Abstract
BackgroundEarly detection of disease outbreaks enables public health officials to implement disease control and prevention measures at the earliest possible time. A time periodic geographical disease surveillance system based on a cylindrical space-time scan statistic has been used extensively for disease surveillance along with the SaTScan software. In the purely spatial setting, many different methods have been proposed to detect spatial disease clusters. In particular, some spatial scan statistics are aimed at detecting irregularly shaped clusters which may not be detected by the circular spatial scan statistic.ResultsBased on the flexible purely spatial scan statistic, we propose a flexibly shaped space-time scan statistic for early detection of disease outbreaks. The performance of the proposed space-time scan statistic is compared with that of the cylindrical scan statistic using benchmark data. In order to compare their performances, we have developed a space-time power distribution by extending the purely spatial bivariate power distribution. Daily syndromic surveillance data in Massachusetts, USA, are used to illustrate the proposed test statistic.ConclusionThe flexible space-time scan statistic is well suited for detecting and monitoring disease outbreaks in irregularly shaped areas.
Highlights
Detection of disease outbreaks enables public health officials to implement disease control and prevention measures at the earliest possible time
A time periodic geographical disease surveillance system based on a cylindrical space-time scan statistic has already been proposed by Kulldorff [10]
A flexible space-time scan statistic which we propose in this paper imposes a three dimensional prismatic window with an arbitrarily shaped base Z
Summary
A flexibly shaped space-time scan statistic for disease outbreak detection and monitoring. Address: 1Department of Technology Assessment and Biostatistics, National Institute of Public Health, Japan and 2Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, Boston, USA. Published: 11 April 2008 International Journal of Health Geographics 2008, 7:14 doi:10.1186/1476-072X-7-14.
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