Displaying results 1 - 8 of 15
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Delineating Spatial Clusters with Artificial Neural Networks
Content Type: Abstract
Multiple or irregularly shaped spatial clusters are often found in disease or syndromic surveillance maps. We develop a novel method to delineate the contours of spatial clusters, especially when there is not a clearly dominating primary cluster,… read more -
Dual Graph Spatial Cluster Detection for Syndromic Surveillance in Networks
Content Type: Abstract
Early warning systems must not always rely on geographical proximity for modeling the spread of contagious diseases. Instead, graph structures such as airways or social networks are more adequate in those situations. Nodes,… read more -
Exploring Multi-Cluster Structures with the Multi-Objective Circular Scan
Content Type: Abstract
The spatial scan statistic is the usual measure of strength of a cluster [1]. Another important measure is its geometric regularity [2]. A genetic multiobjective algorithm was developed elsewhere to identify irregularly shaped clusters [3]. A search… read more -
Geographically Meaningful Cluster Scanning Through Weak Link Correction
Content Type: Abstract
Many heuristics were developed recently to find arbitrarily shaped clusters (see review [1]). The most popular statistic is the spatial scan [2]. Nevertheless, even if all cluster solutions could be known, the problem of… read more -
Optimizing Simultaneously the Geometry and the Internal Cohesion of Clusters
Content Type: Abstract
Irregularly shaped cluster finders frequently end up with a solution consisting of a large zone z spreading through the map, which is merely a collection of the highest valued regions, but not a geographically sound cluster. One way… read more -
What Is the True Shape of a Disease Cluster? The Multi-Objective Genetic Scan
Content Type: Abstract
Irregularly shaped spatial disease clusters occur commonly in epidemiological studies, but their geographic delineation is poorly defined. Most current spatial scan software usually displays only one of the many possible cluster solutions with… read more -
Significant multiple high and low risk regions in event data maps
Content Type: Abstract
The Voronoi Based Scan (VBScan)[1] is a fast method for the detection and inference of point data set space-time disease clusters. A Voronoi diagram is built for points representing population individuals (cases and controls). The number of Voronoi… read more -
Mapping the uncertainty of non-contagious disease clusters boundaries in Brazil
Content Type: Abstract
The intrinsic variability that exists in the cases counting data for aggregated-area maps amounts to a corresponding uncertainty in the delineation of the most likely cluster found by methods based on the spatial scan statistics [3]. If this cluster… read more