A scoping review of spatial cluster analysis techniques for point-event data

  • Charles E. Fritz | charles.e.fritz@gmail.com Department of Geography, Faculty of Environment, Simon Fraser University, Burnaby, BC, Canada.
  • Nadine Schuurman Department of Geography, Faculty of Environment, Simon Fraser University, Burnaby, BC, Canada.
  • Colin Robertson Department of Geography and Environmental Studies, Wilfrid Laurier University, Waterloo, ON, Canada.
  • Scott Lear Department of Biomedical Physiology and Kinesiology, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada.

Abstract

Spatial cluster analysis is a uniquely interdisciplinary endeavour, and so it is important to communicate and disseminate ideas, innovations, best practices and challenges across practitioners, applied epidemiology researchers and spatial statisticians. In this research we conducted a scoping review to systematically search peer-reviewed journal databases for research that has employed spatial cluster analysis methods on individual-level, address location, or x and y coordinate derived data. To illustrate the thematic issues raised by our results, methods were tested using a dataset where known clusters existed. Point pattern methods, spatial clustering and cluster detection tests, and a locally weighted spatial regression model were most commonly used for individual-level, address location data (n = 29). The spatial scan statistic was the most popular method for address location data (n = 19). Six themes were identified relating to the application of spatial cluster analysis methods and subsequent analyses, which we recommend researchers to consider; exploratory analysis, visualization, spatial resolution, aetiology, scale and spatial weights. It is our intention that researchers seeking direction for using spatial cluster analysis methods, consider the caveats and strengths of each approach, but also explore the numerous other methods available for this type of analysis. Applied spatial epidemiology researchers and practitioners should give special consideration to applying multiple tests to a dataset. Future research should focus on developing frameworks for selecting appropriate methods and the corresponding spatial weighting schemes.

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Published
2013-05-01
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Original Articles
Keywords:
spatial clustering, spatial epidemiology, cluster detection.
Statistics
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How to Cite
Fritz, C. E., Schuurman, N., Robertson, C., & Lear, S. (2013). A scoping review of spatial cluster analysis techniques for point-event data. Geospatial Health, 7(2), 183-198. https://doi.org/10.4081/gh.2013.79