Unequal Lives: A Sociodemographic Analysis of Covid19 Transmission and Mortality in India (preprint)

The hierarchy of social structures shape, in very particular and measurable ways, the differential impact that a disease has on different parts of society. In this study, we use district-level disease data to perform an ecological analysis of Covid19 outcomes in India vis a vis the local socioeconomic gradient. Average doubling times and case fatality ratios have been quantified as measures of transmission and mortality, respectively, and association analysis performed with twenty variables of socioeconomic vulnerability. Persistent patterns are observed between disease outcome and social inequality, linking poor living conditions to a faster spread, an elderly populace to a slower spread, and both a college education and the presence of medical facilities to low fatality rates.

An India-specific Compartmental Model for Covid-19: Projections and Intervention Strategies by Incorporating Geographical, Infrastructural and Response Heterogeneity (preprint)

We present a compartmental meta-population model for the spread of Covid-19 in India. Our model simulates populations at a district or state level using an epidemiological model that is appropriate to Covid-19. Different districts are connected by a transportation matrix developed using available census data. We introduce uncertainties in the testing rates into the model that takes into account the disparate responses of the different states to the epidemic and also factors in the state of the public healthcare system. Our model allows us to generate qualitative projections of Covid-19 spread in India, and further allows us to investigate the effects of different proposed interventions. By building in heterogeneity at geographical and infrastructural levels and in local responses, our model aims to capture some of the complexity of epidemiological modeling appropriate to a diverse country such as India.