin-converting enzyme 2 (ACE2) (Yan, R., et al. (2020); Wrapp, D., et al. (2020); Walls, A. C., et al. (2020)).

In this report, we demonstrate that it is possible to design epitope-based peptide vaccine candidates to counteract the novel China coronavirus (2019-nCoV) by using an approach similar to the one used in cancer neoantigen vaccination therapy. We identified multiepitope peptide vaccine candidates against 2019-nCov that can potentially trigger both CD4⁺ and CD8⁺ T cell immune response with increased efficiency due to the presence of CD4⁺ and CD8⁺ T cell epitopes and a cathepsin-sensitive linker. Furthermore, we suggest that the peptide design strategy should incorporate population-specific HLA alleles in order to optimize binding specificity of the peptides. We refer to this as populationalized vaccinomics.

A novel coronavirus called 2019-nCoV was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the world. 2019-nCoV spreads more rapidly than SARS-CoV. Unfortunately, there is no drug to combat the virus. It is of high significance to develop a drug that can combat the virus effectively before the situation gets worse. It usually takes a much longer time to develop a drug using traditional methods. For 2019-nCoV, it is now better to rely on some alternative methods to develop drugs that can combat such a disease effectively since 2019-nCoV is highly homologous to SARS-CoV. In this paper, we first collected virus RNA sequences from the GISAID database, translated the RNA sequences into protein sequences, and built a protein 3D model using homology modeling. Coronavirus main protease is considered to be a major therapeutic target, thus this paper focused on drug screening based on the modeled 2019-nCov_main_protease structure. The deep learning based method DFCNN, developed by our group, can identify/rank the protein-ligand interactions with relatively high accuracy. DFCNN is capable of performing virtual screening quickly since no docking or molecular dynamic simulation is needed. DFCNN identifies potential drugs for 2019-nCoV protease by performing drug screening against 4 chemical compound databases. Also, we performed drug screening for all tripeptides against the binding site of 2019-nCov_main_protease since peptides often show better stability, more bio-availability and negligible immune responses. In the end, we provided the list of possible chemical ligands and peptide drugs for experimental validation.

Studies have shown that COVID-19 patients with prediabetes frequently present with high plasma glucose levels on hospital admission. However, whether the glycemic abnormalities are temporary or persist after recovery from the illness is unclear. We conducted a prospective cohort study of 69 COVID-19 patients with prediabetes (HbA1c 5.7-6.4%) who were admitted to a tertiary care hospital in Chennai, India, from May to October 2020 and were discharged alive. Over a mean follow-up of 146.6 (SD: 72.5) days, the mean fasting plasma glucose rose by 16.8 mg/dl (from 119.3-136.1 mg/dl), 2-hr post-prandial glucose by 61.0 mg/dl (from 176.2-237.2 mg/dl), and HbA1c by 0.6% (5.9-6.5%). Of the 49 (84.5%) patients who were discharged with glucose-lowering medications, 40 (81.6%) continued taking them at the first follow-up visit (mean of 50.1 days from admission), and 39 (79.6%) continued taking them at the second follow-up visit (mean of 114.3 days from first the follow-up visit). In addition, 12.1% of patients developed new-onset diabetes after recovery from the illness. Continuous monitoring of glycemia and detecting new-onset diabetes in COVID-19 patients with prediabetes after recovery are essential, as the metabolic effects of SARS-CoV-2 persist for several months.

The global SARS-Cov-2 which caused the coronavirus disease 2019 (COVID-19) pandemic has had a significant impact over the last 3.5 years, especially among healthcare workers (HCWs) who were constantly in the forefront of the pandemic. Due to the nature of their work, HCWs faced a potential risk of exposure. Therefore, this study investigated the individual-level factors associated with perceived COVID-19 risk among South African HCWs. We used an analytical cross-sectional study design to analyse data from the South African Health Care workers’ response to the Coronavirus (COVID-19) pandemic online survey conducted by the Human Sciences Research Council across the nine provinces in South Africa, from 11th April to 7th May 2020. In this study, only data (n= 5 579) with non-missing values for COVID-19 risk and individual-level factors (age, gender, educational level, occupational category, and race) was analysed. Univariate and Multivariate binomial logistic regression analyses were conducted. The crude and adjusted odds ratio and p-value ≤ 0.05, were used to describe the association between the individual-level factors and perceived COVID-19 risk, from low-medium to high. The binomial logistic regression was used to assess the factors associated with high perceived risk. Perceived COVID-19 risk among HCWs in South Africa was significantly associated with age, race, educational level and occupational category. Being 60 years and older, being “White”, having a Master’s and Doctorate degrees and being a healthcare worker other than a nurse practitioner and medical practitioner, all had higher odds of having high perceived COVID-19 risk. The findings may be used to guide policies and programs aimed at mitigating the impacts of COVID-19 and other similar pandemics.

