A two-stage approach to estimate spatial and spatio-temporal disease risks in the presence of local discontinuities and clusters
- 13 April 2018
- journal article
- conference paper
- Published by SAGE Publications in Statistical Methods in Medical Research
- Vol. 28 (9), 2595-2613
- https://doi.org/10.1177/0962280218767975
Abstract
Disease risk maps for areal unit data are often estimated from Poisson mixed models with local spatial smoothing, for example by incorporating random effects with a conditional autoregressive prior distribution. However, one of the limitations is that local discontinuities in the spatial pattern are not usually modelled, leading to over-smoothing of the risk maps and a masking of clusters of hot/coldspot areas. In this paper, we propose a novel two-stage approach to estimate and map disease risk in the presence of such local discontinuities and clusters. We propose approaches in both spatial and spatio-temporal domains, where for the latter the clusters can either be fixed or allowed to vary over time. In the first stage, we apply an agglomerative hierarchical clustering algorithm to training data to provide sets of potential clusters, and in the second stage, a two-level spatial or spatio-temporal model is applied to each potential cluster configuration. The superiority of the proposed approach with regard to a previous proposal is shown by simulation, and the methodology is applied to two important public health problems in Spain, namely stomach cancer mortality across Spain and brain cancer incidence in the Navarre and Basque Country regions of Spain.Keywords
This publication has 41 references indexed in Scilit:
- Spatio-temporal trends in gastric cancer mortality in Spain: 1975–2008Cancer Epidemiology, 2013
- A Bayesian model for cluster detectionBiostatistics, 2013
- Comparing CAR and P-spline models in spatial disease mappingEnvironmental and Ecological Statistics, 2012
- A P-spline ANOVA type model in space-time disease mappingStochastic Environmental Research and Risk Assessment, 2012
- Space-time Bayesian small area disease risk models: development and evaluation with a focus on cluster detectionEnvironmental and Ecological Statistics, 2008
- A flexibly shaped space-time scan statistic for disease outbreak detection and monitoringInternational Journal of Health Geographics, 2008
- Interpreting Posterior Relative Risk Estimates in Disease-Mapping StudiesEnvironmental Health Perspectives, 2004
- Bayesian Measures of Model Complexity and FitJournal of the Royal Statistical Society Series B: Statistical Methodology, 2002
- A spatial scan statisticCommunications in Statistics - Theory and Methods, 1997
- Objective Criteria for the Evaluation of Clustering MethodsJournal of the American Statistical Association, 1971