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Copyright of Disasters is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Regional Science Policy & Practice is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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 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]

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]

During the post‐COVID period, demand augmenting policies were needed and have been exercised by the Government of India to prevent the Indian economy from falling into recession. However, these demand augmenting policies seem to be inflationary as in the recent past high inflation has been observed in India. Thus, optimum combination of monetary and fiscal policies is needed to simultaneously achieve the objectives of demand growth and price stability. This paper proposes combinations of the two policies based on the results of a sign‐restricted vector autoregressive (VAR) modelling framework. The experimentation was performed using sign restrictions on macroeconomic target variables viz. demand growth and inflation rate while leaving the policy variables free to suggest proposed stances to achieve desired objectives. On the basis of the empirical findings, the proposed stances of monetary and fiscal authorities were then compared with the actual stances and requisite correction in the policy behaviours has been suggested in terms of improvements to the magnitude and frequency of contraction and expansion. [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]

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]

India has been hard‐hit by the Covid‐19 pandemic. The virus has exacted a heavy toll in terms of lives lost and deteriorating health outcomes. The economic consequences of the pandemic have been similarly grim. In this paper we attempt an initial, interim, assessment of the impacts of the crisis on poverty. We review the growing literature that considers emerging poverty impacts, noting that there remain significant knowledge gaps due to limited evidence on current welfare outcomes. We analyze pre‐Covid survey data to examine the incidence of chronic poverty and downward mobility during a period of rapid economic growth and declining poverty. A profile of poverty during such a period might offer a plausible, partial, window on population groups currently at risk. We suggest that, notwithstanding the severe initial impacts of the crisis on poverty, there are grounds for expecting further consequences going forward. As the virus has spread out of the relatively affluent cities, and as economic stagnation persists, rural areas, with historically higher rates of chronic poverty and vulnerability, may see particularly sharp increases in poverty. While recent vaccination developments offer some grounds for optimism, there remains an urgent need to identify, implement and amplify effective policy alleviation measures. [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 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]

Infectious COVID‐19 transformed the world overnight, freezing all physical activities and forcing the majority toward online mode. Technology came up as a savior to alleviate the consequences of COVID‐19 on the economy, causing a rapid transformation in consumers' behavior, and an overall jump in the sale of e‐commerce could be witnessed globally. This paper aims to explore the factors that caused the transformation in consumers' behavioral attitude (AT) and intention toward online shopping (BITOS). The study integrates the TPB and UTAUT models while adding two additional variables, namely, perceived risks (PR) and perceived benefits (PB), to predict consumers' BITOS. A survey was conducted to collect a sample of 402 consumers Aligarh city, and the National Capital Region of India using the mall intercept sampling method. The data were analysed to establish the measurement model and test the hypothesized structural model with the Smart‐PLS software. The study's findings confirmed that PB, subjective social norms, perceived ease of use, and perceived usefulness positively affect AT and BITOS, whereas PR does not influence AT and BITOS. The study also indicated that AT has a positive effect on BITOS. Concerning AT, it does not mediate the relationship between PR and BITOS; however, it mediates between the direct link PB and BITOS, making it stronger. The study's findings help the E‐commerce industry understand consumers' transformed attitudes/intentions and restructure their strategies to strengthen their online business further. Despite its regional and design limitations, it contributes significantly to the current research on online shopping behavior in India during COVID‐19. [ABSTRACT FROM AUTHOR]

COVID‐19 pandemic brought novel challenges for society and businesses. Along with psychological impact on humans, COVID‐19 led to significant changes in business processes. Managerial competencies, which positively impact performance of both the employees and businesses, are influenced by changing social and business context. In this milieu, there is a call for research to understand the impact of recent changes on managerial competencies to make them future‐ready. Further, in light of prior studies that present opposing findings, a related question worth exploring is—does the importance of managerial competencies differ across countries? By answering these questions, key competencies, that can boost both employee performance and business profitability, can be assessed and nurtured for a positive global impact. This paper presents theoretical background, methodology, findings and implications from a two‐part study that was conducted to answer above questions. Phase 1, which included literature review, analysis of US Government's O*NET database and expert validation, yielded a unique 9 × 51 Managerial Competencies Framework. Using quantitative methodology, that involved primary survey of Indian experts and hypothesis testing on matching data‐sets, Phase 2 of this cross‐country study reports a broad agreement amongst US and Indian experts on the importance of key managerial competencies. Study offers many theoretical and practical implications, along with directions for future research. [ABSTRACT FROM AUTHOR]