The recently reported microbial natural product N-benzoyl-tryptophane (1) along with twenty-two diverse known bioactive compounds were isolated from the marine Aspergillus terreus LGO13 after its re-cultivation using liquid culture fermentation. Structures of the isolated compounds were established on the basis of HR-ESIMS 1D/2D NMR spectroscopy, and comparison with literature data. The antimicrobial, cytotoxicity, and antiviral activities of the microbial extract and the obtained compounds were investigated using a set of microorganisms, cervix carcinoma KB-3-1, non-small cell lung cancer (NSCLC) A549, and coronavirus (SARS-CoV-2), respectively. Molecular docking (MD) simulation was employed to explore the theoretical targets of the isolated metabolites as anti-SARS-CoV-2 agents. Chaetominine (2) seemed to be a potential candidate against papain-like protease (PLpro), one of the viral proteins being aimed by recent research as a possible target of anti-covid agents. Inspired by the MD results, we accordingly assessed the antiviral efficacy of chaetominine (2), fumitremorgin C (6), and azaspirofuran A (9) against SARS-CoV-2. Fumitremorgin C (6) showed a high selectivity index (SI = 20.3), while chaetominine (2) and azaspirofuran A (9) showed moderate selectivity index (SI = 6.6 and 3.2, respectively). These results showed a promising antiviral activity of Fumitremorgin C against SARS-CoV-2 virus.

The global population is currently experiencing the impact of the SARS-CoV-2 coronavirus, which has caused the Coronavirus Disease 2019 (COVID-19) pandemic. By our profound comprehension of COVID-19, encompassing the involvement sequence of the respiratory tract, gastrointestinal system, and cardiovascular apparatus, the multiorgan symptoms of this infectious disease have been discerned. Metabolic-associated fatty liver disease (MAFLD) is a pervasive public health concern, intricately linked with metabolic dysregulation and estimated to afflict one-fourth of the global adult population. The burgeoning focus on the association between COVID-19 and metabolic dysfunction-associated fatty liver disease (MAFLD) is justified by the potential role of the latter as a risk factor for both SARS-CoV-2 infection and the subsequent emergence of severe COVID-19 symptoms. Investigations have suggested that changes in both innate and adaptive immune responses among metabolic dysfunction-associated fatty liver disease (MAFLD) patients may play a role in determining the severity of COVID-19. The remarkable similarities observed in the cytokine pathways implicated in both diseases imply the existence of shared mechanisms governing the chronic inflammatory responses characterizing these conditions. The effect of metabolic dysfunction-associated fatty liver disease (MAFLD) on the severity of COVID-19 illness remains uncertain, as indicated by conflicting results in cohort investigations.

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

COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), is estimated to have caused over 6.5 million deaths to date worldwide. The emergence of fast-evolving SARS-CoV-2 variants of concern alongside increased transmissibility and/or virulence as well as immune and vaccine escape capabilities highlight the urgent need for more effective antivirals to combat the disease in the long run along with regularly updated vaccine boosters. One of the early risk factors identified during the COVID-19 pandemic was that men are more likely to get infected by the virus, more likely to develop severe disease and exhibit higher likelihood of hospitalisation and mortality rates compared to women. An association exists between SARS-CoV-2 infectiveness and disease severity with sex steroid hormones and in particular androgens. Several studies underlined the importance of the androgen-mediated regulation of the host protease TMPRSS2 and the cell entry protein ACE2 as well as the key role of these factors in the entry of the virus into target cells. In this context, modulating androgen signalling is a promising strategy to block viral infection and antiandrogens could be used as a preventative measure at the pre- or early-hospitalisation stage of COVID-19 disease. Different antiandrogens, including commercial drugs used to treat metastatic castration-sensitive prostate cancer and other conditions, have been tested as antivirals with varying success. In this review, we summarise the most recent updates concerning the use of antiandrogens as prophylactic and therapeutic options for COVID-19.

