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兰州市城关区流行性感冒与气象因素的时间序列 被引量:8

An analysis of the relationship between meteorological factors and flu in Chengguan District,Lanzhou City
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摘要 采用相关性分析、主成分分析及时间序列半参数广义相加模型对兰州市城关区2005-2010年气象因素与流行性感冒日就诊人数之间的关系进行了分析.该区的流行性感冒多发于冬、春季;流行性感冒日就诊人数与平均气温、平均风速、平均气压显著相关;平均气温、日照时数、降水量、相对湿度、平均风速及平均气压对流行性感冒的影响具有滞后效应(0~7 d),各气象因素每上升1个4分位间距,流行性感冒的相对危险度分别为0.49、0.74、0.91、0.89、0.84和2.61,即日就诊人数分别减少51.3%、26.1%、8.7%、11.5%、15.9%,增加160.5%.兰州市城关区的流行性感冒呈明显的季节性,低温容易引起发病. The connection between the outpatients with flu and meteorological conditions for Chengguan District, Lanzhou City was investigated into, and relationship between the time area of 2005 to 201 O's meteorological factors and the number of the outpatients with flu-days was analyzed. Correlation analysis, principal component analysis and time series of semi-parametric generalized additive model analysis of the meteorological factors and the number of the outpatients with flu-days were done. As were shown by the results, influenza outbreak mainly occurred in spring and winter; daily influenza visits number had an obvious connection with the average air temperature, average wind speed and mean air press; the influence of average temperature, insolation duration, precipitation, mean air press, relative humidity, average wind speed, mean air press had lag effects (1-7 d), the influence of average wind speed lagged one day, with the increase of 1 inter quartile range, the influenza relative risk value was 0.49, 0.74, 0.91, 0.89, 0.84 and 2.61, which meant that the daily influenza visits decreased separately by 51.3%, 26.1%, 8.7%, 11.5%, 15.9% respectively and increased by 160.5%. The result showed that the outpatients with flu number in Chengguan District occurred seasonally, and the low temperature can easily cause the influenza.
出处 《兰州大学学报(自然科学版)》 CAS CSCD 北大核心 2018年第1期137-142,共6页 Journal of Lanzhou University(Natural Sciences)
基金 国家自然科学基金项目(41075102 41005087) 中央高校基本科研业务费专项资金项目(LZUJBKY-2013-m03)
关键词 流行性感冒 气象因素 时间序列分析 广义相加模型 influenza meteorological factor time series analysis generalized additive model
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