Using panel data for the period between April 2019 and September 2021, this paper investigates how the Covid‐19 pandemic‐induced lockdowns imposed differential labor market shocks on different social identity groups. We find that while all caste groups lost jobs in the first 2 months of the lockdown, the job losses for lowest‐ranked caste are greater by factor of more than two. The data shows that caste gaps in employment outcomes remain sizeable, even when we compare groups within the same industry, occupations, or those who have completed secondary schooling. These findings suggest that caste is not merely a proxy for class, and identity‐based policies might be essential to overcoming these disparities. [ABSTRACT FROM AUTHOR]

This paper examines the employment effects of an emergency assistance package by the Indian government, the Garib Kalyan Rozgar Abhiyaan that had the sole objective of providing employment to returning migrants. It was targeted to 116 districts that had seen returning migrants in excess of 25,000, was limited in duration to 4 months, and was directed at top‐up funding to public works and 25 other target sectors in rural areas. Using a sharp RD approach, we find that the intervention had substantive impacts on employment and in reducing rationing in public works and that it did so in a cost‐effective manner. In contrast to the widespread impression of a slow‐moving bureaucracy, these results point to an administrative machinery that was able to successfully implement this project within a relatively short period of time. [ABSTRACT FROM AUTHOR]

This paper contributes to the evidence base on the impact of the COVID‐19 on child marriage prevalence and on the protective potential of girl‐centred, community‐level interventions in buffering communities against aggregate shocks. Drawing on data from repeat cross‐sectional surveys completed with adolescent girls aged 12–19 in 609 villages in four states in India as a part of the More Than Brides Alliance impact evaluation, we examine whether the intervention appears to have impacted child marriage prevalence over its 5‐year implementation period, whether the onset of COVID‐19 affected ongoing trends in child marriage prevalence, and whether the intervention appeared to have buffered against increased child marriage risk resulting from the pandemic. Results show that significant differences emerged between treatment and control villages between midline and endline—and these differences were larger following the onset of COVID‐19—suggesting both that the treatment was successful in preventing child marriage and that the intervention had a protective effect. Results suggest that girl‐centred, community‐based interventions can help communities to weather environmental shocks and protect girls against potential increased child marriage risk during times of acute crisis. [ABSTRACT FROM AUTHOR]

In India, 15 nutrition interventions are delivered and financed through the National Health Mission (NHM). Programmatic know-how, however, on tracking nutrition budgets in health sector plans is limited. Following the four phases of the budget cycle-planning, allocations, disbursements and expenditure, this paper presents a new method developed by the authors to track nutrition budgets within health sector plans. Using the example of the Anemia Mukt Bharat (AMB) or Anemia Free India strategy, it reports preliminary findings on the application of the first two phases of the method, that is, to track and act for improved planning and allocations, covering 12 states. The paper lists out the budget heads, cost norms and developed tools to plan adequately. Supportive action was undertaken through sharing trends and trainings for AMB's budgeting to create opportunities for improvements. It was observed that the AMB budget increased over 3 years despite the COVID situation. It increased from INR 6184 million in FY 2019-2020 to INR 6293 million, a 2% increase in FY 2020-2021, and to INR 7433 million, an 18% increase in FY 2021-2022. The difference in allocations and planned budgets were low (16%, 4% and 11%, respectively) while the difference in required budgets and planned budgets were significant but reduced consistently (41%, 31% and 22%, respectively). The paper concludes that the methods adopted for tracking and acting for improved nutrition budgets helped in informing national and state governments regarding yearly trends. Such methods can be effective and be developed for other nutrition interventions., (© 2022 The Authors. Maternal & Child Nutrition published by John Wiley & Sons Ltd.)

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]

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]

This paper explores social work students' perspectives of online fieldwork practice that emerged due to sudden disruption in field placement as a result of the outbreak of COVID‐19 in India. We have recruited and interviewed 32 Master's students from five north‐Indian universities to participate in the research. The study's findings highlight ill‐equipped agencies lacking social work components in online/virtual field placement. Also, ethical dilemmas in working virtually, disconnectedness from the field, and superficial supervision were experienced by the students. The study result implies the urgent need to develop and innovate a pedagogical approach to deal with uncertainties and crises like the COVID‐19. [ABSTRACT FROM AUTHOR]