On 11th March 2020, the World Health Organization declared COVID-19 as a pandemic. Vaccination programs have advanced greatly in the global health period, despite widespread anti-vaccination attitudes and misinformation. Vaccine hesitancy of COVID-19 vaccine is currently a major issue in Saudi Arabia. This cross-sectional study was carried out from June 25, 2021 to October 2021 in order to investigate the knowledge levels of acceptance and hesitancy of COVID-19 vaccine among Saudi’s nationals. The data was collected through a close-ended structured questionnaire from a total of 565 respondents. Overall, 78.41% respondents were female, 62.48% having university level education and 61.06% were unemployed. Majority of the participants 82.30% (n=465) think that Pfizer vaccine has the highest efficiency against COVID-19. Our study concludes that majority of the participants have satisfactory knowledge about COVID-19 vaccination. Concerns over vaccine components, effectiveness of vaccine and possible side effects are among the key causes for vaccine hesitancy.

This study aimed to examine trust in information provided by public authorities and financial measures put in place to address the impact of COVID-19. Using a cross-national approach among four Western countries; the United States of America, Norway, Australia, and the United Kingdom provides an analysis of responses related to trust and how they were associated with age group, gender, education level, employment status, size of place of residence, infection sta-tus, and social media use. When controlling for all included variables in logistic regression analyses, the likelihood of having trust in the public authorities’ information was higher for women, those with higher levels of education, and those living in urban areas. Being infected with the coronavirus, and spending more time daily on social media was associated with lower likelihood reporting trust in information. Although policies implemented to respond to eco-nomic concerns varied cross-nationally, higher age, identifying as female, being employed, liv-ing in a city, and lower levels of social media usage were associated with higher likelihood of trusting in the financial measures put in place to counteract the economic effects of COVID-19.

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

There is a relatively high risk of virus transmission in dental procedures and oropharyngeal examinations. We investigated the effects of mouthwashes on covid-19 viral load reduction during dental practices and oro-pharyngeal assessments. We performed a systematic search in PubMed, EMBASE, Scopus, Web of Science, Cochrane library for relevant studies up to February 2021. Papers evaluating patients with covid-19 infection (patients) who rinse mouthwashes (intervention) compared to patients who don’t rinse them (comparison) for reducing covid-19 viral load or reducing cross-infection of covid-19 (outcome) in the randomized and non-randomized clinical trial and quasi-experimental studies (study) were included due to PICOS question. Three independent authors conducted literature screening and data extraction. We extracted the most relevant data and we evaluated the risk of bias from the included studies. Out of 344 potentially eligible articles, six studies were included in this systematic review. Regarding viral load and negative cycle threshold (ct) values, 1% PVP_I and Listerine mouthwash were effective. 0.12% CHX mouthwash was effective 0-2 hours post rinsing, but it was not effective after 2 hours. A mixture solution of 0.2% Chlorhexidine gluconate and 6% Hydrogen peroxide was effective on day 5 of intervention. Gargling 1% hydrogen peroxide, 0.075% Cetylpiridinum Chloride (CPC), 0.5%PVP-I and 0.2% CHX mouthwashes was not effective on SARS-COV-2. It cannot be guaranteed that rinsing a specific kind of mouthwash prevents cross-infection of covid-19; however, the viral load of SARS-COV-2 in saliva will be decreased after rinsing mouthwashes containing 1%PVP-I and Listerine.

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.

COVID-19 has been a global healthcare concern impacting multiple aspects of individual and community wellness. As one moves forward with different methods to reduce the infection and mortality rates, it is critical to continue to study the impact that national and local ‘social distancing’ policies have on the daily lives of individuals. The aim of this study was to examine loneliness in relation to risk assessment, measures taken against risks, concerns, and social media use, while adjusting for sociodemographic variables. The cross-sectional study collected data from 3469 individuals from USA, UK, Norway, and Australia. Loneliness was measured with the de Jong Gierveld Loneliness Scale. Multiple linear regression was used in the analysis of associations between variables. The results showed that concerns about finances were more strongly associated with social loneliness, while concerns about the future was more strongly associated with emotional loneliness. Longer daily time spent on social media was associated with higher emotional loneliness. In conclusion, pandemic-related concerns seem to affect their perceptions of loneliness. While social media can be used productively to maintain relationships, and thereby prevent loneliness, excessive use may be counterproductive.

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

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

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

Human civilizations are under enormous threats due to the outbreak of novel coronavirus (COVID-19) originated from Wuhan, China. The asymptomatic carriers are the potential spreads of this novel virus. Since, guaranteed antiviral treatments have not been available in the market so far, it is really challenging to fight against this contagious disease. To save the living mankind, it is urgent to know more about how the virus transmits itself from one to another quite rapidly and how we can predict future infections. Scientists and Researchers are working hard in investigating to understand its high infection rate and transmission process. One possible way to know is to use our existing COVID-19 infection data and prepare a useful model to predict the future trend. Mathematical modelling is very useful to understand the basic principle of COVID-19 transmission and provide necessary guidelines for future prediction. Here, we have reviewed 9 distinct commonly used models based on Mathematical implementations for COVID-19 transmission and dig into the deep head to head comparison of each model. Finally, we have discussed interesting key behaviour of each model, relevant upcoming important issues, challenges and future directions.

