The macroeconomic and epidemiological impacts of Covid-19 in Pakistan. (preprint)

'Coronavirus Disease 2019' (C19) is a respiratory illness caused by 'new Coronavirus' SARS-CoV-2. The C19 pandemic, which engulfed the world in 2021, also caused a national C19 epidemic in Pakistan, who responded with initial forced lockdowns (15-30 March 2020) and a subsequent switch to a smart lockdown strategy, and, by 31 December 2020, Pakistan had managed to limit confirmed cases and case fatalities to 482,506 (456 per 100,000) and 10,176 (4.8 per 100,000). The early switch to a smart lockdown strategy, and successful follow-up move to central coordination and effective communication and enforcement of Standard Operating Procedures, was motivated by a concern over how broad-based forced lockdowns would affect poor households and day-labour. The current study aims to investigate how the national Pakistan C19 epidemic would have unfolded under an uncontrolled baseline scenario and an alternative set of controlled non-pharmaceutical intervention (NPI) policy lockdown scenarios, including health and macroeconomic outcomes. We employ a dynamically-recursive version of the IFPRI Standard Computable General Equilibrium model framework (Lofgren, Lee Harris and Robinson 2002), and a, by now, well-established epidemiological transmission-dynamic model framework (Davies, Klepac et al 2020) using Pakistan-specific 5-year age-group contact matrices on four types of contact rates, including at home, at work, at school, and at other locations (Prem, Cook & Jit 2017), to characterize an uncontrolled spread of disease. Our simulation results indicate that an uncontrolled C19 epidemic, by itself, would have led to a 0.12% reduction in Pakistani GDP (-721mn USD), and a total of 0.65mn critically ill and 1.52mn severely ill C19 patients during 2020-21, while 405,000 Pakistani citizens would have lost their lives. Since the majority of case fatalities and symptomatic cases, respectively 345,000 and 35.9mn, would have occurred in 2020, the case fatality and confirmed case numbers, observed by 31. December 2020 represents an outcome which is far better than the alternative. Case fatalities by 31. December 2020 could possibly have been somewhat improved either via a more prolonged one-off 10 week forced lockdown (66% reduction) or a 1-month forced lockdown/2-months opening intermittent lockdown strategy (33% reduction), but both sets of strategies would have carried significant GDP costs in the order of 2.2%-6.2% of real GDP.

How Does Health Uncertainty Impact Greenhouse Gas Emissions in European Union Economies? A Blessing in Disguise.

The global outbreak of COVID-19 caused serious threats to public health and economic growth all around the world, but on the other hand, the betterment of the environment took place. How pandemics' health uncertainty will affect environmental quality is a crucial matter to address. The paper investigates the asymmetric association between pandemics-related health uncertainty and greenhouse gas emissions (GHG) in the top emitter European Union economies (Italy, Germany, France, Poland, Netherlands, Spain, Czech Republic, Belgium, Romania, and Greece). Employing data from 1996 to 2019, a unique approach called 'Quantile-on-Quantile', is adopted to evaluate the influence of various quantiles of the health uncertainty on GHG emissions. According to estimates, health uncertainty enhances environmental quality by minimizing GHG in most of our chosen nations at certain quantiles of data, which makes pandemics a blessing in disguise for environmental quality. Additionally, the estimations indicate that the grades of asymmetry between our variables varies by locality, accentuating the requisite for authorities to give specific consideration while executing health uncertainty and environmental quality policies.

Examining the convergence of dominant themes related to social entrepreneurship, NGOs and globalization-A systematic literature review.

Social entrepreneurship (SE) is an all-encompassing concept in comparison to a typical non-government organization (NGO). It is a topic that has captured the interest of academics investigating nonprofit, charitable, and nongovernmental organizations. Despite the interest, few studies have examined the overlap and convergence of entrepreneurship and non-governmental organizations (NGOs), in congruence with the new phase of globalization. The study gathered and evaluated 73 peer-reviewed papers using a systematic literature review methodology, mainly from Web of Science but also from Scopus, JSTOR, and Science Direct, and supplemented by a search of existing databases and bibliographies. Based on the findings, 71 percent of studies suggest that organizations must reconsider the concept of social work, which has evolved rapidly, aided by globalization. The concept has changed from the NGO model to a more sustainable one, such as that proposed by SE. However, it is difficult to draw broad generalizations regarding the convergence of context-dependent complex variables such as SE, NGOs, and globalization. The results of the study will significantly contribute to a better understanding of the convergence of SE and NGOs, as well as the recognition that many aspects of NGOs, SE, and post-COVID globalization remain unexamined.

