Title: Forecasting hepatitis epidemic situation by applying the time series model

Authors: Yinping Chen; Aiping Wu; Hongmin Fan; Cuiling Wang

Addresses: Hebei Province Key Laboratory of Occupational Health and Safety for Coal Industry, Department of Epidemiology and Health Statistics, School of Public Health, Hebei United University, No. 57, Jianshe South Road, Tangshan, Hebei 063000, China. ' Department of Pathology, Hebei United University, Tangshan, Hebei 063000, China. ' Hebei Province Key Laboratory of Occupational Health and Safety for Coal Industry, Department of Epidemiology and Health Statistics, School of Public Health, Hebei United University, No. 57, Jianshe South Road, Tangshan, Hebei 063000, China. ' Center for Disease Control and Prevention of Qian'an County, Department of Infectious Disease Control, Gangcheng East Road, Qian'an, China

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.

Keywords: ARIMA model; time series; short-term forecasting; hepatitis epidemics; modelling; monthly incidence; infectious diseases.

DOI: 10.1504/IJSPM.2012.047857

International Journal of Simulation and Process Modelling, 2012 Vol.7 No.1/2, pp.42 - 49

Published online: 15 Nov 2014 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article