June 2023 Estimating global and country-specific excess mortality during the Covid-19 pandemic
Victoria Knutson, Serge Aleshin-Guendel, Ariel Karlinsky, William Msemburi, Jon Wakefield
Author Affiliations +
Ann. Appl. Stat. 17(2): 1353-1374 (June 2023). DOI: 10.1214/22-AOAS1673


Estimating the true mortality burden of COVID-19 for every country in the world is a difficult, but crucial, public health endeavor. Attributing deaths, direct or indirect, to COVID-19 is problematic. A more attainable target is the “excess deaths,” the number of deaths in a particular period, relative to that expected during “normal times,” and we develop a model for this endeavor. The excess mortality requires two numbers, the total deaths and the expected deaths, but the former is unavailable for many countries, and so modeling is required for such countries. The expected deaths are based on historic data, and we develop a model for producing estimates of these deaths for all countries. We allow for uncertainty in the modeled expected numbers when calculating the excess. The methods we describe were used to produce the World Health Organization (WHO) excess death estimates. To achieve both interpretability and transparency we developed a relatively simple overdispersed Poisson count framework within which the various data types can be modeled. We use data from countries with national monthly data to build a predictive log-linear regression model with time-varying coefficients for countries without data. For a number of countries, subnational data only are available, and we construct a multinomial model for such data, based on the assumption that the fractions of deaths in subregions remain approximately constant over time. Our inferential approach is Bayesian, with the covariate predictive model being implemented in the fast and accurate INLA software. The subnational modeling was carried out using MCMC in Stan. Based on our modeling, the point estimate for global excess mortality during 2020–2021 is 14.8 million, with a 95% credible interval of (13.2, 16.6) million.


The authors would like to thank the WHO Technical Advisory Group on COVID-19 Mortality Assessment for helpful feedback during the model development and Sondre Ulvund Solstad and Haidong Wang for generously sharing details on “The Economist” and IHME approaches, respectively. We would like to acknowledge Saki Narita for her support throughout the country consultation and also to thank the Editor and three referees for their comments. The authors alone are responsible for the views expressed in this article, and they do not necessarily represent the views, decisions, or policies of the institutions with which they are affiliated.


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Victoria Knutson. Serge Aleshin-Guendel. Ariel Karlinsky. William Msemburi. Jon Wakefield. "Estimating global and country-specific excess mortality during the Covid-19 pandemic." Ann. Appl. Stat. 17 (2) 1353 - 1374, June 2023. https://doi.org/10.1214/22-AOAS1673


Received: 1 April 2022; Revised: 1 May 2022; Published: June 2023
First available in Project Euclid: 1 May 2023

MathSciNet: MR4582716
zbMATH: 07692386
Digital Object Identifier: 10.1214/22-AOAS1673

Keywords: Bayesian inference , global health , Poisson framework , subnational modeling

Rights: Copyright © 2023 Institute of Mathematical Statistics


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Vol.17 • No. 2 • June 2023
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