The application of a novel ‘rising activity, multi-level mixed effects, indicator emphasis’ (RAMMIE) method for syndromic surveillance in England
Open Access
- 20 July 2015
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 31 (22), 3660-3665
- https://doi.org/10.1093/bioinformatics/btv418
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. Contact: roger.morbey@phe.gov.ukKeywords
This publication has 12 references indexed in Scilit:
- Development and refinement of new statistical methods for enhanced syndromic surveillance during the 2012 Olympic and Paralympic GamesHealth Informatics Journal, 2014
- Developing a new syndromic surveillance system for the London 2012 Olympic and Paralympic GamesEpidemiology and Infection, 2012
- Situational Awareness of Influenza Activity Based on Multiple Streams of Surveillance Data Using Multivariate Dynamic Linear ModelPLOS ONE, 2012
- Establishing an emergency department syndromic surveillance system to support the London 2012 Olympic and Paralympic GamesEmergency Medicine Journal, 2012
- Method selection and adaptation for distributed monitoring of infectious diseases for syndromic surveillanceJournal of Biomedical Informatics, 2011
- Assessment of syndromic surveillance in EuropeThe Lancet, 2011
- Statistical Methods for the Prospective Detection of Infectious Disease Outbreaks: A ReviewJournal of the Royal Statistical Society Series A: Statistics in Society, 2011
- Use of a large general practice syndromic surveillance system to monitor the progress of the influenza A(H1N1) pandemic 2009 in the UKEpidemiology and Infection, 2011
- Review of methods for space–time disease surveillanceSpatial and Spatio-temporal Epidemiology, 2010
- Use of hierarchical models to evaluate performance of cardiac surgery centres in the Italian CABG outcome studyBMC Medical Research Methodology, 2007