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The impact of COVID-19 on the Global scale is tremendously drastic. There are several types of research going on across the world simultaneously to understand and overcome this dire pandemic outbreak. This paper is purely a statistical study on a distinct set of datasets regarding COVID-19 in India. The motivation of this study is to provide an insight into the rapid growth of confirmed COVID-19 cases in India. The rapid growth of COVID-19 cases in India started in March 2020. The main objective of this paper is to provide a solid statistical model for the policymaker to handle this kind of pandemic situation in the near future with nonlinear data. In this paper, the data was got from 1st April to 29th November 2020. To come up with a solid statistical model, various nonlinear data such as confirmed COVID-19 cases, maximum temperature, minimum temperature, the total population (state-wise), the total area in km2 (state-wise), and the total rural and urban population count (state-wise) have been analyzed. In this paper, six different Generalized Additive Models (GAM) was identified after a thorough analysis of other researchers' (Xie and Zhu, 2020; Prata et al., 2020) findings. In all perspectives, the results were identified and analyzed. The GAM model regarding total COVID-19 confirmed cases, total population, and the total rural population provides the best average fit of R2 value of 0.934. As the population value is quite high, the author has concise it using logarithm to provide the best p -value of 0.000542 and 0.001407 for a relation between the total number of COVID-19 cases regarding the total population and total rural population respectively. [ABSTRACT FROM AUTHOR]

Data is already recognized as an essential piece for unlocking maximum value within a transportation system and it has the potential to create more efficient passenger mobility. The aim of this research is to critically assess the ecosystem for mobility data including policies and regulations in India to administer the pandemic and post-pandemic scenario. The paper identified various data sources based on a typical public transport journey, further summarizing strategies adopted world-wide during COVID-19. The application of data during and post pandemic scenario is discussed to identify that contact tracing and development of digital payment systems as most necessary for same. The paper concludes with a critical evaluation of current ecosystem of data policies putting forward the recommendations to current data policies in India. • Correlation and analytics of mobility data necessary for informed decisions. • Mobility data generated from multiple sources could act as key decision making tool during pandemic. • Location data, spatial and ticketing information supported by digital infrastructure backbone of disaster management decision. • Surveillance of the data usage, digital payment systems, data access and sharing policies are required to create necessary ecosystem for realizing full potential of mobility data during a pandemic. [ABSTRACT FROM AUTHOR]

Impacts of COVID-19 in maritime transportation and its related policy measures have been investigated by more and more organizations and researchers across the world. This paper aims to examine the impacts of COVID-19 on seaport transportation and the maritime supply chain field and its related issues in India. Secondary data are used to analyze the performance indicators of major seaports in India before and during the COVID-19 crisis. We further explore and discuss the expert's views about the impact, preparedness, response, and recovery aspects for the maritime-related sector in India. The results on the quantitative performance of Indian major seaports during the COVID-19 indicate a negative growth in the cargo traffic and a decrease in the number of vessel traffic compared to pre-COVID-19. The expert survey results suggest a lack of preparedness for COVID-19 and the need for developing future strategies by maritime organizations. The overall findings of the study shall assist in formulating maritime strategies by enhancing supply chain resilience and sustainable business recovery process while preparing for a post-COVID-19 crisis. The study also notes that the Covid-19 crisis is still an ongoing concern, as the government, maritime organizations, and stakeholders face towards providing vaccine and remedial treatment to infected people. Further, this study can be expanded to the global maritime supply chain business context and to conduct interdisciplinary research in marine technical fields and maritime environment to measure the impact of COVID-19. • With the outbreak of COVID-19, maritime industry accounting to 90% of the international trade has been impacted. • The major seaports of India handle about 60% of the country's total cargo traffic. • This paper examines implications of COVID-19 on Indian major ports by identifying patterns for quantitative performance data before & during the COVID-19 crisis. • This study explores & discusses expert's views about impact, preparedness, response, and recovery aspects for the maritime-related sector in India. • The results for quantitative performance data for major seaports in India indicate negative growth in during COVID-19 compared to pre COVID-19 period. • The expert survey result suggests a negative impact of COVID-19, and there is a need to develop future strategies by maritime organizations. • The overall findings of the study assist in formulating maritime strategies by enhancing supply chain resilience and sustainable business recovery process while preparing for a post-COVID-19 crisis in Indian maritime Context. [ABSTRACT FROM AUTHOR]

This paper examines the effectiveness of the monetary policies undertaken by the central bank on economic growth during COVID-19 uncertainty in case of India and Indonesia. We use an innovative framework of Growth-at-Risk as oppose to standard macroeconomic models, which can predict the growth in a much robust way particularly when an economy is facing shocks like COVID-19. The empirical results based on Growth-at-Risk model clearly reveal that effect of COVID-19 pandemic on economic growth is much adverse in comparison to actual declines. Further, this study shows the effectiveness of monetary and financial policies undertaken by the central banks of both India and Indonesia, which have actually subsided the adverse impact of COVID-19. [ABSTRACT FROM AUTHOR]

• Examine link between perceived COVID-19 risk and return decision among migrants. • Use novel survey data of 495 reverse male migrants in India in april-may 2020. • Migrants with greater perceived COVID-19 infection risk less willing to return. • Impatience positively associated with greater willingness to return. • Higher recall of prevention strategies linked to lower perceived COVID-19 risk. This paper explores the causal link between the likelihood of re-migration to cities and the perceived threat of contracting COVID-19 using novel data on male reverse migrant workers in India. We find that reverse-migrants who believe there is a significant chance of contracting COVID-19 display a significantly lower likelihood of returning to their urban workplaces, regardless of their duration of migration. On the other hand, longer-duration migrants display a lower perceived chance of contracting COVID-19 than shorter-duration migrants. We also contribute to the migration literature by linking behavioural attributes to the decision to migrate. We find that more impatient individuals display a heightened belief regarding contracting COVID-19 and a higher projected likelihood of returning to work. Finally, we find that while both loss and risk-averse individuals have a lower projected likelihood of returning to urban workplaces, only loss-averse individuals perceive that their chance of contracting COVID-19 is lower. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, which is a global health emergency, has potentiality had a serious impact on students' mental health. An online cross-sectional survey design that included 534 senior year college students from South India revealed a significant and direct positive effect of the fear of a third wave of COVID-19 on academic anxiety which in turn showed a significant and direct positive effect on COVID-19 burnout. Academic anxiety was also found to mediate the relationship between the fear of a third wave of COVID-19 and subsequent cases of burnout. The study suggested measures to be taken by policy makers for the broader interest and wellbeing of student communities. Managerial implications, limitations and future studies were also examined in the paper. [ABSTRACT FROM AUTHOR]

