Sensitivity and Uncertainty Analyses for Burden of Disease and Risk Factor Estimates

Excerpt

Modern epidemiological studies generally report confidence or uncertainty intervals around their estimates, often based on the variation observed in sample data. Estimates of the burden of disease and of risk factors, which extrapolate from specific data sources and epidemiological studies to population-level measures, are subject to a broader range of uncertainty because of the combination of multiple data sources and value choices. Hence, the reported uncertainty intervals should ideally include all sources of uncertainty, including those arising from measurement error, systematic biases, and modeling and extrapolation to compensate for incomplete data. In contrast to uncertainty analysis, which attempts to formally quantify the limitations of available data, sensitivity analysis examines how key analytic outputs vary when input quantities are systematically varied. Following Murray and Lopez (1996b), this chapter uses sensitivity analysis to examine the specific effects of social values that have been incorporated in the design of the disability-adjusted life year (DALY).