Tradeoffs driving policy and research decisions in biosurveillance

In view of concerns over bioterrorism, pandemic Influenza, and other public health threats, development of advanced surveillance systems to corroborate and supplement physician sentinel surveillance is a research imperative. Objectives of this article are to describe Interrelated decisions underlying the design of a public health surveillance system and to show these decisions' effects on data acquisition and transfer, on analysis methods, and on visualization tools. Some of these decisions are dictated by data limitations, others by goals and resources of the monitoring organization. Most such decisions involve three characteristic tradeoffs: the extent of monitoring for exceptional versus customary health threats, the level of data aggregation for monitoring, and the degree of automation to be used. A fundamental motivation is to extract outbreak information from background noise to empower epidemiologists monitoring public health on a day-to-day basis. This article discusses each of these tradeoffs and Illustrates them with three detailed examples.