How Deadly Is COVID-19? Understanding The Difficulties With Estimation Of Its Fatality Rate

20 Pages Posted: 13 Apr 2020 Last revised: 7 Mar 2026

See all articles by Andrew Atkeson

Andrew Atkeson

University of California, Los Angeles (UCLA) - Department of Economics; National Bureau of Economic Research (NBER)

Date Written: April 2020

Abstract

To understand how best to combat COVID-19, we must understand how deadly is the disease. There is a substantial debate in the epidemiological lit- erature as to whether the fatality rate is 1% or 0.1% or somewhere in between. In this note, I use an SIR model to examine why it is difficult to estimate the fatality rate from the disease and how long we might have to wait to resolve this question absent a large-scale randomized testing program. I focus on un- certainty over the joint distribution of the fatality rate and the initial number of active cases at the start of the epidemic around January 15, 2020. I show how the model with a high initial number of active cases and a low fatality rate gives the same predictions for the evolution of the number of deaths in the early stages of the pandemic as the same model with a low initial number of active cases and a high fatality rate. The problem of distinguishing these two parameterizations of the model becomes more severe in the presence of effective mitigation measures. As discussed by many, this uncertainty could be resolved now with large-scale randomized testing.

Suggested Citation

Atkeson, Andrew G., How Deadly Is COVID-19? Understanding The Difficulties With Estimation Of Its Fatality Rate (April 2020). NBER Working Paper No. w26965, Available at SSRN: https://ssrn.com/abstract=3574430

Andrew G. Atkeson (Contact Author)

University of California, Los Angeles (UCLA) - Department of Economics ( email )

Box 951477
Los Angeles, CA 90095-1477
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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