The application of a novel 'rising activity, multi-level mixed effects, indicator emphasis' (RAMMIE) method for syndromic surveillance in England

Bioinformatics. 2015 Nov 15;31(22):3660-5. doi: 10.1093/bioinformatics/btv418. Epub 2015 Jul 20.

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.uk.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Emergency Service, Hospital
  • England
  • Humans
  • Population Surveillance*
  • Predictive Value of Tests
  • Public Health