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COVID-19 has transformed higher education learning and teaching practices globally. Tertiary students, internationally face both opportunities and challenges in learning and adapting to this paradigm shift in the delivery of education. It remains unclear how students in international contexts are responding to these changes in digital learning during and post-COVID-19. This paper aims to compare student perceptions of digital competence, confidence, and resilience in present times using data from surveys of tertiary students from Australia, Cambodia, China, India, and Malaysia. There are disparities not only in the teaching and learning pedagogies amongst these countries but also in the levels of technological advancement, infrastructure support, and pace of digital innovation in the delivery of courses. These differences have put in focus students' both digital competencies and resilience as they pursue higher education on various digital learning platforms. Resilience includes the ability to bounce back or adapt from stress (Smith et al., 2008). Digital resilience is students' tech-savviness and preparedness to adapt to different digital environments as they pursue higher education. This paper examines the perceptions of tertiary undergraduate students from these countries in this emerging new digital learning norm. A total of 687 tertiary students from the aforementioned countries participated in a survey to questions related to digital competence, confidence in using and/or adapting to digital innovation, and resilience. Statistically significant attributes are identified to help better understand the challenges these culturally diverse students perceive in digital learning environments. This study will reveal barriers that impact the digital transformation of undergraduate students which can be used to recommend necessary teaching and learning support frameworks to enhance their digital competence and resilience. This will help tertiary institutions better equip all stakeholders in adapting to the new normal of higher education in the future.

This rapid systematic review aims to examine emerging evidence on the effects of COVID-19 on educational institutions and assess the prevalence of e-learning changes in the sector. This paper reviews literature on learning, teaching, and assessment approaches adopted since the COVID-19 outbreak, and assesses the impact on the sector, staff, and students, summarizing findings from peer-reviewed articles. It categorizes these into five key themes: (1) digital learning; (2) e-learning challenges; (3) digital transition to emergency virtual assessment (EVA); (4) psychological impact of COVID-19; and (5) creating collaborative cultures. This represents the first systematic review of COVID-19's impact on education, clarifying current themes being investigated. The author suggests that the term 'emergency virtual assessment' (EVA) is now added for future research discussion. Finally, the paper identifies research gaps, including researching the impact on lesser developed countries, the psychological impact of transition, and the important role of leadership and leadership styles during the transition and handling of the pandemic.

This paper presents a compilation of personal reflections from 66 contributors on the impact of, and responses to, COVID-19 in accounting education in 45 different countries around the world. It reveals a commonality of issues, and a variability in responses, many positive outcomes, including the creation of opportunities to realign learning and teaching strategies away from the comfort of traditional formats, but many more that are negative, primarily relating to the impact on faculty and student health and well-being, and the accompanying stress. It identifies issues that need to be addressed in the recovery and redesign stages of the management of this crisis, and it sets a new research agenda for studies in accounting education.

As the COVID-19 pandemic unfolds, every aspect of daily life is being altered in response to the virus. The pandemic has altered secondary education. Classes online, teachers struggling to learn Zoom and make lessons meaningful and relevant to students. Students struggling to make sense of this moment, struggling with mental health issues due to the loss of routine and in many cases contact with adult role models. Unfortunately, in times of crisis such as these some of the most disenfranchized people in society are completely overlooked and forgotten, such as refugees. However, if more teachers were to leverage the social studies potential of current events such as the Coronavirus, greater empathy would be felt for marginalized people more starkly impacted by the pandemic, leading ultimately to a heightened sense of civic engagement among the next generation. The purpose of this paper is to assist teachers in guiding their students through analyzing current events, such as COVID-19's impact on refugees, toward developing civic mindedness. In addition to this, the paper will discuss some of the broader societal impacts the virus is having within the United States, as well as ways in which this event may be viewed as a historical subject in the future. The paper will begin by building the content knowledge of high school social studies teachers through addressing the following question: "What is the difference between a refugee entering the United States now versus one year ago before the COVID-19 pandemic?" Following this, the authors will present an inquiry-based learning segment designed to teach the History correlated to the COVID-19 pandemic to a classroom of secondary education students. The inquiry template follows the standard C3 format utilized by the State of Connecticut.

Given the increased load of waste plastic in the solid waste stream after the outbreak of the COVID-19 pandemic, we investigated the fate of selected plastic additives along open burning dumps, industrial and residential transects in tropical riverine catchments of India. Polyurethane foam disk passive air samples, surface water and community stored water (CSW) samples were collected along the Adyar River (AR), Cooum River (CR) and canals in Chennai and Daman Ganga River (DG) in Vapi. Among the quantified phthalic acid esters (PAEs), a widely used plastic additive, di(2-ethylhexyl) phthalate (DEHP), was ubiquitous across all the transects. More open drains and leaching of littered single-use plastic items can be the reason for significantly higher (p < 0.05) levels of PAEs in CR over other rivers with a dominance of di-n-butyl phthalate (DnBP). Prevalence of open burning of dumped plastic waste was the possible primary emission source of PAEs in these riverine catchments. Excluding highly soluble dimethyl phthalate (DMP), air-water exchange processes reflected the secondary emission of all the PAEs from the surface water along the open burning sites. Despite the cleansing effect of the oceanic air mass from the Bay of Bengal and the Indian Ocean, the average atmospheric PAE level was two-fold higher in Chennai than Vapi. Even though Vapi is a coastal city along the Arabian Sea, it was impacted by inland air masses during the sampling event. Open burning dumpsites showed a five-fold increase in atmospheric priority PAEs in Chennai city after the outbreak of the COVID-19 pandemic. DnBP was the major contributor to estrogenicity in CSW and DG, and also posed maximum risk for fishes in the open burning transect of these tropical rivers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The outbreak of Coronavirus 2019 (COVID‐19) has impacted everyday lives globally. The number of positive cases is growing and India is now one of the most affected countries. This paper builds predictive models that can predict the number of positive cases with higher accuracy. Regression‐based, Decision tree‐based, and Random forest‐based models have been built on the data from China and are validated on India's sample. The model is found to be effective and will be able to predict the positive number of cases in the future with minimal error. The developed machine learning model can work in real‐time and can effectively predict the number of positive cases. Key measures and suggestions have been put forward considering the effect of lockdown. [ABSTRACT FROM AUTHOR]

Remote sensing (RS), satellite imaging (SI), and geospatial analysis have established themselves as extremely useful and very diverse domains for research associated with space, spatio-temporal components, and geography. We evaluated in this review the existing evidence on the application of those geospatial techniques, tools, and methods in the coronavirus pandemic. We reviewed and retrieved nine research studies that directly used geospatial techniques, remote sensing, or satellite imaging as part of their research analysis. Articles included studies from Europe, Somalia, the USA, Indonesia, Iran, Ecuador, China, and India. Two papers used only satellite imaging data, three papers used remote sensing, three papers used a combination of both satellite imaging and remote sensing. One paper mentioned the use of spatiotemporal data. Many studies used reports from healthcare facilities and geospatial agencies to collect the type of data. The aim of this review was to show the use of remote sensing, satellite imaging, and geospatial data in defining features and relationships that are related to the spread and mortality rate of COVID-19 around the world. This review should ensure that these innovations and technologies are instantly available to assist decision-making and robust scientific research that will improve the population health diseases outcomes around the globe.

