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目的探索湖北省不同类型分布区村级尺度钉螺分布的时空格局,为钉螺防治策略与措施提供依据。方法将2007-2012年湖北省30个主要血吸虫病流行县(市)的村级螺情资料与村地理信息相关联,建立螺情空间数据库,制图反映各类型分布区钉螺面积及变化趋势;构建钉螺分布的多水平模型。结果各行政村各年间钉螺面积的相关性较强(组内相关系数Intra-class correlation coefficient,ICC=95.7%);各行政村有螺面积的初始值不同(σ2u0=4 766.53,P<0.01),且变化率在各行政村间也显著不同(σ2u1=20.96,P<0.01);初始年份钉螺面积较高的行政村,有螺面积随时间的变化率较大(σ2u01=126.78,P<0.01);行政村有螺面积呈逐年缓慢增加趋势(year=0.64,P<0.01);湖沼洲滩亚型钉螺分布区行政村的平均钉螺面积最大(type=-29.84,P<0.01),且钉螺面积平均增加的幅度最大(year*type=-0.52,P<0.01)。结论湖北省各行政村及各类型分布区间钉螺面积差异显著。本研究将湖北省30个县(市)螺情数据进行了空间可视化及多水平模型模拟,结果可为不同类型分布区的灭螺工作提供依据。
Objective To explore the spatio-temporal pattern of snail distribution at different scales in Hubei Province, and to provide evidences for the prevention and treatment of Oncomelania snails. Methods The village-level information of 30 major schistosomiasis endemic counties in Hubei Province from 2007 to 2012 was correlated with the village geographic information, and the snail spatial database was established. The mapping reflected snail snail area and its changing trend in various types of distribution areas. Multilevel model of snail distribution. Results There was a strong correlation between snail area in each administrative village (intra-class correlation coefficient, ICC = 95.7%); initial values of snail area were different in each administrative village (σ2u0 = 4 766.53, P <0.01) (Σ2u1 = 20.96, P <0.01). In the administrative villages with high snail area in the initial years, the rate of change of snail area was greater with time (σ2u01 = 126.78, P <0.01) ). The area of snail in administrative village showed a slowly increasing trend year by year (year = 0.64, P <0.01), and the average snail area of administrative villages in submarginal snail distribution area of lake marshland was the largest (type = -29.84, P <0.01) The average increase in area was the largest (year * type = -0.52, P <0.01). Conclusion There are significant differences in the area of snail in all administrative villages and various types of distribution in Hubei Province. In this study, spline data of 30 counties (cities) in Hubei Province were simulated by spatial visualization and multi-level model. The results can provide basis for snail control work in different types of distribution areas.