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Emerging disease clusters must be detected in a timely manner so that necessary remedial action can be taken to prevent the spread of an outbreak. The Exponentially Weighted Moving Average method (EWMA) is a particularly popular method, and has been utilized for disease surveillance in the... Read more

Content type: Abstract

The traditional SaTScan algorithm[1],[2] uses the euclidean dis- tance between centroids of the regions in a map to assemble a con- nected (in the sense that two connected regions share a physical border) sets of regions. According to the value of the respective log- arithm of the likelihood... Read more

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, through artificial neural networks. The method... Read more

Content type: Abstract

Estimation of representative spatial probabilities and expected counts from baseline data can cause problems in applying spatial scan statistics when observed events are sparse in a large percentage of the spatial zones (e.g., zip codes or census tracts) found in the data records. In... Read more

Content type: Abstract

TOA identifies clusters of patients arriving to a hospital ED within a short temporal interval. Past implementations have been restricted to records of patients with a specific type of complaint. The Florida Department of Health uses TOA at the county level for multiple subsyndromes (1). In 2011... Read more

Content type: Abstract

Event-based biosurveillance is a practice of monitoring diverse information sources for the detection of events pertaining to human health. Online documents, such as news articles on the Internet, have commonly been the primary information sources in event-based biosurveillance. With the large... Read more

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While results from syndromic surveillance systems are commonly presented in the literature, few systems appear to have been thoroughly evaluated to examine which events can and cannot be detected, the time to detection and the efficacy of different syndromic surveillance data streams. Such an... Read more

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This study uses data on births in New York City between 2000-2005 to investigate the spatial pattern of birthweight and gestation, two primary risk factors for infant mortality. The analysis uses SatScan to perform normal-distribution cluster detection after controlling for individual-level... Read more

Content type: Abstract

We apply recently developed spatial biosurveillance techniques to the law enforcement domain, with the goal of helping local police departments to rapidly detect and respond to (or better yet, to predict and prevent) emerging spatial patterns of crime.

Content type: Abstract

Bio-surveillance systems monitor multiple data streams (over-the-counter (OTC) sales, Emergency Department visits, etc.) to detect both natural disease outbreaks (e.g. influenza) and bio-terrorist attacks (e.g. anthrax re-lease). Many detection algorithms show impressive results under simulated... Read more

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