Abstract
Motivation: Syndromic surveillance is the real-time collection and interpretation of data to allow the early identification of public health threats and their impact, enabling public health action. The 'rising activity, multi-level mixed effects, indicator emphasis' method was developed to provide a single robust method enabling detection of unusual activity across a wide range of syndromes, nationally and locally. Results: The method is shown here to have a high sensitivity (92%) and specificity (99%) compared to previous methods, whilst halving the time taken to detect increased activity to 1.3 days. Availability and implementation: The method has been applied successfully to syndromic surveillance systems in England providing realistic models for baseline activity and utilizing prioritization rules to ensure a manageable number of 'alarms' each day.
Original language | English |
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Pages (from-to) | 3660-3665 |
Number of pages | 6 |
Journal | Bioinformatics |
Volume | 31 |
Issue number | 22 |
DOIs | |
Publication status | Published - 25 May 2015 |
Bibliographical note
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