Abstract #301368

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JSM 2003 Abstract #301368
Activity Number: 394
Type: Invited
Date/Time: Wednesday, August 6, 2003 : 2:00 PM to 3:50 PM
Sponsor: Environmental and Ecological Statistics
Abstract - #301368
Title: An Elliptic Scan Statistic for Geographical Disease Surveillance
Author(s): Martin Kulldorff*+ and Lan Huang and Linda Williams Pickle
Companies: University of Connecticut and University of Connecticut and National Cancer Institute
Address: Dept. Community Med. & Health Care, Farmington, CT, 06030-0001,
Keywords: spatial statistics ; disease surveillance
Abstract:

The spatial scan statistic is commonly used for geographical cluster detection, cluster evaluation and disease surveillance. Recent use include daily analyses of syndromic emergency room data for the early detection of disease outbreaks in New York City. Whether an outbreak is due to a natural cause or a bioterrorism attack, this system enables city health officials to investigate the outbreak as early as possible, and if needed, to rapidly implement disease prevention and control measures. When applying the spatial scan statistic, it is natural to use a circular window to define the potential cluster areas, as the circle is the most compact shape that can be obtained. Other shapes are also possible, such as ellipses. These may have higher power if the true cluster shape is noncircular, which one would often expect to be the case. We describe and illustrate the use of an elliptic spatial scan statistic, applying it to breast cancer mortality data in the northeastern United States. Comparisons are made with the circular spatial scan statistic.

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