This paper intends to ascertain the veracity of reported data on deaths and testing pertaining to the novel coronavirus in India. We use a widely used forensic audit technique called Benford's law to analyze the data, and our findings suggest anomalies in the reported numbers and the reported data for most of the states do not adhere to the Benford distribution. The implications of these findings are manifold, especially on the trajectory of policy‐making, vaccination strategy, and preparedness for future waves and new variants. We strongly argue for the need for a robust data collection and reporting mechanism, creating a central data repository, and instituting a data‐driven policy framework as key steps in the process management bulwark for managing such future pandemics and other events concerning public health. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID‐19) pandemic has decimated the lives and livelihoods of people worldwide. The impact of COVID‐19 has been especially devastating for low‐income families in rural areas of India. Soon after the nationwide lockdown was announced, food insecurity became pervasive in rural areas, as many families relied on daily wage work to fund necessities. By providing cash transfers and additional foodgrains, Indian policymakers acted swiftly to reduce the financial impact on family income and consumption. This paper investigates the factors affecting rural families' participation in the cash transfer program and the effect of government cash transfers on food insecurity. Results indicate that India's government cash transfer program decreased moderate food insecurity by 2.4% and severe food insecurity by about 0.92% [EconLit Citations: O12, I31, I32, I38]. [ABSTRACT FROM AUTHOR]

We examine how the market valuation of firms varies on account of their operational fragility that makes them vulnerable to the COVID‐19 pandemic. Using the data on plant location that uniquely identifies the vulnerability of firms to operational disruptions, we find that firms with plants located in zones susceptible to higher infections earn significantly lower returns. For firms with high operational fragility, the marginal value of financial flexibility and operating flexibility is higher. The adverse impact of the operational fragility is lower for firms affiliated with the larger business groups. The paper identifies unique channels associated with the pandemic that impact firm value. [ABSTRACT FROM AUTHOR]

Copyright of Regional Science Policy & Practice is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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]

Since the outbreak of the Covid 19 pandemic, governments across the world including India, a South‐Asian country is busy 'strategizing', 'managing' 'containing' the crisis to restrict its spread. But given the vastness and diversity of the Indian territory, one pan Indian model of is not possible and the states have been working in consonance with the centre in a matter of 'cooperative federalism' and are implementing various micro models of Covid 19 governance. This paper explores the micro models of governance strategies taken by states in India namely, Kerala located in its Southern coast and Odisha in the Eastern coast which have been experiencing disasters be it health or natural calamities. Inspite of the differences in social development indicators between both the states, they have managed to keep the death rates lower in the initial phases of the outbreak in comparison to other states. This is reflected in the strategies they took in controlling the pandemic like "preparedness" "decentralisation", "community participation". However, inspite of deploying various governance models, the gradual unlocking led to the explosion of positive cases as a result of which the challenges to deal with the pandemic still looms large. [ABSTRACT FROM AUTHOR]

Spatial hot spots of COVID‐19 infections and fatalities are observed at places exposed to high levels of air pollution across many countries. This study empirically investigates the relationship between exposure to air pollutants that is, sulfur dioxide, nitrogen dioxide, and particulate matter (SO2, NO2, and PM10) and COVID‐19 infection at the smallest administrative level (ward) of Mumbai City in India. The paper explores two hypotheses: COVID‐19 infection is associated with air pollution; the pollutants act as determinants of COVID‐19 deaths. Kriging is used to assess the spatial variations of air quality using pollution data, while information on COVID‐19 are retrieved from the database of Mumbai municipality. Annual average of PM10 in Mumbai over the past 3 years is much higher than the WHO specified standard across all wards; further, suburbs are more exposed to SO2, and NO2 pollution. Bivariate local indicator of spatial autocorrelation finds significant positive relation between pollution and COVID‐19 infected cases in certain suburban wards. Spatial Auto Regressive models suggest that COVID‐19 death in Mumbai is distinctly associated with higher exposure to NO2, population density and number of waste water drains. If specific pollutants along with other factors play considerable role in COVID‐19 infection, it has strong implications for any mitigation strategy development with an objective to curtail the spreading of the respiratory disease. These findings, first of its kind in India, could prove to be significant pointers toward disease alleviation and better urban living. Plain Language Summary: The study investigates the relationship between exposure to pollutants (local SO2, NO2, and PM10) and COVID‐19 (cases and deaths) in Mumbai. It also explains whether pollutants act as determinants of COVID‐19 deaths when other factors like population density, health infrastructure, number of slums, waste water drains and roads are controlled through spatial modelling. PM10 concentration is much above the WHO specified standard across Mumbai. Overall, people living in the suburbs of Mumbai are at a higher risk of respiratory morbidity. High exposure to specific pollutants (SO2, NO2, and PM10) and high‐presence of COVID‐19 cases are well established in certain wards in the suburban parts of the city. Further, exposure to NO2 and COVID‐19 deaths reveals strong linkages in Mumbai. Association of COVID‐19 and environmental pollution should be considered as a measure of an integrated approach in sustainable development as it has strong implications for mitigation strategies related to the novel virus. Key Points: Significant association between COVID‐19 infection with SO2, NO2, and PM10 reveals spatial hot spots in MumbaiWith increase in NO2 there is substantial increase in COVID‐19 deaths in MumbaiAir quality is an important element to address COVID‐19 management and sustainable urban development [ABSTRACT FROM AUTHOR]

