Managing uncertainty in early estimation of epidemic behaviors using scenario trees

Abstract

The onset of an epidemic can be foreshadowed theoretically through observation of a number of syndromic signals, such as absenteeism or rising sales of particular pharmaceuticals. The success of such approaches depends on how well the uncertainty associated with the early stages of an epidemic can be managed. This article uses scenario trees to summarize the uncertainty in the parameters defining an epidemiological process and the future path the epidemic might take. Extensive simulations are used to generate various syndromic and epidemic time series, which are then summarized in scenario trees, creating a simple data structure that can be explored quickly at surveillance time without the n..