Displaying results 1 - 5 of 5
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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 -
A Voronoi based scan for space-time cluster detection in point event data
Content Type: Abstract
Scan statistics are highly successful for the evaluation of space-time clusters. Recently, concepts from the graph theory were applied to evaluate the set of potential clusters. Wieland et al. introduced a graph theoretical… read more -
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 -
Dry Climate as a Predictor of Chagas; Disease Irregular Clusters: A Covariate Study
Content Type: Abstract
Chagas’ disease, caused by the protozoan Trypanosoma cruzi, is spread mostly by Triatominae bugs. High carbon dioxide emission and strong infra-red (IR) radiation are indicative of their presence. Periods of low atmospheric water saturation favor… read more