Systematic Review: Surveillance Systems for Early Detection of Bioterrorism-Related Diseases

1 June 2004 | Volume 140 Issue 11 | Pages 910-922

Background: Given the threat of bioterrorism and the increasing availability of electronic data for surveillance, surveillance systems for the early detection of illnesses and syndromes potentially related to bioterrorism have proliferated.

Purpose: To critically evaluate the potential utility of existing surveillance systems for illnesses and syndromes related to bioterrorism.

Data Sources: Databases of peer-reviewed articles (for example, MEDLINE for articles published from January 1985 to April 2002) and Web sites of relevant government and nongovernment agencies.

Study Selection: Reports that described or evaluated systems for collecting, analyzing, or presenting surveillance data for bioterrorism-related illnesses or syndromes.

Data Extraction: From each included article, the authors abstracted information about the type of surveillance data collected; method of collection, analysis, and presentation of surveillance data; and outcomes of evaluations of the system.

Data Synthesis: 17 510 article citations and 8088 government and nongovernmental Web sites were reviewed. From these, the authors included 115 systems that collect various surveillance reports, including 9 syndromic surveillance systems, 20 systems collecting bioterrorism detector data, 13 systems collecting influenza-related data, and 23 systems collecting laboratory and antimicrobial resistance data. Only the systems collecting syndromic surveillance data and detection system data were designed, at least in part, for bioterrorism preparedness applications. Syndromic surveillance systems have been deployed for both event-based and continuous bioterrorism surveillance. Few surveillance systems have been comprehensively evaluated. Only 3 systems have had both sensitivity and specificity evaluated.

Limitations: Data from some existing surveillance systems (particularly those developed by the military) may not be publicly available.

Conclusions: Few surveillance systems have been specifically designed for collecting and analyzing data for the early detection of a bioterrorist event. Because current evaluations of surveillance systems for detecting bioterrorism and emerging infections are insufficient to characterize the timeliness or sensitivity and specificity, clinical and public health decision making based on these systems may be compromised.

Author and Article Information

From the University of California, San Francisco–Stanford Evidence-based Practice Center and Center for Primary Care and Outcomes Research, Stanford University School of Medicine, Stanford, California; Veterans Affairs Palo Alto Healthcare System, Palo Alto, California; and Kaiser Permanente, Redwood City, California.

Acknowledgments: The authors thank Emilee Wilhelm and Vandana Sundaram for their assistance preparing this manuscript. They also recognize the contributions of the Stanford University research librarians who helped them design their search strategies: Rikke Greenwald (Lane Medical Library), Ann Latta (Social Sciences Resource Center), Joan Loftus (U.S. Government Documents Bibliographer), and Michael Newman (Falconer Biology Library).

Grant Support: This work was performed by the University of California, San Francisco–Stanford Evidence-based Practice Center under contract to the Agency for Healthcare Research and Quality (contract no. 290-97-0013). The project also was supported in part by the U.S. Department of Veterans Affairs.

Potential Financial Conflicts of Interest: None disclosed.

Requests for Single Reprints: Dena M. Bravata, MD, MS, Center for Primary Care and Outcomes Research, 117 Encina Commons, Stanford, CA 94305-6019; e-mail, bravata{at}healthpolicy.stanford.edu.

Current Author Addresses: Drs. Bravata, Haberland, and Owens and Ms. McDonald, Ms. Smith, and Ms. Rydzak: Center for Primary Care and Outcomes Research, 117 Encina Commons, Stanford, CA 94305-6019.

Dr. Szeto: Department of Medicine, Kaiser Permanente, 1150 Veterans Boulevard, Redwood City, CA 94063.

Dr. Buckeridge: Stanford Medical Informatics, 251 Campus Drive, MSOB X215, Stanford, CA 94305-5479.