2015-2024年云南省临沧市登革热时空聚集特征分析

Spatiotemporal clustering of dengue fever in Lincang, Yunnan, 2015-2024

  • 摘要:
    目的 分析2015-2024年云南省临沧市登革热流行特征及时空维度的聚集性分布规律,为登革热防控提供科学依据。
    方法 运用描述性流行病学方法进行流行特征分析,采用Excel 2010、Joinpoint 5.1.0、ArcGIS 10.8和SatScan10.3软件对病例和发病率数据进行空间自相关和时空扫描分析,并进行可视化。
    结果 2015-2024年临沧市共报告登革热病例2 591例,其中本地病例1 560例,输入性病例1 031例(缅甸等境外输入性病例945例,境内输入性病例86例)。全局和局部自相关分析提示,2015年、2022年、2023年和2024年临沧市登革热存在明显空间聚集性,高-高和高-低聚集区主要分布在中国-缅甸边境地区的耿马傣族佤族自治县(耿马县)孟定镇、沧源佤族自治县(沧源县)芒卡镇和镇康县南伞镇。标准差椭圆及重心分析显示临沧市登革热发病率的空间格局分布呈现东南−西北向格局,疫情从点状输入发展为网状扩散。时空扫描分析发现,一类和二类聚集区均为耿马县孟定镇;三类聚集区以永德县小勐统镇为中心,最大扫描半径为56.42 km,共包含16个乡镇。
    结论 2015-2024年临沧市登革热高风险聚集区主要分布在我国与缅甸接壤的耿马县孟定镇、沧源县芒卡镇和镇康县南伞镇,疫情由缅甸输入该市边境县(乡镇)并扩散至各县、区。该地登革热属于境外输入性疾病,仍需加强重点边境县登革热跨境传播防控和伊蚊控制工作。

     

    Abstract:
    Objective To understand the epidemiological characteristics and spatiotemporal clustering patterns of dengue fever in Lincang, Yunnan province, from 2015 to 2024, and provide scientific evidence for the development and implementation of targeted prevention and control strategies.
    Methods Descriptive epidemiological methods were used for the analysis on the epidemiological characteristics of dengue fever. Spatial autocorrelation and spatiotemporal scanning were conducted on the case and incidence data by using software Excel 2010, Joinpoint 5.1.0, ArcGIS 10.8, and SaTScan 10.3. The results were subsequently visualized through mapping.
    Results A total of 2 591 dengue fever cases were reported in Lincang during 2015-2024, including 1 560 local cases and 1 031 imported cases (945 cases from other countries, mainly from Myanmar, and 86 cases from other areas in China). Global and local spatial autocorrelation analyses indicated significant spatial clustering of dengue fever incidence in Lincang in 2015, 2022, 2023, and 2024. High-high and high-low clustering were mainly in areas bordering Myanmar, especifically in Mengding township of Gengma Dai Autonomous county(Gengma county), Mangka township of Cangyuan Va Autonomous county(Cangyuan county), and Nansan township of Zhenkang county. Standard deviational ellipse and centroid analyses revealed a southeast-northwest distribution of dengue fever incidence, with the epidemic evolving from a point-source importation to a network-like spread pattern. Spatiotemporal scanning identified the primary and secondary clusters were all in Mengding township of Gengma county. The tertiary clustering was in Xiaomengtong township of Yongde county. The maximum scanning radius was 56.42 km, covering a total of 16 townships.
    Conclusion High-risk clustering of dengue fever in Lincang were mainly in the China-Myanmar-border townships of Mengding in Gengma, Mangka in Cangyuan, and Nansan in Zhenkang. The disease originated from Myanmar then spread to other counties and districts in Lincang. Dengue fever is an imported infectious disease, it is still necessary to strengthen the cross-border transmission prevention and control of the disease and Aedes control efforts in key border counties.

     

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