Uncertainty in firm innovation scheme and impact of green fiscal policy, Economic recovery of Chinese firms in the post-Covid-19 era

With the Covid-19 outbreak, changing prices of natural resource raw materials are driving up industrial costs, limiting output, and jeopardising economic growth. To encourage the revival of the green economy, fiscal and budgetary policies must focus on fostering innovation and growth. This essay investigates the incentives and mechanics of innovation as a recovery strategy by looking at the impact of tiny tax cuts on energy. Using quarterly data from listed Chinese firms from Q1 2019 to Q2 2021, estimate and draw numerous conclusions using a variance-variance technique. To begin with, innovation is a means of regaining and expanding market share, and tax incentives to enhance energy efficiency may be extremely beneficial to a company's inventive efforts. Second, our findings suggest that tax incentives for energy efficiency encourage businesses to invest in innovation by alleviating financial constraints. Finally, corporations may cut financial expenditures and internal cash flow by sponsoring creative activities. The findings have significant policy implications, since they show that successful eco-design fiscal policies might be part of a post-Covid-19 recovery business transformation programme.

The SARS-CoV-2 Spike Protein Activates the Epidermal Growth Factor Receptor-Mediated Signaling.

The coronavirus disease-19 (COVID-19) pandemic is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). At the molecular and cellular levels, the SARS-CoV-2 uses its envelope glycoprotein, the spike S protein, to infect the target cells in the lungs via binding with their transmembrane receptor, the angiotensin-converting enzyme 2 (ACE2). Here, we wanted to investigate if other molecular targets and pathways may be used by SARS-CoV-2. We investigated the possibility of the spike 1 S protein and its receptor-binding domain (RBD) to target the epidermal growth factor receptor (EGFR) and its downstream signaling pathway in vitro using the lung cancer cell line (A549 cells). Protein expression and phosphorylation were examined upon cell treatment with the recombinant full spike 1 S protein or RBD. We demonstrate for the first time the activation of EGFR by the Spike 1 protein associated with the phosphorylation of the canonical Extracellular signal-regulated kinase1/2 (ERK1/2) and AKT kinases and an increase in survivin expression controlling the survival pathway. Our study suggests the putative implication of EGFR and its related signaling pathways in SARS-CoV-2 infectivity and COVID-19 pathology. This may open new perspectives in the treatment of COVID-19 patients by targeting EGFR.

Machine learning-based analytics of the impact of the Covid-19 pandemic on alcohol consumption habit changes among United States healthcare workers.

The COVID-19 pandemic is a global health concern that has spread around the globe. Machine Learning is promising in the fight against the COVID-19 pandemic. Machine learning and artificial intelligence have been employed by various healthcare providers, scientists, and clinicians in medical industries in the fight against COVID-19 disease. In this paper, we discuss the impact of the Covid-19 pandemic on alcohol consumption habit changes among healthcare workers in the United States during the first wave of the Covid-19 pandemic. We utilize multiple supervised and unsupervised machine learning methods and models such as decision trees, logistic regression, support vector machines, multilayer perceptron, XGBoost, CatBoost, LightGBM, AdaBoost, Chi-Squared Test, mutual information, KModes clustering and the synthetic minority oversampling technique on a mental health survey data obtained from the University of Michigan Inter-University Consortium for Political and Social Research to investigate the links between COVID-19-related deleterious effects and changes in alcohol consumption habits among healthcare workers. Through the interpretation of the supervised and unsupervised methods, we have concluded that healthcare workers whose children stayed home during the first wave in the US consumed more alcohol. We also found that the work schedule changes due to the Covid-19 pandemic led to a change in alcohol use habits. Changes in food consumption, age, gender, geographical characteristics, changes in sleep habits, the amount of news consumption, and screen time are also important predictors of an increase in alcohol use among healthcare workers in the United States.

