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Although both central and state governments in India took the decisions to impose hard paternalistic policies of lockdown/shutdown to manage the spread of COVID-19, new cases were rising even after the first and second waves. Reverse migration, lack of social distancing, and failure to adhere to appropriate covid behavior are attributed as the leading cause of COVID-19 spread. The policy measures like 'Pradhan Mantri Gareeb Kalyan Yojana,' financial assistance, and series of lockdowns and shutdowns by the government of India have not significantly controlledthe spread of disease owing to a lack of understanding of individual's reaction to the pandemic and their reactive behavior. This paper used daily COVID-19 positive cases data to show the overall picture of COVID-19 in India. It used the explorative method to review articles related to behavioral biases involved in the decision-making process of migrant workers and individuals during the pandemic. The paper's findings show that different behavioral biases like base rate neglect, herd behavior, anchoring effect, availability bias are responsible for creating chaos, trauma, and anxiety among the migrant workers and leading to reverse migration in India. Despite knowing that COVID-19 is a fatal disease, some individuals' reaction to it was casual mainly because of hyperbolic discounting bias, optimism bias, overconfidence bias, confirmation bias, status quo bias, and loss aversion. Taking behavioral economics lessons, the paper suggests different nudging techniques for guiding people to maintain social distancing during this pandemic. Nudging has been proved to be an inexpensive tool in bringing desired behavioral changes in health economics. The paper concludes that nudging techniques can influence human behavior to control the spread of the disease. In the end, it gives direction for future work in this area to explore how behavioral economics can help policymakers to tackle the spread of infectious diseases such as COVID-19. [ABSTRACT FROM AUTHOR]

To monitor the spread of the novel coronavirus (COVID-19), India, during the last week of March 2020, imposed national restrictions on the movement of its citizens (lockdown). Although India's economy was shut down due to restrictions, the nation observed a sharp decline in particulate matter (PM) concentrations. In recent years, Delhi has experienced rapid economic growth, leading to pollution, especially in urban and industrial areas. In this paper, we explored the linkages between air quality and the nationwide lockdown of the city of Delhi using a geographic information system (GIS)-based approach. Data from 37 stations were monitored from 12 March, 2020 to 2 April, 2020 and it was found that the Air Quality Index for the city was almost reduced by 37% and 46% concerning PM2.5 and PM10, respectively. The study highlights that, in regular conditions, the atmosphere's natural healing rate against anthropogenic activities is lower, as indicated by a higher AQI. However, during the lockdown, this sudden cessation of anthropogenic activities leads to a period in which the natural healing rate is greater than the induced disturbances, resulting in a lower AQI, and thus proving that this pandemic has given a small window for the environment to breathe and helped the districts of Delhi to recover from serious issues related to bad air quality. If such healing windows are incorporated into policy and decision-making, these can prove to be effective measures for controlling air pollution in heavily polluted regions of the World. [ABSTRACT FROM AUTHOR]

To arrest the spread of COVID-19, most countries have imposed some form of lockdown to ensure social distancing. For India, a complete was imposed by the Central Government over four phases and over two months (April-June, 2020). While the effectiveness of such a stringent measure is yet to be established, some estimates of the economic distress owing to lockdown are available and it projects a substantial drop in GDP as well as State Domestic Products. It is therefore important for India to plan the unlock down phase well. Unfortunately, with the possibility of may more pandemic related disruptions that are likely to happen in the future, both lock down as well as removal of lockdown becomes a key determinant for both controlling the spread of pandemics as well as revive the economy. In this paper, we develop a theoretical framework to address how un lockdown must be planned and discuss the respective roles of the States as well as the Centre. The model is set against the backdrop where a large part of the migrant labor has also been forced to return to their home States. In our model, the Centre as well as the States maximize the Expected Economic output while planning un lockdown. The probability of COVID spread is modeled using simple Epidemiological probability function. We find that a centralized lockdown would mean lower lockdown levels for the labor receiving state compared to the case when such decisions were decentralized and a higher lockdown level for the labor sending state as compared to the case when such decisions were decentralized. We recommend that the role of the Centre in easing of lockdown must be limited to two things. One, support the States with more investments in health infrastructure that will help them reduce lockdown intensities. Two, compensate the expected shortfall in wage income through a Direct Benefit Transfer to the labor in the two States. Our model can be used to implement unlock down phases should a contingency in the future arise. [ABSTRACT FROM AUTHOR]

