Spatially clustered associations in health GIS


Overlaying maps using a desktop GIS is often the first step of a multivariate spatial analysis. The potential of this operation has increased considerably as data sources and Web services to manipulate them are becoming widely available via the Internet. Standards from the OGC enable such geospatial mashups to be seamless and user driven, involving discovery of thematic data. The user is naturally inclined to look for spatial clusters and correlation of outcomes. Using classical cluster detection scan methods to identify multivariate associations can be problematic in this context, because of a lack of control on or knowledge about background populations. For public health and epidemiological mapping, this limiting factor can be critical but often the focus is on spatial identification of risk factors associated with health or clinical status. Spatial entropy index HSu for the ScankOO analysis of the hypothetical dataset using a vicinity which is fixed by the number of points without distinction between their labels. (The size of the labels is proportional to the inverse of the index) In this article we point out that this association itself can ensure some control on underlying populations, and develop an exploratory scan statistic framework for multivariate associations. Inference using statistical map methodologies can be used to test the clustered associations. The approach is illustrated with a hypothetical data example and an epidemiological study on community MRSA. Scenarios of potential use for online mashups are introduced but full implementation is left for further research.

Divisions: ?? 50811700Jl ??
College of Engineering & Physical Sciences > Sustainable environment research group
Event Title: 18th Annual Conference GIS Research UK 2010
Event Type: Other
Event Dates: 2010-04-14 - 2010-04-16
Uncontrolled Keywords: spatial clustering,multivariate associations,co-occurrences,risk factors,health GIS
Last Modified: 05 Feb 2024 08:01
Date Deposited: 11 Mar 2019 16:42
PURE Output Type: Conference contribution
Published Date: 2010
Authors: Leibovici, Didier
Bastin, Lucy (ORCID Profile 0000-0003-1321-0800)
Anand, Suchith
Swan, Jerry
Hobona, Gobe
Jackson, Michael

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