Skip to Main content Skip to Navigation
Journal articles

Spatial risk mapping for rare disease with hidden Markov fields and variational EM

Florence Forbes 1, * Myriam Charras-Garrido 2 Lamiae Azizi 1 Senan Doyle 1, * David Abrial 2
* Corresponding author
1 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, LJK - Laboratoire Jean Kuntzmann, Inria Grenoble - Rhône-Alpes
Abstract : Current risk mapping models for pooled data focus on the estimated risk for each geographical unit. A risk classification, that is, grouping of geographical units with similar risk, is then necessary to easily draw interpretable maps, with clearly delimited zones in which protection measures can be applied. As an illustration, we focus on the Bovine Spongiform Encephalopathy (BSE) disease that threatened the bovine production in Europe and generated drastic cow culling. This example features typical animal disease risk analysis issues with very low risk values, small numbers of observed cases and population sizes that increase the difficulty of an automatic classification.We propose to handle this task in a spatial clustering framework using a nonstandard discrete hidden Markov model prior designed to favor a smooth risk variation. The model parameters are estimated using an EM algorithm and a mean field approximation for which we develop a new initialization strategy appropriate for spatial Poisson mixtures. Using both simulated and our BSE data, we show that our strategy performs well in dealing with low population sizes and accurately determines high risk regions, both in terms of localization and risk level estimation
Complete list of metadata

Cited literature [18 references]  Display  Hide  Download
Contributor : Florence Forbes Connect in order to contact the contributor
Submitted on : Thursday, June 27, 2013 - 1:20:29 PM
Last modification on : Tuesday, October 19, 2021 - 11:13:05 PM
Long-term archiving on: : Wednesday, April 5, 2017 - 4:29:41 AM


Publisher files allowed on an open archive




Florence Forbes, Myriam Charras-Garrido, Lamiae Azizi, Senan Doyle, David Abrial. Spatial risk mapping for rare disease with hidden Markov fields and variational EM. Annals of Applied Statistics, Institute of Mathematical Statistics, 2013, 7 (2), pp.1192-1216. ⟨10.1214/13-AOAS629⟩. ⟨hal-00839184⟩



Les métriques sont temporairement indisponibles