title: An open source environment for the statistical evaluation of outbreak detection methods.
abstract: We describe the design and initial steps to implementation of a computational framework for evaluating outbreak detection methods. The framework will include components for combining simulated and historical data to create artificial outbreaks and components that implement various outbreak detection algorithms. The first algorithms to be implemented are the three Cumulative Sums (cusum) methods described in the CDC Early Aberration Reporting System.
authors.affiliation: Department of Biostatistics, Seattle, Washington, USA.
authors.forename: Thomas
authors.initials: T
authors.lastname: Lumley
authors.forename: Krisztian
authors.initials: K
authors.lastname: Sebestyen
authors.forename: William B
authors.initials: WB
authors.lastname: Lober
authors.forename: Ian
authors.initials: I
authors.lastname: Painter
mesh_terms: D000465:Algorithms; D004196:Disease Outbreaks; D006801:Humans; D015233:Models, Statistical; D011159:Population Surveillance / Q000379:methods*; D011381:Programming Languages; D040442:Public Health Informatics