Syndromic surveillance: two decades experience of sustainable systems - its people not just data!

Gillian E Smith,Obaghe Edeghere,Mike Catchpole,Sue Ibbotson,David L Heymann,Richard Pebody,Iain Lake,Alex J Elliot,Roger Morbey,Jeremy Hawker,Brian Mccloskey

doi:10.1017/s0950268819000074

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.

Highlights

In England, a suite of national real-time SSS have been developed incrementally since 1998, utilising data from a variety of health care settings
Syndromic surveillance is a form of surveillance that generates information for public health action by collecting, analysing and interpreting routine health-related data
Little has been published on the practical experience of establishing and operating such systems, and on how the outputs of SSS can be integrated into wider public health action and response

Summary

Lessons learnt for syndromic surveillance

Whilst developing and using SSS, we have learnt a number of lessons which may be of value for those planning for, establishing and maintaining such systems. In a similar need-driven way, the emergency department surveillance system in France followed the necessity (identified in the 2003 heatwave) to monitor, in real-time, the extreme effects of heat [22] While in both these instances, the individual events gave impetus to (and resources for) the development of the systems (with both continuing to provide surveillance for a wide range of public health threats), a general public health need can be a driver for developing such systems. This is fortuitous for syndromic surveillance in that we are able to work with health service managers to obtain national real-time data (e.g. NHS 111 data encompass the whole of England) This is helpful for surveillance as we only need to negotiate with one organisation, even if other stakeholders need to be consulted, and is a public service that has public health responsibilities in addition to clinical ones (in contrast with countries with numerous private providers of clinical services). We suggest the focus should primarily be on the questions and use for real-time syndromic surveillance, and the acquisition of larger and more diverse datasets and algorithms should follow to support, rather than the surveillance being driven by the data sources

Questions and issues still to be tackled in syndromic surveillance

Summary