In this paper, a SEIR epidemic model related to media coverage and exogenous reinfections is established to explore the transmission dynamics of COVID-19. The basic reproduction number is calculated using the next generation matrix method. First, the existence of equilibrium points is investigated, and different kinds of equilibrium points indicate that the disease may disappear, or exist that result in different quantity of susceptible individuals, pre-symptomatic infected individuals and symptomatic infected individuals. The stability of the equilibria is discussed by a geometric approach, and it is found that controlling reproduction number to be lower than 1 is not sufficient for eradication of COVID-19. Second, transcritical bifurcation is explored, and it is found that improving the ratio of exogenous reinfection may lead to backward bifurcation under poor medical conditions, which indicates that two endemic equilibrium points appear. Third, to investigate the influence of parameters on the basic reproduction, sensitivity analysis is done to choose relatively sensitive parameters, and the parameters for treatment and media coverage are selected. An optimal control model is established to balance the treatment and media awareness. By exploring the existence and the uniqueness of the optimal control solution, the optimal control strategies are given. Finally, we run numerical simulations to verify the theoretical analysis on actual data of China, and the data from the four different states of India is used for forecasting the situation of infected individuals in a short period. It is found by the simulation that the co-function of treatment and media coverage results in the reduced number of infectious individuals. [ABSTRACT FROM AUTHOR]

Recent years has witnessed loss of human life as well as the physical and mental strain to the large populations of the world, which could be termed as disastrous. Many researchers (Arasli et al., 2020; Rezapouraghdam & Karatepe, 2020; Lim & To, 2021; Karatepe et al., 2021) have demonstrated that COVID-19 had a significant impact on the economy and human life globally. In fact, the new Coronavirus COVID-19 pandemic first appeared in the late December 2019 in China and then moved into other countries, before reaching India in March 2020. Further, the pandemic continued into 2021 & 2022 in the developed, developing and underdeveloped countries. Added to this, Governments are meeting the costs of dealing with the pandemic and supporting business and citizens. Therefore, we consider how both the pandemic and resultant economic issues have and will affect tourism and hospitality-specifically sustainable tourism & hospitality that will develop and sustain local communities in a balanced way for the benefit of future generations. In fact, beyond the immediacy of the situation and the management of the short-term consequences of the crisis, we must look ahead to the future, to the world of tomorrow, which will inevitably be different from all past societies and all past economies. This paper conceptually focuses on evaluating the potential effects of COVID-19 on the tourism and hospitality industry in India and post COVID-19 settings, recovery strategies and new normal and suggests the theoretical development and policy implication of this relationship. [ABSTRACT FROM AUTHOR]

The South China Sea dispute is developing at an extraordinarily rapid pace with six states' overlapping territorial interest, abundant untapped natural resources and more than hundreds of geological features. The regional consensus opposes coercion and favors diplomacy, but China is out of step with both the regional consensus and international norms and has posed a serious threat to the Asia-Pacific security. With this backdrop, this paper, predominantly taking the geopolitical approach, takes a stand that the South China Sea is going to be the grand chessboard of the world. The study endeavors to project that the world will never get a better place to contain an undemocratic expansionist power like China than the South China Sea. The great powers, including the US, need to take a very strongly articulated South China Sea policy, as the world is getting tired of the ambiguous policy of China from the 'Peaceful Rise' to 'Covid-19'. At the same time, the paper sheds light on the importance of South China Sea in India's strategic gambit and how this complex, potential ground is important to India to turn the Chinese dominated Asia into a multipolar Asia. [ABSTRACT FROM AUTHOR]

This paper investigates whether the Covid-19 virus negatively impacts Indian companies dependent on the Chinese supply chain. As the virus originated from China, there was an anti-China sentiment observed all over the world. Our empirical study analyzes the impact of lockdown and relief measures announced by the government on companies dependent on Chinese suppliers vis-à-vis companies that are not dependent on Chinese suppliers on selected stocks in the Indian stock market. We find no negative sentiment among Indian investors on Chinese supply chain-dependent companies in India. [ABSTRACT FROM AUTHOR]

The aim of this paper is to highlight how TROPOspheric Monitoring Instrument (TROPOMI) trace gas data can best be used and interpreted to understand event-based impacts on air quality from regional to city scales around the globe. For this study, we present the observed changes in the atmospheric column amounts of five trace gases (NO 2 , SO 2 , CO, HCHO, and CHOCHO) detected by the Sentinel-5P TROPOMI instrument and driven by reductions in anthropogenic emissions due to COVID-19 lockdown measures in 2020. We report clear COVID-19-related decreases in TROPOMI NO 2 column amounts on all continents. For megacities, reductions in column amounts of tropospheric NO 2 range between 14 % and 63 %. For China and India, supported by NO 2 observations, where the primary source of anthropogenic SO 2 is coal-fired power generation, we were able to detect sector-specific emission changes using the SO 2 data. For HCHO and CHOCHO, we consistently observe anthropogenic changes in 2-week-averaged column amounts over China and India during the early phases of the lockdown periods. That these variations over such a short timescale are detectable from space is due to the high resolution and improved sensitivity of the TROPOMI instrument. For CO, we observe a small reduction over China, which is in concert with the other trace gas reductions observed during lockdown; however, large interannual differences prevent firm conclusions from being drawn. The joint analysis of COVID-19-lockdown-driven reductions in satellite-observed trace gas column amounts using the latest operational and scientific retrieval techniques for five species concomitantly is unprecedented. However, the meteorologically and seasonally driven variability of the five trace gases does not allow for drawing fully quantitative conclusions on the reduction in anthropogenic emissions based on TROPOMI observations alone. We anticipate that in future the combined use of inverse modeling techniques with the high spatial resolution data from S5P/TROPOMI for all observed trace gases presented here will yield a significantly improved sector-specific, space-based analysis of the impact of COVID-19 lockdown measures as compared to other existing satellite observations. Such analyses will further enhance the scientific impact and societal relevance of the TROPOMI mission. [ABSTRACT FROM AUTHOR]