Inactivated viral vaccines have long been used in humans for diseases of global health threat (e.g., poliomyelitis and pandemic and seasonal influenza) and the technology of inactivation has more recently been used for emerging diseases such as West Nile, Chikungunya, Ross River, SARS and especially for COVID-19. The Brighton Collaboration Benefit-Risk Assessment of VAccines by TechnolOgy (BRAVATO) Working Group has prepared standardized templates to describe the key considerations for the benefit and risk of several vaccine platform technologies, including inactivated viral vaccines. This paper uses the BRAVATO inactivated virus vaccine template to review the features of an inactivated whole chikungunya virus (CHIKV) vaccine that has been evaluated in several preclinical studies and clinical trials. The inactivated whole CHIKV vaccine was cultured on Vero cells and inactivated by ß-propiolactone. This provides an effective, flexible system for high-yield manufacturing. The inactivated whole CHIKV vaccine has favorable thermostability profiles, compatible with vaccine supply chains. Safety data are compiled in the current inactivated whole CHIKV vaccine safety database with unblinded data from the ongoing studies: 850 participants from phase II study (parts A and B) outside of India, and 600 participants from ongoing phase II study in India, and completed phase I clinical studies for 60 subjects. Overall, the inactivated whole CHIKV vaccine has been well tolerated, with no significant safety issues identified. Evaluation of the inactivated whole CHIKV vaccine is continuing, with 1410 participants vaccinated as of 20 April 2022. Extensive evaluation of immunogenicity in humans shows strong, durable humoral immune responses. [ABSTRACT FROM AUTHOR]

This paper investigates the factors affecting access to clean cooking fuel among rural Indian households during the COVID-19 outbreak, based on World Bank's rural impact survey, covering 2731 rural households. Our analysis shows a significant decline in access to clean fuel among rural households from 35% in 2018 i.e. before COVID-19 to 19.7% during the COVID-19 pandemic. This implies that in order to meet their cooking needs, many rural households have switched from conventional fuels, which have numerous health and environmental concerns. The association between states and socio-demographic profiles of rural households with access to sources of cooking fuel shows a significant difference. The analysis results further indicate that socio-demographic characteristics and asset holdings of the rural households are the key factors that determine access to clean cooking fuel during COVID-19. Among the socio-demographic variables, age, gender, family size, social category, and income level are estimated to be significant factors that affect the access to clean fuel for cooking. Similarly, ownership of assets such as exclusive kitchen room, refrigerator, pressure cooker, television, and furniture are significant factors affecting access to clean cooking fuel among Indian rural households. Additionally, this study provides policy insights on developing mechanisms to ensure that rural households have an access to clean cooking fuel during crisis situations such as COVID-19. [Display omitted] • COVID-19 pandemic has impacted the access to clean cooking fuel among the rural households. • Only 19.7% of rural households have reported access to clean cooking fuels, which declined during COVID-19 lockdown • The majority of rural households use conventional sources of cooking fuels, which further increased during COVID-19 outbreak • Socio-demographic characteristics and asset holdings are determining factors on access to clean cooking fuel • A targeted strategy for promoting clean cooking fuel in rural India is essential [ABSTRACT FROM AUTHOR]

As countries across the world modify their travel in the face of the Covid-19 pandemic, the first casualty becomes the public transport sector. Transport authorities across the world have reported about 95% reduction in users during peak COVID-19, decrease of fare box revenues and additional costs for disinfecting and implementing physical distancing measures. The public transport companies in India face a larger crisis as nearly 85% people travelling intercity use public road transport in normal times. In this paper we drawpassenger clusters based on their travel dynamics and develop two frameworks, namely, passenger driven transportation strategy framework and epidemic prevention strategy framework to deal with the COVID-19 induced travel changes. The frameworks use three tenets of mobility, namely, agility, integrated movement, and public based partnership. The strategies aim to enable the transport enterprises to open new windows of travel and efficiencies for the passengers rather than restricting access and choices. However, security remains fundamental to making these new and innovative service changes possible. [ABSTRACT FROM AUTHOR]

Dynamics of COVID-19 outbreak in India are different from other countries for her huge population and different administrative approaches. This paper presents a six compartments (SHIQRD) model with different time delays between them, to analyse and forecast the COVID-19 pandemic in India. The model introduces separate compartments for 'home-quarantined', 'quarantined infectious', and 'undetected infectious' pertaining to the Indian scenario. It also incorporates incubation time, sample testing time, and recovery window as time delays between blocks. With the proposed model, reproduction number of different phases during lock-down are evaluated. Besides, dynamics of pandemic for the next one year are also explored. [ABSTRACT FROM AUTHOR]

• Prophet Model provides understanding of the number of people affected daily by this disease. • The imposed interventions are reflected by five significant changepoints detected by the model in the growth curve of India. • The model forecasts90 days future growth trend and finds the peak time for all the six countries and six states of India. • The model has achieved around 85% MAPE for all the six countries and the six states of India. Covid-19 disease caused by novel coronavirus (SARS-CoV-2) is a highly contagious epidemic that originated in Wuhan, Hubei Province of China in late December 2019. World Health Organization (WHO) declared Covid-19 as a pandemic on 12th March 2020. Researchers and policy makers are designing strategies to control the pandemic in order to minimize its impact on human health and economy round the clock. The SARS-CoV-2 virus transmits mostly through respiratory droplets and through contaminated surfacesin human body.Securing an appropriate level of safety during the pandemic situation is a highly problematic issue which resulted from the transportation sector which has been hit hard by COVID-19. This paper focuses on developing an intelligent computing model for forecasting the outbreak of COVID-19. The Facebook Prophet model predicts 90 days future values including the peak date of the confirmed cases of COVID-19 for six worst hit countries of the world including India and six high incidence states of India. The model also identifies five significant changepoints in the growth curve of confirmed cases of India which indicate the impact of the interventions imposed by Government of India on the growth rate of the infection. The goodness-of-fit of the model measures 85% MAPE for all six countries and all six states of India. The above computational analysis may be able to throw some light on planning and management of healthcare system and infrastructure. [Display omitted] [ABSTRACT FROM AUTHOR]

