Spatial Event Cluster Detection Using a Compound Poisson Distribution
Spatial Event Cluster Detection Using a Compound Poisson Distribution
复制标题
使用复合泊松分布的空间事件簇检测
作者：
R. Rosychuk;C. Huston;N. Prasad
地理疾病监测方法确定疾病发病率高于预期的区域。这些方法一般适用于偶发病例或流行病例。在某些情况下，与疾病相关的事件而不是个体是地理监测的适当分析单位。我们提出了一种复合泊松方法，通过测试可能与其最近邻居组合的单个区域来检测事件群集。该方法适用于种群规模多样、重要地层种群分布因地区而异的情况。例如，一个地理区域可能在北部地区人口稀少，而其他地区主要是退休社区。这种方法需要粗略的地理关系和每个地区人口、病例和事件数量的行政数据。儿童自我造成的伤害需要提交给艾伯塔省急诊科提供一个说明。
Summary Geographic disease surveillance methods identify regions that have higher disease rates than expected. These approaches are generally applied to incident or prevalent cases of disease. In some contexts, disease‐related events rather than individuals are the appropriate units of analysis for geographic surveillance. We propose a compound Poisson approach that detects event clusters by testing individual areas that may be combined with their nearest neighbors. The method is applicable to situations where the population sizes are diverse and the population distribution by important strata may differ by area. For example, a geographical region might have sparse population in the northern areas, and other areas which are predominantly retirement communities. The approach requires a coarse geographical relationship and administrative data for the numbers of population, cases, and events in each area. Pediatric self‐inflicted injuries requiring presentation to Alberta emergency departments provide an illustration.
影响因子：
5
作者：
Bruce W. Turnbull;Eric J. Iwano;William S. Burnett;Holly L. Howe;Larry C. Clark
通讯作者：
Bruce W. Turnbull;Eric J. Iwano;William S. Burnett;Holly L. Howe;Larry C. Clark