The outbreak of coronavirus disease 2019 (COVID-19), caused by the virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already created emergency situations in almost every country of the world. The disease spreads all over the world within a very short period of time after its first identification in Wuhan, China in December, 2019. In India, the outbreak, starts on 2 nd March, 2020 and after that the cases are increasing exponentially. Very high population density, the unavailability of specific medicines or vaccines, insufficient evidences regarding the transmission mechanism of the disease also make it more difficult to fight against the disease properly in India. Mathematical models have been used to predict the disease dynamics and also to assess the efficiency of the intervention strategies in reducing the disease burden. In this work, we propose a mathematical model to describe the disease transmission mechanism between the individuals. Our proposed model is fitted to the daily new reported cases in India during the period 2 nd March, 2020 to 12 th November, 2020. We estimate the basic reproduction number, effective reproduction number and epidemic doubling time from the incidence data for the above-mentioned period. We further assess the effect of implementing preventive measures in reducing the new cases. Our model projects the daily new COVID-19 cases in India during 13 th November, 2020 to 25 th February, 2021 for a range of intervention strength. We also investigate that higher intervention effort is required to control the disease outbreak within a shorter period of time in India. Moreover, our analysis reveals that the strength of the intervention should be increased over the time to eradicate the disease effectively., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The first Covid-19 patient in India was reported on January 30, 2020 at the state of Kerala. The patient number rose to three by February 3, 2020. In the month of March 2020, the transmissions started to increase when the people started to return back to India from the Covid-19 affected countries. On March 12, a 76-year-old man having a travel history to Saudi Arabia was the first reported fatality in India due to Covid 19. Then for the prevention of the propagation of Covid, the Indian government declared a state of health emergency and strict counter measures were taken, including locking down of cities, prohibiting almost all avoidable activities and restricting population's mobility. From March 24, 2020 due to the complete lockdown in the country, human activities were heavily restricted in the whole geographical regions of India. This pandemic lockdown eventually serves as an opportunity to observe the background concentrations of pollutants in the atmosphere. The PM 2.5 distribution can affect human health and to overcome this problem, setting up of regulation for PM is necessary. In the present study Probability density functions (PDF) method have been utilised for the investigation of PM 2.5 pollutant data distribution of five countries namely, India, China, France, Brazil and United States of America (USA) for their respective lockdown period of 2020 and corresponding same period of 2019. A detailed study has been done for India, and for that purpose India has been divided into three regions (Central India, Coastal India and Indo-Gangetic Plain (IGP)) on the basis of different meteorological conditions. PM 2.5 concentration for hourly basis has been analysed for the lockdown period 24th March to 15th June 2020 and compared with the PM 2.5 concentration of previous year 2019 for the same time period. To understand the effect of lockdown in PM 2.5 emission in India, which will give us an idea about the background concentration, PDFs (probability density functions) have also been generated for the whole year from 2015 to 2019. The "goodness-of-fit" of the probability density functions, to the data, was assessed, using various statistical indices (Chi-square test). Results show that the PM 2.5 reduction during the lockdown period of 2020 as compared to the same period of 2019 is sufficiently large. This study will give a certain degree of idea to the regulatory bodies on planning and implementation of strict air quality control plans., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

India's pharmaceutical sector has been one of the largest manufacturers of generic drugs globally. During the pandemic, most countries were dependent on imports of generic drugs from India. However, India has been relying on resources from China for Active Pharmaceutical Ingredients (APIs) which are the raw material for preparing generic drugs. We considered, in our analysis, branded product groups of Paracetamol and Amoxicillin due to their extensive use in the treatment of COVID-19. From a thorough market analysis of both the drugs, we conclude that firms have a monopoly over their brands but compete within the same product group and operate in their respective market under varying prices within certain bandwidths which resembles the feature of monopolistic competitive market. We have introduced compensating function a la Helpman (1981) in the pharmaceutical goods market with the assumption that an 'ideal product' exists among the pharmaceutical goods. Given the framework, this paper explores a general equilibrium model set in a monopolistic competitive product market for branded drugs. We concluded through our propositions that expanding the pharmaceutical sector will increase the employment of unskilled labor under no capacity constraint. We will observe an increase in wages of unskilled labor only under full employment conditions wherein we would observe that the expansion of pharmaceutical good will increase wages in the unskilled labor market. However we obtain an intriguing result wherein we obtain that despite instances of limiting trade dependence on China through implementation of policies like 'Aatmanirbhar Bharat' and 'profit linked incentive schemes', yet to maintain the status quo in the global market for generic drugs, India's dependence on China would increase, owing to API imports due to the pandemic crisis. While India can grab the opportunity in the form of increased demand for pharmaceutical goods to increase the employment level of the economy but this improvement in welfare is also dependent on the degree of dependency of API India has on China. The Indian government has recognized the same through the incorporation of 'Covid-Suraksha' and PLI schemes to minimize import dependency, and accelerate the development of APIs and the production of indigenous drugs. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) pandemic has exposed humans to the highest physical and mental risks. Thus, it is becoming a priority to probe the mental health problems experienced during the pandemic in different populations. We performed a meta-analysis to clarify the prevalence of postpandemic mental health problems. Seventy-one published papers (n = 146,139) from China, the United States, Japan, India, and Turkey were eligible to be included in the data pool. These papers reported results for Chinese, Japanese, Italian, American, Turkish, Indian, Spanish, Greek, and Singaporean populations. The results demonstrated a total prevalence of anxiety symptoms of 32.60% (95% confidence interval (CI): 29.10-36.30) during the COVID-19 pandemic. For depression, a prevalence of 27.60% (95% CI: 24.00-31.60) was found. Further, insomnia was found to have a prevalence of 30.30% (95% CI: 24.60-36.60). Of the total study population, 16.70% (95% CI: 8.90-29.20) experienced post-traumatic stress disorder (PTSD) symptoms during the COVID-19 pandemic. Subgroup analysis revealed the highest prevalence of anxiety (63.90%) and depression (55.40%) in confirmed and suspected patients compared with other cohorts. Notably, the prevalence of each symptom in other countries was higher than that in China. Finally, the prevalence of each mental problem differed depending on the measurement tools used. In conclusion, this study revealed the prevalence of mental problems during the COVID-19 pandemic by using a fairly large-scale sample and further clarified that the heterogeneous results for these mental health problems may be due to the nonstandardized use of psychometric tools., (© 2021. The Author(s).)

This paper analyses the influence of the Covid-19 coverage by the social media upon the shape of the sovereign yield curves of the five major developing countries, namely Federative Republic of B razil, Russian Federation, Republic of India, People's Republic of China, and the Republic of South Africa (BRICS). The coherenc e between the level, slope, and the curvature of the sovereign yield term structures and the Covid-19 medi a coverage is found to vary between low and high ranges, depending on the phases of the pandemic. The empirical estimations of the yield-curve factors a re performed by means of the Diebold-Li modified version of the Nelson-Siegel model. The intervals of low coherence reveal the capacity of the two latent factors, level and slope, to be used for creating cross-factor diversification strategies, workable under crisis conditions, as evidenced on the example of the ongoing pandemic. Diverse coherence patterns are reported on a per-country basis, highlighting a promising potential of sovereign debt investments for designing cross-country and cross-factor fixed-income strategies, capable of hedging downside risks., Competing Interests: The authors have declared that no competing interests exist.

This paper studies the interplay between social distancing and the spread of the COVID-19 disease-a global pandemic that has affected most of the world's population. Our goals are to (1) to observe the correlation between the strictness of social distancing policies and the spread of disease and (2) to determine the optimal adoption level of social distancing policies. The earliest instances of the virus were found in China, and the virus has reached the United States with devastating consequences. Other countries severely affected by the pandemic are Brazil, Russia, the United Kingdom, Spain, India, Italy, and France. Although it is impossible to stop it, it is possible to slow down its spread to reduce its impact on the society and economy. Governments around the world have deployed various policies to reduce the virus spread in response to the pandemic. To assess the effectiveness of these policies, the system's dynamics of the society needs to be analyzed, which is generally not possible with mathematical linear equations or Monte Carlo methods because human society is a complex adaptive system with continuous feedback loops. Because of the challenges with the other methods, we chose agent-based methods to conduct our study. Moreover, recent agent-based modeling studies for the COVID-19 pandemic show significant promise in assisting decision-makers in managing the crisis by applying policies such as social distancing, disease testing, contact tracing, home isolation, emergency hospitalization, and travel prevention to reduce infection rates. Based on modeling studies conducted in Imperial College, increasing levels of interventions could slow the spread of disease and infection. We ran the model with six different percentages of social distancing while keeping the other parameters constant. The results show that social distancing affects the spread of COVID-19 significantly, in turn decreasing the spread of disease and infection rates when implemented at higher levels. We also validated these results by using the behavior space tool with ten experiments with varying social distancing levels. We conclude that applying and increasing social distancing policy levels leads to a significant reduction in infection spread and the number of deaths. Both experiments show that infection rates are reduced drastically when social distancing intervention is implemented between 80% to 100%.

