An Improved Algorithm for Outbreak Detection in Multiple Surveillance Systems
PDF
HTML

How to Cite

Noufaily, A., Enki, D., Farrington, P., Garthwaite, P., Andrews, N., & Charlett, A. (2013). An Improved Algorithm for Outbreak Detection in Multiple Surveillance Systems. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4497

Abstract

A large scale multiple statistical surveillance system for infectious disease outbreaks has been in operation in England and Wales for nearly two decades. This system uses a robust quasi-Poisson regression algorithm to identify aberrances in weekly counts of isolates reported to the Health Protection Agency. We review the performance of the system to reduce the number of false reports, while retaining good power to detect genuine outbreaks. Several improvements are suggested relating to the treatment of trends, seasonality, reweighting of baselines and error structure. The new system greatly reduces the numbers of alarms while maintaining good overall performance.
https://doi.org/10.5210/ojphi.v5i1.4497
PDF
HTML
Authors own copyright of their articles appearing in the Online Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes. Share-alike: when posting copies or adaptations of the work, release the work under the same license as the original. For any other use of articles, please contact the copyright owner. The journal/publisher is not responsible for subsequent uses of the work, including uses infringing the above license. It is the author's responsibility to bring an infringement action if so desired by the author.