扫描统计量在麻疹聚集性分析中的应用探讨

目的 探讨扫描统计量在麻疹实时预警和时空聚集性分析中的应用价值。方法 应用前瞻性时空扫描统计量结合空间准确性评价指标MCS-P(Most Clustering Set-Proportion)去确定最优参数，对北京市朝阳区2016年网络直报的麻疹数据开展模拟预警分析。同时应用空间扫描统计量结合MCS-P分析2006-2016年北京市朝阳区麻疹聚集性。结果 模拟预警提示3月4日双井街道麻疹病例出现异常聚集，与历史监测资料一致。麻疹发病数从2006年后直线下降，但在2009年后出现反复。 2014-2016年，麻疹的局部高发区域的形状较为规则，波及范围更大但并未带来更高的空间聚集性。2014-2016连续三年，十八里店乡、高碑店乡以及豆各庄乡均表现出空间聚集性。结论 运用前瞻性时空扫描统计量结合MCS-P选用最优参数进行逐日分析，可以得到最符合实际情况的聚集区域，在早期预警中具有实际价值。分析连续多年数据有助于发现麻疹分布模式的变化以及空间分布特征，从而发现高危地区，以便进一步分析原因并采取针对性地干预措施。

Application of scan statistics in measles cluster analysis

Objective To evaluate the applicability to use data-driven scan statistics in real-time early warning and spatial pattern explorations of measles.Methods Data-driven prospective scan statistic, of which parameters optimal selected by MCS-P, was employed to simulate the real-time early warning using monitoring data of 2016 in Chaoyang District, Beijing. Data-driven spatial scan statistic was employed in spatial pattern explorations of Measles in Chaoyang District, Beijing from 2014 to 2016. Results A cluster in Shuangjing sub-district located in Chaoyang since March 4 th, 2016 was found in simulated real-time early warning and validated with a classified outbreak according to the record of CDC monitoring system. Spatial pattern showed the measles incidence was large and flat in 2014-2016. Clusters were found in Shibalidian, Gaobeidianxiang and Dougezhuang each year in 2014-2016. Conclusion With optimal parameter selected using MCS-P, daily detection using prospective spatio-temporal scan statistic can timely identify significantly clustering cases, stands for its own value in early warning. Also, yearly spatial pattern identification using scan statistics with MCS-P can provide more accurate characteristics of incidence and provide evidence for specified interventions.