The sensitivity, specificity and timeliness of syndromic surveillance
PHE ePoster Library. Morbey R. Sep 10, 2018; 221203; 169
Dr. Roger Morbey
Dr. Roger Morbey
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Abstract
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Abstract Public health decision makers need to understand what surveillance systems can and cannot detect. For traditional laboratory-based surveillance, we can easily calculate sensitivity and specificity. However, for syndromic surveillance calculating detection capabilities is much more complex. Syndromic surveillance aims to detect infectious disease and the impacts of environmental exposures, or mass-gatherings. Due to these broad aims, we analyse general symptoms, e.g. consultations for fever or diarrhoea. Unlike laboratory surveillance, we cannot attribute syndromic data to a single specific cause. Therefore, it is difficult to create a single statistic for syndromic sensitivity or specificity.PHE's syndromic surveillance involves daily data quality checks, automated statistical tests, prioritisation rules and input from epidemiological scientists. Detection does not just depend on a statistical test's effectiveness. Therefore, we decided to use a 'systems thinking' approach to describe our detection capabilities. We considered, the different aims of syndromic surveillance, all the surveillance stages, and the existing evidence for detection capabilities. By not just focussing on statistical algorithms we are able to provide more relevant assessments of our detection capabilities. Also, by considering each stage in our process we can quantify and understand the factors, like coding and risk assessment, that affect detection.We created a framework to communicate to our stakeholders what we can and cannot detect. Users will be able to choose an 'event' e.g. cryptosporidium outbreak and see what relevant evidence exists, with links to published research. This framework will also aid future research priorities by highlighting areas where evidence is lacking.
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