Meteorological Factors-Based Spatio-Temporal Mapping and Predicting Malaria in Central China
Meteorological Factors-Based Spatio-Temporal Mapping and Predicting Malaria in Central China
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DOI：
10.4269/ajtmh.2011.11-0156
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发表时间：
2011-09-01
影响因子：
3.3
通讯作者：
Li, Weidong
中科院分区：
文献类型：
--
作者：
Huang, Fang;Zhou, Shuisen;Li, Weidong
尽管疟疾的总体负担在20世纪显著减少，但这种疾病在中国，特别是在中部地区，仍然是一个重大的公共卫生问题。了解疟疾的时空分布对规划和实施有效的控制措施至关重要。本研究将归一化气象因子纳入时空模型。采用贝叶斯层次模型和马尔可夫链蒙特卡罗方法在WinBUGS软件中建立了7个模型。M-1、M-2和M-3分别模拟了不同的气象因子，其中M-3对降雨的模拟效果优于M-1和M-2对平均温度和相对湿度的模拟效果。基于偏差信息准则和预测误差，M-7是最优拟合模型。结果表明，降雨对疟疾发病率的影响方式不同于其他因素，这可以解释为降雨对疟疾发病率的影响大于其他因素。
Despite significant reductions in the overall burden of malaria in the 20th century, this disease still represents a significant public health problem in China, especially in central areas. Understanding the spatio-temporal distribution of malaria is essential in the planning and implementing of effective control measures. In this study, normalized meteorological factors were incorporated in spatio-temporal models. Seven models were established in WinBUGS software by using Bayesian hierarchical models and Markov Chain Monte Carlo methods. M-1, M-2, and M-3 modeled separate meteorological factors, and M-3, which modeled rainfall performed better than M-1 and M-2, which modeled average temperature and relative humidity, respectively. M-7 was the best fitting models on the basis of based on deviance information criterion and predicting errors. The results showed that the way rainfall influencing malaria incidence was different from other factors, which could be interpreted as rainfall having a greater influence than other factors.