Seroprevalence of SARS-CoV-2: Insights into the epidemiology of the pandemic.

AIM: This study aimed to assess the seroprevalence of SARS-CoV-2 and disease symptoms in Malakand, Pakistan. MATERIALS & METHOD: 623 samples with suspected SARS-CoV-2 were collected from different regions of Malakand and analyzed to detect SARS-CoV-2 IgG antibodies using ELISA. RESULTS: 306 (49.1%) 0 f 623 patients were anti-SARS-CoV-2 IgG reactive, with a higher prevalence in males (75%) than females (25%). In this study, we enrolled two groups, subjects working in a non-medical setting and subjects working in a medical setting. Clinical symptoms were statistically linked with SARS-CoV-2. Four weeks of follow-up analysis of IgG titers in health care workers showed an increase in IgG antibodies titer. CONCLUSION: This study gives insights into the community-based spread of SARS-CoV-2 infection, associated immunity, and herd immunity in the studied population. This study can provide insights to the government about early vaccination of this population as most of the population is not yet vaccinated.

Identifying non-nucleoside inhibitors of RNA-dependent RNA-polymerase of SARS-CoV-2 through per-residue energy decomposition-based pharmacophore modeling, molecular docking, and molecular dynamics simulation.

BACKGROUND AND OBJECTIVE: The current coronavirus disease-2019 (COVID-19) pandemic has triggered a worldwide health and economic crisis. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes the disease and completes its life cycle using the RNA-dependent RNA-polymerase (RdRp) enzyme, a prominent target for antivirals. In this study, we have computationally screened ∼690 million compounds from the ZINC20 database and 11,698 small molecule inhibitors from DrugBank to find existing and novel non-nucleoside inhibitors for SARS-CoV-2 RdRp. METHODS: Herein, a combination of the structure-based pharmacophore modeling and hybrid virtual screening methods, including per-residue energy decomposition-based pharmacophore screening, molecular docking, pharmacokinetics, and toxicity evaluation were employed to retrieve novel as well as existing RdRp non-nucleoside inhibitors from large chemical databases. Besides, molecular dynamics simulation and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) method were used to investigate the binding stability and calculate the binding free energy of RdRp-inhibitor complexes. RESULTS: Based on docking scores and significant binding interactions with crucial residues (Lys553, Arg557, Lys623, Cys815, and Ser816) in the RNA binding site of RdRp, three existing drugs, ZINC285540154, ZINC98208626, ZINC28467879, and five compounds from ZINC20 (ZINC739681614, ZINC1166211307, ZINC611516532, ZINC1602963057, and ZINC1398350200) were selected, and the conformational stability of RdRp due to their binding was confirmed through molecular dynamics simulation. The free energy calculations revealed these compounds possess strong binding affinities for RdRp. In addition, these novel inhibitors exhibited drug-like features, good absorption, distribution, metabolism, and excretion profile and were found to be non-toxic. CONCLUSION: The compounds identified in the study by multifold computational strategy can be validated in vitro as potential non-nucleoside inhibitors of SARS-CoV-2 RdRp and holds promise for the discovery of novel drugs against COVID-19 in future.

The impact of COVID-19 on small- and medium-sized enterprises (SMEs): empirical evidence for green economic implications.

Small- and medium-sized enterprises (SMEs) in China have been hit hard by the coronavirus (COVID-19) outbreak, which has jeopardized their going out of business altogether. As a result, this research will shed light on the long-term impacts of COVID-19 lockdown on small businesses worldwide. The information was gathered through a survey questionnaire that 313 people completed. Analyzing the model was accomplished through the use of SEM in this investigation. Management and staff at SMEs worldwide provided the study's data sources. Research shows that COVID-19 has a significantly bad influence on profitability, operational, economic, and access to finance. In the study's findings, outside funding aids have played an important role in SMEs' skill to persist and succeed through technological novelty than in their real output. SME businesses, administrations, and policymakers need to understand the implications of this study's results.

