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Spatial Cluster Detection in Case-Control Datasets with the Autonomous Leaves Graph

Description

Ordering-based approaches [1,2] and quadtrees [3] have been introduced recently to detect multiple spatial clusters in point event datasets. The Autonomous Leaves Graph (ALG) [4] is an efficient graph-based data structure to handle the communication of cells in discrete domains. This adaptive data structure was favorably compared to common tree-based data structures (quad-trees). An additional feature of the ALG data structure is the total ordering of the component cells through a modified adaptive Hilbert curve, which links sequentially the cells (the orange curve in the example of Figure 1).

Objective

To detect multiple significant spatial clusters of disease in case-control point event data using the Autonomous Leaves Graph and the spatial scan statistic.

Submitted by elamb on