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Detecting nested clusters of human alveolar echinococcosis

机译：检测人类肺泡棘球co虫病的巢状簇

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SUMMARY Recent changes in the epidemiology of alveolar echinococcosis (AE) in Eurasia have led to increasing concerns about the risk of human AE and the need for a thorough evaluation of the epidemiological situation. The aim of this study was to explore the use of a National Register to detect complex distribution patterns on several scales. The data were human AE cases from the FrancEchino register, diagnosed in France from 1982 to 2011. We used the Kulldorff spatial scan analysis to detect non-random locations of cases. We proposed an exploratory method that was based on the successive detection of nested clusters inside each of the statistically significant larger clusters. This method revealed at least 4 levels of disease clusters during the study period. The spatial variations of cluster location over time were also shown. We conclude that National Human AE registers, although not exempted from epidemiological biases, are currently the best way to achieve an accurate representation of human AE distribution on various scales. Finally, we confirm the multi-scale clustered distribution of human AE, and we hypothesize that our study may be a reasonable starting point from which to conduct additional research and explore the processes that underlie such distributions.
机译：发明内容欧亚大陆的肺泡棘球菌病（AE）流行病学的最新变化导致人们对人类AE风险以及对流行病学状况进行全面评估的担忧日益增加。这项研究的目的是探索使用国家注册簿来检测多种规模的复杂分布模式。数据是从1982年至2011年在法国诊断出的FrancEchino寄存器中的人类AE病例。我们使用Kulldorff空间扫描分析来检测病例的非随机位置。我们提出了一种探索性方法，该方法基于连续检测每个具有统计意义的较大聚类内的嵌套聚类。该方法在研究期间揭示了至少4个水平的疾病簇。还显示了群集位置随时间的空间变化。我们得出的结论是，尽管尚未免除流行病学偏见，但国家人类AE登记册目前是在各种规模上准确显示人类AE分布的最佳方法。最后，我们确认了人类AE的多尺度集群分布，并且我们假设我们的研究可能是进行其他研究并探讨构成这种分布基础的过程的合理起点。

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