Adoption of innovative strategies to mitigate supply chain disruption: COVID-19 pandemic

COVID-19 pandemic outbreak caused supply chain (SC) disruption and threatened human life across the world, which could be mitigated through innovative strategies. Based on this scenario, this study examines the impact of COVID-19 on green practices, SC crisis mitigation strategies, smart technologies, and sustainable supply chain performance in the Pakistani manufacturing industry. Data was collected from Pakistani firms and employed structural equation modeling for testing hypotheses. The empirical results found that the COVID-19 pandemic is statistically related to green practices, SC crisis mitigation strategies, and smart technologies, while it harms sustainable supply chain performance. Moreover, green practices, SC crisis mitigation strategies, and smart technologies positively contribute to sustainable supply chain performance. The results of this study also confirmed the mediating role of green practices, SC crisis mitigation strategies, and smart technologies and moderating role organizational commitment in the context of a developing economy’s manufacturing industry. This study enhances awareness and understanding and contributes to the existing literature on verifying the link between COVID-19 pandemic and green practices, SC crisis mitigation strategies, and smart technologies to increase sustainable supply chain performance during a pandemic disruption in the Pakistani context. This study supports the managers of supply chain and manufacturing firms in adopting green practices and smart technologies. Also, it helps in the formation and successful implementation of SC crisis mitigation strategies during the crisis.

Evolution of basic human values orientations: An application of monitoring changes in cluster solutions.

This study enumerates the evolution of basic human values orientations and the dynamic relationship between them, computed from Schwartz's value survey conducted in European nations. For this purpose, eight datasets related to the human value scale were extracted from the European Social Survey; each corresponds to a single round conducted cross-sectionally every two years since 2001. Change detection algorithm was implemented to the cluster solutions of temporal datasets, and the evolution of important clusters was traced. Finding of the study reveals that Universalism and Benevolence values are on the rise in European societies in the last couple of decades. Most of the European inhabitants believe in the smooth group functioning and form the organismic needs of cooperation. The people prefer anxiety-free life, and love for nature, environment, humanity, and kindness to other beings in society are essential constructs for them. They avoid self-centred behaviour and prefer social physiognomies.

A Cross-sectional Study of Antecedents and Consequence of Panic Buying Behavior: The Moderating Effect of COVID-19 Rumors.

The novel corona virus pandemic has influenced people buying behaviors. Due to the significant psychological and behavioral impact of COVID-19 on society, this study aimed to examine the determinants of panic buying behavior and a resultant psychological outcome in the form of a sense of security. The purpose of this study is to investigate the effect of COVID-19 caller ringback tone (CRT) experiences, that is, informational and stimulation experience, on the panic buying behavior and how rumors moderate this relationship. This research is quantitative and uses a purposive sampling method to collect the survey-based data from 264 respondents. The researchers analyzed the data using Partial Least Square Structural Equation Modeling (PLS-SEM). The results of data analysis indicated that the informational and stimulation experience of COVID-19 CRT had a significant influence on panic buying behavior which further resulted in a sense of security in public. This study could not find evidence of the moderating role of rumors in the relationship between COVID-19 CRT experiences and panic buying behavior. The findings highlight the role of the COVID-19 CRT in causing panic buying behavior and resultant psychological outcome and thus provide implications for policymakers on the control of panic buying under COVID-19.

Functionality of Monoclonal Antibody Therapy in SARS-CoV-2.

