Syndromic surveillance: Two decades experience of sustainable systems – Its people not just data!

Gillian Smith, Alex Elliot, Iain Lake, Obaghe Edeghere, Roger Morbey, Mike Catchpole, David L. Heymann, Jeremy Hawker, Sue Ibbotson, Brian McCloskey, Richard Pebody, Amardeep Bains, Sally Harcourt, Helen Hughes, Winnie Lee, Paul Loveridge, Sue Smith, Ana Soriano

Research output: Contribution to journalReview articlepeer-review

4 Citations (Scopus)

Abstract

Syndromic surveillance is a form of surveillance that generates information for public health action by collecting, analysing and interpreting routine health-related data on symptoms and clinical signs reported by patients and clinicians rather than being based on microbiologically or clinically confirmed cases. In England, a suite of national real-time syndromic surveillance systems (SSS) have been developed over the last 20 years, utilising data from a variety of health care settings (a telehealth triage system, general practice and emergency departments). The real-time systems in England have been used for early detection (e.g. seasonal influenza), for situational awareness (e.g. describing the size and demographics of the impact of a heatwave) and for reassurance of lack of impact on population health of mass gatherings (e.g. the London 2012 Olympic and Paralympic Games).We highlight the lessons learnt from running SSS, for nearly two decades, and propose questions and issues still to be addressed. We feel that syndromic surveillance is an example of the use of ‘big data’, but contend that the focus for sustainable and useful systems should be on the added value of such systems and the importance of people working together to maximise the value for the public health of syndromic surveillance services.

Original languageEnglish
Article numbere101
JournalEpidemiology and Infection
Volume147
DOIs
Publication statusPublished - 2019

Keywords

  • Public health
  • Real-time
  • Syndromic surveillance

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