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

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.

Outbreak of Severe Vomiting in Dogs Associated with a Canine Enteric Coronavirus, United Kingdom

“…Such syndromic surveillance is increasingly being used to monitor the impact of national events like natural disasters and bioterrorism on human population health, as well as changes in gastroenteric and influenza-like illness (6)(7)(8)(9). Such data can be simple to collect, provide real-time wide geographic coverage, and be flexibly applied to different conditions (10,11). Although in some cases these data can identify outbreaks earlier than more active surveillance, their predictive value can sometimes be low, particularly where there is a low signal to noise complaint ratio.…”

“…Data can be collected at great scale and analyzed in nearreal time. EHR data are now routinely used in human heath efforts (5)(6)(7)(8), in which their timeliness, simplicity, and breadth of coverage complements surveillance based on diagnostic data (9,10). Such approaches are beginning to find healthcare value in veterinary species, especially among companion animals (4,(11)(12)(13), a high proportion of which visit veterinarians (14).…”

Changes in public preferences for technologically enhanced surveillance following the COVID-19 pandemic: a discrete choice experiment

“…Several factors influence social licence for novel uses of personal and health data, 19 including for surveillance. 20 The impact of these factors is unlikely to be homogenous, and may be conditional on individuals’ circumstances and contexts. In Australia, previous research has focused on the perspectives of public health practitioners and policymakers, 21–23 and, recently, informed citizens.…”

The impact of the COVID-19 pandemic on gastrointestinal infection trends in England, February – July 2020

“…A retrospective ecological study was conducted by performing secondary analyses on routinely collected national and regional surveillance data from eight national PHE coordinated surveillance systems, detailed in Table 1, and Google Trend data. Systems included outbreak monitoring (HPzone), laboratory notifications Second Generation Surveillance System, (SGSS) and EpiNorth3, and real-time syndromic surveillance [11][12][13].…”

“…Syndromic systems covered the spectrum of severity ranging from the NHS 111 telephone health advice service and routine medical appointments captured in the general practitioner (GP) 'in hours' system (GPIH), to GP 'out of hours', which covers emergency GP appointments for acute or severe illness and the Emergency Department Syndromic Surveillance System (EDSSS), which captures those attending EDs [13].…”