The coronavirus disease 2019 (COVID-19) pandemic emerged as a world crisis in 2019 and started a global search for optimal therapeutic regimen including vaccines, antiviral agents, and recently monoclonal antibody therapy. Clinical trials are currently underway for the efficacy of several neutralizing monoclonal antibodies against COVID-19. The evolution of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with immune evasion capacity has created a challenge for the healthcare workers with urgent need for prospective studies to determine functionality of monoclonal antibody therapy and their role in the reduction of hospitalization for disease severity. Herein, we report three cases of COVID-19 during the beginning of the spread of Omicron variants that were hospitalized after treatment with monoclonal antibody therapy in the emergency department. All the patients showed progression of the disease on imaging and were treated with dexamethasone, remdesivir and anticoagulation based on the symptoms and contraindications. Two of the patients recovered and were discharged with out-patient follow-up; however, one patient expired in the hospital. Monoclonal antibody therapy is a promising treatment to limit the progression of COVID-19 and reduce the hospital strain specifically in small community hospitals. Limited information is available about their efficacy in the new viral variants. These cases emphasize the need of future prospective study and randomized controlled trials to illustrate the utilization of monoclonal antibodies as a therapeutic modality in patients infected with the variants of SARS-CoV-2.

Exploring whole proteome to contrive multi-epitope-based vaccine for NeoCoV: An immunoinformtics and in-silico approach

Neo-Coronavirus (NeoCoV) is a novel Betacoronavirus (β-CoVs or Beta-CoVs) discovered in bat specimens in South Africa during 2011. The viral sequence is highly similar to Middle East Respiratory Syndrome, particularly that of structural proteins. Thus, scientists have emphasized the threat posed by NeoCoV associated with human angiotensin-converting enzyme 2 (ACE2) usage, which could lead to a high death rate and faster transmission rate in humans. The development of a NeoCoV vaccine could provide a promising option for the future control of the virus in case of human infection. In silico predictions can decrease the number of experiments required, making the immunoinformatics approaches cost-effective and convenient. Herein, with the aid of immunoinformatics and reverse vaccinology, we aimed to formulate a multi-epitope vaccine that may be used to prevent and treat NeoCoV infection. Based on the NeoCoV proteins, B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes were shortlisted. Four vaccines (Neo-1–4) were devised by fusing shortlisted epitopes with appropriate adjuvants and linkers. The secondary and three-dimensional structures of final vaccines were then predicted. The binding interactions of these potential vaccines with toll-like immune receptors (TLR-2, TLR-3, and TLR-4) and major histocompatibility complex molecules (MHC-I and II) reveal that they properly fit into the receptors’ binding domains. Besides, Neo-1 and Neo-4 vaccines exhibited better docking energies of -101.08 kcal/mol and -114.47 kcal/mol, respectively, with TLR-3 as compared to other vaccine constructs. The constructed vaccines are highly antigenic, non-allergenic, soluble, non-toxic, and topologically assessable with good physiochemical characteristics. Codon optimization and in-silico cloning confirmed efficient expression of the designed vaccines in Escherichia coli strain K12. In-silico immune simulation indicated that Neo-1 and Neo-4 vaccines could induce a strong immune response against NeoCoV. Lastly, the binding stability and strong binding affinity of Neo-1 and Neo-4 with TLR-3 receptor were validated using molecular dynamics simulations and free energy calculations (Molecular Mechanics/Generalized Born Surface Area method). The final vaccines require experimental validation to establish their safety and effectiveness in preventing NeoCoV infections.

Identifying Lockdown Relaxation Strategies and Policy Implications to Fight against COVID-19: Medical Experts Perspective from Pakistan.

The COVID-19 pandemic, was first identified in Wuhan, China, has had a drastic effect on the world economy and compelled governments to enforce lockdown in territories. However, lockdown is destroying the world economy badly as well as the physical and mental health of people. Therefore, governments must develop Lockdown Relaxation Strategies (LRS) to overcome the negative consequences of lockdown in Pakistan. Identifying LRS is important for public health and economic restoration. Therefore, this work is an initial attempt to develop LRS in a developing country - Pakistan, and prioritize LRS through a novel ISM-MICMAC approach. By taking response from experts, results show that implementation of smart lockdowns in affected areas, meeting minimum criteria of public health standards, limited operations of public transportation are the most important strategies. Results provide a strategic guideline for governments to take necessary measures and allocate resources appropriately.

Dataset on the safety behavior among Pakistani healthcare workers during COVID-19.