• Disruptions during the COVID-19 lockdown caused children to miss immunizations. • Government catch-up efforts substantially reversed these effects. • Yet, children that were due vaccinations during the lockdown remained 10–15% less likely to be immunized 4–5 months later. • Catch-up was more likely to be incomplete among children of low socioeconomic status. • Ensuring all children are fully immunized requires careful tracking and disaggregated data. Governments around the world suspended immunization outreach to control COVID-19 spread. Many have since resumed services with an emphasis on catch-up vaccinations. This paper evaluated immunization disruptions during India's March-May 2020 lockdown and the extent to which subsequent catch-up efforts reversed them in Rajasthan, India. In this retrospective observational study, we conducted phone surveys to collect immunization details for 2,144 children that turned one year old between January and October 2020. We used logistic regressions to compare differences in immunization timeliness and completed first-year immunization status among children that were due immunizations just before (unexposed), during (heavily exposed), and after (post-exposure) the lockdown. Relative to unexposed children, heavily exposed children were significantly less likely to be immunized at or before 9 months (OR 0.550; 95% CI 0.367–0.824; p = 0.004), but more likely to be immunized at 10–12 months (OR 1.761; 95% CI 1.196–2.591; p = 0.004). They were also less likely to have completed their key first-year immunizations (OR 0.624; 95% CI 0.478–0.816; p = 0.001) by the time of survey. In contrast, post-exposure children showed no difference in timeliness or completed first-year immunizations relative to unexposed children, despite their younger age. First-year immunization coverage among heavily exposed children decreased by 6.9 pp to 10.4 pp (9.7% to 14.0%). Declines in immunization coverage were larger among children in households that were poorer, less educated, lower caste, and residing in COVID red zones, although subgroup comparisons were not statistically significant. Disruptions to immunization services resulted in children missing immunization during the lockdown, but catch-up efforts after it was eased ensured many children were reached at later ages. Nevertheless, catch-up was incomplete and children due their immunizations during the lockdown remained less likely to be fully immunized 4–5 months after it lifted, even as younger cohorts due immunizations in June or later returned to pre-lockdown schedules. [ABSTRACT FROM AUTHOR]

Using state-level aggregate data from India, this paper examines the impact of Covid-19 pandemic and its containment efforts on macroeconomic performance after controlling for several initial conditions, the structure of the state economies, and healthcare and public health capabilities. A panel regression analysis based on state-level monthly unemployment data from April to November 2020 indicates that states experiencing higher spread of Covid-19, with adverse initial economic conditions, and larger employment dependence on secondary and tertiary sector have suffered significantly larger economic losses. In contrast, states with better containment strategy, higher healthcare capabilities, and a relatively larger employment share of the primary sector have experienced smaller economic losses. Further, the nationwide lockdown during the months of April and May had significant adverse effects on the state economies. Finally, the spread of the virus interacts with each of the above factors to significantly impact state economic performances. These results are informative not only for policies and strategies for short and long-term recovery of the state economies in India but also for understanding actual and potential economic impacts of the pandemic acrosscountries. [ABSTRACT FROM AUTHOR]

In this paper, deep learning is employed to propose an Artificial Neural Network (ANN) based online incremental learning technique for developing an adaptive and non-intrusive analytical model of Covid-19 pandemic to analyze the temporal dynamics of the disease spread. The model is able to intelligently adapt to new ground realities in real-time eliminating the need to retrain the model from scratch every time a new data set is received from the continuously evolving training data. The model is validated with the historical data and a forecast of the disease spread for 30-days is given in the five worst affected states of India. [ABSTRACT FROM AUTHOR]

Trauma is slowly regaining its pre-COVID-19 status in terms of prevalence. Advanced trauma training cannot be deferred indefinitely in the current pandemic owing to defense requirements and disaster preparedness in vulnerable regions. Advanced Trauma Life Support (ATLS) India resumed ATLS and Advanced Trauma Care For Nurses (ATCN) courses at one civilian and one military site. Stakeholders of respective centers for advanced trauma training deliberated over safe means to resume ATLS and ATCN. Meticulous screening of all participants and pre- and post-course tracking were deemed the most important components for the safe resumption of courses. 'Paperless' course, 'open-air' skill stations, 'payment protection', 'buddy system', point of care sanitizer installation, packed food, and potable beverages were major organizational changes. Participants above 60 years and with uncontrolled comorbidities were not enrolled. Two ATCN, one ATLS (civilian), and one combined ATLS-ATCN (military) were conducted. 78 delegates trained by 32 faculties and 13 personnel. All underwent daily thermal scanning and smartphone application-based COVID-19 tracking. Manikins were utilized instead of moulages and instructors took up the role of nursing assistants in Initial Assessment. Exit exams were conducted with full PPE precautions at the military site and mask-distancing precautions at the civilian site. High fidelity simulator was used at one station at the civilian site. Expenses at the civilian site per course were USD 570 lower than conventional courses. There was no incidence of COVID-19 in any of the 123 participants at 14 days follow up. With stringent participant selection and moderate precautions, ATLS and ATCN can be resumed safely in the current COVID-19 pandemic. To the best of our knowledge and after a thorough search of published English literature, this is the first paper reporting on resuming Advanced trauma training in the COVID-19 era. [ABSTRACT FROM AUTHOR]

This paper analyzes the effects of the 9-min pan-India voluntary lights-off policy that was planned and executed by the Government of India in April 2020 on the National Grid and the steps that were taken to maintain grid stability during the event. The policy was a symbolic gesture of public solidarity with frontline healthcare and emergency workers in the nation's war against the COVID-19 pandemic. The event entailed nationwide switching-off of electric lights and lighting of earthen lamps or switching-on of torch lights. This 9-min event posed a significant challenge to the country's power systems engineers in managing grid stability during the large-scale load reduction, and meticulous planning and implementation of protective measures were carried out. In this article, the strategy implemented by the Indian power sector to manage the grid during the nine-minute event is described. The variations of grid parameters such as frequency, voltage, and load at all dispatch centers before, during, and after the nine-minutes are analyzed, and the generation schedule that was followed is also presented, along with real-time results. This case study provides an overview of power systems management that involves strategic scheduling of generators throughout the country to tackle sudden and mass-reductions of load on the power system. • Covid-19 and its impact on the world • History of blackouts and brownouts brownouts in a power system. • Overview of the India power system and national power grid development. • Pan India lights off policy on 5th April 2020 • Power system operation and control during an emergency [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]

The SARS-CoV-2 is a type of coronavirus that has caused the pandemic known as the Coronavirus Disease of 2019, or COVID-19. In traditional epidemiological models such as SEIR (Susceptible, Exposed, Infected, Removed), the exposed group E does not infect the susceptible group S. A distinguishing feature of COVID-19 is that, unlike with previous viral diseases, there is a distinct "asymptomatic" group A , which does not show any symptoms, but can nevertheless infect others, at the same rate as infected symptomatic patients. This situation is captured in a model known as SAIR (Susceptible, Asymptomatic, Infected, Removed), introduced in Robinson and Stillianakis (2013). The dynamical behavior of the SAIR model is quite different from that of the SEIR model. In this paper, we use Lyapunov theory to establish the global asymptotic stabililty of the SAIR model, both without and with vital dynamics. Then we develop compartmental SAIR models to cater to the migration of population across geographic regions, and once again establish global asymptotic stability. Next, we go beyond long-term asymptotic analysis and present methods for estimating the parameters in the SAIR model. We apply these estimation methods to data from several countries including India, and demonstrate that the predicted trajectories of the disease closely match actual data. We show that "herd immunity" (defined as the time when the number of infected persons is maximum) can be achieved when the total of infected, symptomatic and asymptomatic persons is as low as 25% of the population. Previous estimates are typically 50% or higher. We also conclude that "lockdown" as a way of greatly reducing inter-personal contact has been very effective in checking the progress of the disease. [ABSTRACT FROM AUTHOR]

