利用空间聚集的贝叶斯网络评估手足口病发病风险

发布时间：2018-03-23 06:33

本文选题：手足口病　切入点：贝叶斯网络　出处：《地球信息科学学报》2017年08期 　论文类型：期刊论文

【摘要】：手足口病是一种常见的传染病,以往的研究表明该疾病与气象、环境和社会经济等因素相关联,其影响关系复杂,而疾病本身体现出较强的区域聚集性,采用普通的线性风险建模方法无法捕捉影响因素的复杂性及空间聚集性。因此,本文以山东省为例,在前人研究的基础上,提出了采用贝叶斯网络综合风险建模方法研究手足口病的发病风险与气象、土地利用、社会经济及空气污染等要素间的关系,并通过引入空间扫描统计聚集结果,将空间聚集引入到贝叶斯网络模型加强其空间推理功能,减少模型的偏差,提高评估的精度。结果表明,本文建立的手足口病空间贝叶斯网络风险模型具有较高的估计效果,引入的空间聚集性较好地融入到贝叶斯概率推理模型中,合理建立预测因子同手足口病发病风险之间的关系。通过对建模结果的解译,分析了手足口病的发病风险影响因素,特别是气候、社会经济及空气污染的影响。本文的空间贝叶斯建模方法及研究结果对手足口病暴发的防控预警具有重要的意义。
[Abstract]:Hand, foot and mouth disease (HFMD) is a common infectious disease. Previous studies have shown that the disease is associated with meteorological, environmental and socio-economic factors. The common linear risk modeling method can not capture the complexity and spatial aggregation of influencing factors. Therefore, this paper takes Shandong Province as an example, on the basis of previous studies, The Bayesian network comprehensive risk modeling method is proposed to study the relationship between the incidence risk of HFMD and meteorological, land use, social economy and air pollution. The spatial aggregation is introduced to Bayesian network model to enhance its spatial reasoning function, to reduce the deviation of the model and to improve the accuracy of evaluation. The results show that the proposed spatial Bayesian network risk model for hand, foot and mouth disease has a high estimation effect. The spatial aggregation is well integrated into the Bayesian probability inference model, and the relationship between the predictive factors and the risk of HFMD is reasonably established. Through the interpretation of the modeling results, the influencing factors of HFMD risk are analyzed. Especially the effects of climate, social economy and air pollution. The spatial Bayesian modeling method and its results are of great significance to the prevention and control of HFMD outbreaks.
【作者单位】：中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室;中国科学院大学;
【基金】：国家自然科学基金项目(41471376、41171344) 上海市大气颗粒物污染防治重点实验室开放课题资助
【分类号】：R181.3;R725.1

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