Spatial risk profiling of Schistosoma japonicum in Eryuan county, Yunnan province, China
Spatial risk profiling of Schistosoma japonicum in Eryuan county, Yunnan province, China
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DOI：
10.4081/gh.2007.255
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发表时间：
2007-11-01
影响因子：
1.7
通讯作者：
Utzinger, Juerg
中科院分区：
文献类型：
--
作者：
Steinmann, Peter;Zhou, Xiao-Nong;Utzinger, Juerg
贝叶斯空间风险分析有望提高我们对寄生虫病流行病学的理解，并以具有成本效益的方式采取有针对性的干预措施。在这里，我们提出了一项研究的结果，使用贝叶斯变异函数模型来映射和预测日本血吸虫在洱源县，中国云南省，包括危险因素分析的血清阳性率。通过在35个随机选择的村庄进行横断面调查，共招募了3，220人，获得了问卷和血清学数据。遥感环境数据来自公开数据库。使用双变量和非空间贝叶斯多元逻辑回归模型来确定当地血清阳性率与人口统计学（即年龄和性别）、环境（即村庄位置、海拔、坡度、地表温度和归一化差异植被指数）和社会经济因素之间的关联。在空间显式贝叶斯模型中，S。日本血吸虫病血清阳性率与性别、年龄和居住地有关。男性、10岁以下的人和位于陡坡（坡度>= 20度）或2150米以上>5度的不太陡峭的山坡上的村庄居民的血清转化风险低于其相应的对应人群。我们最终的预测模型显示洱源县东部平原地区的血清转化风险升高。结论：该预测图可用于洱源县血吸虫病防治措施的空间定位。此外，S.日本血吸虫血清阳性率研究可能提供一种方便的方法来评估当地社区所经历的感染压力，并在反复使用吡喹酮后患病率和感染强度下降的地区改善风险分析。
Bayesian spatial risk profiling holds promise to enhance our understanding of the epidemiology of parasitic diseases, and to target interventions in a cost-effective manner. Here, we present findings from a study using Bayesian variogram models to map and predict the seroprevalence of Schistosoma japonicum in Eryuan county, Yunnan province, China, including risk factor analysis. Questionnaire and serological data were obtained through a cross-sectional survey carried out in 35 randomly selected villages with 3,220 people enrolled. Remotely-sensed environmental data were derived from publicly available databases. Bivariate and non-spatial Bayesian Multiple logistic regression models were used to identify associations between the local seroprevalence and demographic (i.e. age and sex), environmental (i.e. location of village, altitude, slope, land Surface temperature and normalized difference vegetation index) and soclo-economic factors. In the spatially-explicit Bayesian model, S. japonicum seroprevalence was significantly associated with sex, age and the location of the village. Males, those aged below 10 years and inhabitants of villages situated on steep slopes (inclination >= 20 degrees) or on less precipitous slopes of >5 degrees above 2, 150 m were at lower risk of seroconversion than their respective Counterparts. Our final prediction model revealed an elevated risk for seroconversion in the plains of the eastern parts of Eryuan county. In Conclusion, the prediction map can be utilized for spatial targeting of schistosomiasis control interventions in Eryuan county. Moreover, S. japonicum seroprevalence Studies might offer a convenient means to assess the infection pressure experienced by local communities, and to improve risk profiling in areas where the prevalence and infection intensities have come down following repeated rounds of praziquantel administration.