Evidence from earlier studies on COVID-19 suggests that the countries led by female leaders were more successful in handling the COVID-19. India being a patrilocal society evident that women's political autonomy in the Gram Panchayat does miracles concerning development. With this backdrop, the present paper aims to explore the role of women's political participation and leadership on the efficiency in reducing the COVID-19 death rate for Indian states. This predominantly empirical paper is entirely based on secondary data compiled from different sources. The empirical analysis of the paper is facilitated by the utilization of the Technical Inefficiency Effects model within the framework of Stochastic Production Frontier. The empirical results accredit us to conclude that the efficiency of the Indian states in reducing the COVID-19 death rate is highly influenced by female political participation and leadership, digitalization, urbanization, and literacy rate. The study ends with suitable policy prescriptions. • The present paper aimed to explore the role of women's political participation and leadership on the efficiency in reducing COVID-19 death rate across Indian states. • The empirical analysis of the paper is conducted by utilizing the Technical Inefficiency Effects model. • The empirical results conclude that the West Bengal, governed by female chief-minister becomes the most efficient state in reducing COVID-19 death rate. • Women MP and Women MLA representing the political leadership of women reveals a positive and significant role in escalating the state's efficiency in combatting COVID-19. [ABSTRACT FROM AUTHOR]

Up until now, countries have adopted a 'isolate-test-treat-trace' strategy to contain the COVID-19 pandemic. The next critical intervention in the fight against COVID-19 will be effective delivery of safe and efficacious vaccines. Various countries such as the USA, the UK, Canada, Israel, etc., have started administering vaccines to priority population groups. India is gearing up its critical components of the vaccine delivery system to effectively deliver vaccines across the country and has prioritized certain population groups to whom the vaccine will be administered. Considering India's ambitious target to vaccinate close to 300 million people in the first phase of the vaccination drive with limited initial supply (which will be ramped up gradually), it is critical for stakeholders at all the levels – national, state and district – to understand the estimated need for vaccines across geographies based on the vulnerable population and disease epidemiology with the objective of preventing maximum number of future infections from the disease. This paper aims to describe a comprehensive geo-prioritization framework based on existing prevalence of COVID-19, high-risk co-morbidities, and demographic analysis to identify states/districts that could be most in need of the COVID-19 vaccines. [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]

In view of school closures due to the COVID-19 pandemic, this paper examines how a Home-Based Learning program affects learning outcomes of children in under-resourced communities. To overcome limited internet connectivity, the program provides remote instructions via phone calls and simple text messages along with automated voice calls to engage children enrolled in grades one to five in activity-based learning content. This intervention was conducted in three districts in the state of Odisha in India. Using a difference-in-differences framework, we find that the intervention led to a statistically significant improvement in basic number recognition and arithmetic operations, and language learning scores of children by 4.69 percentage points and 5.52 percentage points, respectively. Our results are robust to alternative methods of estimation and application of Lee bounds, thus indicating that well-designed low cost interventions could be a useful supplement for continued learning in the face of sudden shocks in low income countries. With a rise in hybrid format of teaching and learning, such interventions have the capability to cushion the decline in learning levels and provide a safety net in the event of school closures. [ABSTRACT FROM AUTHOR]

Over the past few years, an increasing convergence can be observed between international and Indian initiatives towards cashlessness, often involving a broad range of actors and influences. Despite this convergence, it is also clear that the conceptualization and implementation, or goals and outcomes of cashlessness can vary considerably, which indicates the need for a closer look at the Indian case. In this introductory note to the special issue on cashlessness in India, we outline the variety of institutions, stakeholders (regulatory, financial and technological actors), technologies and policies involved. As we have observed, digital payments and financial inclusion are two significant planks of cashlessness in India. Perhaps as a result, digital payments have been intentionally defined in a broad manner in India – ranging from anti-cash to less-cash and now contactless payments in the aftermath of Covid-19. Considering the variety of legal, economic, social and technological concerns involved, this special issue adopts 2 complementary foci to study cashlessness in India: technological visions and the systems undergirding it, and practices of end users. The special issue includes four papers. The first paper argues that the Digital India programme may lead to the commercialization of bias. The second paper historicizes the Indian demonetization of 2016 and examines its stated and unstated goals. The next paper provides a conceptual model on technology adoption in the context of digital payments. The final paper argues that users strategically switch between multiple payments media based on the context in which the transaction is taking place. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has dramatically altered global energy consumption, particularly affecting investment in renewable energy projects. In India, strict shelter-in-place orders enforced during March 2020 have since led to a considerable change in public and private sector investments in planned renewable energy installations. In this paper, we attempt to highlight trends in energy consumption and installed renewable energy capacity noted in India during a period concurrent with the shelter-in-place orders. We discuss recent policy measures and additions to installed renewable energy capacity, and propose key policy recommendations that may help the sector adopt a growth trajectory similar to one noted pre-pandemic. This paper is organized into four main parts. In the first section, we draw focus to India's renewable energy policies and pay special emphasis on recent interventions and campaigns targeted towards achieving high growth rates in the sector. We briefly discuss the need for effective public-private partnerships in order to meet these targets. In the second part, we quantitatively characterise the growth of renewables in India. We present an overview of several mechanisms and missions the government has launched in line with their policy to mitigate the environmental impact of India's energy mix. In the third part, we analyse the decrease in electricity demand in India from 24 March to 30 June 2020, a period concurrent with shelter-at-home orders issued by the Government. We also characterise changes in installed renewable energy capacity between March to December 2016–2020 to provide causal evidence of the effect of the pandemic on the growth of renewables. In this section, we also compile and analyse data on state-wise stressed assets across renewable energy generators in the country. Lastly, in the fourth and final portion of this paper, we highlight policy recommendations that may help the sector overcome logistical and financial bottlenecks in the short-term. We do this with the hope of outlining key measures that decision makers may employ to achieve pre-COVID sectoral growth in the long term. Our recommendations cover three different policy instruments: investment subsidies, operational subsidies, and recommendations for DISCOMs. • The increase in Indian renewable energy capacity installations between February to May 2020 hasseen an increment of 0.75%. • Daily electricity demand has decreased by 18.8% after the announcement of the shelter at home orders. • Immediate effects of the pandemic on the Indian renewable energy sector have been quantified. • A 3 tier system may be adopted to regulate incentives among renewable energy power producers. • Key policy recommendations to improve the fitness of the renewable energy sector have been discussed. [ABSTRACT FROM AUTHOR]