Food addiction (FA) has a long-term impact on the health of individuals. This study analyses the changes in FA and related behaviour in India in the wake of lockdown which started on 25th March 2020 as a response to the COVID-19 outbreak. This paper provides insight into the food consumption behavior of various segments of the population during this lockdown. It offers some new insights in this regard by establishing the relationship between a temporary pause in the consumption of palatable food and FA. This study was conducted between March and May 2020 in two stages. First, a quantitative study used the Yale Food Addiction Scale (YFAS) to identify food addicts from a sample of 150 respondents. In the second stage, in-depth telephone interviews were conducted with the food addicts; the responses were recorded, transcribed, and analysed to ascertain the changes in their overall consumption and addiction behavior towards palatable foods. This was done by conducting a thematic analysis with the help of the NVivo software where various tools like word cloud and cluster analysis were used. This study found that COVID-19 restrictions had significantly brought down the addiction to palatable food in India as the regular consumption chain had got broken during the lockdown. The consumption of palatable food is expected to remain low for a brief period after the lockdown due to hygiene issues like improper or lack of sanitization and cleanliness. However, in the long-run, the consumption of palatable food is expected to rise in India owing to its growing population, modernisation, increasing disposable income and changes in customer preferences. These findings have significant implications for the food, packaging and health industries as the changes in customer behavior will certainly impact them, and they need to duly change their strategy to adapt to the changes promptly. [ABSTRACT FROM AUTHOR]

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

COVID-19 virus has resulted in the lockdown of schools, offices, factories, temples, railway stations, and even the airspace. It is estimated that due to the lockdown, the Indian economy may face prolonged adverse impact. The paper is an attempt to ascertain the impact of lockdown on the Indian economy and explore future perspective. The study has addressed important issues like consumption expenditure, demand & supply, unemployment rate, purchasing power, financial market, etc. Under the given circumstances, the lockdown will cost India around USD 120 bn. The manufacturing and service sector has come to an abrupt stop and interrupted domestic supply chains. If this crisis continuous it will indirectly affect all economic sectors. The study has given suggestions as a learning curve which can be used by different stakeholder to improve the economic situation of the country and minimize negative effect of lockdown. [ABSTRACT FROM AUTHOR]

COVID-19 virus has resulted in the lockdown of schools, offices, factories, temples, railway stations, and even the airspace. It is estimated that due to the lockdown, the Indian economy may face prolonged adverse impact. The paper is an attempt to ascertain the impact of lockdown on the Indian economy and explore future perspective. The study has addressed important issues like consumption expenditure, demand & supply, unemployment rate, purchasing power, financial market, etc. Under the given circumstances, the lockdown will cost India around USD 120 bn. The manufacturing and service sector has come to an abrupt stop and interrupted domestic supply chains. If this crisis continuous it will indirectly affect all economic sectors. The study has given suggestions as a learning curve which can be used by different stakeholder to improve the economic situation of the country and minimize negative effect of lockdown. [ABSTRACT FROM AUTHOR]

