Abstract: Objective To utilize the product seasonal model to predict the trend of TB and provide scientific evidence for formulating the related measures of prevention and cure.  Methods The product seasonal model was combined with ARIMA model and stochastic seasonal model by using the least square principle.  Results The ARIMA（0,1,1）（0,1,1）₄ model was established by the data from 1996 to 2008, and the effectiveness of prediction of this model showed to be good with the actual values in the 95％ confidence interval of predicted values.  Conclusion The ARIMA product seasonal model shows effective to predict the incidence of TB in Guangdong province, and the Results is in according to the current status of TB, moreover, it could provide information for us to take measures for TB prevention and control.

Key words: tuberculosis,pulmonary/prevention and control, tuberculosis, pulmonary/epidemiology, incidence, time, Guangdong province