The first confirmed case of COVID-19 in Colombia was reported on March 6, 2020. For this reason, on March 25, preventive isolation was declared mandatory. These measures involved the suspension of economic activities and drastically reduced the number of vehicles on the road. The objective of this study is to evaluate the impact of the lockdown due to the COVID-19 pandemic on PM 2.5 concentrations at 5 monitoring stations and aerosol optical depth values of the Terra/MODIS satellite. We analyzed and compared the weekly and monthly concentrations of PM 2.5 before and during the lockdown between the week of January 6 to June 22, 2020, and compared the daily values obtained from the Terra/MODIS satellite for the months of January-June during the years 2018-2020 to elucidate the effects of the lockdown. Similar to other monitored sites in the world, we observed substantial reductions in weekly PM 2.5 concentrations, from 41 to 84% (Bogotá), from 13 to 66% (Funza), from 17 to 57% (Boyacá), from 35 to 86% (Valledupar) and 31 at 60% (Risaralda). Unlike other studies, the aerosol optical depth values increased up to 59% during the months of lockdown compared to previous years and up to 70% of the weekly mean when compared to before the lockdown. These spatiotemporal behaviors of PM 2.5 and the aerosol optical depth in Colombia are influenced by reductions in vehicular flow during quarantine, regional rainfall, and height of the planetary boundary layer. Emissions from economic activities affect pollutant levels in the area. The analysis of the levels of pollutants during the lockdown provides a baseline for regulatory agencies to establish mitigation plans., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

COVID-19 has brought the world to a standstill with a wave of destruction in country after country with tremendous loss of lives and livelihood in advanced to developing nations. Whole world is staring at the prospect of repeated lockdowns with another wave of COVID-19 predicted to hit the world in September of 2020. The second wave is assumed to be even more destructive with severe impact across much of the world. The only way to defeat this pandemic is to quickly develop a safe and effective vaccine against this raging menace and initiate a global vaccination drive. Our study is an attempt to deploy various computational methods to identify B-cell and T-cell epitopes from the spike surface glycoprotein of SARS-COV-2 which have the novel potential for vaccine development against COVID-19. For this we have taken 8 unique strains with one each from India, China, France, USA, Italy, Australia, Iran and Pakistan. The strain data was extracted from NCBI Database. By analyzing the immune parameters like surface accessibility, antigenicity, variability, conservancy, flexibility, hydrophilicity, allergenicity and toxicity of the conserved sequences of spike glycoprotein using various databases and bioinformatics tools, we identified two potential novel linear (SGTNGTKRFDN and ASVYAWNRK) and one structural B-cell epitope as well as two T-cell epitopes (RLFRKSNLK and IPTNFTISV) which can be used as epitope-based peptide vaccines. Docking simulation assay revealed that above T-cell epitopes have minimum free binding energy and showed strong hydrogen bond interaction which strengthened its potential as being a T-cell epitope for the epitope-based novel vaccine against SARS-CoV-2. This study allows us to claim that B-cell and T-cell epitopes mentioned above provide potential pathways for developing an exploratory vaccine against spike surface glycoprotein of SARS-CoV-2 with high confidence for the identified strains. We will need to confirm our findings with biological assays., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Social lockdowns improved air quality during the COVID-19 pandemic. Governments had previously spent a lot of money addressing air pollution without success. This bibliometric study measured the influence of COVID-19 social lockdowns on air pollution, identified emerging issues, and discussed future perspectives. The researchers examined the contributions of countries, authors, and most productive journals to COVID-19 and air pollution research from January 1, 2020, to September 12, 2022, from the Web of Sciences Core Collection (WoS). The results showed that (a) publications on the COVID-19 pandemic and air pollution were 504 (research articles) with 7495 citations, (b) China ranked first in the number of publications (n = 151; 29.96% of the global output) and was the main country in international cooperation network, followed by India (n = 101; 20.04% of the total articles) and the USA (n = 41; 8.13% of the global output). Air pollution plagues China, India, and the USA, calling for many studies. After a high spike in 2020, research published in 2021 declined in 2022. The author's keywords have focused on "COVID-19," "air pollution," "lockdown," and "PM25." These keywords suggest that research in this area is focused on understanding the health impacts of air pollution, developing policies to address air pollution, and improving air quality monitoring. The COVID-19 social lockdown served as a specified procedure to reduce air pollution in these countries. However, this paper provides practical recommendations for future research and a model for environmental and health scientists to examine the likely impact of COVID-19 social lockdowns on urban air pollution. [ABSTRACT FROM AUTHOR]

Background: Since the start of the COVID-19 outbreak, a large number of COVID-19-related papers have been published. However, concerns about the risk of expedited science have been raised. We aimed at reviewing and categorizing COVID-19-related medical research and to critically appraise peer-reviewed original articles., Methods: The data sources were Pubmed, Cochrane COVID-19 register study, arXiv, medRxiv and bioRxiv, from 01/11/2019 to 01/05/2020. Peer-reviewed and preprints publications related to COVID-19 were included, written in English or Chinese. No limitations were placed on study design. Reviewers screened and categorized studies according to i) publication type, ii) country of publication, and iii) topics covered. Original articles were critically appraised using validated quality assessment tools., Results: Among the 11,452 publications identified, 10,516 met the inclusion criteria, among which 7468 (71.0%) were peer-reviewed articles. Among these, 4190 publications (56.1%) did not include any data or analytics (comprising expert opinion pieces). Overall, the most represented topics were infectious disease (n = 2326, 22.1%), epidemiology (n = 1802, 17.1%), and global health (n = 1602, 15.2%). The top five publishing countries were China (25.8%), United States (22.3%), United Kingdom (8.8%), Italy (8.1%) and India (3.4%). The dynamic of publication showed that the exponential growth of COVID-19 peer-reviewed articles was mainly driven by publications without original data (mean 261.5 articles ± 51.1 per week) as compared with original articles (mean of 69.3 ± 22.3 articles per week). Original articles including patient data accounted for 713 (9.5%) of peer-reviewed studies. A total of 576 original articles (80.8%) showed intermediate to high risk of bias. Last, except for simulation studies that mainly used large-scale open data, the median number of patients enrolled was of 102 (IQR = 37-337)., Conclusions: Since the beginning of the COVID-19 pandemic, the majority of research is composed by publications without original data. Peer-reviewed original articles with data showed a high risk of bias and included a limited number of patients. Together, these findings underscore the urgent need to strike a balance between the velocity and quality of research, and to cautiously consider medical information and clinical applicability in a pressing, pandemic context. SYSTEMATIC REVIEW REGISTRATION: https://osf.io/5zjyx/.