The paper explores the experiences of Indian middle-class and upper-middle-class women managing working motherhood in the context of pandemic-induced remote work. The increased paid and unpaid work during the COVID-19 crisis amplified the tensions between becoming a 'good mother' and an 'ideal worker'. The collapsed boundaries between work and home, resulting from flexible work that gained momentum in the pandemic, threatened the carefully negotiated boundaries by women. Using an interpretive qualitative approach, the present study investigates how women negotiated the meaning of working motherhood in the face of frequent boundary violations. The findings show how classed and neoliberal maternal subjectivities of Indian working women manifested during the crisis. When forced to integrate maternal with professional, working mothers claimed identities that aligned with middle-class values that were appropriately modern and global, at the same time rooted in patriarchy. Concurrently, the findings reveal the classed and gendered nature of remote work, which manifests as an extension of gendered organization and neoliberal ideology within the homes of working mothers, fortifying their role as caregivers. [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]

When on March 24, 2020 the Government of India ordered a complete lockdown of the country as a response to the COVID-19 pandemic, it had serious unwanted implications for farmers and the supply chains for agricultural produce. This was magnified by the fact that, as typically in developing countries, India's economy is strongly based on farming, industrialization of its agricultural systems being only modest. This paper reports on the various consequences of the COVID-19 lockdown for farming systems in India, including the economy, taking into account the associated emergency responses of state and national governments. Combining quantitative and qualitative sources of information with a focus on the Indian state of Uttar Pradesh, including expert elicitation and a survey of farmers, the paper identifies and analyzes the different factors that contributed to the severe disruption of farming systems and the agricultural sector as a whole following the lockdown. Among other issues, our study finds that the lack of migrant labor in some regions and a surplus of workers in others greatly affected the April harvest, leading to a decline in agricultural wages in some communities and an increase in others, as well as to critical losses of produce. Moreover, the partial closure of rural markets and procurement options, combined with the insufficient supply of products, led to shortages of food supplies and dramatically increased prices, which particularly affected urban dwellers and the poor. We argue that the lessons learned from the COVID-19 crisis could fuel the development of new sustainable agro-policies and decision-making in response not only to future pandemics but also to the sustainable development of agricultural systems in India and in developing countries in general. • The lockdown in response to COVID-19 has seriously disrupted Indian farms. • Farms have been less profitable amid rising food prices, putting pressure on food security. • A lack of migrant labor has led to a loss of produce and affected the spring harvest. • Experience and relief packages may help to develop Indian agriculture sustainably. [ABSTRACT FROM AUTHOR]

COVID-19 is the pandemic caused by one of the coronaviruses. This virus was not known before the outbreak in Wuhan, China, in December 2019. By January of 2020 it was declared to be a global human health crisis. The deaths and illnesses caused by the virus caused extensive fear and anxiety among people in all societies. The pandemic slowed economic activities nearly to a halt. The challenges of how companies should respond to the disruptions in their supply chains and how they can build more resilient systems, must be systematically addressed. The authors of this paper highlighted essential factors which can help companies to overcome this crisis and other types of crises, by learning from the approaches taken in India, which has a unique and diverse economic system. The Analytical Hierarchy Process (AHP) technique was used to identify the essential factors which can help companies to improve their resilience so they can recover during and after the COVID-19 pandemic era and potentially in other similar complex crises. The results of the AHP evaluation were prioritized by performing a sensitivity analysis to prioritise the essential factors. The "Role of governance" was found to be the most important factor that can be used to help in rebuilding industries and societies and in helping them to become more resilient to future severe shocks. The results of this research were used to develop recommendations for company managers, practitioners and policy-makers. The authors hope that this advice will help India to become a stronger nation with more resilient companies, which are better prepared to anticipate and to respond to future crises. We hope people in other nations will also benefit from the finding presented in this paper. Image 1 • Factors influencing rebuilding resilient industries and societies are proposed. • Focus is on measures to avoid disruption in supply chain in Indian context. • The ranking framework is developed using AHP followed by sensitivity analysis. • Role of governance reported highest rank indicating its importance in post COVID era. • Policy implications are derived to build resilient nation, which can face shocks. [ABSTRACT FROM AUTHOR]

• Exams emergency amidst covid-19 pandemic has created a contention among government, exam authorities and students in India. • The paper presents challenges and problems faced by students while preparing exams and appearing in the exam centres. • The paper finds no concrete attempt of negotiation from government to deal student's concern. • Safety measures taken by government and exam authorities are inadequate. The paper examines 'exam emergency' in India through an engaging dialogue of importance, dissension, and contention over conducting all the annual entrance examinations amidst this covid-19 pandemic that have been postponed earlier due to nationwide lockdown. Drawing on the pre-exam living experiences, this paper presents the challenges and problems of student communities and the insecurities of their mental and physical health risks while they are preparing and appearing for their scheduled entrance tests. The paper finds no concrete attempt of negotiations from the authorities to channel majoritarian concerns. The lack of preparation from government and exam authorities to facilitate students in this crisis period has finally made many to fail writing their exam papers and left them behind with unfulfilled dreams. [ABSTRACT FROM AUTHOR]

Fisheries and aquaculture have emerged as a promising food production sector at the global level as well as regional levels. Fish and fish products are produced in one region and then are traded across various parts of the world. The whole sector is dependent on chains of workers engaged at landing centres, breeding units, processing units, and the trade and export chains. When the pandemic and the subsequent lockdown hit the country, it affected the whole sector and caused a huge decline in the production and trade of fishing products. This article aims to have a glimpse into the aquaculture sector and evaluate the impact of the pandemic on this sector in India. This valuable information can be of great importance to government and aquatic food suppliers so that they can evolve their strategies to withstand ongoing and future pandemics. It also helps them in framing regional and sectorial adjustments to transform investment plans, match market demands, improve monitoring strategies and get prepared for future needs. • The purpose of this article is to have a glimpse into the aquaculture sector and evaluate the impact of the COVID-19 pandemic on this sector in India. • This valuable information can be of great importance to the government and aquatic food suppliers so that they can evolve their strategies to withstand ongoing and future pandemics. • It also helps them frame regional and sectorial adjustments to transform investment plans, match market demands, improve monitoring strategies and prepare for future needs. • Some of the major challenges the entire fishing community faced during the COVID-19 lockdown are (i)difficulty in hiring truck drivers for transport of cargo. • (ii) Delayed seaweed seed material transportation. • (iii) Total shutdown of shrimp processing unit, forced engagement of minimal labour in shrimp feed, medicine and probiotics industries. • and (iv) Negative impacts on the livelihood of local fishermen due to fishing ban and low demand. • The paper also summarizes the reformations in the aquaculture sector in India to future pandemics. • Outbreak of COVID-19 has stimulated digital transformation across many aquaculture supply chain in India to reduce the dependence on manpower. • Scientific farming practices, the inclusion of technology and decreasing the over-dependency on export (around 90%) can recover the sector and can help take it to a desired level. [ABSTRACT FROM AUTHOR]

