Spatial modelling of lupus incidence over 40 years with changes in census areas

Ye Li*, Patrick Brown, Håvard Rue, Mustafa Al-Maini, Paul Fortin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Clinical data on the location of residence at the time of diagnosis of new lupus cases in Toronto, Canada, for the 40 years to 2007 are modelled with the aim of finding areas of abnormally high risk. Inference is complicated by numerous irregular changes in the census regions on which population is reported. A model is introduced consisting of a continuous random spatial surface and fixed effects for time and ages of individuals. The process is modelled on a fine grid and Bayesian inference performed by using integrated nested Laplace approximations. Predicted risk surfaces and posterior probabilities of exceedance are produced for lupus and, for comparison, psoriatic arthritis data from the same clinic. Simulations studies are also carried out to understand better the performance of the model proposed as well as to compare with existing methods.

Original languageEnglish (US)
Pages (from-to)99-115
Number of pages17
JournalJournal of the Royal Statistical Society. Series C: Applied Statistics
Volume61
Issue number1
DOIs
StatePublished - Jan 2012
Externally publishedYes

Keywords

  • Bayesian inference
  • Changing boundaries
  • Disease mapping
  • Integrated nested Laplace approximation

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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