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Draft framework for evaluating syndromic surveillance systems.

Daniel M Sosin1

  • 1Division of Public Health Surveillance and Informatics, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA.

Journal of Urban Health : Bulletin of the New York Academy of Medicine
|June 7, 2003
PubMed
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A new framework evaluates syndromic surveillance systems for public health, aiding in terrorism preparedness and outbreak detection using nontraditional data. This systematic approach guides development and research priorities for enhanced disease surveillance.

Area of Science:

  • Public Health
  • Epidemiology
  • Biosecurity

Background:

  • Growing interest in public health surveillance for terrorism-related outbreaks.
  • Need for systematic evaluation of nontraditional data sources in surveillance systems.

Purpose of the Study:

  • To introduce a draft framework for evaluating syndromic surveillance systems.
  • To guide researchers and practitioners in developing and maintaining surveillance systems.
  • To identify and prioritize research and evaluation needs in public health surveillance.

Main Methods:

  • Development of a five-component evaluation framework.
  • Framework includes system description, performance, outbreak detection capacity, and data quality assessment.
  • Emphasis on adaptability, sensitivity, predictive value, and timeliness for outbreak detection.

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Main Results:

  • The framework provides a systematic approach for reviewing and communicating surveillance system efforts.
  • It facilitates comparison and decision-making regarding the development and maintenance of syndromic surveillance systems.
  • The framework aids in prioritizing research and evaluation needs for terrorism preparedness.

Conclusions:

  • The draft framework offers guidance for public health practice in terrorism preparedness and outbreak detection.
  • It is intended to evolve into comprehensive guidance for surveillance system development and evaluation.
  • The framework supports the effective use of nontraditional data sources for public health surveillance.