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
* Auteur correspondant
1 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
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
Type de document :
Article dans une revue
Annals Of Applied Statistics, Institute Mathematical Statistics, 2013, 7 (2), pp.1192-1216. 〈10.1214/13-AOAS629〉
Liste complète des métadonnées

Littérature citée [18 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-00839184
Contributeur : Florence Forbes <>
Soumis le : jeudi 27 juin 2013 - 13:20:29
Dernière modification le : vendredi 24 novembre 2017 - 13:30:52
Document(s) archivé(s) le : mercredi 5 avril 2017 - 04:29:41

Fichier

AOAS629publie.pdf
Fichiers éditeurs autorisés sur une archive ouverte

Identifiants

Collections

Citation

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 Mathematical Statistics, 2013, 7 (2), pp.1192-1216. 〈10.1214/13-AOAS629〉. 〈hal-00839184〉

Partager

Métriques

Consultations de la notice

368

Téléchargements de fichiers

849