tetano
Editor, Senior Moderator
Zhonghua Yu Fang Yi Xue Za Zhi. 2011 Dec;45(12):1108-11.
[The application of time series analysis in predicting the influenza incidence and early warning].
[Article in Chinese]
Zhu M, Zu RQ, Huo X, Bao CJ, Zhao Y, Peng ZH, Yu RB, Shen HB, Chen F.
Source
Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 210029, China.
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.
CONCLUSION:
The ARIMA model fits the trend of influenza-like illness in Jiangsu province.
PMID:
22336347
[PubMed - in process]
http://www.ncbi.nlm.nih.gov/pubmed/22336347
[The application of time series analysis in predicting the influenza incidence and early warning].
[Article in Chinese]
Zhu M, Zu RQ, Huo X, Bao CJ, Zhao Y, Peng ZH, Yu RB, Shen HB, Chen F.
Source
Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 210029, China.
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.
CONCLUSION:
The ARIMA model fits the trend of influenza-like illness in Jiangsu province.
PMID:
22336347
[PubMed - in process]
http://www.ncbi.nlm.nih.gov/pubmed/22336347