Reengineering real time outbreak detection systems for influenza epidemic monitoring

Abstract

In the wake of fears over pandemic influenza, triggered by concern about avian influenza, a top national priority is to adapt surveillance systems, such as Biosense, for influenza monitoring. While real time surveillance system architects have been largely focused on the problem of discrete outbreak detection, the data in these systems have been shown to have unique advantages for the timely detection of influenza. In this study, we evaluate the utility influenza detection by real-time surveillance as an adjunct to the traditional CDC surveillance systems.

Figure 1

Timing of influenza activity in 3 systems. Analysis shows that syndromic surveillance provides the earliest indication of an influenza season.

Figure 2

Alerting algorithms used for monitoring influenza epidemics. Four thresholds were tested (1) Mean + 1 SD (green) (2) Mean + 2 SD (red) (3) Seasonal baseline (4) Percent increase (blue) and were compared to viral isolate data (red bars).