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目的分析2014年杭州市萧山区手足口病的时空分布及空间聚集性,为手足口病防控提供依据。方法通过中国疾病预防控制信息系统获取萧山区手足口病发病数据。以1∶65 000萧山区区划图在Map Info10.0软件中制作矢量地图,村(社区)地理位置信息采集于百度地图。在村(社区)尺度上,利用地理信息系统Arc GIS 10.2软件进行空间自相关分析,采用Sa TScan 9.2软件进行时空重排扫描。结果 2014年萧山区手足口病流行主高峰为4—7月,次高峰为9—10月。全局自相关系数Moran’s I值为0.442 7,P<0.01。广义Getis-Ord G值为0.003 3,E(G)为0.002 1,Z(G)为11.82,P<0.01。LISA分析结果提示手足口病呈High-High关联模式,其中宁围街道热点最多,共有14个。时空扫描统计探测到5个聚集区,最可能的聚集区位于河上镇内,时间为2014年1月6日—2月4日(RR=23.00,LLR=17.45,P<0.05)。结论 2014年萧山区手足口病主要流行高峰为4—7月,病例分布存在时空聚集性,聚集区主要分布在城乡结合部和农村工业开发区附近的村(社区)。
Objective To analyze the spatio-temporal distribution and spatial aggregation of hand-foot-mouth disease in Xiaoshan District of Hangzhou City in 2014 and provide basis for prevention and control of hand-foot-mouth disease. Methods The data of hand, foot and mouth disease in Xiaoshan District were obtained from China Disease Prevention and Control Information System. To 1: 65 000 Xiaoshan District zoning map in Map Info10.0 software to create a vector map, village (community) geographic location information collected in Baidu map. On the scale of village (community), spatial autocorrelation analysis was carried out by using ArcGIS 10.2 software of GIS, and Sa TScan 9.2 software was used to perform space-time rearrangement scanning. Results The main peak of HFMD in Xiaoshan district in 2014 was from April to July, with the next peak from September to October. The global autocorrelation coefficient Moran’s I was 0.442 7, P <0.01. The generalized Getis-Ord G value is 0.003 3, E (G) is 0.002 1, and Z (G) is 11.82, P <0.01. The results of LISA analysis suggest that HFMD is associated with High-High pattern, of which Ningwei Street has the most hot spots, a total of 14. Spatial and temporal scanning statistics detected five clusters, the most likely cluster located in the river town, the time for the January 6, 2014 - February 4 (RR = 23.00, LLR = 17.45, P <0.05). Conclusion The main epidemic peak of hand-foot-mouth disease in Xiaoshan district in 2014 was from April to July. There was spatiotemporal aggregation of case distribution. The aggregation areas were mainly distributed in the urban-rural junction and villages (communities) near rural industrial development zones.