The dataset includes the particulars of 515 respondents on safety behavior during COVID-19. The questionnaires were adapted using Social Learning Theory and Social Exchange Theory. The variables included in dataset are Transactional Leadership (TSL), Transformational Leadership (TFL), Employee Well-Being (EWB) and Safety behavior (SB). Moreover, the dataset also contains the demographic profile of the respondents. Data was collected with the help of self-administered questionnaire from eight public hospitals in Punjab, Pakistan, namely Services Hospital Lahore, Sir Ganga Ram Hospital Lahore, Government General Hospital Faisalabad, DHQ Hospital Chiniot, Municipal General Hospital Sargodha, DHQ Hospital Jhang, DHQ Hospital Multan and Sulehri Children & General Hospital Sialkot. This dataset could provide a significant insight for future research in employee safety behavior.

In Silico Prediction of Novel Inhibitors of SARS-CoV-2 Main Protease through Structure-Based Virtual Screening and Molecular Dynamic Simulation.

The unprecedented pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is threatening global health. SARS-CoV-2 has caused severe disease with significant mortality since December 2019. The enzyme chymotrypsin-like protease (3CLpro) or main protease (Mpro) of the virus is considered to be a promising drug target due to its crucial role in viral replication and its genomic dissimilarity to human proteases. In this study, we implemented a structure-based virtual screening (VS) protocol in search of compounds that could inhibit the viral Mpro. A library of >eight hundred compounds was screened by molecular docking into multiple structures of Mpro, and the result was analyzed by consensus strategy. Those compounds that were ranked mutually in the 'Top-100' position in at least 50% of the structures were selected and their analogous binding modes predicted simultaneously in all the structures were considered as bioactive poses. Subsequently, based on the predicted physiological and pharmacokinetic behavior and interaction analysis, eleven compounds were identified as 'Hits' against SARS-CoV-2 Mpro. Those eleven compounds, along with the apo form of Mpro and one reference inhibitor (X77), were subjected to molecular dynamic simulation to explore the ligand-induced structural and dynamic behavior of Mpro. The MM-GBSA calculations reflect that eight out of eleven compounds specifically possess high to good binding affinities for Mpro. This study provides valuable insights to design more potent and selective inhibitors of SARS-CoV-2 Mpro.

COVID-19-induced Returns, Attention, Sentiments and Social Isolation: Evidence from Dynamic Panel Model

This article develops a dynamic panel model to examine the association among coronavirus outbreak, investor attention, social isolation, investor sentiments and stock returns in the German Stock exchange. The results of the two-step GMM estimator show a significant effect of coronavirus disease 2019 (COVID-19) cases on the Frankfurt Stock Exchange after controlling for calendar anomalies, meteorological conditions, country-specific factors and oil returns. Results also show that a higher level of stock returns during social isolation (lockdown period) is explained by investor attention to buy underpriced stocks. Thus, temporary social isolation enhances an investor?s ability to make better investment decisions. Investor sentiment indicators (momentum and liquidity) are also positively associated with the stock return and partially mediate the COVID-returns link, but they have no direct effect on investor attention. The stock market attracts investor attention under good news shocks (recovered cases) when investor sentiments are optimistic. Our results are robust across the transparency level of firms and their size.

Immunoinformatics and Molecular Docking Studies Predicted Potential Multiepitope-Based Peptide Vaccine and Novel Compounds against Novel SARS-CoV-2 through Virtual Screening.