Lockdown measures led to air pollution decrease in several countries around the world such as China and India, whereas other regions experimented an increase in pollutant concentrations. Northern South America (NSA) was one of those areas where pollution changed during lockdown due to high fire activity. This study aims to analyze, for the first time in NSA, the behavior of selected criteria air pollutants during the implementation of the SARS-CoV-2 lockdown in two high populated cities of the region: Bogotá and Medellín in Colombia. A set of tools including surface measurements, as well as satellite and modeled data were used. 24-hour average concentrations of PM 10 , PM 2.5 , and NO 2 were collected from air quality stations for the lockdown period ranging from February 21 to June 30, 2020. The Copernicus Atmosphere Monitoring Service (CAMS) was used to analyze the fire flux OC as a biomass burning (BB) indicator, and tropospheric NO 2 concentrations were retrieved from TROPOMI. The HYSPLIT model was used to analyze back trajectories and fire data were obtained from MODIS sensor measurements. Our analysis shows short-term background NO 2 , PM 10 , and PM 2.5 concentration reductions of 60%, 44%, and 40%, respectively, for the strict lockdown; and 62%, 58%, and 69% for the relaxed lockdown. Corresponding long-term reductions were of 50%, 32%, and 9% for the strict lockdown; and 37%, 29%, and 19% for the relaxed lockdown. Regional BB increased PM 2.5 concentrations by 20 μg/m 3 during the strict lockdown, and the Saharan dust event increased PM 10 concentrations up to 168 μg/m 3 in Bogotá, and 104 μg/m 3 in Medellín, bringing an additional risk of morbidity and mortality for population. Regional BB has several causes that need to be properly managed to benefit local air quality improvement plans. Future cleaner transport policies equivalent to reduced lockdown mobility could bring pollution close to WHO guidelines., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The outburst of the pandemic COVID-19 in 2019 from the land of China to the entire world has brought a major change in people's living style. The severity of the disease is so much that more than 20 million people are affected by it worldwide. The recommended preventive measure to avoid the spread of this fatal disease is to maintain social distance leading to a significant economic disruption that could submerge the economies globally. However in order to keep the economies moving, the work from culture is adopted globally wherein the employees are connected via the internet and the work continues to happen. This paper aims to discover how people adopt such an attempt in the working culture. Also, the purpose of the paper is to find out its bearing on the employees' working capacity and whether they would like to continue with this arrangement in the future. The research employs primary data collected from 400 employees across various industries who are currently working from home. The research proposes advantages and challenges in working from home with a majority of employees preferring the method. [ABSTRACT FROM AUTHOR]

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Objective: The objective of this paper is to prepare the government and citizens of India to take or implement the control measures proactively to reduce the impact of coronavirus disease 2019 (COVID-19)., Method: In this work, the COVID-19 outbreak in India has been predicted based on the pattern of China using a machine learning approach. The model is built to predict the number of confirmed cases, recovered cases, and death cases based on the data available between January 22, 2020, and April 3, 2020. The time series forecasting method is used for prediction models., Results: The COVID-19 effects are predicted to be at peak between the third and fourth weeks of April 2020 in India. This outbreak is predicted to be controlled around the end of May 2020. The total number of predicted confirmed cases of COVID-19 might reach around 68 978, and the number of deaths due to COVID-19 are predicted to be 1557 around April 25, 2020, in India. If this outbreak is not controlled by the end of May 2020, then India will face a severe shortage of hospitals, and it will make this outbreak even worse., Conclusion: The COVID-19 pandemic may be controlled if the Government of India takes proactive steps to aggressively implement a lockdown in the country and extend it further. This presented epidemiological model is an effort to predict the future forecast of COVID-19 spread, based on the present scenario, so that the government can frame policy decisions, and necessary actions can be initiated.

The Wuhan Municipal Corporation reported the first case of coronavirus in China on December 31, 2019. After that, the virus spread across the globe. And as the pandemic caused by the coronavirus continues to spread, governments across the globe are having a difficult time in analyzing and predicting the course of the evolving situation. The first case of coronavirus in India was reported on January 30, 2020, post which the virus gradually spread its tentacles, forcing the government to declare a stringent lockdown on March 24, 2020. While the pandemic is a global problem, it is all the more severe in India given the large population base of 1.3 billion people. The other challenge is limited medical resources per capita population base. The leadership has to contain the spread of the virus and at the same time upgrade its medical infrastructure to deal with the disease. This paper is an effort to map leadership initiatives in the context of VUCA, an acronym which stands for Volatility, Uncertainty, Complexity and Ambiguity, to fight the coronavirus. [ABSTRACT FROM AUTHOR]

We aimed to examine the rate and characteristics of retracted articles in infectious diseases and clinical microbiology. Using the Retraction Watch Database, we conducted a cross-sectional study for retracted publications categorized as 'Infectious Disease' or 'Microbiology' until June 30 2022. We included publications for which citation information was available through the Web of Science database. Study characteristics, retraction trends and number of citations before and after the retraction year were analysed. Overall, 1004 retracted publications were included, retracted between August 1968 and June 2022. The number of retractions climbed through the years, peaking in 2020–2021. A total of 614 retractions originated from USA, China, and India, of total 183 736 PubMed publications from these countries. Overall, 378 (38%) were retracted because of errors; 182 (18%) because of plagiarism; and 142 (14%) because of falsification/fabrication. Specific reasons included 'concerns/issues about data' (158, 16%); 'duplication of image' (127, 13%); and 'unreliable results' (116, 12%). Of the 347 retractions during 2020 to June 2022, 91 (26%) were COVID-19 related. Fifty of 895 (5.6%) first authors had two retracted papers, and 14 (1.6%) had ≥2 retractions. Of 824 publications cited at least once, 466 (57%) were cited more often after retraction. Retractions of infectious diseases and clinical microbiology publications are increasing. Concerning reasons such as plagiarism, falsification/fabrication and errors are not uncommon. Nonetheless, these publications continue to be commonly cited after being retracted. [ABSTRACT FROM AUTHOR]

Access to medicines has become a major concern for countries worldwide during the COVID-19 pandemic, as pharmaceutical production and trade have been disrupted in the course of the crisis. Antibiotics are one group of medicines where worries about access have been raised. Access to the right antibiotic at the right time is important not only for curing infections of individual patients, but also for curbing antibiotic resistance globally. Reliable pharmaceutical supply is key to ensuring access to medicines. The global supply of generic medicines has over the last decades been transformed by the rise of India's pharmaceutical industry. In this paper, I trace the changing role of this industry for the global export of antibiotics, by mapping and describing changes in Indian antibiotic exports and discussing these in light of historical processes and events. The paper offers a novel approach to analyse global antibiotic trajectories by using international trade data from publicly available resources combined with a secondary literature review. I show that India's pharmaceutical industry today holds a key role as one of the world's biggest exporters of antibiotic medicines, but with an increasing dependency on China as a supplier of antibiotic ingredients. This produces both opportunities and concerns for access to antibiotics globally. • Offers a novel approach to trace antibiotic and pharmaceutical geographies. • Uses international trade data to map India's role for global antibiotics supply. • Describes that India has become one of the world's biggest exporters of antibiotics. • Shows that India is highly dependent on China for import of antibiotic ingredients. [ABSTRACT FROM AUTHOR]

