Severity of the COVID-19 pandemic in India.

The main objective of this study is to identify the socioeconomic, meteorological, and geographical factors associated with the severity of COVID-19 pandemic in India. The severity is measured by the cumulative severity ratio (CSR)-the ratio of the cumulative COVID-related deaths to the deaths in a pre-pandemic year-its first difference and COVID infection cases. We have found significant interstate heterogeneity in the pandemic development and have contrasted the trends of the COVID-19 severities between Maharashtra, which had the largest number of COVID deaths and cases, and the other states. Drawing upon random-effects models and Tobit models for the weekly and monthly panel data sets of 32 states/union territories, we have found that the factors associated with the COVID severity include income, gender, multi-morbidity, urbanization, lockdown and unlock phases, weather including temperature and rainfall, and the retail price of wheat. Brief observations from a policy perspective are made toward the end.