COVID-19 is a respiratory infection caused by a coronavirus that spreads from person to person. In the present situation, the COVID-19 pandemic is a swiftly rising phase. Now the time is the second wave ending phase of coronavirus and the third wave coming phase of coronavirus in India. The pandemic situation is moving forward all over India. Nowadays, the worldwide COVID-19 pandemic structure is a very hazardous situation. The COVID-19 vaccine can suppress this situation and gain preventive measures against coronavirus. In producing the COVID-19 vaccine, the Indian medical board plays a significant role. The COVID-19 vaccines have exhibited 90%–95% efficacy in preventing symptomatic COVID-19 infections. Against COVID-19, for emergency purposes, the Indian medical board has approved three vaccines: Covishield, Covaxin, and Sputnik V. Generally, the Indian people are embarrassed about the vaccination of COVID-19. All people are thinking about which vaccine is best for them. This labyrinth can be evaluated effectively using the multi-criteria decision-making (MCDM) technique. Therefore, we have proposed a novel MCDM technique for selecting COVID-19 vaccines. The main aim of this paper is to develop an MCDM technique based on a λ -weighted ranking interpreter ( R λ + , R λ − ). The first time, we have defined positive and negative λ -weighted rank interpreter for the ranking of single-valued bipolar neutrosophic (SVbN) number. Additionally, positive and negative λ -weighted values and positive and negative λ -weighted ambiguity of an SVbN-number are formulated here. Some important, valuable theorems and corollary of SVbN-number are formulated. To show the applicability of the proposed MCDM technique, we have considered a real decision-making problem where ratings of the alternatives are with SVbN-numbers. [ABSTRACT FROM AUTHOR]

India's nearly 1-million strong band of quasi-volunteer accredited social health activists (ASHAs) have been key actors in government efforts to control COVID-19. Utilizing a nationalist rhetoric of war, ASHAs were swiftly mobilized by the government in March 2020 as 'COVID warriors' engaged in tracking illness, disseminating information, and caring for quarantined individuals. The speed at which ASHAs were mobilized into mentally and physically grueling labor was all the more stunning given these minimally paid community health workers have long been seen to have low morale given their precarious, informalized work arrangements. Building on work examining the spatialities of global health governance alongside literature on geographic contingency, this paper explores the ways that nationalist COVID-19 war rhetoric promulgated from Delhi worked as a technology of health governance to propel ASHAs into certain forms of action, yet also opened up spaces of potentiality for them to reimagine their relationship to both the state and the communities they serve. In particular, in our analysis of in-depth telephone interviews with ASHA workers in the state of Himachal Pradesh, we find that their hailing as COVID warriors inspired patriotic calls to duty and legitimized their (long over-looked) roles as critical governance actors, yet also was subject to resistance and reworking due to a combination of institutional histories, local politics, as well as happenstantial everyday encounters of ASHA work. The precarious employment of ASHAs – in terms of basic remuneration as well as the great on-the-job risks that they have faced – underscores both the fragile nature of India's health governance system as well as possible political movements for its renewal. We conclude by calling for geographers to give greater attention to community health care workers as a key window into understanding the uneven ways in which health systems are made manifest on the ground, and their ability to respond to citizens' healthcare needs – both in the COVID-19 pandemic and beyond. [ABSTRACT FROM AUTHOR]

[Display omitted] • Indian electricity demand reduced by 11 % vis-à-vis 2019 during the lockdown. • Sectoral demand reduction—73 % industrial, remaining 27 % commercial. • Pan India lights-off event—hydropower provides the bulk of the flexibility (60 %). • The plant load factor of coal dropped to a record low of 35 % during phase-1. • Power sector emissions reduced by 16 % (86 MtCO2) compared to 2019. This paper aims to understand the responsiveness of the power sector during the lockdown due to the COVID-19 pandemic beginning from March 25, 2020 and analyses its impact on the demand, operation and supply of electricity in the Indian power system. The role of the C&I load share in reducing the electricity demand of the different states in India has been examined using multi-sectoral regression analysis. The impact of the pan India lights-off event on the short-term operational flexibility response of the power system has also been analysed using high-temporal resolution data. The results indicate that there has been a reduction of nearly 70 TWh of electricity demand during the lockdown period, an 11 % reduction compared to 2019. The top three states recording the highest reduction were Maharashtra, Gujarat and Tamil Nadu at 11 TWh, 10.6 TWh and 8.4 TWh, respectively. Regression analysis revealed that out of the total drop in load demand — 73 % is owed to the industrial sector, while the remaining 27 % is to the commercial sector. This demand drop also impacted the upstream electricity supply mix where 96 % of the reduction in supply was borne by the coal generating units, recording its lowest national plant load factor at 35 % with a 16 % reduction in overall CO 2 emission compared to the same period in 2019. In conclusion, a case study of Maharashtra has been used to analyse the impact of this reduction in electricity demand on the supply mix, hourly load profile and cost of supply under the different lockdown phases. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic and the associated lockdown have globally impacted the food-insecure low-income population. A community-based initiative of an NPO - working on malnutrition issues among the below poverty line children in an urban Indian setting - towards adoption of the slum- and shelter-dwelling children, faced challenges during the pandemic in tackling the twofold uncertainties regarding supply capacity reduction and demand surge. This paper extends earlier research on this NPO's pre-COVID-time food assistance program by introducing a robust optimization-based mathematical programming model to determine the donors to engage, donor-to-beneficiary allocations, and the associated optimal donation flows while addressing these uncertainties. The issue of over-conservatism in robust optimization is addressed by parameterizing the decision-maker's uncertainty budget. We present a detailed numerical study on a test problem along with interesting observations elicited by our sensitivity analyses. ● We introduce a strategic problem of engaging donors to beneficiaries in a food-support program, motivated by an NPO's operations in India. During the COVID-19 pandemic, the NPO experienced extreme supply and demand uncertainties. ● A robust optimization model is proposed to address the decision-making problem under uncertainties. Uncertainty budgets are considered on both supply and demand values. ● Sensitivity analyses are conducted on a test problem to highlight impacts of changing the NPO's capability of engaging multiple donors, uncertainty budgets, deviations from nominal supply and demand values, etc. [ABSTRACT FROM AUTHOR]

