摘要
目的通过时间序列分析方法揭示广州市流感的流行特征。方法采用差分自回归移动平均模型(ARIMA)、季节结构、互相关、谱分析等常用的时间序列分析方法对广州市流感监测数据进行分析。结果 2004-2008年,广州市流感样病例就诊百分比(ILI%)夏季最高,季节指数为1.637;ILI%ARIMA模型为xt=0.785xt-1+0.201xt-2;对暴发疫情序列分别与ILI%、病毒分离率两条序列进行互相关分析,当lag=-1、-2、-3时,病毒分离率与暴发疫情、ILI%与暴发疫情相关系数均有统计学意义。ILI%、病毒分离率、暴发疫情的原始序列的周期图,每12个月有1个很强的周期活动。结论时间序列分析方法应用于广州流感监测的数据,能较全面揭示广州市流感的时间流行特征。
Objective To analyze the epidemiologic characteristics of influenza in time series in Guangzhou. Methods Autoregressive integrated moving average model （ARIMA）, seasonal decomposition, cross-correlation, and spectral analysis were adopted for the study. Results From 2004 to 2008, ILI%（influenza-like illness,ILI） is the highest in summer, the seasonal index is 1.637; the ARIMA model of ILI% is xt=0.785xt=1＋0.201xt-2〉 The correlation analysis with these three groups of data were conducted. When lag = - 1, -2, -3, the cross correlation coefficient of virus isolation rate and outbreaks, ILI% and outbreaks were statistical significance. In view of the initial series periodogram of ILI%, virus isolation rate and epidemic outbreaks, a strong periodicity can be found at ＂twelve months＂. Conclusion The time series analysis skills may be applied to analyze the data of influenza surveillance in Guangzhou,to reflect the epidemiologic characteristics of influenza.
出处
《热带医学杂志》
CAS
2012年第11期1373-1375,1412,共4页
Journal of Tropical Medicine
