This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 42
Type: Contributed
Date/Time: Sunday, August 1, 2010 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #308590
Title: A Bayesian Surveillance System for Detecting Clusters of Noninfectious Diseases
Author(s): Albert Y. Kim*+
Companies: University of Washington
Address: Department of Statistics, Seattle, WA, 98195,
Keywords: cluster detection ; spatial epidemiology ; bayesian modeling ; cancer ; surveillance
Abstract:

We consider the problem of detecting spatial clusters of non-infectious, rare diseases. Cluster detection is the routine surveillance over a large expanse of small administrative regions to identify 'hot-spots' of elevated residual spatial risk of disease, without any preconceptions about their locations. We propose a Bayesian framework for modeling disease clusters where potential clusters are enumerated by a moving-window method, with a mixture prior on the underlying relative risks. The model accounts for prior knowledge on the spatial clustering of the disease, the numbers of potential clusters, and boundary effects. The methodology is applied to the Surveillance, Epidemiology and End Results (SEER) program database of cancers for the 13 counties in Western Washington.


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