Comparison of immune response to SARS-COV-2 vaccine in COVID-recovered versus non-infected Individuals.

To determine the antibody levels at 6 months in SARS-CoV-2 vaccinated individuals in COVID-recovered versus non-infected groups to determine the need to administer booster COVID vaccine in each group. Prospective longitudinal study. Pathology Department, Combined Military Hospital, Lahore for a period of eight months from July 2021 to February 2022. Two hundred and thirty three study participants in both COVID recovered and non-infected groups (105 participants in infected group, 128 participants in non-infected group) were subjected to blood sampling at 6 months post-vaccination. Anti-SARS-CoV-2 IgG antibody test was done using Chemiluminescence method. Comparison of antibody levels between COVID-recovered and non-infected groups was made. Results were compiled and statistically analyzed using SPSS version 21. Out of 233 study participants, males were 183 (78%) while females were 50 (22%), mean age being 35.93 years ± 8.298. Mean Anti-SARS-CoV-2 S IgG levels among COVID-recovered group was 1342 U/ml and among non-infected group was 828 U/ml at 6 months post-vaccination. Mean antibody titers in COVID-19 recovered group are higher than in non-infected group at 6 months post-vaccination in both groups.

Recent Developments in Vaccines for Viral Diseases.

The world is continuously facing the threat of emerging infectious diseases [...].

Machine Learning-based Analytics of the Impact of the Covid-19 Pandemic on Alcohol Consumption Habit Changes Among United States Healthcare Workers (preprint)

The COVID-19 pandemic is a global health concern that has spread around the globe. Machine Learning (ML) is promising in the fight against the COVID-19 pandemic. Machine learning and artificial intelligence have been employed by various healthcare providers, scientists, and clinicians in medical industries in the fight against COVID-19 disease. In this paper, we discuss the impact of the Covid-19 pandemic on alcohol consumption habit changes among healthcare workers in the United States during the first wave of the Covid-19 pandemic. We utilize multiple supervised and unsupervised machine learning methods and models such as decision trees, logistic regression, support vector machines, multilayer perceptron, XGBoost, CatBoost, LightGBM, AdaBoost, Chi-Squared Test, mutual information, KModes clustering and the synthetic minority oversampling technique (SMOTE) on a mental health survey data obtained from the University of Michigan Inter-University Consortium for Political and Social Research to investigate the links between COVID-19-related deleterious effects and changes in alcohol consumption habits among healthcare workers. Through the interpretation of the supervised and unsupervised methods, we have concluded that healthcare workers whose children stayed home during the first wave in the US consumed more alcohol. We also found that the work schedule changes due to the Covid-19 pandemic led to a change in alcohol use habits. Changes in food consumption, age, gender, geographical characteristics, changes in sleep habits, the amount of news consumption, and screen time are also important predictors of an increase in alcohol use among healthcare workers in the United States.

Visualizing the sustainable development goals and natural resource utilization for green economic recovery after COVID-19 pandemic.

After the COVID-19 outbreak, this study examines the influence of modifications in China's Sustainable Growth Goals (SDGs) and economic development goals on Chinese enterprises' energy conservation and emissions reduction behavior. Meanwhile, the COVID-19 epidemic has erupted, displacing the flimsy traditional techniques. As a result, the post-COVID-19 pandemic emphasizes the need for a long-term sustainable development method compatible with the local and regional environmental systems. The main objective of this study is used as a roadmap to steer the post-COVID-19 pandemic on a sustainable green path by emphasizing sustainable energy strategies to connect in SDG-related efforts. The investigation in this paper begins with examining significant impacts in the energy industry and their impact on progress toward sustainability. The empirical findings that the CO2 emissions reduction objectives in long-term development plans had a considerable impact on energy saving and emissions reduction, lowering energy consumption intensity by 3.33% and carbon emission intensity by 4.23% between 2010 and 2019. Besides, the results and long and short run techniques are built to describe the Sustainable Development Goals interface, with the result revealing that Sustainable Development Goals enhance the green economic recovery performance. Furthermore, this study recommends that the key natural resources and green economic recovery policies to overcome the climate change impacts by COVID-19 pandemic.