The economic impacts of COVID‐19 lockdowns on poor and vulnerable households living in rural areas of developing countries are not well understood due to a lack of detailed micro‐survey data at the household level. Utilizing weekly financial transaction data collected from households residing in a rural region of India, we estimate the impacts of India's COVID‐19 lockdown on household income, food security, welfare, and access to local loan markets. A large portion of households living in our study region is reliant on remittances from migrants to sustain their livelihoods. Our analysis reveals that in the month immediately after India's lockdown announcement, weekly household local income fell by INR 1,022 (US$ 13.5), an 88% drop compared to the long‐term average with another 63% reduction in remittance. In response to the massive loss in earnings, households substantially reduced meal portions and consumed fewer food items. Impacts were heterogeneous; households in lower income quantiles lost a higher percentage of their income and expenditures, but government food aid slightly mitigated the negative impacts. We also find an increase in the effective interest rate of local borrowing in cash and a higher demand for in‐kind loans, which are likely to have an adverse effect on households who rely on such services. The results from this paper have immediate relevance to policymakers considering additional lockdowns as the COVID‐19 pandemic resurges around the globe and to governments thinking about responses to future pandemics that may occur. [ABSTRACT FROM AUTHOR]

The rapid spread of COVID‐19 has led to a global shortfall in essential items, turning many countries into resource‐constrained environments. In response, an unprecedented number of do‐it‐yourself hobbyists (i.e. makers) have started to use digital fabrication tools to produce critical items. These bottom‐up communities are mobilising as part of a global movement to produce innovative solutions to much‐needed items, such as face masks, face shields and ventilators. As these individuals tackle widespread resource constraints, the conceptual lens of frugal innovation becomes highly relevant to study how these solutions developed. Frugal innovation is a type of resource‐constrained innovation that refers to the practice of doing more with less, for more people. In this study, we present two instrumental case studies of maker projects that use digital fabrication to tackle COVID‐19. The first case study is from Italy (a High Income Country) and the second is from India (a Lower Middle Income Country). We analyse the frugality of these cases and highlight their similar approaches. In doing so, we suggest that current theories of frugal innovation can be expanded to new geographical and technological contexts. We put forward that frugal innovation is an important strategy in crisis response beyond emerging markets and that digital fabrication can be considered as an important frugal innovation enabler, both in its ability to produce frugal solutions and to support distributed networks of innovation actors. This study advances knowledge on how frugal innovation unfolds in the Maker movement. It is among one of the first studies to connect the domains of makers and frugal innovation, and the paper concludes by identifying several promising areas for further research. [ABSTRACT FROM AUTHOR]

Although the COVID‐19 pandemic resulted in about a 24% decline in India's GDP during the April–June 2020 quarter, the nation's agricultural sector, somewhat surprisingly, seems to have done remarkably well. This paper examines whether the public transfer program Pradhan Mantri Garib Kalyan Yojana (PMGKY), announced immediately after the lockdown, benefited farmers in dealing with the COVID shock. Overall, 95% of the smallholders received support from at least one of PMGKY's four components. Direct cash transfers had significantly more impact than in‐kind transfer schemes. The result shows that farmers receiving cash transfers under PM‐KISAN, one component of PMGKY, were more likely to invest in buying seeds. In contrast, farmers receiving cash transfers under PM‐UY, another piece of PMGKY, were more likely to invest in fertilizer and pesticides. Finally, smallholders who received benefits from all four components of PMGKY were more likely to invest in purchasing seeds, fertilizer, and pesticides. Findings suggest the fungibility of public cash transfers from the recent PMGKY scheme is significant in alleviating credit constraints and increasing future investments in modern inputs. [ABSTRACT FROM AUTHOR]

