title: [The application of time series analysis in predicting the influenza incidence and early warning].
abstract: OBJECTIVE
  This research aimed to explore the application of ARIMA model of time series analysis in predicting influenza incidence and early warning in Jiangsu province and to provide scientific evidence for the prevention and control of influenza epidemic.
  
  
  METHODS
  The database was created based on the data collected from monitoring sites in Jiangsu province from October 2005 to February 2010. The ARIMA model was constructed based on the number of weekly influenza-like illness (ILI) cases. Then the achieved ARIMA model was used to predict the number of influenza-like illness cases of March and April in 2010.
  
  
  RESULTS
  The ARIMA model of the influenza-like illness cases was (1 + 0.785B(2))(1-B) ln X(t) = (1 + 0.622B(2))ε(t). Here B stands for back shift operator, t stands for time, X(t) stands for the number of weekly ILI cases and ε(t) stands for random error. The residual error with 16 lags was white noise and the Ljung-Box test statistic for the model was 5.087, giving a P-value of 0.995. The model fitted the data well. True values of influenza-like illness cases from March 2010 to April 2010 were within 95%CI of predicted values obtained from present model.
  
  
  CONCLUSIONS
  The ARIMA model fits the trend of influenza-like illness in Jiangsu province.
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 210029, China.
authors.forename: Meng
authors.initials: M
authors.lastname: Zhu
authors.forename: Rong-qiang
authors.initials: RQ
authors.lastname: Zu
authors.forename: Xiang
authors.initials: X
authors.lastname: Huo
authors.forename: Chang-jun
authors.initials: CJ
authors.lastname: Bao
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhao
authors.forename: Zhi-hang
authors.initials: ZH
authors.lastname: Peng
authors.forename: Rong-bin
authors.initials: RB
authors.lastname: Yu
authors.forename: Hong-bing
authors.initials: HB
authors.lastname: Shen
authors.forename: Feng
authors.initials: F
authors.lastname: Chen
mesh_terms: D006801:Humans; D007251:Influenza, Human / Q000517:prevention & control*; D015233:Models, Statistical; D013997:Time Factors