Meta-analysis and adjusted estimation of COVID-19 case fatality risk in India and its association with the underlying comorbidities

There is a lack of COVID-19 adjusted case fatality risk (aCFR) estimates and information on states with high aCFR. State-specific aCFRs were estimated, using 13-day lag for fatality. To estimate country-level aCFR, state estimates were meta-analysed. Multiple correspondence analyses (MCA), followed by univariable logistic regression, were conducted to understand the association between aCFR and geodemographic, health and social indicators. Based on health indicators, states likely to report a higher aCFR were identified. Using random- and fixed-effects models, the aCFRs in India were 1.42 (95% CI 1.19 – 1.70) and 2.97 (95% CI 2.94 – 3.00), respectively. The aCFR was grouped with the incidence of diabetes, hypertension, cardiovascular diseases and acute respiratory infections in the first and second dimensions of MCA. The current study demonstrated the value of using meta-analysis to estimate aCFR. To decrease COVID-19 associated fatalities, states estimated to have a high aCFR must take steps to reduce co-morbidities.