The Long Tail of Disease Modeling

• Activity Number: 562
• Type: Topic Contributed
• Date/Time: Wednesday, August 4, 2010 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Abraham D. Flaxman*+ and Stephen S. Lim and Christopher J.L. Murray
• Companies: Institute for Health Metrics and Evaluation and Institute for Health Metrics and Evaluation and Institute for Health Metrics and Evaluation
• Keywords: Disease Modeling ; Bayesian ; MCMC ; Global Health ; Health Metrics

Abstract

The Global Burden of Disease Study (GBD), is a major study which needs to know about the incidence and duration of many diseases, injuries, and risk factors for 21 regions of the world. Data is not voluminous in high-income regions, and is quite sparsely availble in middle- and low-income regions. Hence the need for disease modeling to estimate the epidemiological parameters needed for GBD.

This is accomplished with a generic model of disease progression through a population. The model parameters are estimated in a Bayesian framework, to allow epidemiologists to combine all data extracted from literature reviews with their prior knowledge about the nature of disease, in order to produce consistent estimates of age-specific prevalence, incidence, duration, etc.