This paper looks at the disruption in food supply chains due to COVID‐19 induced economic shutdown in India. We use a novel dataset from one of the largest online grocery retailers to look at the impact on product stockouts and prices. We find that product availability falls by 10% for vegetables, fruits, and edible oils, but there is a minimal impact on their prices. On the farm‐gate side, it is matched by a 20% fall in quantity arrivals of vegetables and fruits. We then show that supply chain disruption is the main driver behind this fall. We compute the distance to production zones from our retail centers and find that the fall in product availability and quantity arrivals is larger for items that are cultivated or manufactured farther from the final point of sale. Our results show that long‐distance food supply chains have been hit the hardest during the current pandemic with welfare consequences for urban consumers and farmers. [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]

Background: COVID‐19 has been linked to over 40 million infections and 1.1 million deaths in 210 countries as of October 19, 2020. This highly contagious communicable disease has put not only infected individuals but other patients and frontline workers like nurses at risk in hospitals, especially in Intensive Care units (ICUs). There is a need for minimizing patient contact, improving hand hygiene practices, and optimizing healthcare provider time, especially nurses. Globally it is estimated that nearly a million health care providers have been infected with COVID‐19 as of the end of October 2020. Methods: This retrospective service evaluation documents the experience of health care providers in a COVID‐19 ICU in India that was used to implement new protocols for secretion management and oral hygiene. Patient chart information and staff feedback were utilized. Intervention: This pilot study captures the practical benefits of using VAPCare, an automated, closed‐loop system for oral secretion removal. Results: Six patients were included in this small‐scale study; three patients following the current standard of care for suctioning and oral hygiene and three receiving the new VAPCare and Lumen device protocol. With the new device protocol, the number of infected secretion interactions by a nurse was 50% lower, and nursing time spent on oral hygiene and secretion management 70% less than seen with the current standard of care. The number of disposable gloves used with VAPCare and Lumen was reduced by over 50%. All 10 nurses and six doctors gave positive feedback on device usage. The department recommended updating protocols to prioritize the use of the new secretion management system for patients with COVID19 and other highly contagious conditions. Conclusion: The findings are an early indication that using VAPCare for patients could help protect infected patients, other ICU patients, and health care workers. [ABSTRACT FROM AUTHOR]

Motivated by the prevailing severe situation in India, we extend the SIR(S) model of infectious diseases to incorporate demand dynamics and its interaction with COVID‐19 spread. We argue that, on one hand, the spread of COVID‐19 creates panic among consumers and firms and negatively affects economic activity. On the other hand, economic activity intensifies the spread of the infection. Initially assuming that recovered individuals do not develop antibodies and become susceptible again, we capture the interaction between economic activity and the spread of the disease in a two‐dimensional dynamical system. We show that a large fiscal expansion combined with measures to boost community health and improve the health sector's capacity to provide critical care can simultaneously improve the economy and control the spread of the disease. Finally, assuming that only a fraction of recovered individuals become susceptible to contracting the diseases again, we obtain richer dynamics in a three‐dimensional dynamical system. This paper also highlights the important role of infection rates and the recovery rate in determining the uniqueness and the stability properties of steady state. [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]

Background: This study identified the risk factors for severe acute respiratory syndrome coronavirus 2 infection among household contacts of index patients and determined the incubation period (IP), serial interval, and estimates of secondary infection rate in Kerala, India. Methods: We conducted a cohort study in three districts of Kerala among the inhabitants of households of reverse transcriptase polymerase chain reaction‐positive coronavirus disease 2019 patients between January and July 2021. About 147 index patients and 362 household contacts were followed up for 28 days to determine reverse transcriptase polymerase chain reaction positivity and the presence of total antibodies against SARS‐CoV‐2 on days 1, 7, 14, and 28. Results: The mean IP, serial interval, and generation time were 1.6, 3, and 3.9 days, respectively. The secondary infection rate at 14 days was 43.0%. According to multivariable regression analysis persons who worked outside the home were protected (adjusted odds ratio [aOR], 0.45; 95% confidence interval [CI], 0.24–0.85), whereas those who had kissed the coronavirus disease 2019‐positive patients during illness were more than twice at risk of infection (aOR, 2.23; 95% CI, 1.01–5.2) than those who had not kissed the patients. Sharing a toilet with the index patient increased the risk by more than twice (aOR, 2.5; 95% CI, 1.42–4.64) than not sharing a toilet. However, the contacts who reported using masks (aOR, 2.5; 95% CI, 1.4–4.4) were at a higher risk of infection in household settings. Conclusions: Household settings have a high secondary infection rate and the changing transmissibility dynamics such as IP, serial interval should be considered in the prevention and control of SARS‐CoV‐2. [ABSTRACT FROM AUTHOR]

