【摘要】 目的探讨北京市结核病时空演化特征与生态影响因素。方法基于Bayes时空理论,对2005-2009年北京市18区县结核病患病数据进行时空建模,以DIC值最小为标准找出最优模型,并研究协变量对模型的影响,结合ArcGis10.0软件绘制北京市18区县结核病时空危险度的分布图谱。结果全部模型中,含协变量的时空交互效应模型最优(DIC=818.834),生态分析的结果表明,除人均地区生产总值的升高会降低结核病危险度之外,每千人口拥有床位数、年平均相对湿度、年平均空气质量指数和年平均最高温度的升高会增高结核病患病危险度。结论 Bayes时空模型与生态学分析技术结合,能动态分析结核病的时空演化特征和生态影响因素,有利于发现重点疫区,为制定适宜的防治措施提供科学依据。更多还原

【Abstract】 Objective To explore tuberculosis temporal-spatial evolution characteristics and ecological factors.Methods The model is based on the tuberculosis data in Beijing 18 districts and counties between2005 and 2009,find out the optimum model( DIC minimum value),and by using ecology analysis technology,finding out association of tuberculosis risk and covariates,and combined with ArcGis10.0 show the distribution of space and time risk of tuberculosis in Beijing 18 districts and counties.Results The optimization model is Bayes spatial-temporal interactive model( DIC =818.834).The results of ecological analysis shows that the risk of tuberculosis are significantly associated with the number of bed in hospital,annual average relative humidity,annual average air quality index and annual average temperature.Conclusion Combination of Bayes spatial-temporal model and ecological analysis will help for finding key areas of tuberculosis.更多还原