title: Automated biosurveillance data from England and Wales, 1991-2011.
abstract: Outbreak detection systems for use with very large multiple surveillance databases must be suited both to the data available and to the requirements of full automation. To inform the development of more effective outbreak detection algorithms, we analyzed 20 years of data (1991-2011) from a large laboratory surveillance database used for outbreak detection in England and Wales. The data relate to 3,303 distinct types of infectious pathogens, with a frequency range spanning 6 orders of magnitude. Several hundred organism types were reported each week. We describe the diversity of seasonal patterns, trends, artifacts, and extra-Poisson variability to which an effective multiple laboratory-based outbreak detection system must adjust. We provide empirical information to guide the selection of simple statistical models for automated surveillance of multiple organisms, in the light of the key requirements of such outbreak detection systems, namely, robustness, flexibility, and sensitivity.
authors.affiliation: Open University, Milton Keynes, UK.
authors.forename: Doyo G
authors.initials: DG
authors.lastname: Enki
authors.forename: Angela
authors.initials: A
authors.lastname: Noufaily
authors.forename: Paul H
authors.initials: PH
authors.lastname: Garthwaite
authors.forename: Nick J
authors.initials: NJ
authors.lastname: Andrews
authors.forename: André
authors.initials: A
authors.lastname: Charlett
authors.forename: Chris
authors.initials: C
authors.lastname: Lane
authors.forename: C Paddy
authors.initials: CP
authors.lastname: Farrington
mesh_terms: D000465:Algorithms; D001331:Automation; D001419:Bacteria / Q000254:growth & development; D001424:Bacterial Infections / Q000453:epidemiology*; D058491:Bacterial Load; D055877:Biosurveillance / Q000379:methods*; D015169:Colony Count, Microbial; D004196:Disease Outbreaks; D004739:England / Q000453:epidemiology; D005658:Fungi / Q000254:growth & development; D006801:Humans; D015994:Incidence; D015233:Models, Statistical; D009181:Mycoses / Q000453:epidemiology*; D040442:Public Health Informatics / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014777:Virus Diseases / Q000453:epidemiology*; D014780:Viruses / Q000254:growth & development; D014852:Wales / Q000453:epidemiology