In this talk, Assistant Professor Abraham Flaxman explores the methods underlying morbidity estimations in the Global Burden of Disease (GBD) study, as laid out in the new book An Integrative Metaregression Framework for Descriptive Epidemiology, published by the University of Washington Press.

In many parts of the world, health data are sparse and of variable quality. Mathematical modeling is used to take data collected from different sources, correct for inconsistencies, and fill in gaps when data are incomplete, ultimately producing estimates of disease burden. Dr. Flaxman is the primary architect of the software tool known as DisMod-MR (for Disease Modeling – Metaregression), which is used in the GBD study to quantify deaths from each cause by age, sex, country, and year.