Abstract: Objective To build appropriate prediction model of influenza like illness (ILI) using Autoregressive Integrated Moving Average (ARIMA) modelMethods We collected the data of ILI surveillance from 2006 to 2011 in Nanshan District, Shenzhen, and built ARIMA model according to Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC). The autocorrelation analysis and Partial correlation analysis were used to identify the model. The model diagnosis was performed using Q statistic analysis.The actual ILI surveillance data in 2012 were compared with predictive value of the model to evaluate its predictive effect. Results A total of 199 360 ILI cases were reported from 2006 to 2011.The month max was 9765cases, the month min was 594 cases, and the average was 2769 cases per month. The annual incidence of ILI cases presented obvious peaks and valleys in 2006-2011. The incidence peak was from May to August and the incidence valley was from November to February each year. Relatively smooth sequence was obtained and suitable for model fitting. ARIMA (0,1,1)×(0,0,1)12 was selected as the optimal model.AIC and BIC values were the least, 1239.19 and 1245.98, respectively. The Q statistic was 19.07 (P>0.05) by Box-Ljung testing, indicating the applicability of the model. There was no statistically significant difference between the observed value in 2012 and predicted value (P>0.05). Conclusion ARIMA model is suitable for prediction of ILI incidence