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Early Detection of Outbreaks Using the BioDefend™
Syndromic Surveillance System --- Florida, May 2002--July 2004
Kristin B. Uhde,1 C.
Farrell,1 Y. Geddie,2 M. Leon,3 J.
Cattani1
1University of South Florida, Tampa, Florida;
2MacDill Air Force Base, Tampa, Florida;
3Celebration Research Institute, Celebration, Florida
Corresponding author: Corey L. Farrell, University of South Florida, 3602 Spectrum Blvd., Tampa, FL 33612. Telephone: 813-974-1473; Fax: 813-974-1479; E-mail: cfarrell@bt.usf.edu.
Disclosure of relationship: The contributors of this report have disclosed that they have no financial interest, relationship, affiliation, or other association with any organization that might represent a conflict of interest. In addition, this report does not contain any discussion
of unlabeled use of commercial products or products for investigational use.
Abstract
Introduction: The threat of biologic terrorism (BT) requires the public health infrastructure to
focus attention on challenges posed by emerging and re-emerging infectious diseases. Validating realtime approaches to
surveillance that can provide timely alerts of epidemics is critical whether the epidemics occur naturally or through a BT attack.
Objectives: This research study implemented and evaluated the BioDefend™ syndromic surveillance system
to determine if outbreaks and potential BT attacks could be detected 24--36 hours before routine surveillance and if syndromic surveillance is a feasible approach for BT preparedness and early detection of infectious disease.
Methods: The study was conducted in central Florida high-risk facilities (i.e., theme parks,
hospitals, and a military base). A 6-month period of baseline data was collected to identify normal illness trends and seasonality patterns and to serve as the comparison for the test period. Internet-based data entry of provider-identified syndromes was
linked to an automated analysis tool that provided alerts through an e-mail--enabled device when substantial increases
of syndromes exceeded the pre-established thresholds. Thresholds are based on a 30-day rolling
mean, and
alerts
were generated when any syndrome exceeded three standard deviations above the 30-day rolling mean.
Results: Outbreaks of public health importance were detected by comparing the BioDefend™ data with regional, state, and national surveillance data. Two epidemics, one of gastroenteritis and one of influenza-like illness, were detected by BioDefend™ >1 month before identification through routine surveillance. In addition, a small
cluster of cases (five) of fifth disease was identified among South American children visiting central Florida theme parks.
Conclusion: This study indicated that health events can0 be recognized in near real-time through the use
of automated analysis and notification. Early detection of events allowed for timely interventions, including vaccination campaigns at military and civilian hospitals, and it demonstrated one way
that syndromic
surveillance can be an effective tool for early detection of outbreaks in addition to its potential role in BT preparedness.
The system continues to be used in central Florida and was implemented for the 2005 Super Bowl.
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