Spatially clustered associations in health GIS

Didier Leibovici, Lucy Bastin, Suchith Anand, Jerry Swan, Gobe Hobona, Michael Jackson

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

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.
Original languageEnglish
Title of host publicationProceedings of the GIS Research UK 18th Annual Conference GISRUK 2010. University College London: London, UK
EditorsM. Haklay, J. Morle, H. Rahemtulla
Publication statusPublished - 2010
Event18th Annual Conference GIS Research UK 2010 - London, United Kingdom
Duration: 14 Apr 201016 Apr 2010

Conference

Conference18th Annual Conference GIS Research UK 2010
Abbreviated titleGISRUK
CountryUnited Kingdom
CityLondon
Period14/04/1016/04/10

Keywords

  • spatial clustering
  • multivariate associations
  • co-occurrences
  • risk factors
  • health GIS

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