The forecast results suggest that the HFRS incidence in China will experience a slight growth in the next three years (2009) (2010) (2011) . A rise in the number of HFRS incidence may also result from an increase in the number and size of natural foci [25] , climate change, especially the increase of mean temperature [26, 27] . Therefore, knowledge of HFRS forecasts is necessary to prompt health departments to strengthen surveillance systems and reallocate resources in anticipation of increasing HFRS incidence. Several studies have used ARIMA model to fit and predict changing trends in infectious disease. Luz et al applied an ARIMA(2,0,0)×(1,0,0) 12 model to predict dengue incidence in Rio de Janeiro [18] and found that ARIMA models were useful tools for monitoring dengue incidence. Earnest et al indicated that ARIMA models provided useful tools for administrators and clinicians in planning for real-time bed capacity during infectious diseases outbreaks such as SARS [28] . Li et al have applied an ARIMA model to monthly incidence of HFRS in Linyi City, China to predict HFRS incidence, and found that the ARIMA model could be used to predict HFRS incidence with high predictive precision in the short-term [29] . In the present study, we further confirmed the consensus that ARIMA model is a useful tool in monitoring and predicting changing trends in infectious diseases.