Success Factors of European Syndromic Surveillance Systems: A Worked Example of Applying Qualitative Comparative Analysis

Abstract

IntroductionSyndromic surveillance aims at augmenting traditional public health surveillance with timely information. To gain a head start, it mainly analyses existing data such as from web searches or patient records. Despite the setup of many syndromic surveillance systems, there is still much doubt about the benefit of the approach. There are diverse interactions between performance indicators such as timeliness and various system characteristics. This makes the performance assessment of syndromic surveillance systems a complex endeavour. We assessed if the comparison of several syndromic surveillance systems through Qualitative Comparative Analysis helps to evaluate performance and identify key success factors.Materials and MethodsWe compiled case-based, mixed data on performance and characteristics of 19 syndromic surveillance systems in Europe from scientific and grey literature and from site visits. We identified success factors by applying crisp-set Qualitative Comparative Analysis. We focused on two main areas of syndromic surveillance application: seasonal influenza surveillance and situational awareness during different types of potentially health threatening events.ResultsWe found that syndromic surveillance systems might detect the onset or peak of seasonal influenza earlier if they analyse non-clinical data sources. Timely situational awareness during different types of events is supported by an automated syndromic surveillance system capable of analysing multiple syndromes. To our surprise, the analysis of multiple data sources was no key success factor for situational awareness.ConclusionsWe suggest to consider these key success factors when designing or further developing syndromic surveillance systems. Qualitative Comparative Analysis helped interpreting complex, mixed data on small-N cases and resulted in concrete and practically relevant findings.

Influenza and other respiratory viruses: standardizing disease severity in surveillance and clinical trials

“…Hospitalbased surveillance of respiratory viral infections is of great value to understand the full disease spectrum, from mild symptoms to serious presentations. Children are the most avid transmitters of respiratory viral infections, and the information gained from syndromic surveillance in children's hospitals can complement decentralized sentinel surveillance systems in a meaningful way [133]. With the advent of rapid diagnostics and mobile health applications, it has now become possible to monitor virological and clinical end points in real time [134][135][136][137][138][139][140].…”

Syndromic Surveillance Systems for Mass Gatherings: A Scoping Review

“…Previous research has examined the potential for syndromic surveillance to detect disease outbreaks earlier than other forms of public health surveillance [7,38]. In the present review, the evidence to support these claims is limited with regard to a mass gathering scenario.…”

“…A provisional diagnosis, or "syndrome," can be established via the synthesis of clinical features, disease trends, and surrogate measures (e.g., derived from pharmaceutical sales and doctor visits, among others) [6]. Syndromic surveillance has been shown to be a potentially effective method for the early detection of seasonal outbreaks of influenza as well as other pathogens, and previous research has shown the viability of this surveillance strategy for detecting larger outbreaks (>1000 symptomatic cases) [7,8]. Additionally, syndromic surveillance is potentially useful in occupational scenarios, where emerging threats such as COVID-19 or influenza pose a risk to workplace staff [9,10].…”

Partnering for enhanced digital surveillance of influenza‐like disease and the effect of antivirals and vaccines (PEDSIDEA)

“…The successful PEDSIDEA pilot programme demonstrates that surveillance systems for influenza can be set‐up quickly enabling individualized patient data analysis in epi/pandemics . Stakeholders will receive real‐time information on influenza incidence and severity, allowing the allocation of resources where they are most in need.…”

“…This paper aims to present a simple, standardized way of measuring clinical outcomes in children at the time of initial presentation to allow for meaningful comparisons across clinical settings. It invites other clinicians to use these standardized measures as well, to improve the monitoring of quality of care, to understand overall disease burden and the prevalence of risk factors, and finally, to explore the relationship between severity and prescribing practices, cost, and other outcome measures of interest.The successful PEDSIDEA pilot programme demonstrates that surveillance systems for influenza can be set-up quickly enabling individualized patient data analysis in epi/pandemics 3,22. Stakeholders will receive real-time information on influenza incidence and severity, allowing the allocation of resources where they are most in need.…”