A flexibly shaped spatial scan statistic for detecting clusters.
A flexibly shaped spatial scan statistic for detecting clusters.
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DOI：
10.1186/1476-072x-4-11
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发表时间：
2005-05-18
影响因子：
4.9
通讯作者：
Takahashi, Kunihiko
中科院分区：
文献类型：
--
作者：
Tango, Toshiro;Takahashi, Kunihiko
背景：库尔多夫提出的空间扫描统计已被应用于各种流行病学研究中的聚类检测。然而，这种扫描统计使用圆形窗口来定义潜在的簇区域，因此难以正确检测实际的非圆形簇。 Duczmal 和 Assuncao 最近提出的用于检测非圆形簇的提议被证明可以检测形状非常不规则的簇，该簇比我们经验中的真实簇大得多。方法：我们提出了一种灵活形状的空间扫描统计量，可以检测每个区域相对较小邻域内的不规则形状簇。通过考虑几种圆形和非圆形热点簇模型，将所提出的空间扫描统计量的性能与采用蒙特卡罗模拟的 Kulldorff 圆形空间扫描统计量的性能进行了比较。为了进行比较，我们还提出了一种新的双变量功率分布，根据检测为最可能的簇的区域数量和最可能的簇中包含的热点区域的数量进行分类。结果：圆形空间扫描统计显示在准确检测圆形簇方面具有很高的准确性。所提出的空间扫描统计量被证明具有良好的常用功效，并且能够比圆形热点簇更准确地检测非圆形热点簇。结论：所提出的空间扫描统计量被证明对于中小簇大小（最多 30 个）效果良好。对于较大的簇大小，该方法实际上不可行，需要更有效的算法。
BACKGROUND: The spatial scan statistic proposed by Kulldorff has been applied to a wide variety of epidemiological studies for cluster detection. This scan statistic, however, uses a circular window to define the potential cluster areas and thus has difficulty in correctly detecting actual noncircular clusters. A recent proposal by Duczmal and Assuncao for detecting noncircular clusters is shown to detect a cluster of very irregular shape that is much larger than the true cluster in our experiences.METHODS: We propose a flexibly shaped spatial scan statistic that can detect irregular shaped clusters within relatively small neighborhoods of each region. The performance of the proposed spatial scan statistic is compared to that of Kulldorff's circular spatial scan statistic with Monte Carlo simulation by considering several circular and noncircular hot-spot cluster models. For comparison, we also propose a new bivariate power distribution classified by the number of regions detected as the most likely cluster and the number of hot-spot regions included in the most likely cluster.RESULTS: The circular spatial scan statistics shows a high level of accuracy in detecting circular clusters exactly. The proposed spatial scan statistic is shown to have good usual powers plus the ability to detect the noncircular hot-spot clusters more accurately than the circular one.CONCLUSION: The proposed spatial scan statistic is shown to work well for small to moderate cluster size, up to say 30. For larger cluster sizes, the method is not practically feasible and a more efficient algorithm is needed.