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2005—2024年宁夏回族自治区西吉县囊型棘球蚴病病例时空分布特征

Spatiotemporal distribution of cystic echinococcosis in Xiji, Ningxia, 2005-2024

    摘要
  • 摘要:
    目的 探讨2005—2024年宁夏回族自治区西吉县囊型棘球蚴病的流行现状、时间变化趋势及空间分布特征，为精准化防控提供科学依据。
    方法 收集2005—2024年西吉县囊型棘球蚴病病例资料，运用Joinpoint回归分析发病率变化趋势，采用ArcGIS 10.8软件进行空间分布与空间自相关分析，利用莫兰指数（Moran’s I）评价空间聚集性，结合SaTScan 10.3.2软件进行时空扫描，识别聚集区域。
    结果 2005—2024年西吉县共发现囊型棘球蚴病病例595例，高峰期出现在2007—2009年（各年份病例数分别为95、73、75例）。Joinpoint回归分析结果显示2008年为转折点：2005—2008年发病率快速上升年度变化百分比（APC）=163.21%，95%置信区间（CI）：2.42%～402.14%，P<0.05，2008—2024年发病率呈持续下降趋势（APC=−10.88%，95%CI：−21.62%～−6.12%，P<0.01），2015—2024与2020—2024年平均年度变化百分比均为−10.88%（P<0.01）。空间分布显示，西吉县19个乡（镇）均有病例分布，北部新营乡发病率最高（51.18/10万），整体呈“北高南低”格局。全局自相关Moran’s I=0.35（Z=3.55，P<0.01），存在显著聚集性。局部自相关分析发现高-高聚集区位于北部火石寨乡，低-高聚集区为吉强镇，低-低聚集区集中于南部各乡（镇），热点区域主要位于北部区域。时空扫描分析结果提示，2007—2018年西吉县北部新营、火石寨、白崖乡为主要聚集区相对危险度（RR）=8.82，对数似然比（LLR）=247.60，P<0.01），2007—2009年中西部6个乡（镇）（红耀乡、田坪乡、马建乡、震湖乡、兴平乡和吉强镇）为次要聚集区（RR=1.95，LLR=11.26，P<0.01）。
    结论 2005—2024年西吉县囊型棘球蚴病总体呈下降趋势，空间分布广泛且存在聚集性，高风险区域长期集中于北部区域。防控应突出重点地区和人群，强化犬源与畜牧环节管理，并建立基于时空监测的预警体系，以实现精准化防控。

     

    Abstract:
    Objective To investigate the epidemiological characteristics, temporal trends, and spatial distribution of cystic echinococcosis in Xiji county, Ningxia Hui autonomous region, from 2005 to 2024, and provide evidence for the precision control of cystic echinococcosis.
    Methods The incidence data of cystic echinococcosis were collected from the national echinococcosis control program conducted in Xiji from 2005 to 2024. Temporal trends were analyzed by using Joinpoint regression model, while software ArcGIS 10.8 was used for spatial distribution and spatial autocorrelation analyses, Moran’s I was used to evaluate spatial clustering and software SaTScan 10.3.2 was used for spatiotemporal scanning to identify spatiotemporal clustering areas.
    Results A total of 595 cystic echinococcosis cases were reported in Xiji from 2005 to 2024, with high case counts during 2007–2009 (95, 73, and 75 cases). Joinpoint regression analysis revealed that the incidence increased rapidly during 2005–2008 annual percent change (APC)=163.21%, 95% confidence Interval (CI): 2.42%–402.14%, P<0.05, then decreased significantly during 2008–2024 (APC=−10.88%, 95% CI: −21.62%––6.12%, P<0.01). The average annual percent change (AAPC) was −10.88% during 2015−2025 and during 2020−2024 (P<0.01). Spatial distribution showed the cases were distributed in all 19 townships, with the highest incidence in Xinying in northern area (51.18/100,000) and an overall pattern of “high in the north and low in the south”. Global spatial autocorrelation showed significant clustering (Moran’s I = 0.35, Z=3.55, P<0.01). Local autocorrelation analysis identified high–high clustering area in Huoshizhai in northern area, low–high clustering area in Jiqiang, and low–low clustering areas in southern townships, hot spots were mainly distributed in northern area. Spatiotemporal analysis revealed the primary clustering areas in Xinying, Huoshizhai, and Baiya in northern area from 2007 to 2018 Relative Risk (RR)=8.82, Log-Likelihood Ratio (LLR)=247.60, P<0.01, and the secondary clustering areas in six central-western areas (Hongyao, Tianping, Majian, Zhenhu, Xingping, and Jiqiang) during 2007–2009 (RR=1.95, LLR=11.26, P<0.01).
    Conclusion From 2005 to 2024, the incidence of cystic echinococcosis in Xiji exhibited a decline trend with significant spatial clustering, and high-risk areas were usually distributed in northern area. It is necessary to target the areas and populations at high-risk, strengthen dog and livestock management, and establish spatiotemporal surveillance-based early warning systems for the precision control of cystic echinococcosis.

     

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