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This paper analyses findings of the 'PROWELLMIGRANTS'2 project, which qualitatively investigated COVID‐19 impacts on migrants' well‐being and mental health in Kerala, India. It draws on a novel conceptual framework that combines assemblage‐thinking with theories of social contracts in disasters. The paper first explores how past development processes and contemporary migration policies in Kerala, and India more widely, generated conditions of vulnerability for migrant workers in Kerala prior to the pandemic. Next it shows that Government of Kerala interventions, in some cases supported by the central Government of India, temporarily addressed these vulnerabilities during the pandemic. In acknowledging the helpful response of the Kerala government, we problematise its stance on migrant workers during 'normal' times and speculate that permanently addressing these conditions of vulnerability would be a more logical approach. We acknowledge this involves overcoming many wider barriers. Thus, the paper also contains national‐level policy implications. [ABSTRACT FROM AUTHOR]

The first case of COVID‐19 in India detected on January 30, 2020, after its emergence in Wuhan, China, in December 2019. The lockdown was imposed as anemergency measure by the Indian government to prevent the spread of COVID‐19 but gradually eased out due to its vast economic consequences. Just 15 days after the relaxation of lockdown restrictions, Delhi became India's worst city in terms of COVID‐19 cases. In this paper, we propose a variable‐order fractional SIR (susceptible, infected, removed) model at state‐level scale. We introduce a algorithm that uses the differential evolution algorithm in combination with Adam–Bashforth–Moulton method to learn the parameters in a system of variable‐order fractional SIR model. The model can predict the confirm COVID‐19 cases in India considering the effects of nationwide lockdown and the possible estimate of the number of infliction inactive cases after the removal of lockdown on June 1, 2020. A new parameter p is introduced in the classical SIR model representing the fraction of infected people that get tested and are thereby quarantined. The COVID‐19 trajectory in Delhi, as per our model, predicts the slowing down of the spread between January and February 2021, touching a peak of around 5 lakh confirmed cases. [ABSTRACT FROM AUTHOR]

The outbreak of the SARS CoV2 virus, commonly referred to as the COVID‐19 pandemic, has impacted the social, economic, political, and cultural lives of citizens around the world. The sudden outbreak of the pandemic has exposed the legal preparedness, or lack thereof, of governments to reduce and contain its drastic impact. Strong legislative measures play a crucial role in any epidemic or pandemic situation. In this situation, the Indian Government has requested all state governments to invoke the Epidemic Disease Act (EDA) of 1897 to address the COVID‐19 emergency. The Central Government has also used the powers provided in the Disaster Management Act (DMA) of 2005. As the country is facing its first major health emergency since independence, the existing legislative measures to deal with a COVID‐19 like situation are lacking and require certain amendments to address such situations in the future. This paper aims to present the current constitutional and legislative response to health emergencies in India and attempts to identify gray areas in the statutory provisions. Based on the analysis, this paper suggests several recommendations for amending current legislation and suggests the promulgation of comprehensive public health law. This paper is largely based on primary sources such as the EDA and the DMA, regulations, guidelines, rules issued by the public authorities and court cases related to health and health emergencies along with secondary resources such as newspaper articles and published papers. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic presents a threat to physical and psychosocial health of individuals. In lieu of the subsequent lockdown and containment measures, helpline counselling becomes a viable method of accessing psychosocial services during the pandemic. The present paper describes experiences of counsellors working with a special COVID‐19 counselling helpline initiated by iCALL, a national‐level technology‐assisted counselling service of the Tata Institute of Social Sciences, India, which aims to address the psychosocial impact of the pandemic and the lockdown. The paper is based on two focus group interviews held with 11 counsellors during the initial two months of the helpline's functioning. Findings of the study highlight the diverse profile of the callers, with individuals belonging to different strata of society and to marginalised communities. The nature of concerns presented by the callers were often a mix of psychological, relational and practical issues. The resultant distress emanated from an interplay of these factors with the relational contexts, their social locations and social structures the individuals were embedded in. This highlighted the need for conceptualising and responding from a psychosocial lens, whereby interventions involved traditional counselling approaches and strategies for addressing determinants of distress by connecting callers to required ground‐level resources. Counsellors' engagement with this process impacted their professional and personal selves, necessitating the need for structured and continuous training, supervision and support. At a larger level, the counsellors' narratives asserted the need for adopting a psychosocial paradigm for conceptualising and addressing mental health concerns in India. [ABSTRACT FROM AUTHOR]

The COVID‐19 crisis has translated into an unprecedented humanitarian crisis for the poor and marginalized groups in society. The countrywide lockdowns, quarantine measures, and mobility restrictions across 200 countries of the world have resulted in a host of negative manifestations for women. There have been unprecedented losses in the informal economy, which is dominated by women. Some scholars also contend that the pandemic will translate into heightened burden of unpaid domestic work, loss of economic autonomy and disruption to maternal health services. Despite these factors a gendered perspective is absent in the policy response to this crisis. It is against this background that the present paper employed a feminist intersectionality lens to conduct participatory field based research on the lived experiences of women in informal employment in Indian Punjab during the COVID‐19 crisis. The research unearthed the specific pathways through which existing socio‐economic inequities rooted in caste, class and occupational entities magnify the vulnerabilities experienced by women during such a health crisis. The research offers a contextualized framework for understanding the gendered impacts of the crisis. It also highlights the urgency of taking account of gender specific constraints during the health crisis so as to institute robust, effective and equitable policy interventions. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the impact of COVID‐19 on the volatility of stock prices in India with the help of a generalized autoregressive conditional heteroscedasticity model. Daily closing prices of stock indices, Nifty and Sensex from September 3, 2019 to July 10, 2020 has been used for the analysis. Further, the study has been attempted to make a comparison of stock price return in pre‐COVID‐19 and during COVID‐19 situation. Findings reveal that the stock market in India has experienced volatility during the pandemic period. While comparing the result during COVID period with that of the pre‐COVID, we found that the return on the indices is higher in the pre‐COVID‐19 period than during COVID‐19. [ABSTRACT FROM AUTHOR]

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]

With growing interest in the lives of individuals and communities during the COVID‐19 pandemic, there is consensus among scholars, academicians, and policy makers that the pandemic has had unequal impacts on different sections of the society. The dominant idea that “we are in this together” needs to be critically unpacked to understand the differential impact of the same pandemic on people with varied vulnerabilities. The concept of “intersectional vulnerability” has been key to understanding the unequal distribution of the pandemic risk. Using a gendered intersectional lens, this paper aims to understand the lived experiences of migrant women workers during the pandemic and their narratives of gendered inequality. Through a narrative study in Delhi and the National Capital Region (NCR), India, from May to October 2020, this study brings out stories of precarity faced by five migrant women while battling the social, psychological, and economic effects of the pandemic. Loss of livelihood, home, savings, and prospects of a better future shape the narratives of these women. The pandemic exacerbated the already precarious positions of these women by creating a situation where—(a) patriarchal structures were further reinforced, and (b) losing gender solidarity and companionship through lockdown and social distancing. [ABSTRACT FROM AUTHOR]