Post Pandemic Reforms In Education And Role Of Leadership In Critical Situation At Higher Education Institutions Of Pakistan

Pandemic modified the educational setting and brought reformation in education at all levels especially in higher education level through innovation trends of technology and moderation. Higher Education Commission n has framed a holistic mechanism for the sustainability and flow of education and established the flexible policy to facilitate the students for future calamities and disasters. This study explored the post Pandemic Reforms at higher education and role of leadership to encounter the critical situation in higher education institutions of Pakistan. Qualitative methodology was used for this study and narrative research technique was utilized and data was collected conveniently from 20 administrators of higher educational institutions through semi structured interview tool. Study explored that higher education Commission has design policy and framework to mitigate the losses of education and brought the revolutionary steps at higher educational institution such as hybrid educational system, virtual classroom, electronic evaluation and assessment, scholarship and financial aids facilitation of digital library and flexibility of teaching personnel.

Assessment of Economic Sustainability in the Construction Sector: Evidence from Three Developed Countries (the USA, China, and the UK)

The construction sector plays a significant role in contributing to uplifts in economic stability by generating employment and providing standardized social development. Economic sustainability in the construction sector has been less addressed despite its wide applicability in the economy. This study aimed to perform a comparative analysis to determine the application of a circular economy in the construction sector toward economic sustainability, along with its long-term forecasting. A time series analysis was used on the construction sector of the United States of America (USA), China, and the United Kingdom (UK) from 1970 to 2020, by taking into account individual effects to propose a framework with global validity. Statistical analysis was performed to analyze the dependence of the construction sector and determine its short- and long-term contributions. The results revealed that the construction sectors in these countries tend to bounce back to equilibrium in the case of short-term effects;however, the construction sector behaves differently with respect to each sector after experiencing long-term effects. The results show that the explanatory power of the forecasting model (R2) was found to be 0.997, 0.992, and 0.996 for the USA, China, and the UK. Based on the concept of the circular economy, it was concluded that the USA will become a leader in attaining sustainability in construction owing to its ability to recover quickly from shocks, and that the USA will become the largest construction sector in terms of GDP, with a USD 0.3 trillion higher GDP than that of the Chinese sector. Meanwhile, there will be no significant change in the construction GDP of the UK up to the end of 2050. Moreover, the speeds of the construction sector toward equilibrium in the long run in the USA, China, and the UK, and regaining of their original positions, is 0.267%, 1.04%, and 0.41% of their original positions, respectively. This study has a significance in acting as a guideline for introducing economic and environmental sustainability in construction policies, because of the potential of the construction sectors to recover from possible recessions in their respective countries.

Potential Immunogenic Activity of Computationally Designed mRNA- and Peptide-Based Prophylactic Vaccines against MERS, SARS-CoV, and SARS-CoV-2: A Reverse Vaccinology Approach.

The continued emergence of human coronaviruses (hCoVs) in the last few decades has posed an alarming situation and requires advanced cross-protective strategies against these pandemic viruses. Among these, Middle East Respiratory Syndrome coronavirus (MERS-CoV), Severe Acute Respiratory Syndrome coronavirus (SARS-CoV), and Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2) have been highly associated with lethality in humans. Despite the challenges posed by these viruses, it is imperative to develop effective antiviral therapeutics and vaccines for these human-infecting viruses. The proteomic similarity between the receptor-binding domains (RBDs) among the three viral species offers a potential target for advanced cross-protective vaccine designs. In this study, putative immunogenic epitopes including Cytotoxic T Lymphocytes (CTLs), Helper T Lymphocytes (HTLs), and Beta-cells (B-cells) were predicted for each RBD-containing region of the three highly pathogenic hCoVs. This was followed by the structural organization of peptide- and mRNA-based prophylactic vaccine designs. The validated 3D structures of these epitope-based vaccine designs were subjected to molecular docking with human TLR4. Furthermore, the CTL and HTL epitopes were processed for binding with respective human Lymphocytes Antigens (HLAs). In silico cloning designs were obtained for the prophylactic vaccine designs and may be useful in further experimental designs. Additionally, the epitope-based vaccine designs were evaluated for immunogenic activity through immune simulation. Further studies may clarify the safety and efficacy of these prophylactic vaccine designs through experimental testing against these human-pathogenic coronaviruses.

