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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]

India's indigenous communities represent 8% of the total population and 25% of them are listed as the most impoverished (Government of India, 2011). The COVID-19 pandemic has already infected over 70 000 indigenous people with 2000 deaths (WHO, 2020). A quick search of the word "COVID-19" in Web of Science database for 2020 has yielded 41 798 papers and when the phrase "COVID-19 indigenous people" was used, it yielded only 38 papers. Likewise in March 2020, the Chhattisgarh state government reported only six COVID-19 cases (Raju, 2020). [Extracted from the article]

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 economic crisis triggered by the COVID‐19 urgently required active policy interventions to enhance the revival strategies of the world economy. This paper examines the effectiveness of policy intervention of the State Government of Kerala in India in mitigating the risks caused by the pandemic. The policy effectiveness is evaluated by analyzing the data collected from a sample of 300 beneficiaries with the help of descriptive statistics, ordered probit (OP) model, and semi nonparametric extended OP (SNEOP) model. Our results are assertive with the fact that state policies are effective in reviving the crisis‐hit economy as they have primarily helped low‐income groups and other marginalized communities. The majority of BPL families, self‐help group members, and social security beneficiaries rated government policies as highly or fairly effective. Though the policies are found to be highly effective among those who have suffered income loss, the study does not find sufficient evidence to believe that the government interventions are effective in helping those who have lost their jobs. The level of effectiveness is inversely related to age, education, and family size. Our results suggest that an extensive fiscal package is required to help people recover from the crisis. [ABSTRACT FROM AUTHOR]

This study examines whether investing in R&D reduces the impact of exogenous shocks like the COVID‐19 on stock market performance and accounting performance of manufacturing firms in India. For the sample of listed manufacturing firms, the paper finds that the firms engaged in R&D activities had lower negative cumulative abnormal return than those firms that did not invest in R&D in the pre‐pandemic period using multiple event windows. The result suggests that R&D investments can lower value erosion for the shareholders during a severe crisis period. Further, using a difference‐in‐difference fixed effects model, the study finds that manufacturing firms engaged in R&D activities in the pre‐pandemic period exhibited higher return on sales and growth of total income during the pandemic quarter vis‐à‐vis the non‐R&D firms. The favorable accounting performance indicates the possibility of firm‐level R&D being associated with the firm's ability to adjust its functioning during a crisis, thereby reducing the effect of the crisis. Finally, the study documents that government intervention to reduce the spread of the virus had a differential impact on firms based on their industry of operation. The findings have implications for investors, corporate managers, and policymakers in India. [ABSTRACT FROM AUTHOR]

This article traces what I term the affective activism of volunteers, civil society organizations, and lorry drivers engaged in relief work to assist stranded migrant workers wanting to travel home during the first wave of the coronavirus pandemic and national lockdown in India. I define affective activism as an archival practice that is driven by relief figures' affects of fear, anger, and aspirations—in this instance, toward their legal and administrative accountability to funders. Drawing on my ethnographic work in a relief network and using independent interviews I conducted, this article critically compares two modalities of digital archiving conducted by relief figures: collecting migrant workers' Aadhaar—unique biometric number identifiers issued to Indians—and digitally archiving their relief efforts through videos, voice‐notes, and WhatsApp Messenger screenshots. I argue that relief figures expressed their anxieties in the form of talismanic beliefs that records of Aadhaar and their material infrastructure would keep safe the migrant workers they were trying to help. Alternately, and sometimes, concomitantly, they performatively deployed Whatsapp artifacts to support their accountability in the face of bureaucratic and political specters. Both forms highlight the desire of relief figures to exceed paper forms and state practices in their archival impulses. [affective activism, India relief work, Covid‐19 lockdown, migrant workers, digital archiving, and visual politics] [ABSTRACT FROM AUTHOR]

Prior research in judgment and decision making (JDM) has investigated the effect of problem framing on human preferences. Furthermore, research in JDM documented the absence of such reversal of preferences when making decisions from experience. However, little is known about the effect of context on preferences under the combined influence of problem framing and problem format. Also, little is known about how cognitive models would account for human choices in different problem frames and types (general/specific) in the experience format. One of the primary objectives of this research is to investigate the presence of preference reversals under the influence of problem framing (gain/loss), problem format (experience/description), and problem type (general/specific). Another objective of this research is to develop cognitive models to account for human choices across different problem frames and types in the experience format. A total of 320 participants from India were randomly assigned to one of eight between‐subjects conditions that differed in problem frame, format, and type. Results revealed preference reversals in the description condition; however, they were absent in the experience condition. Moreover, preference reversals were less pronounced in the general problem framing compared to the specific problem framing. Furthermore, specific problems influenced risk‐seeking behavior among participants. We developed cognitive and heuristics models using instance‐based learning theory and natural mean heuristic. Results reveal models' dependency on recent and frequent observations during information sampling. These experience‐based cognitive models could help build artificial intelligence models with fewer preference reversals. This paper focuses on investigating the presence of preference reversals under the influence of problem framing (gain/loss), problem format (experience/description), and problem type (general/specific). Furthermore, Uttrani et al. develop cognitive models using instance‐based learning theory and natural mean heuristic to account for human choices across different problem frames and types in the experience format. [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]

The COVID‐19 pandemic has seen a sudden increase in the demand for healthcare organizations to improve their utilization of digital platforms to supplement the reach of conventional healthcare services. In the wake of this crisis, dentistry is on the cusp of a major overhaul, promoting preventive practices and a rapid shift to teledentistry platforms. A random push to adapt to teledentistry platforms may cause the straining of available resources and manpower, especially in sectors involved in the care of vulnerable population groups like children, individuals with special needs and those in the low socioeconomic strata. It is thus advisable to make this transition systematically, beginning with an analysis of feasibility, done periodically, to maximize efficiency. Described in this article is a system to facilitate this transition by utilizing a matrix model, laying foundation for assessment of feasibility based on target population characteristics. It calls for the improvement of population characteristics to reduce strain on the healthcare sector using key indicators of the model, paired against potential barriers, and is described using a case study from the field. Key points: • The concept model described in this paper lays foundation for assessment of the feasibility for tele‐dentistry platforms based on population characteristics. • Key indicators for assessing feasibility and suggestions for improvement have been highlighted against the barriers in each component of the model categories. • Applicability of this model has been described using a case study from an integrated platform for children and individuals with special health care needs, in South India. [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]

The COVID‐19 pandemic has brought renewed attention to the lack of urban planning and its public health implications in developing countries. Slum communities face the dual challenges of chronically poor residential environments and the acute effects of a pandemic and the preventive measures that follow. In this paper, I assess the effectiveness and implications of social distancing, frequent handwashing, and lockdown in the context of slums in Indian cities, where overcrowding, lack of access to water and sanitation, and dependence on daily wages for sustenance and livelihood are common. Using data from multiple sources, I demonstrate that not only will these measures be hard to achieve in slums in the short term due to specific characteristics of these habitats, but they will bring new challenges in the long term due to disproportionate impacts on the urban poor. Lessons learned from this pandemic will require us to rethink public health responses and urban planning practices that could better prepare our cities for future pandemics. [ABSTRACT FROM AUTHOR]