Emerging viruses description have grown at an unprecedented rate since the beginning of the 21^st century. The emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and its related illness, Coronavirus Disease 2019 (COVID-19) has been reported as the third highly pathogenic coronavirus introducing itself into human population in the current era after the SARS-CoV and Middle East Respiratory Syndrome (MERS-CoV). Molecular and cellular studies considering the pathogenesis of this novel coronavirus are still in the early stages of research, however, regarding the similarity of SARS-CoV-2 and other coronaviruses, it could be hypothesized that the NF-κB, Cytokine regulation, ERK, and TNF-α signaling pathways are the more likely causes of inflammation upon onset of COVID-19. There are several drugs prescribed and used to alleviate the activity of these inflammatory cellular signaling pathways which might be beneficial for developing novel therapeutic modalities against COVID-19. In this review, we briefly summarized the alteration of cellular signaling pathways affected by coronavirus infection, particularly SARS-CoV and MERS-CoV and tabulated the current therapeutic agents approved for previous human diseases.

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

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), an RNA virus, is responsible for coronavirus disease 2019 (COVID-19) pandemic of 2020. Experimental evidence suggests that microRNA can mediate an intracellular defence mechanism against some RNA viruses. The purpose of this study was to identify microRNA with predicted binding sites in the SARS-CoV-2 genome, compare these to their microRNA expression profiles in lung epithelial tissue and make inference towards possible roles for microRNA in mitigating coronavirus infection. We hypothesize that high expression of specific coronavirus-targeting microRNA in lung epithelia may protect against infection and viral propagation, conversely low expression may confer susceptibility to infection. We have identified 128 human microRNA with potential to target the SARS-CoV-2 genome, most of which have very low expression in lung epithelia. Six of these 128 microRNA are differentially expressed upon in vitro infection of SARS-CoV-2. Twenty-eight and 23 microRNA also target the SARS-CoV and MERS-CoV, respectively. In addition, 48 and 32 microRNA are commonly identified in two other studies. Further research into identifying bona fide coronavirus targeting microRNA will be useful in understanding the importance of microRNA as cellular defence mechanism against pathogenic coronavirus infections.

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

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

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

The biosynthesis of DNA inherently competes with RNA synthesis because it depends on the reduction of ribonucleotides (RNA precursors) to 2’-deoxyribonucleotides by ribonucleotide reductase (RNR). Hence, RNA viruses can increase viral RNA production in cells by partially blocking the synthesis of DNA, e.g. by downregulating the mammalian selenoprotein thioredoxin reductase (TR), which normally acts to sustain DNA synthesis by regenerating reduced thioredoxin, a hydrogen donor for RNR. Computational and preliminary experimental evidence supports the hypothesis that a number of pathogenic RNA viruses, including HIV-1, Ebola, Zika, some flu viruses, and SARS-CoV-2, target TR isoforms by antisense. TR knockdown would create a host antioxidant defect that could be partially rectified by increased selenium intake, or be exacerbated by selenium deficiency, contributing to viral pathogenesis. There are several non-selenium-dependent means that viruses might also exploit to slow DNA synthesis, such as targeting RNR itself, or components of the glutaredoxin system, which serves as a backup redox system for RNR. HIV-1 substantially downregulates glutathione synthesis, so it interferes with both the thioredoxin and glutaredoxin systems. Computational results suggest that, like Ebola, SARS-CoV-2 targets TR3 by antisense. TR3 is the only TR isoform that includes an N-terminal glutaredoxin domain, so antisense knockdown of TR3 may also affect both redox systems, favoring RNA synthesis. In contrast, some DNA viruses encode their own glutaredoxins, thioredoxin-like proteins and even RNR homologues – so they are doing just the opposite, favoring DNA synthesis. This is clear evidence that viruses can benefit from shifting the RNA:DNA balance to their advantage.

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

This brief note aims to explain the scope in conducting large-scale serological surveys of SARS-CoV-2 to define the landscape of population immunity without overlooking the inherent uncertainty steaming from sampling design and diagnostic validity. The note completes with a succinct statistical appendix of simple methods for estimating prevalence from random population samples using imperfect diagnostic tests.