Estimating the Infection Fatality Rate from SARS-CoV-2 in India

Abstract

There has been much discussion and debate around the underreporting of COVID-19 infections and deaths in India. In this short report we first estimate this underreporting factor for infections from publicly available data released by the Indian Council of Medical Research from national seroprevalence surveys. We then use a rigorous compartmental epidemiologic model to estimate the undetected number of infections and deaths. We compare the serosurvey-based ad hoc estimates with the model-based estimates. Both estimates qualitatively show that there is a large degree of “covert infections” in India, with model-based estimated underreporting factor for infections as 11.11 (95% CI 10.71-11.47) and for deaths as 3.56 (95% CI 3.48- 3.64). This implies approximately 91% of infections and 72% of deaths related to COVID-19 remain unreported in India. While seroprevalence data are not available across all states and union territories in India in a uniform way, epidemiologic models can prove to be useful tools to estimate the extent of underreporting. These estimates enable us to calculate the infection fatality rate (IFR) for India. If we rely on only reported deaths the IFR estimate is 0.13% while taking underreporting of deaths into account, the IFR estimate is 0.46%. There is considerable variation in these estimates across states.Funding Statement: This research is supported by the Michigan Institute of Data Science (MIDAS), Precision Health Initiative and Rogel Scholar Fund at the University of Michigan. Bhramar Mukherjee's research is supported by NSF DMS 1712933 and CA 046592.Declaration of Interests: The authors have declared no competing interest