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This Article Full Text Full Text (PDF) All Versions of this Article: AJPH.2008.133926v1 99/8/1360    most recent Submit a response View Shopping Cart Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Google Scholar Articles by Chretien, J.-P. Articles by Kelley, P. W. PubMed PubMed Citation Articles by Chretien, J.-P. Articles by Kelley, P. W. Related Collections Public Health Practice Government Surveillance

Jean-Paul Chretien, MD, PhD, Nancy E. Tomich, BS, Joel C. Gaydos, MD, MPH and Patrick W. Kelley, MD, DrPH

At the time of writing, Jean-Paul Chretien and Joel C. Gaydos were with the Department of Defense Global Emerging Infections Surveillance and Response System, Silver Spring, MD. Nancy E. Tomich is with the Institute of Federal Health Care, Washington, DC. Patrick W. Kelley is with the Institute of Medicine, National Academy of Sciences, Washington, DC.

Correspondence: Correspondence should be sent to Jean-Paul Chretien, Division of Preventive Medicine, Walter Reed Army Institute of Research, 503 Robert Grant Ave, Silver Spring, MD 20910 (e-mail: jeanpaul.chretien{at}us.army.mil). Reprints can be ordered at http://www.ajph.org by clicking on the "Reprints/Eprints" link.

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.