With humans, animals and the environment being as interconnected as they are, the science describing their interactions needs to cut across disciplinary boundaries. Systems research at the interface between the three goes by several names, such as 'Eco‐Health' and 'Planetary Health', each with a varied focus, but the concept of 'One Health' (OH) has stood out as the most popular one. COVID‐19 has reiterated the importance of OH in response to health challenges. This review aimed to assess the OH approach integration and implementation level in Kerala state, India, in the context of emerging zoonotic diseases. A systematic literature review was conducted by searching for relevant articles with specific keywords across six electronic databases. This involved screening the initial hits for titles and abstracts, then systematic sorting to identify the ones that met the criteria, followed by more thorough scrutiny to finally shortlist the six studies to be included in the review. We found that OH in Kerala has made good progress, as evident from a few recent examples, but has a long way to go with significant challenges. In line with the study's aim, identifying and analysing what is already done, what is missing and what needs to be done can have wider implications for future OH implementation. Relevant threats and opportunities were identified, with lessons for Kerala and India and broader applications. [ABSTRACT FROM AUTHOR]

Since March 2020, the COVID‐19 pandemic has significantly reduced the availability of global aircraft‐based observations (ABOs), which has been restored later in 2021. This study focuses on the impact of ABOs on a regional reanalysis. Indian Monsoon Data Assimilation and Analysis (IMDAA) is a regional reanalysis for a period from 1979 to 2020 (originally up to 2018) over India and surrounding regions produced at the National Centre for Medium Range Weather Forecasting (NCMRWF), India, in collaboration with the UK Met Office. A comparison of the impact of ABOs on other conventional and satellite observations assimilated in the NCMRWF global model and IMDAA during 2019 and 2020 revealed the importance of ABOs, particularly in IMDAA, since it did not assimilate the latest satellite data as the IMDAA system was frozen in October 2016. A data denial experiment that removes all the ABOs from the IMDAA assimilation system for a period from March to November 2019 is designed. The results from the IMDAA reanalysis run, which assimilates ABOs during the same period, are compared with the data denial experiment. Assimilation of ABOs strengthened the upper tropospheric circulation, the Tropical Easterly Jet (TEJ), during the Indian summer monsoon compared to the data denial experiment. Analysis of the features of two cyclones that developed over the North Indian Ocean during the study period revealed that ABO assimilation played a key role in simulating the track and intensity of these cyclones when they were in the 'severe' category. Since the sample is small, more cyclone cases need to be analysed to consolidate the result. [ABSTRACT FROM AUTHOR]

We examine the effect of COVID‐19‐induced lockdown on the profitability of listed firms in India. We use quarterly income statement of 4168 listed firms for the period between April–June 2020 quarter and April–June 2022 quarter and compare their financial data with previous quarters (2015–2019). Using a difference‐in‐difference estimation framework and various profitability measures, we find that the COVID‐19 lockdown has reduced profits by around 15 per cent for listed firms in India. Our results are robust to various robustness tests and alternate specifications. We find evidence of firms losing revenues more than expenses, thus leading to decline in profits. The main effect is conditioned by firm‐specific factors. Specifically, firms that are smaller, older, unlisted and that do not belong to any group witnessed larger decline in profitability due to lockdown. Additionally, the effect of lockdown is more pronounced in areas that had lower mobility and higher COVID‐19 spread. These results underscore the importance of institutional factors and pre‐existing firm characteristics in conditioning the impact of lockdown on firm profitability. [ABSTRACT FROM AUTHOR]

We examine the effect of testing and social distancing measures on the severity of COVID19 across Indian states during the 68th day nationwide lockdown period. We also explore whether pre‐existing socio‐economic factors such as quality of health care and the ability to practice social distancing influences the effect of these policy measures across states. Using daily level data between April 1 and May 31 for 18 of the major states, we find that both testing and social distancing have a negative effect on COVID‐19 fatalities in India. Further, testing is more helpful in reducing CFR for states with lower per capita health expenditure and weaker medical infrastructure. This highlights how ramping up testing can aid states that have a weak health care system through the detection of infection, contact tracing and isolation. In contrast, social distancing measures are more effective in states that are less populous and have lesser people dwelling in single‐room houses. Our results confirm the role of pre‐existing institutional factors in shaping the effect of policy actions on health outcomes. [ABSTRACT FROM AUTHOR]

