Hospital emergency department (ED) syndromic surveillance has been proposed for early detection of a large-scale biologic terrorist attack. However, questions remain regarding its usefulness. The authors examined the use of active syndromic surveillance at hospital EDs in Virginia for early detection of disease events and analyzed the effectiveness of the cumulative sum (CUSUM) algorithm in identifying disease events from syndromic data. Daily chief-complaint data were collected for 10 months at seven hospital EDs in southeastern Virginia. Data were categorized into seven syndromes (fever, respiratory distress, vomiting, diarrhea, rash, disorientation, and sepsis), and the CUSUM algorithm was used to detect anomalies in each of the seven syndromes at each hospital. Fever and respiratory distress syndromes exhibited monthly and ambient-temperature-specific trends consistent with southeastern Virginia's influenza season. Furthermore, preliminary frequencies of hospital ED patient chief complaints in southeastern Virginia during a 10-month period were produced by using syndromic data. This system represents an example of a local syndromic surveillance program serving multiple cities in a limited geographic region.