Many studies have suggested herbal medicines as alternatives or adjuvants to modern drugs for COVID-19. Their scientometric analyses can provide a scientific overview of this topic. Web of Science (WOS) and Scopus were searched for articles on the use of herbal medicines in COVID-19 published until 26 October 2020. Collected data were analyzed for document type, subject area, top journal, citation number, and authors' collaboration network using VOSviewer 1.6.15, ScientoPy 2.0.3, Gephi 0.9.2, and SPSS 15 statistical tools. After screening the 3185 retrieved records, 378 and 849 records, respectively from WOS and Scopus, remained for quantity analysis. Original and review articles were the two main types of papers in both databases. Top subject areas were drug and medicine, respectively in the WOS and Scopus databases. The top three productive countries in the field were China, the US, and India. The most cited article was a practice guideline in both databases. "Journal of Biomolecular Structure Dynamics" in WOS and "Chinese Traditional and Herbal Drugs" in Scopus were the top journals. Top keywords included "COVID-19″ and "Traditional Chinese Medicine". US authors had the highest collaboration with other authors. The current study provides a snapshot of the quantity and characteristics of published scholarly documents in recent months in the intersection of herbal medicines and COVID-19. Our findings help scientists to find the existing gaps, identify the active authors and scientific institutes to collaborate with and use their experience to produce new knowledge in the future. [Display omitted] • This scientometrics was propsed to show an overview of the published documents on herbal medicine therapy for COVID-19 in WOS and Scopus databases and compare their characteristics. • Quantity analysis showed original and review articles as the main types of papers, drug and medicine as top subject areas, and China as top productive country. • A practice guideline was the highest cited article "Journal of Biomolecular Structure Dynamics" and "Chinese Traditional and Herbal Drugs" were the toppest journals in WOS, and Scopus, respectively. • US authors had the highest collaboration with other authors. • The topic modeling could give an overview of issues that publications have been focused on whether it is clinical care, management, public heath, and pathogenesis. [ABSTRACT FROM AUTHOR]

COVID-19 is now becoming a global issue and declared as pandemic by world health organization. This virus spread out from China to entire world. This paper performed a descriptive analysis of COVID-19 in special reference of India. Different attributes such as age, gender, travel history, communication type and current status are analyzed. Till now it can be stated from the study that age is not a significant factor that affect a person to be captured by this disease, also age attribute is normally distributed in current dataset. A significant relationship is found between gender (male and female) and Transmission Type (imported from other country or communicated from local) of the patients. [ABSTRACT FROM AUTHOR]

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most people infected with the COVID-19 virus will experience mild to moderate respiratory illness and recover without requiring special treatment. People in extremes of age and those having pre-existing disease are more prone to the infection. Transmission is by droplet/contact route or by airborne transmission in special circumstances i.e endotracheal intubation, bronchoscopy, tracheostomy, cardiopulmonary resuscitation etc. Not only the treatment of living infected subjects, handling of COVID-19 dead bodies is also having utmost importance to prevent the transmission of deadly virus to the body handlers (hospital staff/cremation staff/family members) in the hospital or at the cremation/burial site. Here in this review paper, we have discussed about the pros and cons of the cremation and burial of the body keeping in mind that no further spread of the virus could occur to the community. However for eg China and Sri Lankan authorities made cremation compulsory by official order while WHO, India and many other did not objected to either of them. In our opinion, cremation should be preferred for complete elimination of chances of infection. However keeping in mind the religious views of the family, if the burial of the body is requested, then it should be assured that the body is buried in a thick, air tight coffin and placed at normal depth of about 2 meter. It is recommended that the area above and adjacent to the grave should be cemented immediately as an additional precautionary to avoid scavenging by animal. [ABSTRACT FROM AUTHOR]

This research is aimed to escalate Adaptive Neuro-Fuzzy Inference System (ANFIS) functioning in order to ensure the veracity of existing time-series modeling. The COVID-19 pandemic has been a global threat for the past three years. Therefore, advanced forecasting of confirmed infection cases is extremely essential to alleviate the crisis brought out by COVID-19. An adaptive neuro-fuzzy inference system-reptile search algorithm (ANFIS-RSA) is developed to effectively anticipate COVID-19 cases. The proposed model integrates a machine-learning model (ANFIS) with a nature-inspired Reptile Search Algorithm (RSA). The RSA technique is used to modulate the parameters in order to improve the ANFIS modeling. Since the performance of the ANFIS model is dependent on optimizing parameters, the statistics of infected cases in China and India were employed through data obtained from WHO reports. To ensure the accuracy of our estimations, corresponding error indicators such as RMSE, RMSRE, MAE, and MAPE were evaluated using the coefficient of determination ( R 2 ). The recommended approach employed on the China dataset was compared with other upgraded ANFIS methods to identify the best error metrics, resulting in an R 2 value of 0.9775. ANFIS-CEBAS and Flower Pollination Algorithm and Salp Swarm Algorithm (FPASSA-ANFIS) attained values of 0.9645 and 0.9763, respectively. Furthermore, the ANFIS-RSA technique was used on the India dataset to examine its efficiency and acquired the best R 2 value (0.98). Consequently, the suggested technique was found to be more beneficial for high-precision forecasting of COVID-19 on time-series data. [ABSTRACT FROM AUTHOR]

COVID-19 is a buzz word nowadays. The deadly virus that started in China has spread worldwide. The fundamental principle is "if the disease can travel faster information has to travel even faster". The sequence of events reveals the upheaval need to strengthen the ability of the early warning system, risk reduction, and management of national and global risks. Digital contact tracing apps like Aarogya setu (India) and Pan-European privacy preserving proximity tracing (German) has somehow helped but they are more effective in the initial stage and less relevant in the community spread phase. Thus, there is a need to devise a Decision Support System (DSS) based on machine learning algorithms. In this paper, we have attempted to propose an Additive Utility Assumption Approach for Criterion Comparison in Multi-criterion Intelligent Decision Support system for COVID-19. The dataset of Covid-19 has been taken from government link for validating the results. In this paper, an additive utility assumption-based approach for multi-criterion decision support system (MCDSS) with an accurate prediction of identified risk factors on certain well-defined input parameters is proposed and validated empirically using the standard SEIR model approach (Susceptible, Exposed, Infected and Recovered). The results includes comparative analysis in tabular form with already existing approaches to illustrate the potential of the proposed approach including the parameters such as Precision, Recall and F-Score. Other advanced parameters such as, MCC (Matthews Correlation Coefficient), ROC (Receiver Operating Characteristics) and PRC (Precision Recall) have also been considered for validation and the graphs are illustrated using Jupyter notebook. The statistical analysis of the most affected top eight states of India is undertaken effectively using the Weka software tool and IBM Cognos software to correctly predict the outbreak of pandemic situation due to Covid-19. Finally, the article has immense potential to contribute to the COVID-19 situation and may prove to be instrumental in propelling the research interest of researchers and providing some useful insights for the current pandemic situation. • Proposing a Multi-criterion Intelligent DSS • Epidemiology modeling of data using a SEIFR Model • Our approach applies data to get trained using multiple parameters to handle and serve significant challenges existing especially in healthcare. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases (CVD) caused by household air pollution (HAP) have sparked widespread concern globally in the recent decade. Meanwhile, increased ischemic heart disease (IHD) mortality has been the leading cause of worldwide CVD deaths. Both China and India experienced a high IHD burden and high exposure to HAP. The present study aimed to estimate and compare the long-term trends of HAP-attributable IHD mortality in the two countries. The data of this study were extracted from the Global Burden of Diseases (GBD) Study 2019. The age-period-cohort (APC) analysis was utilized to estimate the independent trends of the age, period, and cohort effects from 1990 to 2019. The age-standardized mortality rates (ASMRs) of HAP-attributable IHD have fallen faster in China than in India for both sexes. The local drift and net drift values were < 0 for all age groups in both countries. The age effects in both countries and sexes increased with time, suggesting age is a risk factor for IHD; conversely, period and cohort effects in China demonstrated a faster decline in both genders than in India. It indicated that China has been more successful than India in decreasing HAP-attributable IHD mortality. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak has led to a substantial loss of human life throughout the world and has a tremendous impact on healthcare services. Industry 4.0 technologies have established effective supply chain management towards the fulfillment of customized demands in the healthcare field. In addition, the internet of things, artificial intelligence, big data analytics, and 3D printing have been extensively used to combat the COVID-19 pandemic and assist in providing value-added services in the healthcare sector. Henceforth, this paper presents a scientometric analysis on the literature of aforementioned Industry 4.0 technologies in the context of COVID-19. It provides extensive insights into co-citation and co-occurrence analysis of high cited publications, participating countries, influential authors, prolific journals, and keywords using the CiteSpace tool. The analyses reveal that China has produced the highest research outputs, although India is the most collaborative country in this field. The current research hotspots include supply chain, 4D printing, and social distancing technologies. Furthermore, it explores emerging trends, intellectual structure of publications, research frontiers, and potential research directions for further work in the Industry 4.0 assisted healthcare domain. [Display omitted] • Industry 4.0 technologies have emerged in the healthcare domain as an area of growing interest in academia and industry discipline. • Artificial intelligence, big data analytics, internet of things and 3D printing have been extensively used to control the COVID-19 spread and assist in providing value-added services in the healthcare sector. • It explores emerging trends, intellectual structure of publications, and potential research directions for further work in the Industry 4.0 assisted healthcare domain. [ABSTRACT FROM AUTHOR]

