Covid-19 has caused significant distress around the globe Apart from the evident physical symptoms in infected cases, it has caused serious damage to public mental health India, like other countries, implemented a nationwide lockdown to contain and curb the transmission of the virus The current research is an attempt to explore psychological distress among people residing in India during the lockdown Four hundred and three participants were asked to complete a questionnaire with questions around symptoms of depression, anxiety, stress, and family affluence The results indicated that people who do not have enough supplies to sustain the lockdown were most affected, and family affluence was found to be negatively correlated with stress, anxiety, and depression Among different professions, students and healthcare professionals were found to experience stress, anxiety, and depression more than others Despite the current situation, stress, anxiety, and depression were found to be in normal ranges for mental health professionals highlighting their capabilities to remain normal in times of distress Policymakers and other authorities may take the assistance of mental health professionals to help overcome psychological issues related to Covid-19

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Depression, Anxiety and Stress Among Indians in Times of Covid-19 Lockdown.

We have entered an era of a pandemic that has shaken the world with major impact to medical systems, economics and agriculture. Prominent computational and mathematical models have been unreliable due to the complexity of the spread of infections. Moreover, lack of data collection and reporting makes any such modelling attempts unreliable. Hence we need to re-look at the situation with the latest data sources and most comprehensive forecasting models. Deep learning models such as recurrent neural networks are well suited for modelling temporal sequences. In this paper, prominent recurrent neural networks, in particular \textit{long short term memory} (LSTMs) networks, bidirectional LSTM, and encoder-decoder LSTM models for multi-step (short-term) forecasting the spread of COVID-infections among selected states in India. We select states with COVID-19 hotpots in terms of the rate of infections and compare with states where infections have been contained or reached their peak and provide two months ahead forecast that shows that cases will slowly decline. Our results show that long-term forecasts are promising which motivates the application of the method in other countries or areas. We note that although we made some progress in forecasting, the challenges in modelling remain due to data and difficulty in capturing factors such as population density, travel logistics, and social aspects such culture and lifestyle.

Deep learning via LSTM models for COVID-19 infection forecasting in India

Purpose




The purpose of this paper is to identify the role of cognitive styles (CgStys) and self-efficacy (SEff) in the formation of social entrepreneurial intentions (SEIs) among the students of a premier multi-campus technical university in India using the theory of planned behaviour as the research framework.




Design/methodology/approach




A 54-item questionnaire was responded by 550 students. The data were collected by employing a systematic random sampling method. In the total sample of the respondents, 67 per cent (n=368) were male and 33 per cent (n=182) were female and the average age of the respondents was 20 years. Structural equation modelling has been used for data analysis.




Findings




The results of the study support that the relationship between antecedents (CgStys and SEff) and SEIs was mediated by the attitude towards becoming a social entrepreneur, subjective norms and perceived behavioural control. Findings of this research study also suggest that students with high level of SEff are more inclined towards social entrepreneurial activities.




Research limitations/implications




The study was confined to the students from a technical university, and it may not give the generalized findings for students from the non-technical stream.




Practical implications




The finding of this research study will facilitate policy makers and educators for promoting social entrepreneurial activities at the university level. Based on the results and findings of the study, the educators may improve upon the support system to help and motivate students to opt social entrepreneurship as their career choice.




Originality/value




This is one of its kinds of research conducted in the Indian context. Findings of this research will be helpful in predicting how the intention process of Indian students is affected by their CgStys and SEff.

Predictors of social entrepreneurial intention: an empirical study

During the current century, each major coronavirus outbreak has triggered a quick and immediate surge of academic publications on its respective topic. The spike in research publications following the 2019 Novel Coronavirus (Covid-19) outbreak, however, has been like no other. The global crisis caused by the Covid-19 pandemic has mobilised scientific efforts at an unprecedented scale. In less than 5 months, more than 12,000 research items and in less than seven months, more than 30,000 items were indexed, while it is projected that the number could exceed 80,000 by the end of 2020, should the current trend continues. With the health crisis affecting all aspects of life, research on Covid-19 seems to have become a focal point of interest across many academic disciplines. Here, scientometric aspects of the Covid-19 literature are analysed and contrasted with those of the two previous major coronavirus diseases, i.e., Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS). The focus is on the co-occurrence of key-terms, bibliographic coupling and citation relations of journals and collaborations between countries. Interesting recurring patterns across all three literatures were discovered. All three outbreaks have commonly generated three distinct cohorts of studies: (i) studies linked to public health response and epidemic control, (ii) studies on chemical constitution of the virus; and (iii) studies related to treatment, vaccine and clinical care. While studies affiliated with category (i) seem to have been relatively earliest to emerge, they have overall received relatively smaller number of citations compared to publications the two other categories. Covid-19 studies seem to have been disseminated across a broader variety of journals and across a more diverse range of subject areas. Clear links are observed between the geographical origins of each outbreak as well as the local geographical severity of each outbreak and the magnitude of research originated from regions. Covid-19 studies also display the involvement of authors from a broader variety of countries compared to SARS and MERS. Considering the speed at which the Covid-19-related literature is accumulating, an interesting dimension that warrants further exploration could be to assess if the quality and rigour of these publications have been affected.

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Covid-19 pandemic and the unprecedented mobilisation of scholarly efforts prompted by a health crisis: Scientometric comparisons across SARS, MERS and 2019-nCoV literature.

India was one of the leading countries to implement the initial lockdown to contain the COVID-19 pandemic, but still, the lockdown failed and within a few months, India joined the list of countries most affected by the coronavirus epidemic. Why did this transpire? What were the reasons abaft this? Where did the Indian government miss? This manuscript endeavors to study the lacunae in the lockdown plans of the Indian Government and highlights the mistakes committed by the Government which caused the lockdown in India to fail and further exposed the domestic migrant laborers to unbearable difficulties. The manuscript argues that the fundamental and economic rights bestowed upon the domestic migrant workers and other laborers under labor laws and the Indian constitution were breached extensively during the lockdown and that the state’s policies during the lockdown worsened the condition of the domestic migrant workers.

Migrant Workers and Human Rights: A Critical Study on India's COVID-19 Lockdown Policy

The notion of the “migrant” in the current capitalist times and the world of migrants in it are explored The source to destination streams of migrant labour is outlined, and it is then argued that reverse migration will perhaps usher in the greatest crisis in the rural landscape of India, for which we are not yet prepared © 2020 Economic and Political Weekly All rights reserved

Migration and reverse migration in the age of covid-19

The 97th amendment: Some concerns

Contested spaces, democratic rights people and forests today

Addressing the issue of agrarian crisis in India in general, the article explores the particularities of the distress emphasising some of the crucial aspects of burden of indebtedness that often leads to farmersâ suicide. Following a narrative approach, it analyses the relationship between some of the shocking figures related to agriculture at large and some of the astounding field observations related to rising input prices, uncompetitive minimum support prices (MSPs), faulty cropping pattern, nature of indebtedness and lack of sufficient state support for the farmers.

Contested Spaces and Resultant Conflicts: Some Aspects of the Agrarian Crisis in India

Integrated Management of Acute Malnutrition or POSHAN Phase 2.0 was implemented in 20 districts of Rajasthan in 2018. After 12 weeks of outpatient therapeutic care of children with Severe Acute Mal...

Ajay Vishwas Dandekar

Papers

Migration and reverse migration in the age of covid-19

The 97th amendment: Some concerns

Contested spaces, democratic rights people and forests today

Contested Spaces and Resultant Conflicts: Some Aspects of the Agrarian Crisis in India

A Sociocultural Perspective on Malnutrition in Children: Evidence from POSHAN Programme, Rajasthan: