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Fast Graph Structure Learning from Unlabeled Data for Outbreak Detection
Content Type: Abstract
Disease surveillance data often has an underlying network structure (e.g. for outbreaks which spread by person-to-person contact). If the underlying graph structure is known, detection methods such as GraphScan (1) can be used to identify an… read moreScalable Detection of Irregular Disease Clusters Using Soft Compactness Constraints
Content Type: Abstract
The spatial scan statistic [1] detects significant spatial clusters of disease by maximizing a likelihood ratio statistic F(S) over a large set of spatial regions, typically constrained by shape. The fast localized scan [2] enables scalable… read moreStarScan: A Novel Scan Statistic for Irregularly-Shaped Spatial Clusters
Content Type: Abstract
Kulldorff’s spatial scan statistic1 detects significant spatial clusters of disease by maximizing a likelihood ratio statistic over circular spatial regions. The fast localized subset scan2 enables scalable detection of proximity-constrained subsets… read more