Department of Pediatrics, University of Alberta, 3-077B Edmonton Clinic Health Academy, 11405 87 Avenue NW, Edmonton, Alberta, Canada.
Stat Med. 2013 Dec 20;32(29):5106-18. doi: 10.1002/sim.5891. Epub 2013 Jul 3.
The topic of spatial cluster detection gained attention in statistics during the late 1980s and early 1990s. Effort has been devoted to the development of methods for detecting spatial clustering of cases and events in the biological sciences, astronomy and epidemiology. More recently, research has examined detecting clusters of correlated count data associated with health conditions of individuals. Such a method allows researchers to examine spatial relationships of disease-related events rather than just incident or prevalent cases. We introduce a spatial scan test that identifies clusters of events in a study region. Because an individual case may have multiple (repeated) events, we base the test on a compound Poisson model. We illustrate our method for cluster detection on emergency department visits, where individuals may make multiple disease-related visits.
空间聚类检测这一主题在 20 世纪 80 年代末和 90 年代初的统计学中受到关注。人们致力于开发在生物科学、天文学和流行病学中检测病例和事件空间聚类的方法。最近，研究还检验了检测与个体健康状况相关的相关计数数据聚类的方法。这种方法允许研究人员检查与疾病相关事件的空间关系，而不仅仅是发病或流行病例。我们引入了一种空间扫描测试，以识别研究区域内的事件集群。由于单个病例可能有多个（重复）事件，我们基于复合泊松模型进行测试。我们在急诊科就诊中演示了我们的聚类检测方法，个体可能会进行多次与疾病相关的就诊。
