Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China.
Parasit Vectors. 2013 Jul 24;6:214. doi: 10.1186/1756-3305-6-214.
The recent rebounds of schistosomiasis in the middle and lower reaches of the Yangtze River pose a challenge to the current control strategies. In this study, identification of potential high risk snail habitats was proposed, as an alternative sustainable control strategy, in Xingzi County, China. Parasitological data from standardized surveys were available for 36,208 locals (aged between 6-65 years) from 42 sample villages across the county and used in combination with environmental data to investigate the spatial pattern of schistosomiasis risks.
Environmental factors measured at village level were examined as possible risk factors by fitting a logistic regression model to schsitosomiasis risk. The approach of ordinary kriging was then used to predict the prevalence of schistosomiasis over the whole county.
Risk analysis indicated that distance to snail habitat and wetland, rainfall, land surface temperature, hours of daylight, and vegetation are significantly associated with infection and the residual spatial pattern of infection showed no spatial correlation. The predictive map illustrated that high risk regions were located close to Beng Lake, Liaohuachi Lake, and Shixia Lake.
Those significant environmental factors can perfectly explain spatial variation in infection and the high risk snail habitats delineated by the predicted map of schistosomiasis risks will help local decision-makers to develop a more sustainable control strategy.
长江中下游地区血吸虫病的近期反弹对当前的控制策略构成了挑战。本研究在中国星子县提出了一种潜在的有针对性的可持续控制策略，即确定有螺环境的高风险区域。结合环境数据，对全县 42 个抽样村的 36208 名（年龄在 6-65 岁之间）当地居民进行了标准化调查的寄生虫学数据，用于调查血吸虫病风险的空间模式。
通过拟合逻辑回归模型，将村级测量的环境因素作为可能的风险因素进行检验，探讨血吸虫病风险。然后采用普通克里金法对全县的血吸虫病流行情况进行预测。
风险分析表明，与感染相关的因素有螺环境和湿地的距离、降雨量、地表温度、日照时间和植被，而感染的残差空间模式无空间相关性。预测图表明，高风险区域靠近滨湖北部、蓼花池和石峡池。
这些显著的环境因素可以很好地解释感染的空间变化，预测的血吸虫病高风险有螺环境图有助于地方决策者制定更可持续的控制策略。
