目的基于贝叶基斯模型构建日本血吸虫病时空分布模型,分析血吸虫病时空格局变化,评估环境变化对血吸虫病疫情的影响。方法利用湖南省汉寿县1996-2005年的查病数据和遥感提取的环境因子,在考虑血吸虫病检查方法灵敏度和特异度的不确定性和血吸虫病时空格局的基础上,构建不同的血吸虫病贝叶斯模型,筛选最佳模型,分析10年间血吸虫病的时空格局变化,并评估退田还湖工程对血吸虫病疫情的影响。结果血吸虫病贝叶斯时空交互模型为最佳模型。10年间,汉寿县人群血吸虫感染率无显著时间相关性,每年人群血吸虫感染率的空间相关结构差异较大;血吸虫感染率预测变化图显示汉寿县沅水以南地区无显著性变化,沅水以北地区的感染率显著增加,提示本研究区域内单退型退田还湖对血吸虫病的影响程度可能要强于双退型。结论基于贝叶斯模型,构建血吸虫病时空分析模型是切实可行的。该类模型在分析和预测血吸虫病分布中将发挥重要作用,可作为确定防治措施、提高防治效果的重要工具。
Objective To develop a spatio-temporal model of schistosomiasis japonica based on Bayesian model, and to analyze the spatio-temporal pattern of schistosomiasis, as well as to evaluate the impact of environment changes on schistosomiasis endemic. Methods Different Bayesian models were established by employing the data of the periodical surveillance on schistosomiasis during 1996-2005 period by taking into account of the uncertainty in sensitivity and specificity of diagnostic test, then the best fitness model was selected to analyze the spatio-temporal pattern of schistosomiasis and evaluate the impact of environment changes on schistosomiasis. Results The model with space-time interaction was a better fitting model. No significant temporal correlation was found in human infection rate of Schistosoma japonicum, and the difference of spatial structure between human infection rates of each year was significant. The prediction map of S. japonicum infection showed the changes of infection in the south areas of the Yuan River were not significant, while the prevalence increased significantly in the north areas of the river, which indicated that the impact of the implementation of project on partial abandon areas for water storing on prevalence of S. japonicum was stronger than that of the project on completed abandon areas for water storing. Conclusions It is feasible to develop the spatio-temporal model of schistosomiasis japonica based on Bayesian model, and this integrated Bayesian model approach may become a powerful and statistically robust tool for estimating and evaluating the control strategy.