Excess Mortality Estimation

Jon Wakefield, University of Washington
Victoria Knutson, University Of Washington

Estimating the mortality associated with a specific mortality crisis event (for example, a pandemic, natural disaster or conflict) is clearly an important public health undertaking. In many situations, deaths may be directly or indirectly attributable to the mortality crisis event, and both contributions may be of interest. Unfortunately, estimating the deaths directly attributable to the event will frequently be problematic. Hence, the excess mortality, defined as the difference between the observed mortality and that which would have occurred in the absence of the crisis event, is an estimation target. If the region of interest contains a functioning vital registration system, so that the mortality is fully observed and reliable, then the only modeling required is to produce the expected deaths counts, but this is a non-trivial exercise. In low- and middle-income countries it is common for there to be incomplete (or non-existent) mortality data, and one must then use additional data and/or modeling, including predicting mortality using auxiliary variables. We describe and review each of these aspects, give examples of excess mortality studies, and provide a case study on excess mortality across states of the United States, during the COVID-19 pandemic.

Keywords: Bayesian methods , Population, Shocks and Pandemics, Civil Registration and Vital Statistics

See extended abstract.