Evaluation of Syndromic Surveillance Systems in 6 US State and Local Health Departments
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Evaluation of Syndromic Surveillance Systems in 6 US State and Local Health Departments

  • Published Date:

    2018 May/Jun

  • Source:
    J Public Health Manag Pract. 24(3):235-240.
  • Language:
Filetype[PDF-59.84 KB]

  • Alternative Title:
    J Public Health Manag Pract
  • Description:
    Objective: Evaluating public health surveillance systems is critical to ensuring that conditions of public health importance are appropriately monitored. Our objectives were to qualitatively evaluate 6 state and local health departments that were early adopters of syndromic surveillance in order to (1) understand the characteristics and current uses, (2) identify the most and least useful syndromes to monitor, (3) gauge the utility for early warning and outbreak detection, and (4) assess how syndromic surveillance impacted their daily decision making. Design: We adapted evaluation guidelines from the Centers for Disease Control and Prevention and gathered input from CDC subject matter experts in public health surveillance to develop a questionnaire. Participants: We interviewed staff members from a convenience sample of 6 local and state health departments with syndromic surveillance programs that had been in operation for >10 years. Results: Three of the 6 interviewees provided an example of using syndromic surveillance to identify an outbreak (ie, cluster of foodborne illness in 1 jurisdiction) or detect a surge in cases for seasonal conditions (eg, influenza in 2 jurisdictions) prior to traditional, disease-specific systems. Although all interviewees noted that syndromic surveillance has not been routinely useful or efficient for early outbreak detection or case finding in their jurisdictions, all agreed that the information can be used to improve their understanding of dynamic disease control environments and conditions (eg, situational awareness) in their communities. Conclusion: In the jurisdictions studied, syndromic surveillance may be useful for monitoring the spread and intensity of large outbreaks of disease, especially influenza; enhancing public health awareness of mass gatherings and natural disasters; and assessing new, otherwise unmonitored conditions when real-time alternatives are unavailable. Future studies should explore opportunities to strengthen syndromic surveillance by including broader access to and enhanced analysis of text-related data from electronic health records.
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