Disease outbreak detection system using syndromic data in the greater Washington DC area

Area of Science:

• Public Health Surveillance
• Infectious Disease Epidemiology
• Biosecurity

Background:

• Infectious disease outbreaks and intentional attacks can initially present as non-specific syndromes.
• Early detection of suspicious patterns at the community level is crucial before individual patient data raise alarms.

Purpose of the Study:

• To develop and evaluate a real-time surveillance system for early detection of disease outbreaks.
• To assess the system's capability in identifying both natural outbreaks and potential bioterrorism events.

Main Methods:

• Utilized centralized Department of Defense medical information systems to collect daily diagnoses (ICD-9-CM codes) from military clinics.
• Grouped codes into seven diagnostic clusters and monitored for deviations from historical patterns.
• Employed geospatial mapping and trend analysis using geographic information systems software.

Main Results:

• Surveillance data from 99 military clinics in the Washington, DC region were analyzed over two years.
• The system detected expected seasonal and daily variations, as well as several natural disease outbreaks.
• Retrospective analysis showed similar patterns to CDC sentinel surveillance for respiratory illnesses during influenza season.

Conclusions:

• The developed surveillance system shows promise for early detection of outbreaks, including influenza and potential intentional acts.
• Early detection facilitates targeted resource allocation, reduces mortality, and improves risk communication.
• The system is simple, flexible, and requires no additional burden on healthcare providers.