平原湖区钉螺分异规律及孳生环境特征研究——以湖北公安县为例

以血吸虫病典型流行区湖北省公安县为研究区，以行政村为基本研究单元，通过空间自相关和分组分析方法探究公安县钉螺空间分异规律，进而运用逐步回归、地理加权回归和地理探测器模型探讨公安县钉螺分布影响因素及其交互作用。结果如下：（1）公安县钉螺密度具有较强的空间集聚特性，形成2个较大的热点集聚区；综合考虑公安县钉螺密度水平和空间连接性，将公安县划分为高、中、低3个钉螺密度区。（2）人口密度、水网密度、水田比例、春季NDVI和秋季NDVI是公安县村级尺度钉螺密度主要影响因素，其影响效应具有空间异质性。（3）从整个研究区来看，两因子交互作用均产生非线性增强（NE），即两因子交互作用于钉螺密度时要比单因子具有更大的影响力。从钉螺密度类型分区来看，高、中钉螺密度区各因子之间的交互作用类型有双因子增强型（BE）和非线性增强型（NE）；而低钉螺密度区各因子交互作用均产生非线性增强作用。研究结果可为江汉平原乃至全省钉螺及血吸虫病防控工作提供决策支持。

Research on Spatial Disparity and Breeding Environment Characteristics of Oncomelania hupensis in Plain Lakes: A Case Study in Gongan County of Hubei Province,China

Schistosomiasis is a parasitic disease that threatens human health and impedes socioeconomic development in the Oncomelania hupensis endemic areas. Oncomelania is the only intermediate host of schistosoma japonicum, and therefore to analyze the spatial-temporal distribution patterns of Oncomelania and their influencing factors is of vital importance for Schistosomiasis control. Hubei province has long suffered from the threat of the Schistosomiasis. This paper selected Gongan county, which is a typical Oncomelania hupensis endemic area, to study spatial disparity of Oncomelania density with the methods of spatial autocorrelation analysis and grouping analysis. The stepwise regression, geographically weighted regression and Geodetector models were used to analyze the influencing factors of Oncomelania’s density, followed with the discussion of the spatial heterogeneity and the interaction between the influencing factors. The results are as follows: (1) The incidence of Oncomelania density in Gongan county clusters spatially, forming two hot spots. Based on the Oncomelania density degree and the spatial connectivity, the county can be divided into low Oncomelania density area, mid Oncomelania density area and high Oncomelania density area. (2) The major influencing factors of the Oncomelania density in Gongan county include population density, water network density, the ratio of paddy, the NDVI of spring and autumn. The influencing effects of all factors display spatial heterogeneity. The NDVI of autumn is negatively correlated with the Oncomelania density while the other factors display positive correlations with the Oncomelania density. (3) From the perspective of the whole study area, the interactions of each two factors display nonlinear enhancement - that is the influence of two factors is stronger than a single factor. From the perspective of the Oncomelania's density type, the interaction between two factors displays bi-factor enhancement and nonlinear enhancement in mid Oncomelania density area and high Oncomelania density area, while the interaction modes of two factors display nonlinear enhancement in low Oncomelania density area. This research can provide decision support for the prevention and control of Oncomelania snails and schistosomiasis in Jianghan plain and even the whole province.