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	A spatial scan statistic for nonisotropic two-level risk cluster
	Li X. Z. ; Wang J. F. ; Yang W. Z. ; Li Z. J. ; Lai S. J.
	2012
关键词	geographical disease surveillance hand-foot-mouth disease nonisotropic two-level risk cluster spatial scan statistic disease surveillance tests power
英文摘要	Spatial scan statistic methods are commonly used for geographical disease surveillance and cluster detection. The standard spatial scan statistic does not model any variability in the underlying risks of subregions belonging to a detected cluster. For a multilevel risk cluster, the isotonic spatial scan statistic could model a centralized high-risk kernel in the cluster. Because variations in disease risks are anisotropic owing to different social, economical, or transport factors, the real high-risk kernel will not necessarily take the central place in a whole cluster area. We propose a spatial scan statistic for a nonisotropic two-level risk cluster, which could be used to detect a whole cluster and a noncentralized high-risk kernel within the cluster simultaneously. The performance of the three methods was evaluated through an intensive simulation study. Our proposed nonisotropic two-level method showed better power and geographical precision with two-level risk cluster scenarios, especially for a noncentralized high-risk kernel. Our proposed method is illustrated using the handfootmouth disease data in Pingdu City, Shandong, China in May 2009, compared with two other methods. In this practical study, the nonisotropic two-level method is the only way to precisely detect a high-risk area in a detected whole cluster. Copyright (C) 2011 John Wiley & Sons, Ltd.
出处	Statistics in Medicine
卷	31
期	2
页	177-187
收录类别	SCI
语种	英语
ISSN号	0277-6715
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/26871]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Li X. Z.,Wang J. F.,Yang W. Z.,et al. A spatial scan statistic for nonisotropic two-level risk cluster. 2012.

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