ABSTRACT
OBJECTIVES: Existing socio-economic inequalities shape, in very particular and measurable ways, the differential impact that a disease has on different sections of the same society. This is particularly true of COVID-19, which has rapidly exhausted the public health system in India, and magnified the gradient of vulnerability in an underserved populace. Using publicly available data, we have aimed to deconstruct this gradient into individual variables of inequality and quantify their impact on the transmission and mortality outcomes of COVID-19 in India. STUDY DESIGN: Sociodemographic analysis. METHODS: We quantify doubling times and case fatality ratios for all districts in India, then correlate them to 20 variables of socio-economic vulnerability and demographic structure. Variables that exhibit persistent correlation are then analysed using multivariate beta regression models to validate their impact on COVID-19 outcomes in India. RESULTS: The transmission of COVID-19 in India is enhanced by the lack of access to indoor latrines, drainage facilities, electricity, and proximate sources of drinking water. Transmission is slowed by the presence of an elderly population. Fatality rates relate negatively to an area's medical infrastructure and the presence of a college-educated populace. CONCLUSIONS: An interactive matrix of social inequalities, cultural practices, and behavioural patterns determines the path of COVID-19 through a community. Specific variables exhibit patterns of persistent vulnerability; others indicate a resistance to infection and mortality. This body of evidence, when incorporated into policy design, may lead to localised, need-sensitive models of intervention, both for preventive measures and medical care.