张平, 张静. 2014-2016年我国三峡地区细菌性痢疾发病时空特征分析[J]. 疾病监测, 2018, 33(3): 229-234. DOI: 10.3784/j.issn.1003-9961.2018.03.015
引用本文: 张平, 张静. 2014-2016年我国三峡地区细菌性痢疾发病时空特征分析[J]. 疾病监测, 2018, 33(3): 229-234. DOI: 10.3784/j.issn.1003-9961.2018.03.015
Zhang Ping, Zhang Jing. Spatial-temporal analysis on bacillary dysentery incidence in three gorges area of China,2014-2016[J]. Disease Surveillance, 2018, 33(3): 229-234. DOI: 10.3784/j.issn.1003-9961.2018.03.015
Citation: Zhang Ping, Zhang Jing. Spatial-temporal analysis on bacillary dysentery incidence in three gorges area of China,2014-2016[J]. Disease Surveillance, 2018, 33(3): 229-234. DOI: 10.3784/j.issn.1003-9961.2018.03.015

2014-2016年我国三峡地区细菌性痢疾发病时空特征分析

Spatial-temporal analysis on bacillary dysentery incidence in three gorges area of China,2014-2016

  • 摘要: 目的 了解我国三峡地区2014-2016年细菌性痢疾(菌痢)发病的时空分布特征,为影响因素分析和防控提供依据。方法 2014-2016年三峡地区菌痢报告病例数据和菌痢突发事件资料分别来源于传染病报告信息管理系统和突发公共卫生事件报告管理系统,采用GeoDa 1.8.16.4软件进行全局和局部空间自相关分析,SaTScan 9.4软件进行时空扫描统计分析,利用ArcGIS 10.3实现结果三维可视化。结果 2014-2016年,三峡地区菌痢报告发病率依次为24.00/10万、22.14/10万和20.84/10万,呈下降趋势。仅重庆市城口县报告一起菌痢暴发疫情,罹患率为5.36%(70/1 305)。全局空间自相关表明,三峡地区菌痢报告发病率整体上具有空间自相关性(Moran's I依次为0.194、0.227和0.482,P=0.001);局部空间自相关显示,2014-2016年菌痢发病热点县(区)个数分别为2、5和8个;冷点县(区)范围变化不大,依次为6、6和8个。逐年时空扫描分析发现,一类聚集区的聚集时间为每年的5-10月,且位置较稳定,均覆盖重庆西南部的渝中、大渡口、江北、沙坪坝、九龙坡、南岸、北碚、渝北、巴南和长寿共10个县(区),此外2014年和2015年还包含璧山区,2016年包含合川区;2014-2016年依次有4、3和5个二类聚集区,持续存在的是重庆市东北部的城口县和宜昌市中部的西陵区和伍家岗区。结论 三峡地区菌痢报告发病率在县(区)水平上存在时空聚集性,重庆市主城区及其周边县(区)为高发聚集区,空间分析方法可以较好地应用于菌痢的时空聚集性分析,为菌痢防控提供参考依据。

     

    Abstract: Objective To investigate the spatial and temporal distribution of bacillary dysentery in the three gorges area from 2014 to 2016,and provide evidence for both further investigation of risk factors and interventions. Methods The incidence and outbreak data of bacillary dysentery in the three gorges area from 2014 to 2016 were obtained from National Notifiable Infectious Disease Reporting System and National Public Health Emergency Reporting Information System. The spatial autocorrelation analysis and spatial-temporal scan statistic were conducted by using software GeoDa1.8.16.4 and SaTScan 9.4 respectively. The results were visualized by using software ArcGIS 10.3. Results The reported annual incidences of bacillary dysentery in the three gorges area from 2014 to 2016 were 24.00/100 000,22.14/100 000 and 20.84/100 000 respectively,showing a decrease trend. Only 1 bacillary dysentery outbreak was reported in Chengkou county in the northeast of Chongqing and the attack rate was 5.36%(70/1 305). Global spatial autocorrelation indicated that there was a spatial clustering in the incidence of bacillary dysentery(In turn,Moran's I coefficient is 0.194,0.227,0.482,and P=0.001). Local spatial autocorrelation showed that the number of hot spot areas was 2,5 and 8 during 2014-2016 respectively. The number of cold spot areas had slight change,which was 6,6 and 8 during 2014-2016 respectively. Spatial-temporal scan statistic analysis found that the clustering period was during May-October in class Ⅰ cluster areas steadily found in southwest Chongqing,including Yuzhong,Dadukou,Jiangbei,Shapingba,Jiulongpo,Nanan,Beibei,Yubei, Banan districts and Changshou county. Bishan county was included in 2014 and 2015,and Hechuan district was included in 2016. A total of 4,3 and 5 class Ⅱ cluster areas were found from 2014 to 2016 respectively,including Chengkou county of Chongqing,Xiling and Wujiagang districts of central Yichang all the time. Conclusion The incidence of bacillary dysentery had spatial and temporal clustering at county level in the three gorges area,and the areas with high incidences were the urban area of Chongqing and its surrounding counties. Spatial statistical analysis is suitable for the analysis of the spatial and temporal clusters of bacillary dysentery and can provide useful information for the disease prevention and control in the future.

     

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