韩建康, 刘小琦, 顾志伟, 金玫华, 朱红, 陈卫峰. 气象因素对呼吸道疾病的影响及预报研究[J]. 疾病监测, 2008, 23(11): 674-677. DOI: 10.3784/j.issn.1003-9961.2008.11.674
引用本文: 韩建康, 刘小琦, 顾志伟, 金玫华, 朱红, 陈卫峰. 气象因素对呼吸道疾病的影响及预报研究[J]. 疾病监测, 2008, 23(11): 674-677. DOI: 10.3784/j.issn.1003-9961.2008.11.674
HAN Jian-kang, LIU Xiao-qi, GU Zhi-wei, JIN Mei-hua, ZHU Hong, CHEN Wei-feng. Study of the impact of meteorological factors to respiratory tract diseases and the prediction model[J]. Disease Surveillance, 2008, 23(11): 674-677. DOI: 10.3784/j.issn.1003-9961.2008.11.674
Citation: HAN Jian-kang, LIU Xiao-qi, GU Zhi-wei, JIN Mei-hua, ZHU Hong, CHEN Wei-feng. Study of the impact of meteorological factors to respiratory tract diseases and the prediction model[J]. Disease Surveillance, 2008, 23(11): 674-677. DOI: 10.3784/j.issn.1003-9961.2008.11.674

气象因素对呼吸道疾病的影响及预报研究

Study of the impact of meteorological factors to respiratory tract diseases and the prediction model

  • 摘要: 目的 研究气象条件对呼吸道疾病发病影响,并建立最佳预报模型。方法 收集湖州市2006年呼吸道疾病发病资料以及同期气象资料,进行Spearman相关分析;采用决策树自动交互检测方法(AID)建立预报模型,并对模型进行评价。结果 相关分析显示,最低气温、水汽压、相对湿度、最小湿度、降水量、日照时数与呼吸道疾病存在相关性,按周建立气象因素与呼吸道疾病预报模型和三个预警等级,预报模型拟合结果IR/Isup2/sup=0.3857。结论 呼吸道疾病发病与气象因素密切相关,按周建立预警、预报模型效果较好,可行性较佳。

     

    Abstract: Objective To study the impact of meteorological factors on the incidence of respiratory tract diseases and establish an optimal prediction model for the incidence of the diseases. Methods The meteorological data and the incidence data of respiratory tract diseases in Huzhou in 2006 were collected for Spearman correlation analysis. The prediction model was established by automatic interaction detectors (AID). Results Correlation analysis revealed that the incidence of respiratory tract diseases was correlated with the minimum temperature, water-vapor pressure, relative humidity, minimum humidity, precipitation and sunshine duration. The weekly prediction model of meteorological factors to respiratory tract diseases with three warning levels was set up with the fit value IR/Isup2/sup=0.3857. Conclusion Meteorological factors were closely related to the incidence of respiratory tract diseases. The weekly warning/prediction model is feasible.

     

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