A simulation study comparing aberration detection algorithms for syndromic surveillance
Open Access
- 1 March 2007
- journal article
- research article
- Published by Springer Nature in BMC Medical Informatics and Decision Making
- Vol. 7 (1) , 6
- https://doi.org/10.1186/1472-6947-7-6
Abstract
The usefulness of syndromic surveillance for early outbreak detection depends in part on effective statistical aberration detection. However, few published studies have compared different detection algorithms on identical data. In the largest simulation study conducted to date, we compared the performance of six aberration detection algorithms on simulated outbreaks superimposed on authentic syndromic surveillance data.Keywords
This publication has 27 references indexed in Scilit:
- Factors affecting automated syndromic surveillanceArtificial Intelligence in Medicine, 2005
- Algorithms for rapid outbreak detection: a research synthesisJournal of Biomedical Informatics, 2005
- A Space–Time Permutation Scan Statistic for Disease Outbreak DetectionPLoS Medicine, 2005
- Comparing Aberration Detection Methods with Simulated DataEmerging Infectious Diseases, 2005
- A simulation model for assessing aberration detection methods used in public health surveillance for systems with limited baselinesStatistics in Medicine, 2005
- Syndromic Surveillance for Influenzalike Illness in Ambulatory Care SettingEmerging Infectious Diseases, 2004
- Syndromic Surveillance in Public Health Practice, New York CityEmerging Infectious Diseases, 2004
- Syndromic Surveillance: Is it Worth the Effort?CHANCE, 2004
- Use of Automated Ambulatory-Care Encounter Records for Detection of Acute Illness Clusters, Including Potential Bioterrorism EventsEmerging Infectious Diseases, 2002
- The Sverdlovsk Anthrax Outbreak of 1979Science, 1994