Covid-19: Recovering Estimates of the Infected Fatality Rate During an Ongoing Pandemic Through Partial Data

Author
Matteo Villa, James F. Myers, Federico Turkheimer
Content Type
Commentary and Analysis
Institution
Italian Institute for International Political Studies (ISPI)
Abstract
In an ongoing epidemic, the case fatality rate is not a reliable estimate of a disease’s severity. This is particularly so when a large share of asymptomatic or pauci-symptomatic patients escape testing, or when overwhelmed healthcare systems are forced to limit testing further to severe cases only. By leveraging data on COVID-19, we propose a novel way to estimate a disease’s infected fatality rate, the true lethality of the disease, in the presence of sparse and partial information. We show that this is feasible when the disease has turned into a pandemic and data comes from a large number of countries, or regions within countries, as long as testing strategies vary sufficiently. For Italy, our method estimates an IFR of 1.1% (95% CI: 0.2% – 2.1%), which is strongly in line with other methods. At the global level, our method estimates an IFR of 1.6% (95% CI: 1.1% – 2.1%). This method also allows us to show that the IFR varies according to each country’s age structure and healthcare capacity.
Topic
Health, Pandemic, Data, COVID-19
Political Geography
Europe, Italy, Global Focus