Statistics Across Campuses: Jun Zhu -- Change-set analysis for spatial clustering in environmental health

Change-set analysis for spatial clustering in environmental health 

Date: 20 November 2020, Friday 

Time: 10am AEDT 

Speaker: Prof Jun Zhu (University of Wisconsin-Madison) 

Abstract: 

Mapping of disease incidence is of importance to environmental health.  In this talk, we
consider identification of clusters of spatial units with elevated disease rates and
develop a new approach that estimates the relative disease risk in association with
potential environmental risk factors and simultaneously identifies clusters
corresponding to elevated risks.  A heterogeneity measure is proposed to enable the
comparison of a candidate cluster and its complement under a pair of complementary
models.  A quasi-likelihood procedure is developed for estimating the model parameters
and identifying the clusters.  An advantage of our approach over traditional spatial
clustering methods is the identification of clusters that can have arbitrary shapes due
to abrupt or non-contiguous changes while accounting for risk factors and spatial
correlation.  Asymptotic properties of the proposed methodology are established and a
simulation study shows empirically sound finite-sample properties.  The mapping and
clustering of enterovirus 71 infection in Taiwan are carried out for illustration.  

Link: https://au.bbcollab.com/guest/fcf219c74ac743e89565a9e6e8d349a9