Abstract
Naus’s early 1965 paper [Naus (1965)] on spatial scan statistics paved the way for a considerable amount of research on geographic-based statistical analysis, inspiring intensive work in the most diverse contexts and applications, including epidemiology, syndromic surveillance, criminality and environmental sciences. Following one line of work, several methods for the detection of irregularly shaped clusters were developed. New tools were devised in order to account for the spatial mobility of individuals, the study of the spatial distribution of individuals according to their survival times and multiple data streams from different sources of syndromic counts. Several algorithms explored the utilization of parametric models other than the Poisson or Bernoulli distributions, and also non-parametric and learning models. We expect that this strong trend of application-driven methodologies in spatial scan statistics should continue in the foreseeable future.
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Duczmal, L., Duarte, A., Tavares, R. (2009). Extensions of the Scan Statistic for the Detection and Inference of SpatialClusters. In: Glaz, J., Pozdnyakov, V., Wallenstein, S. (eds) Scan Statistics. Statistics for Industry and Technology. Birkhäuser Boston. https://doi.org/10.1007/978-0-8176-4749-0_7
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