We examine the dynamics of the impact of the evolving policy response during the COVID‐19 pandemic on the equity market sentiment in India. We operationalise our study by examining the India VIX, the fear gauge of the Indian equity market as an indicator for the market sentiment, and the country level Government Response Index of the Blavatnik School of Government, Oxford University as an indicator for the policy response. The relation is examined through the Markov‐switching model using high‐frequency daily data from January 30, 2020, to May 31, 2021. The evidence suggests that the policy response has a positive impact on the market sentiment when the market is fearful. Further, the evidence suggests that both the high‐fear state and the low‐fear state of the market sentiment given by the model are short‐lived indicating heightened volatility and possible speculation during the ongoing pandemic in the Indian equity market. [ABSTRACT FROM AUTHOR]

Based on in‐depth interviews with 24 middle‐class Indian child participants, this is the first exploratory qualitative study, in India, to demonstrate the ways in which children as reflexive social actors re‐negotiated everyday schedules, drew on classed resources at their disposal and made sense of the impact of the pandemic on their educational pathways and future aspirations. These narratives offer a unique lens on the politics of middle‐classness and its constitutive relation to constructions of normative childhoods in contemporary India. Study findings contribute to the sociology of Indian childhood and more generally help enrich our understanding of southern childhoods and the reproduction of inequalities in contemporary India. [ABSTRACT FROM AUTHOR]

Summary: Motivation: COVID‐19 has disrupted the lives of millions of people worldwide. Migrants in developing economies have been among the most affected. This vulnerable population faces a threat to their livelihood and way of life. Hence, there is an urgent need to understand the impact of the pandemic on their lives to be able to tackle subsequent waves of the pandemic or similar future exogenous shocks. Purpose: We delve into the economic and social disruptions caused by the COVID‐19 pandemic on the employment, sources of income, and lives of different categories of migrant labourers in the Indian state of Kerala. Methods and approach: Using the livelihood portfolio theory, we dissect this impact in relation to a wide range of issues. This was corroborated by in‐depth semi‐structured interviews with three categories of respondents. The interview data was analysed by using the directed qualitative content analysis method. We created themes from the data and juxtaposed them with the livelihood portfolio theory in addressing the research objectives. Findings Results highlight the impact on livelihood, lifestyles, migration prospects, and gender aspects. First, households dependent on international migrants were more severely affected than those with family members who were internal migrants. Second, a considerable lifestyle change (more reliance on a plant‐based diet) and borrowing patterns (more reliance on informal money lending) was reported. Third, opinions on future migration prospects were pessimistic, and a trend towards reverse migration was noted. We also captured resilience measures for each of the themes. Policy implications: We find that blanket responses to mitigate migrants' hardships could be counterproductive. Policy‐makers ought to implement tailor‐made policies keeping in mind the migrants' classification and socioeconomic demographics. Further, we recommend specific measures to address challenges that women face, to ease their workload and mitigate the loss of income. Specific measures aimed at initiating attitudinal change such as creating mental health awareness, curbing misinformation, and providing counselling services could also add immense value in tackling the pandemic. [ABSTRACT FROM AUTHOR]

Long coronavirus disease (COVID) or postacute sequelae of coronavirus disease of 2019 (COVID‐19) is widely reported but the data of long COVID after infection with the Omicron variant is limited. This study was conducted to estimate the incidence, characteristics of symptoms, and predictors of long COVID among COVID‐19 patients diagnosed during the Omicron wave in Eastern India. The cohort of COVID‐19 patients included were adults (≥18 years) diagnosed as severe acute respiratory syndrome coronavirus 2 positive with Reverse Transcription Polymerase Chain Reaction. After 28 days of diagnosis; participants were followed up with a telephonic interview to capture data on sociodemographic, clinical history, anthropometry, substance use, COVID‐19 vaccination status, acute COVID‐19 symptoms, and long COVID symptoms. The long COVID symptoms were self‐reported by the participants. Logistic regression was used to determine the predictors of long COVID. The median follow‐up of participants was 73 days (Interquartile range; 67–83). The final analysis had 524 participants' data; among them 8.2% (95% Confidence Interval [CI]: 6%–10.9%) self‐reported long COVID symptoms. Fatigue (34.9%) was the most common reported symptom followed by cough (27.9%). In multivariable logistic regression only two predictors were statistically significant—number of acute COVID‐19 symptoms ≥ five (Adjusted odds ratio (aOR) = 2.95, 95% CI: 1.30–6.71) and past history of COVID‐19 (aOR = 2.66, 95% CI: 1.14–6.22). The proportion of self‐reported long COVID is considerably low among COVID‐19 patients diagnosed during the Omicron wave in Eastern India when compared with estimates during Delta wave in the same setting. [ABSTRACT FROM AUTHOR]

