深圳市2014年登革热疫情时空分析

许艳子, 吴楠, 张振, 王敬忠

doi:10.11853/j.issn.1003.8280.2017.04.008

中国媒介生物学及控制杂志 >

2017 , Vol. 28 >Issue 4: 340 - 342

DOI: https://doi.org/10.11853/j.issn.1003.8280.2017.04.008

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深圳市2014年登革热疫情时空分析

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1 深圳市南山区疾病预防控制中心传染病防制科, 广东深圳 518054;
2 深圳市疾病预防控制中心, 广东深圳 518055

许艳子,女,主治医师,从事传染病防制工作,Email:422402339@qq.com

收稿日期: 2017-04-25

网络出版日期: 2017-08-20

基金资助

广东省医学科学技术研究基金（A2015449）

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Spatial-temporal analysis of dengue fever in Shenzhen,China,2014

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1 Nanshan District Center for Disease Control and Prevention, Shenzhen 518054, Guangdong Province, China;
2 Shenzhen Center for Disease Control and Prevention

Received date: 2017-04-25

Online published: 2017-08-20

Supported by

Supported by the Medical Scientific Research Foundation of Guangdong Province (No. A2015449)

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摘要

目的分析2014年深圳市登革热疫情时空分布特征。方法基于2014年深圳市登革热本地病例数据和人口数据，建立地理信息数据库，采用ArcGIS 10.2和SaTScan软件进行全局、局部空间自相关分析及时空扫描聚类分析，确定登革热时空热点区域。结果 2014年深圳市登革热本地病例高发于9、10月，本地病例高聚集区在深圳市西南区域，聚集中心为深圳市蛇口、招商和粤海街道（对数似然比为44.46，相对危险度为7.30，P<0.001）。结论登革热疫情存在明显的时空聚集特征，为制定登革热防控策略和评价防制效果提供了参考。

关键词： 登革热; 空间自相关; 时空聚类分析

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许艳子, 吴楠, 张振, 王敬忠 . 深圳市2014年登革热疫情时空分析[J]. 中国媒介生物学及控制杂志, 2017 , 28(4) : 340 -342 . DOI: 10.11853/j.issn.1003.8280.2017.04.008

Abstract

Objective To understand the spatial-temporal distribution of dengue fever epidemics in Shenzhen city, 2014. Methods Geographic information database was established by using the incidence data of dengue fever and demographic data reported. Global indication of spatial autocorrelation, local indication of spatial autocorrelation, and spatial-temporal clustering analysis were conducted with software ArcGIS 10.2 and SaTScan to determine high risk areas of dengue fever. Results The occurrence of local cases had a characteristic of seasonality, mainly occurred in September and October. The spatial aggregation of dengue fever was obvious in Shenzhen city, 2014. The spatial-temporal clustering analysis showed that the most likely clustering was mainly at Southwest districts of Shenzhen city, such as Shekou, Zhaoshang, and Yuehai counties (LLR=44.46, RR=7.30, P<0.001). Conclusion Obvious spatial-temporal clustering of dengue fever distribution was found in Shenzhen city, Attention should be paid to the hot spots in monitoring and early warning to mitigate the transmission.

Key words： Dengue fever; Spatial autocorrelation; Spatial-temporal clustering analysis

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