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首页> 美国卫生研究院文献>International Journal of Environmental Research and Public Health >Japanese Encephalitis Risk and Contextual Risk Factors in Southwest China: A Bayesian Hierarchical Spatial and Spatiotemporal Analysis
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Japanese Encephalitis Risk and Contextual Risk Factors in Southwest China: A Bayesian Hierarchical Spatial and Spatiotemporal Analysis

机译：中国西南地区的日本脑炎风险和背景风险因素：贝叶斯分层时空分析

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摘要

It is valuable to study the spatiotemporal pattern of Japanese encephalitis (JE) and its association with the contextual risk factors in southwest China, which is the most endemic area in China. Using data from 2004 to 2009, we applied GISmapping and spatial autocorrelation analysis to analyze reported incidence data of JE in 438 counties in southwest China, finding that JE cases were not randomly distributed, and a Bayesian hierarchical spatiotemporal model identified the east part of southwest China as a high risk area. Meanwhile, the Bayesian hierarchical spatial model in 2006 demonstrated a statistically significant association between JE and the agricultural and climatic variables, including the proportion of rural population, the pig-to-human ratio, the monthly precipitation and the monthly mean minimum and maximum temperatures. Particular emphasis was placed on the time-lagged effect for climatic factors. The regression method and the Spearman correlation analysis both identified a two-month lag for the precipitation, while the regression method found a one-month lag for temperature. The results show that the high risk area in the east part of southwest China may be connected to the agricultural and climatic factors. The routine surveillance and the allocation of health resources should be given more attention in this area. Moreover, the meteorological variables might be considered as possible predictors of JE in southwest China.
机译：研究日本脑炎（JE）的时空格局及其与中国西南地区（这是中国最流行的地区）的环境危险因素的关联。利用2004年至2009年的数据，我们应用GIS映射和空间自相关分析来分析中国西南438个县的报告的脑卒中发病数据，发现脑卒中病例并非随机分布，并且贝叶斯时空模型确定了中国西南东部作为高风险地区。同时，2006年的贝叶斯分层空间模型显示了JE与农业和气候变量之间的统计显着关联，其中包括农村人口比例，猪与人的比例，月降水量以及月平均最低和最高温度。特别强调了气候因素的时间滞后效应。回归方法和Spearman相关分析都确定了降水两个月的滞后，而回归方法发现了温度一个月的滞后。结果表明，西南地区东部的高风险地区可能与农业和气候因素有关。在这一领域应更加重视常规监测和卫生资源的分配。此外，气象变量可能被认为是中国西南地区可能发生的JE的预测指标。

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