The healthcare sector is increasingly facing changing demand patterns and escalating pressures for innovative services during the COVID‐19 pandemic. Market‐focused flexibility refers to the capabilities of adaptation and facilitating the innovative performance of the firm. Accepting the overall role of innovation in COVID‐19 response, this study aims to explore how public healthcare organizations exhibit market‐focused flexibility to introduce new and innovative services. This study conducts an exploratory case study in a national‐level healthcare firm in India. This study identifies four specific dimensions of market‐focused flexibility that healthcare firms execute to deliver customized services. The study's findings contribute to an integrative framework of market‐focused flexibility and innovative performance in public healthcare. The mechanisms of market‐focused flexibility are unearthed and explained how the different facets influence innovative services in various manners. The implications to theory and practices are discussed, and future research avenues are sketched. [ABSTRACT FROM AUTHOR]

Governments around the world are utilizing their digital ecosystems to respond to the COVID‐19 pandemic. To increase awareness among the beneficiaries about privacy risks, they must proactively publish the data handling practices for their digital initiatives through appropriate privacy policies. This study analyzes the privacy policies of public COVID‐support mobile applications (apps) in the context of India. We found a total of 63 government initiated COVID‐support apps in India out of which 38% were found to have an app‐specific privacy policy. These policies were analyzed further to assess their coverage of key principles, such as "Purpose," "Data Categories," and "Data Retention," derived from legal requirements. We also analyzed the extent of the specificity of policies with a high coverage. In India, only one nation‐wide app stood out to have both considerable coverage of key principles as well as a high level of specificity. Other national/regional apps fail to display the desired levels of coverage and/or specificity. The broader policy recommendations of this study are that the government should better address privacy concerns regarding its existing and future disaster management apps as well as its other digital initiatives by (a) establishing and enforcing a comprehensive legislative framework for data protection and (b) increasing privacy awareness among the beneficiaries. [ABSTRACT FROM AUTHOR]

In this study, we developed and analyzed a mathematical model for explaining the transmission dynamics of COVID‐19 in India. The proposed SIuIkR model is a modified version of the existing SIR model. Our model divides the infected class I of SIR model into two classes: Iu (unknown infected class) and Ik (known infected class). In addition, we consider R a recovered and reserved class, where susceptible people can hide them due to fear of the COVID‐19 infection. Furthermore, a non‐monotonic incidence function is deemed to incorporate the psychological effect of the novel coronavirus diseases on India's community. The epidemiological threshold parameter, namely the basic reproduction number, has been formulated and presented graphically. With this threshold parameter, the local and global stability analysis of the disease‐free equilibrium and the endemic proportion equilibrium based on disease persistence have been analyzed. Lastly, numerical results of long‐run prediction using MATLAB show that the fate of this situation is very harmful if people are not following the guidelines issued by the authority. [ABSTRACT FROM AUTHOR]

Several global health incidents and evidences show the increasing likelihood of pandemics (large‐scale outbreaks of infectious disease), which has adversely affected all aspects of human lives. It is essential to develop an analytics framework by extracting and incorporating the knowledge of heterogeneous data‐sources to deliver insights for enhancing preparedness to combat the pandemic. Specifically, human mobility, travel history, and other transport statistics have significantly impact on the spread of any infectious disease. This article proposes a spatio‐temporal knowledge mining framework, named STOPPAGE, to model the impact of human mobility and other contextual information over the large geographic areas in different temporal scales. The framework has two key modules: (i) spatio‐temporal data and computing infrastructure using fog/edge based architecture; and (ii) spatio‐temporal data analytics module to efficiently extract knowledge from heterogeneous data sources. We created a pandemic‐knowledge graph to discover correlations among mobility information and disease spread, a deep learning architecture to predict the next hotspot zones. Further, we provide necessary support in home‐health monitoring utilizing Femtolet and fog/edge based solutions. The experimental evaluations on real‐life datasets related to COVID‐19 in India illustrate the efficacy of the proposed methods. STOPPAGE outperforms the existing works and baseline methods in terms of accuracy by ≈$$ \approx $$(18–21)% in predicting hotspots and reduces the power consumption of the smartphone significantly. The scalability study yields that the STOPPAGE framework is flexible enough to analyze a huge amount of spatio‐temporal datasets and reduces the delay in predicting health status compared to the existing studies. [ABSTRACT FROM AUTHOR]