Dynamic common correlated effects of pandemic uncertainty on environmental quality: fresh insights from East-Asia and Pacific countries

It is well known that pandemic-related uncertainty affects various macroeconomic indicators, including environmental quality. Due to pandemic outbreaks, the reduction in economic activities affects the environmental quality in many economies. The study explores the impact of pandemic uncertainty on environmental quality in East-Asia and Pacific countries. Most past research use only CO2 emissions, which is an inappropriate measurement of environmental quality. Besides CO2 emissions, we have utilized other pollutants like N2O and CH4 emissions along with ecological footprint. The traditional econometric approaches ignore cross-sectional dependence and heterogeneity and give biased outcomes. Hence, we have employed a new method, “Dynamic Common Correlated Effects (DCCE),” which can excellently deal with the problems mentioned above. The short-run and long-run DCCE estimations show a negative and significant influence of pandemic uncertainty on ecological footprint, CO2 and CH4 emissions in whole and lower-income group of East-Asia and Pacific region. Moreover, pandemic uncertainty has a negative relationship with all indicators of environmental quality in higher-income economies. The study provides a unique opportunity to examine how pandemic uncertainty through anthropogenic activities affects environmental quality and serves as a significant resource for policymakers in planning and estimating the effectiveness of environmental quality measures. It is necessary to carry out sustainable environmental policies in East-Asia and Pacific region according to the vulnerabilities and resilience to global pandemic uncertainty.

Psychosocial impact of the COVID-19 pandemic on doctor's children: Are we heading towards a mental health pandemic?

The coronavirus pandemic (COVID-19) may affect the behavior of children. Non infected children of doctors seem to be susceptible to psychosocial health disorders. Objective: To assess the psychosocial impact of the COVID-19 pandemic on children of doctors. Methods: This questionnaire-based survey filled up by doctors was done with the Pediatric Symptom Check List-17 (PSC-17) to assess the psychosocial impact of the COV-ID-19 pandemic on doctors’ children aged 10-15 years with no clinical evidence of being infected with coronavirus and possible contributing factors to mental distress/psychosocial health disorders. A PSC -17 Score of ≥15 was considered as a significant indicator of suspected psychosocial impact. Results: Children’s mean age was 12.5 (SD 1.9) years, and 53.8% of them were male. Of 357 questionnaire responses, 36.1% had a significant PSC-17 score (>15) and a small, but significant inverse correlation was observed with age (r=-0.147;P=0.005). More screen time than usual was perceived by doctors to be the most common potential contributing factor (63%) to their children’s psychosocial impact. Conclusion: The COVID-19 pandemic is likely to leave lasting effects on children’s mental health. Parents should closely monitor children for any changes in psychosocial behavior, so that timely intervention can be considered. Psychosocial screening of children is needed and should be conducted at schools.

An Insight Into COVID-19: A 21st Century Disaster and Its Relation to Immunocompetence and Food Antioxidants.

Coronavirus Disease 2019 (COVID-19) ranks third in terms of fatal coronavirus diseases threatening public health, coming after SARS-CoV (severe acute respiratory syndrome coronavirus), and MERS-CoV (Middle East respiratory syndrome coronavirus). SARS-CoV-2 (severe acute respiratory syndrome coronavirus type 2) causes COVID-19. On January 30, 2020, the World Health Organization (WHO) announced that the current outbreak of COVID-19 is the sixth global health emergency. As of December 3, 2020, 64 million people worldwide have been affected by this malaise, and the global economy has experienced a loss of more than $1 trillion. SARS-CoV-2 is a positive-sense single-stranded RNA virus belonging to the Betacoronavirus genus. The high nucleotide sequence identity of SARS-CoV-2 with the BatCoV RaTG13 genome has indicated that bats could be the possible host of SARS-CoV-2. SARS-CoV-2 penetrates the host cell via binding its spike protein to the angiotensin-converting enzyme 2 (ACE2) receptor, which is similar to the mechanisms of SARS-CoV and MERS-CoV. COVID-19 can spread from person to person via respiratory droplets and airborne and contaminated fomites. Moreover, it poses a significant risk to smokers, the elderly, immunocompromised people, and those with preexisting comorbidities. Two main approaches are used to control viral infections, namely, vaccination, and biosecurity. Studies to analyze the antigenicity and immunogenicity of SARS-CoV-2 vaccine candidates are underway, and few vaccines may be available in the near future. In the current situation, the Human Biosecurity Emergency (HBE) may be the only way to cope effectively with the novel SARS-CoV-2 strain. Here, we summarize current knowledge on the origin of COVID-19 as well as its epidemiological relationship with humans and animals, genomic resemblance, immunopathogenesis, clinical-laboratory signs, diagnosis, control and prevention, and treatment. Moreover, we discuss the interventional effects of various nutrients on COVID-19 in detail. However, multiple possibilities are explored to fight COVID-19, and the greatest efforts targeted toward finding an effective vaccine in the near future. Furthermore, antioxidants, polyphenols, and flavonoids, both synthetic and natural, could play a crucial role in the fight against COVID-19.