Distortion in distribution and consumption of agricultural commodities is a result of disruptive shocks in prices and food value chains leading to a significant food loss as well as waste. We investigated the COVID-19 induced lockdown effects in India through an interrupted time series analysis coupled with a survey result of 729 consumers, 225 farmers and synthesis of the literature evidence on food loss as well as food waste. Our article complements the literature inventory on COVID-19 by estimating and tracking the effects on prices and consumer behaviour apart from discussing the implications for food loss and waste. Prices post-lockdown shot up immediately and significantly for chickpea (4.8%), mung bean (5.2%), and tomato (78.2%) corroborating the loss in highly perishable product – tomato – owing to its spiked price. We find no structural break in prices due to lockdown implying that lockdown-induced price change was not sufficient to alter the long-run price movement, and the prices of the major commodities reverted to the pre-lockdown levels. The pandemic induced lockdown did restrict the access to food markets and a majority of consumers (75.31%) experienced a price increase across COVID zones of different intensity of incidence leading to food loss along supply chain and wastage at consumers end. Consumers' livelihood affected from moderate (59.53%) to severe (3.3%) with 92 per cent reporting a change in shopping behavior. The Kruskal-Wallis test on consumption behavior change indicated a significant shift among the consumers reporting altered income, mostly in the downside, post-lockdown. Despite the relaxation for agricultural related activities during the lockdown, farmers reported disruption in disposing their winter produce barring wheat, bolstered by a record state procurement in 2020. The paper affirms that the pandemic has caused a significant price change and unprecedented panic purchase that led to the food wastage but subsided soon exhibiting the resilience in Indian agriculture. We strongly recommend for promoting the capacity and collective resilience of small-scale production systems through institutions, policies and reforms. Contract farming, farmer producer organizations, creation and functioning of social safety nets to overcome income, production and price shocks, access to digital national markets and capacity building on food waste management practices will insulate vulnerable section as well as reduce the loss of food across supply chain. [Display omitted] • Radical change in prices and consumption behaviour during COVID-19 induced lockdown. • Prices increased significantly for chickpea (4.8%), mung bean (5.2%) and tomato (78.2%). • Price rise felt by 75.31% consumers due to supply disruption has implications for food loss and waste. • As livelihood affected from moderate (59.53%) to severe (3.3%), 92% changed shopping behaviour. • Reforms with food loss and waste management practices will insulate vulnerable section. [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]

To combat the recent coronavirus disease 2019 (COVID-19), academician and clinician are in search of new approaches to predict the COVID-19 outbreak dynamic trends that may slow down or stop the pandemic. Epidemiological models like Susceptible–Infected–Recovered (SIR) and its variants are helpful to understand the dynamics trend of pandemic that may be used in decision making to optimize possible controls from the infectious disease. But these epidemiological models based on mathematical assumptions may not predict the real pandemic situation. Recently the new machine learning approaches are being used to understand the dynamic trend of COVID-19 spread. In this paper, we designed the recurrent and convolutional neural network models: vanilla LSTM, stacked LSTM, ED_LSTM, BiLSTM, CNN, and hybrid CNN+LSTM model to capture the complex trend of COVID-19 outbreak and perform the forecasting of COVID-19 daily confirmed cases of 7, 14, 21 days for India and its four most affected states (Maharashtra, Kerala, Karnataka, and Tamil Nadu). The root mean square error (RMSE) and mean absolute percentage error (MAPE) evaluation metric are computed on the testing data to demonstrate the relative performance of these models. The results show that the stacked LSTM and hybrid CNN+LSTM models perform best relative to other models. • Various variants of LSTM and CNN deep learning architectures have been designed. • Predicted COVID-19 confirmed cases for India and its four most affected states. • RMSE and MAPE are computed to compare the performance of the designed models. • Experimental results show that predicted cases are very close to actual cases. [ABSTRACT FROM AUTHOR]

Viruses are known to significantly affect global health and are the leading cause of death worldwide as evident from numerous virus epidemics/ pandemics in the present and past. Though there are several antiviral therapies for human health care, only a few of them have significant therapeutic efficacy. The high costs of synthetic antiviral drugs, the rapid emergence of resistance, and the related side effects, are important challenges faced in anti-viral therapies. Traditional Indian Medicine (TIM) has a major advantage over modern medicine with their wider therapeutic window and rare side effects. The phytochemicals from the plants have shown strong inhibition of many viral infections. In the present study, the TIM plants in the classical codified texts of Ayurveda, Unani, Siddha, Homoeopathy, Sowa Rigpa (AYUSH) and plant repository of the National Innovation Foundation –India (NIF) database was reviewed to explore plants that have sufficient scientific experimental data demonstrating efficacy against different viruses. Fifteen years of literature presenting different treatment options available for control of viral infections was reviewed. It was found that reducing inflammation, enhancing immunity, and disrupting viral infection cycle were useful strategies for combating acute viral infections. In this paper, the authors suggest an integrative strategy of incorporating TIM plants in preventive healthcare that may act as the first line of defence against acute viral infections. Development of an effective polyherbal formulation from a combination of potent TLR antagonists (anti-inflammatory), immuno-modulators, antivirals, and herbs that are rich source of micronutrients (especially Vitamin C and Zn) can act as a preventive strategy for a wide range of viral infections. [ABSTRACT FROM AUTHOR]

• Commendable of planning, coordination, execution, and resilience of power sector. • Grid security analysis in the pandemic. • The status of COVID-19, statistics of global electricity demand. • Analysis of main policies implemented by countries. Technology is advancing progressively at a very sharp rate in every phase of the commercial and economic issues, where energy plays a vital role in hi-tech enrichment. After continuous and multi directive research, human is efficient enough to put their steps on the peak of all imaginable pitches. But a human cannot fight against the environment in all instances. COVID-19, or Corona Virus, is such a type of environmental pandemic. Due to a large spread rate of COVID-19, the human society of the entire Globe is getting affected within a very small period. During its first and second wave, it collapses maximum countries health, economic structures along with the electrical sector. Many countries have enforced the 'lockdown' to their citizen for minimizing the community spread rate, which directly affects the energy sector. Standing in this scenario, this study focuses on the significant effect of COVID-19 on the energy sector of the Globe, especially in India. This paper also demonstrates that how several countries are trying to secure their power sector in this pandemic situation. [ABSTRACT FROM AUTHOR]

This paper compares and contrasts the spread and impact of COVID-19 in the three countries most heavily impacted by the pandemic: the United States (US), India and Brazil. All three of these countries have a federal structure, in which the individual states have largely determined the response to the pandemic. Thus, we perform an extensive analysis of the individual states of these three countries to determine patterns of similarity within each. First, we analyse structural similarity and anomalies in the trajectories of cases and deaths as multivariate time series. Next, we study the lengths of the different waves of the virus outbreaks across the three countries and their states. Finally, we investigate suitable time offsets between cases and deaths as a function of the distinct outbreak waves. In all these analyses, we consistently reveal more characteristically distinct behaviour between US and Indian states, while Brazilian states exhibit less structure in their wave behaviour and changing progression between cases and deaths. • We compare and contrast the natural history of COVID-19 in the US, India and Brazil. • Case, death and mortality rate trajectories are analysed on a state-by-state basis. • We quantify heterogeneity and identify anomalous states therein within each country. • Wave behaviours are explored and clustered across the three countries states. • New mathematical methods quantify the lag in the progression from cases and deaths. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic presents both a challenge and an opportunity to the Indian shrimp sector. With revitalizing the institutional arrangements and redirecting the focus, the Indian shrimp industry can flourish just by adapting to the needs of the local demand, even when the export prospects are uncertain. This paper takes a historical perspective of Indian shrimp farming and exports and suggests a domestic alternative/supplementary market for Indian farmed shrimp, resulting from COVID-19. • COVID -19 lockdowns adversely impacted the shrimp exports from India. • India stares at a huge loss in shrimp exports in both quantitative and value terms. • The health emergency threw the food and agricultural markets in Inda, out of gear. • Institutional support, organizational structural changes and innovative marketing are keys to domestic market development. • The crisis provides an opportunity to build the domestic market for shrimp in India [ABSTRACT FROM AUTHOR]

