Spatial Heterogeneity In Sensitivities of Covid-19 Pandemic 2020-21: A Decomposition Analysis of India

ABSTRACT: The COVID-19 pandemic was unprecedented challenging issue that caused a worldwide economic and health crises resulting in millions losing lives and livelihoods. Despite a large number studies have been conducted to explore this issue, limited research has delved into how the level of COVID-19 sensitivity is determined by multiple factors comprehensively in India. Looking into the complexity of the aforesaid nexus, this paper aims to construct COVID-19 sensitivity indices for major geographical regions of India and identify their determinants for each COVID-19 sensitivity index. This study uses data from various sources mainly including economic and political weekly research foundation (EPWRF) and Ministry of Health and Family welfare (Government of India COVID-19 Dashboard). In doing so, we have constructed five COVID-19 sensitivity indices for the Indian states by six geographical regions (Northern, Nort-eastern, Central, Western and Southern). In addition, we have constructed six composite indices for economic, education, health, infrastructure, labour and migration using various indicators relevant to the Indian rural and urban settings of the country. Further, employing Tobit regression model, we identified the factors that mostly determine COVID-19 sensitivity across six major regions of India. Our results suggest that central region states are likely to have the most vulnerability due to COVID-19 sensitivity, followed by eastern-, northeastern-, western-, and southern region states. In addition, estimated Tobit regression results highlighted that infrastructure-, labour-, health-, education-, migration and economic indices largely determine the level of COVID-19 sensitivity. Nevertheless, it is found that health and physical infrastructures are instrumental for coping COVID-19 contagion in Indian states. In fact, it is witnessed that education level induces recovered cases of COVID-19 contagion. Intensity of labour migration (migration index) had an adverse and significant impact on recovered cases. Our findings suggest heterogeneity policy targets for region specific to strengthen health infrastructure, enhance economic capability and focus on migration law to overcome severe issues like multidimensional adverse impacts of COVID-19 pandemic. Additionally, employment generation programs like MGNREGS and NRLM must be reframed for well implementation to stimulate employment opportunities in rural areas. Further, government should dynamically promote national health protection schemes like Ayushman Bharat to provide additional health facilities to poor and marginalised people especially in the time of contagion like COVID-19 pandemic and extended lockdown.