Representative estimates of COVID-19 infection fatality rates from four locations in India: cross-sectional study

Objectives To estimate age-specific and sex-specific mortality risk among all SARS-CoV-2 infections in four settings India, a major lower-middle-income country to compare age trends with similar estimates high-income countries. Design Cross-sectional study. Setting multiple regions representing combined population >150 million. Participants Aggregate infection counts were drawn from large population-representative prevalence/seroprevalence surveys. Data on corresponding number of deaths official government reports confirmed deaths. Primary secondary outcome measures The primary was fatality rate (IFR), estimated as the per infection. slope IFR-by-age function, increased associated age. Results Among males aged 50–89, measured IFR 0.12% Karnataka (95% CI 0.09% 0.15%), 0.42% Tamil Nadu 0.39% 0.45%), 0.53% Mumbai 0.52% 0.54%) an imprecise 5.64% 0% 11.16%) migrants returning Bihar. Estimated approximately twice high for females, heterogeneous across contexts rose less dramatically at older ages compared studies Conclusions IFRs during first wave varied substantially India. While Mumbai, considerably lower than comparable countries, adjustment under-reporting based crude excess puts them almost exactly equal higher-income benchmarks. In marginalised migrant population, much higher other around world. suggest that elderly India are advantage relative peers Our findings standard estimation approach may underestimate low-income due COVID-19 deaths, be settings.