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兰州市城关区气象因素与麻疹发病人数的时间序列研究
引用本文:陶燕,宋捷,强力,王砚,李子斌.兰州市城关区气象因素与麻疹发病人数的时间序列研究[J].中国环境科学,2014,34(11):2964-2969.
作者姓名:陶燕  宋捷  强力  王砚  李子斌
作者单位:1. 兰州大学资源环境学院,甘肃 兰州,730000
2. 兰州市城关区疾病预防控制中心传染病防制科,甘肃 兰州,730000
3. 甘肃省环境科学设计研究院,甘肃 兰州,730000
基金项目:国家自然科学基金,中央高校基本科研业务费专项资金资助
摘    要:运用SPSS17.0统计软件进行相关分析和主成分分析及R软件的时间序列方法定量评估兰州市城关区气象因素对麻疹发病人数的影响程度.结果表明,气象因素对麻疹日发病人数的影响由大至小依次为相对湿度、日照时间、平均气温、平均气压、降水量、平均风速;各气象因素对麻疹发病的影响均具有一定滞后效应,平均气压、平均风速和日照时间在滞后9d、平均气温和降水量滞后7d、相对湿度滞后5d对麻疹日发病人数的影响最大. 平均气压、平均气温和日照时间每增加1个IQR(四分位距),麻疹日发病人数分别增加175.2%、79.6%和24.3%,而相对湿度、降水量和平均风速每增加1个IQR,麻疹日发病人数则分别减少17.9%、5.2%和15.7%.

关 键 词:麻疹  气象因素  GAM模型  时间序列分析  
收稿时间:2014-02-27

Time series analysis between meteorological factors and measles in Chengguan District,Lanzhou
TAO Yan,SONG Jie,QIANG Li,WANG Yan,LI Zi-bin.Time series analysis between meteorological factors and measles in Chengguan District,Lanzhou[J].China Environmental Science,2014,34(11):2964-2969.
Authors:TAO Yan  SONG Jie  QIANG Li  WANG Yan  LI Zi-bin
Abstract:Influences of meteorological factors on measles in Chengguan District, Lanzhou were estimated by using three methods, including correlation analysis, principal component analyses from statistical software SPSS 17.0, and times series analysis from R software. The results indicated that relative humidity posed the largest influence on the occurrences of measles, followed by sunshine duration, average temperature, average air pressure, average precipitation, and average wind speed. In addition, the influences of various meteorological factors on the occurrence of measles displayed the lag effect. The average air pressure, average wind speed and average sunshine duration displayed the longest lagging time (9 days), followed by average temperature and precipitation (7 days), and relative humidity (5 days), respectively. For every IQR increased for average air pressure, average temperature, and sunshine time, the occurrence of measles increased by 175.2%, 79.6%, and 24.3%, however, for every IQR increased for relative humidity, precipatation and average wind speed resulted in the occurrence of measles decreased by 17.9%, 5.2% and 15.7%, respectively.
Keywords:measles  meteorological factor  GAM model  time series analysis
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