Issues in Bayesian prospective surveillance of spatial health data
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Published on: February 25, 2013
1Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC 29466, USA.
Abstract:
In this paper I review some of the major issues that arise when geo-referenced health data are to be the subject of prospective surveillance. The review focusses on modelbased approaches to this activity, and proposes the Bayesian paradigm as a convenient vehicle for modeling. Various posterior functional measures are discussed including the SCPO and SKL and a number of extensions to these are considered. Overall the value of Bayesian Hierarchical Modeling (BHM) with surveillance functionals is stressed in its relevance to early warning of adverse risk scenarios.
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