Public health agencies conduct surveillance to identify and prioritize health issues and evaluate interventions. Recently, natural and deliberate epidemics have motivated supplementary approaches to traditional surveillance methods based on physician and laboratory reporting.
Fueled initially by post–September 11, 2001, bioterrorism-related funding, and more recently used for detecting natural outbreaks, these systems, many of which are called “syndromic” systems because they focus on syndromes recorded before the diagnosis, capture real-time health data and scan for anomalies suggesting an outbreak. Although these systems as typically implemented have often proven unreliable for detecting natural and simulated epidemics, real-time health-related data hold promise for public health.
If redesigned to reliably perform beyond outbreak detection, syndromic systems could demonstrate unprecedented capabilities in responding to public health emergencies.