TY - JOUR
AU - Beneš, Viktor
AU - Bodlák, Karel
AU - Møller, Jesper
AU - Waagepetersen, Rasmus
PY - 2011/05/03
Y2 - 2024/08/08
TI - A CASE STUDY ON POINT PROCESS MODELLING IN DISEASE MAPPING
JF - Image Analysis and Stereology
JA - Image Anal Stereol
VL - 24
IS - 3
SE - Original Research Paper
DO - 10.5566/ias.v24.p159-168
UR - https://www.ias-iss.org/ojs/IAS/article/view/783
SP - 159-168
AB - We consider a data set of locations where people in Central Bohemia have been infected by tick-borne encephalitis (TBE), and where population census data and covariates concerning vegetation and altitude are available. The aims are to estimate the risk map of the disease and to study the dependence of the risk on the covariates. Instead of using the common area level approaches we base the analysis on a Bayesian approach for a log Gaussian Cox point process with covariates. Posterior characteristics for a discretized version of the log Gaussian Cox process are computed using Markov chain Monte Carlo methods. A particular problem which is thoroughly discussed is to determine a model for the background population density. The risk map shows a clear dependency with the population intensity models and the basic model which is adopted for the population intensity determines what covariates influence the risk of TBE. Model validation is based on the posterior predictive distribution of various summary statistics.
ER -