Introduction: This paper fulfills an identified need to study the mental health status of the population under situations like lockdown, thereby helping fill a persistent gap in Indian research on this issue, and present research on the impact of lockdown on mental health during epidemics is limited, especially in India. This study aims to scale the association between anxiety and sociodemographic factors during the coronavirus disease 2019 lockdown among the general Indian population. Methods: A descriptive cross-sectional nationwide study designed to enroll the general population. The inclusion criteria for this study were Indian citizens aged 18 years and above. The study was conducted from March 29, 2020, to April 12, 2020, using an online google questionnaire. The anxiety among respondents was detected and measured using a Generalized Anxiety Disorder (GAD) Scale, which consists of seven questions (in English), that is, GAD-7. Results: Responders were 392, and from these participants, the prevalence of anxiety was 25.3%. The predictors of anxiety were gender, religion, occupation as business/self-employed, marital status, family size, health status, and sleep deprivation based on the bivariate logistic regression analysis. Conclusion: This study reports the early prevalence of anxiety among the Indian population who were grounded at their homes during lockdown due to coronavirus pandemic in the country. [ABSTRACT FROM AUTHOR]

Although lockdown of the industrial and transport sector and stay at home advisories to counter the COVID-19 pandemic have shown that the air quality has improved during this time, very little is known about the role of ambient air pollutants and meteorology in facilitating its transmission. This paper presents the findings from a study that was conducted to evaluate whether air quality index (AQI), three primary pollutants (PM 2.5 , PM 10 and CO), Ground level ozone (O 3) and three meteorological variables (temperature, relative humidity, wind speed) have promoted the COVID-19 transmission in five megacities of India. The results show significant correlation of PM 2.5 , PM 10 , CO, O 3 concentrations, AQI and meteorological parameters with the confirmed cases and deaths during the lockdown period. Among the meteorological variables considered, temperature strongly correlated with the COVID-19 cases and deaths during the lockdown (r = 0.54 ; 0.25) and unlock period (r = 0.66 ; 0.25). Among the pollutants, ozone, and among the meteorological variables, temperature, explained the highest variability, up to 34% and 30% respectively, for COVID-19 confirmed cases and deaths. AQI was not a significant parameter for explaining the variations in confirmed and death cases. WS and RH could explain 10–11% and 4–6% variations of COVID-19 cases. A GLM model could explain 74% and 35% variability for confirmed cases and deaths during the lockdown and 66% and 19% variability during the unlock period. The results suggest that meteorological parameters may have promoted the COVID-19 incidences, especially the confirmed cases. Our findings may encourage future studies to explore more about the role of ambient air pollutants and meteorology on transmission of COVID-19 and similar infectious diseases. [Display omitted] • During lockdown for COVID-19, air quality improved in five megacities of India. • PM 2.5 , PM 10 , CO concentration across the megacities reduced during the lockdown. • Delhi and Kolkata experienced rise in O 3 concentration during lockdown. • PM 2.5 , PM 10 , CO, O 3 , AQI and T correlated with COVID-19 confirmed cases and deaths. • Temperature explained up to 30% variability for COVID-19 cases during the lockdown. [ABSTRACT FROM AUTHOR]

Worldwide spread of COVID-19 in a quite short time has brought a dramatic decrease in industrial activities, road traffic and tourism. Restricted human interaction with nature during this crisis time has appeared as a blessing for nature and environment. Reports from all over the world are indicating that after the outbreak of COVID-19, environmental conditions including air quality and water quality in rivers are improving and wildlife is blooming. India has always been a hub of pollution with huge population, heavy traffics and polluting industries leading to high air quality index (AQI) values in all major cities. But after declaration of lockdown due to COVID-19, quality of air has started to improve and all other environmental parameters such as water quality in rivers have started giving a positive sign towards restoring. This paper provides evidence-based insight into improvement of air quality and environment during pre and post lockdown of this pandemic situation. An attempt has been made to visualize the improvement in the air quality using tools like satellite images of Indian atmosphere, results of onsite real-time monitoring at specific locations (Ghaziabad-highest polluting city of India) and Air quality index (AQI) calculated by central pollution control board of India. • Brief database of obliteration caused by COVID-19 pandemic. • Assessment of environmental impact of subsequent lockdown. • Data gathered from national & international agencies in Indian context. • Study of Satellite images, onsite monitoring data and Air Quality Index. • Substantial improvement observed in air quality and other environmental indicators. [ABSTRACT FROM AUTHOR]