Fast Bayesian Classification for Disease Mapping and the Detection of Disease Clusters

V. Gómez-Rubio (), John Molitor () and Paula Moraga ()
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V. Gómez-Rubio: Universidad de Castilla-La Mancha, Department of Mathematics, School of Industrial Engineering
John Molitor: Oregon State University, College of Public Health and Human Sciences
Paula Moraga: Lancaster University, Faculty of Health and Medicine

A chapter in Quantitative Methods in Environmental and Climate Research, 2018, pp 1-27 from Springer

Abstract: Abstract We propose a framework fast method for detecting clusters of disease based on generalized spatial scan statistics set in the context of Bayesian Hierarchical Models. The approach models spatio-temporal clusters of disease as dummy variables as part of a Generalized Linear Mixed Model.

Keywords: Spatial statistics; Disease clusters; Bayesian inference; Integrated nested Laplace approximation (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-01584-8_1

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DOI: 10.1007/978-3-030-01584-8_1

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