title: Incorporating retrospective clustering into a prospective Cusum methodology for anthrax: evaluating the effects of disease expectation.
abstract: We analysed livestock anthrax in Kazakhstan from 1960-2006, using a prospective CUSUM to examine the affects of expectation on the detection of spatio-temporal clusters. Three methods for deriving baselines were used for CUSUM; a standard z-score, AVG, a spatially-weighted z-score derived from Local Moran's I, LISA, and a moving-window average, MWA. LISA and AVG elicited alarm signals in the second year that did not return below threshold during the 47-year period, while MWA signaled an alarm at year four and relented at year fifteen. The number of spatial clusters elicited varied: LISA n=16, AVG n=11, and MWA n=3, although there were clusters present around Shymkent, in south-central Kazakhstan, in each method. The results illustrate that the selection of a baseline with an unknown background population has a significant effect on the ability to detect the onset of clusters in space and in time when employing a CUSUM methodology.
authors: Spatial Epidemiology and Ecology Research Laboratory, Emerging Pathogens Institute and Department of Geography, University of Florida, Gainesville, Florida, USA. itk@ufl.edu
authors: Ian
authors: I
authors: Kracalik
authors: Larissa
authors: L
authors: Lukhnova
authors: Alim
authors: A
authors: Aikimbayev
authors: Yerlan
authors: Y
authors: Pazilov
authors: Gulnara
authors: G
authors: Temiralyeva
authors: Jason K
authors: JK
authors: Blackburn
mesh_terms: D000818:Animals; D000881:Anthrax / Q000453:epidemiology* / Q000662:veterinary; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D004196:Disease Outbreaks / Q000706:statistics & numerical data* / Q000662:veterinary; D062306:Geography, Medical / Q000379:methods / Q000706:statistics & numerical data; D007623:Kazakhstan / Q000453:epidemiology; D058751:Livestock; D011446:Prospective Studies; D012189:Retrospective Studies; D062211:Spatio-Temporal Analysis