Beneficial Effects of Anticoagulants on the Clinical Outcomes of COVID-19 Patients.

(1) Background: Severe coronavirus disease can be complicated by a hypercoagulable state in conjunction with sepsis, increasing the risk of venous thromboembolism. This study aimed to observe the effect of anticoagulants on 30-day high-dependency unit (HDU) outcomes of moderate to severe coronavirus disease 2019 (COVID-19) patients of a tertiary care hospital at Rawalpindi, Pakistan. (2) Methods: A retrospective propensity-based case-control study was carried out to examine COVID-19 patients admitted to the HDU. Patient groups who did and did not receive anticoagulants were labeled as "anticoagulant" and "non-anticoagulant", respectively. Case-control matching (1:1) was performed via propensity scores (calculated by a regression model). Kaplan-Meier and logrank analyses were used to study survival probability. Single predictors of outcomes were determined by Cox regression analysis. (3) Results: The anticoagulant group had elevated D-dimers, advanced age, more comorbidities and a higher frequency of severe disease compared to the non-anticoagulant group (p < 0.05). Therefore, 47 cases and 47 matched controls were selected based on their propensity scores. The primary endpoint was outcome (survived vs. died). The 30-day in-HDU mortality was 25.5% for cases and 61.7% for controls (p = 0.0004). The median time from admission to death was 16 days for the case group and 7 days for the control group (p < 0.0001). The 30-day mortality was 19.1% for the enoxaparin group and 16.4% for the heparin group (p > 0.05). Enoxaparin (therapeutic and prophylactic doses) and heparin (prophylactic dose) were found to be independent factors affecting the outcomes of these patients (p < 0.001). (4) Conclusions: Anticoagulants play a beneficial role in reducing mortality among COVID-19 patients. Both anticoagulant formulations, enoxaparin (therapeutic and prophylactic doses) and heparin (prophylactic dose), were associated with improving survival among these patients.

Comparative study of SARS-CoV-2 antibody titers between male and female COVID-19 patients living in Kurdistan region of Iraq.

Recently, there is increasing evidence that coronavirus disease 2019 (COVID-19) causes men to experience more serious symptoms and have a higher mortality rate than women, but the association between sex and immune response stays unknown till now, and weather patient's prognosis associated with sex or not is another vague in COVID-19. In this study, the SARS-CoV-2-specific antibody titer test was performed for 727 patients who were a positive RT-PCR result for COVID-19 and we determined the difference in immune response in both genders. Patients were divided into two groups based on their genders, which were 383 males and 344 females. Plasma was collected from the patients after 17 days of diagnosis with COVID-19, and the concentrations of specific antibodies (IgG and IgM) was measured by multiparametric immunoassay system (VIDAS). Results demonstrated that there was no significant difference in both IgM and IgG production in male participants compared to women. Moreover, despite there was a weak significant positive association between age and IgM in male patients, while there was no significant correlation between IgG and age for the same gender. On the other hand, a slight positive correlation between IgM and IgG with age was observed in female participants. Finally, it concluded that there was no sex biases in patients with COVID-19 in Erbil, Iraq. So, these findings are crucial to treat and care male and female's patients infected with COVID-19 at hospitals.