The article argues that India and Australia have a significant role to play amidst China's expanding maritime footprint in the Indian Ocean and growing influence in the South China Sea. With worsening relations between India and China as well as Australia and China, both New Delhi and Canberra have been deepening their connections, particularly after the COVID-19 pandemic. The article explores China as a key point of interest in India–Australia maritime cooperation and concludes that India–Australia ties have opened up the possibilities for expanding the arc of India's strategic partnerships in the Indo-Pacific region.. [ABSTRACT FROM AUTHOR]

Objective: To provide experience for formulating prevention and control policies, this study analyzed the effectiveness of the Coronavirus disease 2019(COVID-19) prevention and control policies, and evaluated health equity and epidemic cooperation among BRICS countries. Methods: This study summarized the pandemic prevention and control policies in BRICS countries and evaluated the effectiveness of those policies by extracting COVID-19 related data from official websites. Result: As of May 4, 2021, responding to COVID-19. China adopted containment strategies. China's total confirmed cases (102,560) were stable, without a second pandemic peak, and the total deaths per million (3.37) were much lower than others. India and South Africa who adopted intermediate strategies have similar pandemic curves, total confirmed cases in India (20,664,979) surpassed South Africa (1,586,148) as the highest in five countries, but total deaths per million (163.90) lower than South Africa (919.11). Brazil and Russia adopted mitigation strategies. Total confirmed cases in Brazil (14,856,888) and Russia (4,784,497) continued to increase, and Brazil's total deaths per million (1,936.34) is higher than Russia (751.50) and other countries. Conclusion: This study shows BRICS countries implemented different epidemic interventions. Containment strategy is more effective than intermediate strategy and mitigation strategy in limiting the spread of COVID-19. Especially when a strict containment strategy is implemented in an early stage, but premature relaxation of restrictions may lead to rebounding. It is a good choice to combat COVID-19 by improving the inclusiveness of intervention policies, deepening BRICS epidemic cooperation, and increasing health equities. [ABSTRACT FROM AUTHOR]

Purpose: The study tries to find pattern in the bilateral trade and impact of macro happenings like GFC, Chinese meltdown, Galwan conflict, COVID-19 on it over the period of 1995 to 2020. Design/Methodology/Approach: The study has two dimensions. The first one analyses the monthly export and import figures between India and China product wise (based on HS Code at two -digit level) from Jan2016 to Jan 2021 whereas second one focus on annual data of Indo-China Export and Import along with their annual GDP for 26 years starting from 1994 - 1995 to 2019-2020. Bilateral trades are analysed by using four tools namely-Bilateral Trade Dependence Index (BTDI); Trade Intensity Index (TII); Herfindahl Hirschmann Market Concentration Index (HHI); and Index of Export market penetration (IEMP). The study has also used Time series analysis to find the relationship between total bilateral trade and GDP of respective countries using Johansen Cointegration Test, Granger Causality Test, and VAR model. Findings: The annual growth rate of import and export for India with China suggest the short-term impact of macro happenings. Research Limitations: The study has several limitations with respect to availability of very recent data, availability of cost components of trade items in respective countries etc. Managerial Implications: Policy makers for India are suggested to work towards import substitution via various programs like Make-in-India with priority of domestic productions of HS Code 85, 84, 29 which are increasing the trade deficit continuously. Originality/Value: This study is an original effort to highlight the dynamic bilateral trade relationships between India and China in last twenty-five years. [ABSTRACT FROM AUTHOR]

Since 2019 the entire world is facing a crisis named as Corona Virus Disease 2019 (COVID-19). Within a short amount of time this disease which started from a small place in China has transformed into a pandemic and claimed millions of lives worldwide. India has witnessed the first and second wave of this infection with numerous variants of COVID-19, and an upsurge in infectivity rates and mortality rates. COVID-19 is a pernicious infection caused by a recent variant of Coronavirus. There are several research studies that have been carried out to understand it’s aetiology, pathophysiology, prevention and treatment strategies. As per the ancient Indian wisdom - “Prevention is better than Cure.” Any kind of infection can be prevented by taking necessary precautions and preventive measures against exposure to suspected environment and pathogen. A strengthened immune system further is able to fight and curb the disease even if there is exposure to the virus or any other pathogen. Significant data is available to support the need and importance of lifestyle modifications, particularly as mentioned in Āyurvedic and Yogic scriptures for immunity boosting in all age groups. The present review aims to provide a comprehensive, holistic and easy understanding of practical lifestyle modifications that can boost an individual’s immunity and help mitigate infectious diseases like COVID-19. [ABSTRACT FROM AUTHOR]

aimed to make a comparative analysis of the public health containment measures between China and India, explore the causes of the serious COVID-19 epidemic in India, and eventually to improve global infectious disease control. Methods: We extracted publicly available data from official websites, summarized the containment measures implemented in China and India, and assessed their effectiveness. Results: China has responded to the COVID-19 outbreak with strict public health containment measures, including lockdown of Wuhan city, active case tracing, and large-scale testing, ultimately preventing a large increase in daily new cases and maintaining a low mortality rate per million population (as of May 5, 2021, daily new cases were 11 and mortality rate per million population was 3.37). India, although imposing a national lockdown to control the pandemic, has not implemented strict testing, tracking, and quarantine measures due to the overburdened healthcare system. Combined with massive lockdown, it has accelerated human mobility and exacerbated the epidemic, resulting in a rapid increase in daily new cases and a high mortality rate per million population (as of May 5, 2021, daily new cases were 412,431 and mortality rate per million population was 166.79). Conclusion: China and India implemented public health containment measures to contain the spread of the COVID-19 pandemic based on their national situations. Meanwhile, daily new cases and mortality of COVID-19 also were affected by environmental and socioeconomic. Countries make a comprehensive strategy not only in terms of the biological, pharmaceutical, health, and sanitation sectors but also based on sustainability science and environmental science. [ABSTRACT FROM AUTHOR]