BACKGROUND: Coronaviruses (CoVs) are enveloped positive-strand RNA viruses which have club-like spikes at the surface with a unique replication process. Coronaviruses are categorized as major pathogenic viruses causing a variety of diseases in birds and mammals including humans (lethal respiratory dysfunctions). Nowadays, a new strain of coronaviruses is identified and named as SARS-CoV-2. Multiple cases of SARS-CoV-2 attacks are being reported all over the world. SARS-CoV-2 showed high death rate; however, no specific treatment is available against SARS-CoV-2. METHODS: In the current study, immunoinformatics approaches were employed to predict the antigenic epitopes against SARS-CoV-2 for the development of the coronavirus vaccine. Cytotoxic T-lymphocyte and B-cell epitopes were predicted for SARS-CoV-2 coronavirus protein. Multiple sequence alignment of three genomes (SARS-CoV, MERS-CoV, and SARS-CoV-2) was used to conserved binding domain analysis. RESULTS: The docking complexes of 4 CTL epitopes with antigenic sites were analyzed followed by binding affinity and binding interaction analyses of top-ranked predicted peptides with MHC-I HLA molecule. The molecular docking (Food and Drug Regulatory Authority library) was performed, and four compounds exhibiting least binding energy were identified. The designed epitopes lead to the molecular docking against MHC-I, and interactional analyses of the selected docked complexes were investigated. In conclusion, four CTL epitopes (GTDLEGNFY, TVNVLAWLY, GSVGFNIDY, and QTFSVLACY) and four FDA-scrutinized compounds exhibited potential targets as peptide vaccines and potential biomolecules against deadly SARS-CoV-2, respectively. A multiepitope vaccine was also designed from different epitopes of coronavirus proteins joined by linkers and led by an adjuvant. CONCLUSION: Our investigations predicted epitopes and the reported molecules that may have the potential to inhibit the SARS-CoV-2 virus. These findings can be a step towards the development of a peptide-based vaccine or natural compound drug target against SARS-CoV-2.

Psychological Predictors of Anxious Responses to the COVID-19 Pandemic: Evidence from Pakistan.

OBJECTIVE: COVID-19 epidemic can be associated with a variety of anxious responses and safety behaviors. The present research explored the psychological implications associated with COVID-19 during the outbreak in 2020 to date. Pakistani media has given particular attention to this outbreak in the region. METHODS: Three hundred and forty-seven undergraduate university students from Pakistan completed a battery of questionnaires focusing fear of COVID-19, associated safety behaviors, factual knowledge of COVID-19, and other psychological pointers hypothesized to be as predictors of anxious responses to COVID-19 threat and associated safety behaviors. RESULTS: The sample appeared to be fearful of COVID-19 and this fear was related to disgust sensitivity, anxiety sensitivity-related physical concerns, body vigilance, contamination cognitions, and general distress. Results suggested that the tendency of overestimating the severity of contamination and anxiety sensitivity towards physical concerns are significant predictors of COVID-19 related fear and consequent safety behaviors. CONCLUSION: It is suggested that people with a greater concern of contamination are likely to respond fearfully to COVID-19 and that people with higher fear of COVID-19 are likely to feel contamination concerns.

Determine the Potential Epitope Based Peptide Vaccine Against Novel SARS-CoV-2 Targeting Structural Proteins Using Immunoinformatics Approaches.

Coronaviruses (CoVs) belong to the Coronaviridae-family. The genus Beta-coronaviruses, are enveloped positive strand RNA viruses with club-like spikes at the surface with a unique replication process and a large RNA genome (∼25 kb). CoVs are known as one of the major pathogenic viruses causing a variety of diseases in birds and mammals including humans (lethal respiratory dysfunctions). Recently, a new strain of coronavirus has been identified and named as SARS-CoV-2. A large number of COVID-19 (disease caused by SARS-CoV-2) cases are being diagnosed all over the World especially in China (Wuhan). COVID-19 showed high mortality rate exponentially, however, not even a single effective cure is being introduced yet against COVID-19. In the current study, immunoinformatics approaches were employed to predict the antigenic epitopes against COVID-19 for the development of a coronavirus peptide vaccine. Cytotoxic T-lymphocyte (CTL) and B-cell epitopes were predicted for SARS-CoV-2 coronavirus structural proteins (Spikes, Membrane, Envelope, and Nucleocapsid). The docking complexes of the top 10 epitopes having antigenic sites were analyzed led by binding affinity and binding interactional analyses of top ranked predicted peptides with the MHC-I HLA molecule. The predicted peptides may have potential to be used as peptide vaccine against COVID-19.

