Journal of the American Medical Informatics Association · 2003 · 413 citations · 69 references
Public HealthInfectious DiseasesPublic Health PracticeEarly DetectionPublic Health SurveillanceSyndromic SurveillanceDisease Surveillance SystemsHealth SurveillanceIndicator-based SurveillanceSurveillance EvaluationSurveillance MethodsEarly Case DetectionPublic Health Indicators
Syndromic surveillance uses early health indicators—behavioral patterns, symptoms, and laboratory findings—before laboratory confirmation to detect outbreaks, originally aimed at bioterrorism but also applicable to general public health, clinical medicine, quality improvement, patient safety, and research. This report serves as a practical guide for informaticians, public health managers, and practitioners planning the deployment of syndromic surveillance systems.
Syndromic surveillance refers to methods relying on detection of individual and population health indicators that are discernible before confirmed diagnoses are made. In particular, prior to the laboratory confirmation of an infectious disease, ill persons may exhibit behavioral patterns, symptoms, signs, or laboratory findings that can be tracked through a variety of data sources. Syndromic surveillance systems are being developed locally, regionally, and nationally. The efforts have been largely directed at facilitating the early detection of a covert bioterrorist attack, but the technology may also be useful for general public health, clinical medicine, quality improvement, patient safety, and research. This report, authored by developers and methodologists involved in the design and deployment of the first wave of syndromic surveillance systems, is intended to serve as a guide for informaticians, public health managers, and practitioners who are currently planning deployment of such systems in their regions.
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Time Series Analysis: Forecasting and Control
Michael D. Geurts, George E. P. Box, Gwilym M. Jenkins · Journal of Marketing Research · 1977 · 19.3K citations
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The detection of disease clustering and a generalized regression approach.
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