Background: With the outbreak of COVID-19 pandemic across the world, people have suffered an unexpected setback to their mental health. As psychological support is being provided to patients and healthcare workers, the general population and university students go unnoticed. This review aims to present existing literature that reports the effects of COVID-19 on psychological outcomes of the general population and university students in different countries. Methods: A manual search was conducted on PubMed, Google Scholar and Mendeley from inception to 31st January 2021. Articles were selected based on the predetermined eligibility criteria. Results: During COVID-19 pandemic, relatively high rates of depression (4.5% to 72.3%), anxiety (12.7% to 85.7%) and stress (5% to 90.1%) were reported in the general population as well as in university students, depression (3% to 70.5%), anxiety (9% to 63.3%) and stress (61.5% to 25%) in India, Nepal, Pakistan, China, Spain, US, UK, France, Egypt, Ethiopia, Bangladesh, Nigeria and Saudi Arabia. Risk factors associated include female gender, younger age group (≤40 years), unemployment, student status, and frequent exposure to social media/news concerning COVID-19. Conclusions: The COVID-19 pandemic is associated with highly significant levels of psychological disorders such as depression, anxiety and stress. Alleviating the hazardous effects of COVID-19 on mental health should be given due attention internationally. [ABSTRACT FROM AUTHOR]

The World is going through a tough situation and that is a pandemic caused by the Novel Corona virus which originated in the Wuhan Province of China in December 2019. During this tough and critical situation, the only saviors of humanity are our health care professionals, who restore the faith and trust in humanity and ensure the safety of each individual suffering from this COVID-19 disease. The cherry on the cake is the additional health support provided by the staff of Emergency Medical Services who help the health care workers in treating the patients in hospital, by giving the pre-requisite or the initial treatment during this emergency situation. So to tackle this pandemic, it is important to meet up to the increasing demand of Emergency Medical Services so that the situation remains under control and there is a decrease in mortality. The fragile and fragmented healthcare system of India needs to be upgraded and emphasis needs to be put on developing the Emergency Medical Services so as to strengthen the healthcare system as a whole and to make living better. [ABSTRACT FROM AUTHOR]

India, which is called the "world of pharmacy" for being a top supplier of medicines in several countries, can depend on other countries for Active Pharmaceutical Ingredients (API) and other raw materials. Although India is one of the major suppliers of high-quality medicines in several countries, the Indian pharmaceutical industry is highly dependent on China and other countries in terms of raw materials (including the production of essential medicines such as Crocin). These raw materials are called Active Pharmaceutical Ingredients (API), also known as loose drugs. Indian pharmaceutical manufacturers import medicines from China and other countries/regions to account for about 70% of total medicine demand. This article sheds light on the important question of how India depends on other countries to obtain API and other raw materials. Also, the effect of COVID-19 pandemic on the supply chain of bulk drugs, which indirectly affects the pharmaceutical manufacturers. The article concludes that this is the right time for India to remove the dependencies for bulk drugs on china and other countries and start producing their own API in the country itself. COVID-19 situation provides India an opportunity to become a preferred alternate hub for manufacturing APIs and intermediates. [ABSTRACT FROM AUTHOR]

The COVID-19 is disproportionally affecting the poor, minorities and a broad range of vulnerable populations, due to its inequitable spread in areas of dense population and limited mitigation capacity due to high prevalence of chronic conditions or poor access to high quality public health and medical care. Moreover, the collateral effects of the pandemic due to the global economic downturn, and social isolation and movement restriction measures, are unequally affecting those in the lowest power strata of societies. To address the challenges to health equity and describe some of the approaches taken by governments and local organizations, we have compiled 13 country case studies from various regions around the world: China, Brazil, Thailand, Sub Saharan Africa, Nicaragua, Armenia, India, Guatemala, United States of America (USA), Israel, Australia, Colombia, and Belgium. This compilation is by no-means representative or all inclusive, and we encourage researchers to continue advancing global knowledge on COVID-19 health equity related issues, through rigorous research and generation of a strong evidence base of new empirical studies in this field. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic originated in China in December 2019 and has since then, swept across the world. The last Influenza pandemic of 1918 happened before the advent of modern medicine. We have come a long way since then. But the pandemic has still caught us unprepared in many quarters. The review focuses on the management of critically ill COVID-19 patients and the various challenges faced by intensivists. [ABSTRACT FROM AUTHOR]

The sudden breakout of coronavirus disease (COVID-19) rapidly spread across the globe, leaving no country behind in being affected by the global pandemic in the year 2019–20. As COVID-19 commenced, within months two major Asian giants initiated the norms of social distancing and lockdowns in their societies. The indiscriminate nature of the current pandemic has not only impacted the health and quality of life of people but has also disrupted the global economy, supply chains, and countries all over the world. In food and beverage manufacturing industries, the unanticipated disruption has encumbered its lock on the global food supply chain and service sector as major cities shut down for several months in China and India. Human existence is dependent upon food, which renders energy for activity, growth, and all functions of the body. Although both China and India have shown eminent response to tackle the ongoing pandemic, the food supply chain remains vastly exposed to significant COVID-19 risks. This research primarily investigates the ongoing COVID-19 scenario in two major economies (China and India), delivering insight into the pandemic's impact within the food and beverage manufacturing sectors, and explores the policies adopted and strategies undertaken for sustainability in food supply chains. [ABSTRACT FROM AUTHOR]

Objectives: Restricting mobility is a central aim for lowering contact rates and preventing COVID-19 transmission. Yet the impact on mobility of different non-pharmaceutical countermeasures in the earlier stages of the pandemic is not well-understood.Design: Trends were evaluated using Citymapper's mobility index covering 2nd to 26th March 2020, expressed as percentages of typical usage periods from 0% as the lowest and 100% as normal. China and India were not covered. Multivariate fixed effects models were used to estimate the association of policies restricting movement on mobility before and after their introduction. Policy restrictions were assessed using the Oxford COVID-19 Government Response Stringency Index as well as measures coding the timing and degree of school and workplace closures, transport restrictions, and cancellation of mass gatherings.Setting: 41 cities worldwide.Main Outcome Measures: Citymapper's mobility index.Results: Mobility declined in all major cities throughout March. Larger declines were seen in European than Asian cities. The COVID-19 Government Response Stringency Index was strongly associated with declines in mobility (r = - 0.75, p < 0.001). After adjusting for time-trends, we observed that implementing non-pharmaceutical countermeasures was associated with a decline of mobility of 10.0% for school closures (95% CI: 4.36 to 15.7%), 15.0% for workplace closures (95% CI: 10.2 to 19.8%), 7.09% for cancelling public events (95% CI: 1.98 to 12.2%), 18.0% for closing public transport (95% CI: 6.74 to 29.2%), 13.3% for restricting internal movements (95% CI: 8.85 to 17.8%) and 5.30% for international travel controls (95% CI: 1.69 to 8.90). In contrast, as expected, there was no association between population mobility changes and fiscal or monetary measures or emergency healthcare investment.Conclusions: Understanding the effect of public policy on mobility in the early stages is crucial to slowing and reducing COVID-19 transmission. By using Citymapper's mobility index, this work provides the first evidence about trends in mobility and the impacts of different policy interventions, suggesting that closure of public transport, workplaces and schools are particularly impactful. [ABSTRACT FROM AUTHOR]