Forecasting hepatitis epidemic situation by applying the time series model
by Yinping Chen; Aiping Wu; Hongmin Fan; Cuiling Wang
International Journal of Simulation and Process Modelling (IJSPM), Vol. 7, No. 1/2, 2012

Abstract: The autoregressive integrated moving average (ARIMA) model is one of the stochastic time series methods to predict the hepatitis incidence. Considering the Box-Jenkins modelling approach, the incidence of hepatitis was collected monthly from 2004 to 2010 in Qian'an and a model (SARIMA) was fit. Then, this model was used for calculating hepatitis incidence for the last six observations compared with observed data. The constructed model was performed to predict the monthly incidence in 2011. The model SARIMA(0,1,1)(0,1,1)₁₂ was established finally and the residual sequence was a white noise sequence. It is necessary and practical to apply the approach of ARIMA model in fitting time series to predict hepatitis within a short lead time.

Online publication date: Sat, 15-Nov-2014

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