Accurate and precise estimation of disease rates for a given population during a specified time frame is a major concern for public health practitioners and researchers in biosurveillance. Many diseases follow distinct patterns; incidence and prevalence of many diseases increase approximately exponentially with age, including many cancers, respiratory infections, and gastroenteritis. With increasing demographic information available in biosurveillance systems leading to more complex and comprehensive disease databases, seeking concise and informative summary measures of disease burden over space and time is becoming more critical for public health surveillance. In this paper we present two summary measures of disease burden in the elderly that simultaneously reflect disease dynamics and population characteristics.
Objective
To better estimate disease burden in the elderly population we illustrate an approach—the Slope Intercept Modeling for Population Linear Estimation (SIMPLE) method—that summarizes age-specific disease rates in the 65+ population using the observed exponential increase in disease rates with age in this dynamic and rapidly growing population subgroup.