• Ambient noise levels in seven Indian cities is analyzed for lockdown period. • Noise scenario during the lock down and pre-lockdown period is presented. • A pronounced reduction in ambient noise levels was observed. • Strategy for noise control in residential and silence zone sites is suggested. The paper analyzed the impact of lockdown on the ambient noise levels in the seventy sites in the seven major cities of India and ascertained the noise scenario in lockdown period, and on the Janta Curfew day in comparison to the pre-lock down period and year 2019 annual average values. It was observed that the majority of the noise monitoring sites exhibited a decrement in ambient day and night equivalent noise levels on the national Janta Curfew day and Lockdown period as compared with the normal working days attributed to the restricted social, economical, industrial, urbanization activity and reduced human mobility. A mixed pattern was observed at a few sites, wherein the ambient day and night equivalent noise levels during Janta curfew day and Lockdown period had been reported to be higher than that on the normal working days. The study depicts the noise scenario during the lockdown and pre-lockdown period for seventy sites in India and shall be instrumental in analyzing the consequences and implications of imposing lockdowns in future on the environmental noise pollution in Indian cities. [ABSTRACT FROM AUTHOR]

• The likelihood of spousal violence is higher among families who belonged to the poorest living standard. • The prevalence of IPV is higher among those women whose husbands are currently unemployed due to the COVID-19 lockdown. • The women whose husbands have a loan were at more risk for experiencing IPV. • Partner's daily liquor consumption nature is also associated with IPV. Worldwide the incidents of intimate partner violence (IPV) have increased due to lockdowns related to the COVID-19 pandemic. This paper aims to identify the association between IPV and different socio-economic factors of women & their most recent partner during the COVID-19 pandemic in returnee migrant worker families in Balurghat Block (area 363.9 sq. km), Dakshin Dinajpur district, West Bengal, India. A total of 159 ever-married women were included in this present study, whose husbands were engaged as workers elsewhere at least two years before the lockdown. The result of the multinomial logistic regression model revealed that, after controlling for other variables, the women who had the poorest wealth background were 37% more likely (RRR: 1.37; 95% CI [1.18, 1.47]) to experience IPV almost every day in a week than those who had a middle wealth background. Conversely, the women who had the poorest wealth background were 37% (95% CI [0.57, 0.82]) less likely to experience IPV for three to four days in a week. Furthermore, the women whose partners were currently unemployed were 21% more likely (RRR: 1.21; 95% CI [1.16, 1.36]) to experience IPV almost every day in a week than those whose husbands were currently employed. The women whose husband's had a loan were 26% more likely (RRR: 1.26; 95% CI [1.25, 1.33]) to experience IPV for three to four days in a week than those whose husbands did not have any loans. The likelihood to experience IPV almost every day in a week is higher among those women whose husbands attain weekly (31%) loan instalment pattern and consume alcohol daily (31%). Interventions are needed at the grassroots level and some economic planning is required at an urgent basis. [ABSTRACT FROM AUTHOR]

This paper presents a model based on mediative fuzzy logic in this COVID-19 pandemic. COVID-19 (novel coronavirus respiratory disease) has become a pandemic now and the whole world has been affected by this disease. Different methodologies and many prediction techniques based on various models have been developed so far. In the present article, we have developed a mediative fuzzy correlation technique based on the parameters for COVID-19 patients from different parts of India. The proposed mediative fuzzy correlation technique provides the relation between the increments of COVID-19 positive patients in terms of the passage of increment with respect to time. The peaks of infected cases in connection with the other condition are estimated from the available data. The mediative fuzzy logic mathematical model can be utilized to find a good fit or a contradictory model for any pandemic model. The proposed approach to the prediction in COVID-19 based on mediative fuzzy logic has produced promising results for the continuous contradictory prediction in India. [ABSTRACT FROM AUTHOR]

A hidden cost of the COVID-19 pandemic is the stigma associated with the disease for those infected and groups that are considered as more likely to be infected. This paper examines whether the provision of accurate and focused information about COVID-19 from a reliable source can reduce stigmatization. We carry out a randomized field experiment in the state of Uttar Pradesh, India, in which we provide an information brief about COVID-19 by phone to a random subsample of participants to address stigma and misconceptions. We find that the information brief decreases stigmatization of COVID-19 patients and certain groups such as religious minorities, lower-caste groups, and frontline workers (healthcare, police), and reduces the belief that infection cases are more prevalent among certain marginalized social and economic groups (Muslims, low caste, rural-poor population). We provide suggestive evidence that improved knowledge about the prevention and transmission of COVID-19 and reduced stress about the disease are important channels for the reduction in stigmatization. • We carried out a randomized field experiment in the state of Uttar Pradesh, India. • A random subsample of participants received an information brief about COVID-19. • Accurate and focused information about COVID-19 reduces stigmatization. • The information also reduces biased beliefs about outgroups. • Improved knowledge and reduced stress are important channels for the effects. [ABSTRACT FROM AUTHOR]

• Impact of living environment deprivation on COVID-19 hotspots formation is assessed. • GWPCA based improved Index of Multiple Deprivation is devised. • The COVID-19 hotspots and IMD hots spots showing high correspondence. • Northern parts of Kolkata is characterized with COVID-19 containment zone hotspots. • The ZINBR model is best fitted for modelling relationship between living environment condition and COVID-19 hotspots. The emergence of COVID-19 has brought a serious global public health threats especially for most of the cities across the world even in India more than 50 % of the total cases were reported from large ten cities. Kolkata Megacity became one of the major COVID-19 hotspot cities in India. Living environment deprivation is one of the significant risk factor of infectious diseases transmissions like COVID-19. The paper aims to examine the impact of living environment deprivation on COVID-19 hotspot in Kolkata megacity. COVID-19 hotspot maps were prepared using Getis-Ord-Gi* statistic and index of multiple deprivations (IMD) across the wards were assessed using Geographically Weighted Principal Component Analysis (GWPCA).Five count data regression models such as Poisson regression (PR), negative binomial regression (NBR), hurdle regression (HR), zero-inflated Poisson regression (ZIPR), and zero-inflated negative binomial regression (ZINBR) were used to understand the impact of living environment deprivation on COVID-19 hotspot in Kolkata megacity. The findings of the study revealed that living environment deprivation was an important determinant of spatial clustering of COVID-19 hotspots in Kolkata megacity and zero-inflated negative binomial regression (ZINBR) better explains this relationship with highest variations (adj. R2: 71.3 %) and lowest BIC and AIC as compared to the others. [ABSTRACT FROM AUTHOR]