A new approach to investigating spatial variations of disease

Choo, Louise L. and Walker, Stephen G. (2008) A new approach to investigating spatial variations of disease. Journal of the Royal Statistical Society: Series A (Statistics in Society), 171 (2). pp. 395-405. ISSN 0964-1998 . (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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For rare diseases the observed disease count may exhibit extra Poisson variability, particularly in areas with low or sparse populations. Hence the variance of the estimates of disease risk, the standardized mortality ratios, may be highly unstable. This overdispersion must be taken into account otherwise subsequent maps based on standardized mortality ratios will be misleading and, rather than displaying the true spatial pattern of disease risk, the most extreme values will be highlighted. Neighbouring areas tend to exhibit spatial correlation as they may share more similarities than non-neighbouring areas. The need to address overdispersion and spatial correlation has led to the proposal of Bayesian approaches for smoothing estimates of disease risk. We propose a new model for investigating the spatial variation of disease risks in conjunction with an alternative specification for estimates of disease risk in geographical areas-the multivariate Poisson-gamma model. The main advantages of this new model lie in its simplicity and ability to account naturally for overdispersion and spatial auto-correlation. Exact expressions for important quantities such as expectations, variances and covariances can be easily derived.

Item Type: Article
Uncontrolled keywords: Bayesian statistics; conditional auto-regressive models; disease mapping; ecological studies; spatial epidemiology
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Judith Broom
Date Deposited: 27 Mar 2009 18:39
Last Modified: 29 Apr 2014 15:44
Resource URI: https://kar.kent.ac.uk/id/eprint/12610 (The current URI for this page, for reference purposes)
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