Proposed Design of Walk-Through Gate (WTG): Mitigating the Effect of COVID-19

The world is facing a new challenge to overcome the pandemic disease of Coronavirus (COVID-19). An outbreak of COVID-19 to more than 213 countries and territories caused damage to the economy of every country. The proper vaccine to combat this pandemic disease is not invented yet. Due to the lockdown situation, there is a shortage of daily used products globally. To overcome the issue of food shortage and economic survival, the world has to ease the lockdown rules and become operational with the precautionary measures. COVID-19 has a fast transmission rate, therefore, while living with COVID-19, breaking the fast transmission chain of COVID-19 is the only vital solution. Furthermore, there is a dire need to disinfect every individual and his luggage at the entrance of every shopping mall, hospital, public and private institutions, bus stops, metro stations, and railway stations. Hence, the proposed walk-through gate (WTG) with different sensors, i.e., infrared thermal camera, UV disinfectant sensor, disinfectant spraying system, touch-less hand sanitizer, and box having a face mask with a dustbin to discard the previous mask can provide an effective and efficient relief. The world cannot stop working and cannot survive for more than 3-6 months in a lockdown, hence the proposed idea is to install the disinfectant automated spraying WTG with a security walk-through gate at every possible entrance to conform living with the COVID-19 disease such as many other diseases. Breaking the transmission chain is the only solution to win the battle against COVID-19 until an effective vaccine invention.

Potential influence of Nagella sativa (Black cumin) in reinforcing immune system: A hope to decelerate the COVID-19 pandemic.

The world is witnessing a difficult time. The race of developing a new coronavirus (COVID-19) vaccine is becoming more urgent. Many preliminary studies on the pathophysiology of COVID-19 patients have provided some clues to treat this pandemic. However, no suitable treatment has found yet. Various symptoms of patients infected with COVID-19 indicated the importance of immune regulation in the human body. Severe cases admitted to the intensive care unit showed high level of pro-inflammatory cytokines which enhanced the disease severity. Acute Respiratory Distress Syndrome (ARDS) in COVID-19 patients is another critical factor of disease severity and mortality. So, Immune modulation is the only way of regulating immune system. Nigella sativa has been used for medicinal purposes for centuries. The components of this plant are known for its intense immune-regulatory, anti-inflammatory, and antioxidant benefits in obstructive respiratory disorders. A molecular docking study also gave evidences that N. sativa decelerates COVID-19 and might give the same or better results than the FDA approved drugs. The aim of this review was to investigate the possible immune-regulatory effects of N. sativa on COVID-19 pandemic. Our review found N. sativa's Thymoquinone, Nigellidine, and α-hederin can be a potential influencer in reinforcing the immune response on molecular grounds.

The effects of regional climatic condition on the spread of COVID-19 at global scale.

The pandemic outbreak of the novel coronavirus epidemic disease (COVID-19) is spreading like a diffusion-reaction in the world and almost 208 countries and territories are being affected around the globe. It became a sever health and socio-economic problem, while the world has no vaccine to combat this virus. This research aims to analyze the connection between the fast spread of COVID-19 and regional climate parameters over a global scale. In this research, we collected the data of COVID-19 cases from the time of 1st reported case to the 5th June 2020 in different affected countries and regional climatic parameters data from January 2020 to 5th June 2020. It was found that most of the countries located in the relatively lower temperature region show a rapid increase in the COVID-19 cases than the countries locating in the warmer climatic regions despite their better socio-economic conditions. A correlation between metrological parameters and COVID-19 cases was observed. Average daylight hours are correlated to total the COVID-19 cases with a coefficient of determination of 0.42, while average high-temperature shows a correlation of 0.59 and 0.42 with total COVID-19 cases and death cases respectively. The finding of the study will help international health organizations and local administrations to combat and well manage the spread of COVID-19.