According Figure 1 , the series showed a non-stationary mean, so we stabilized the mean of HFRS incidence by taking both second and third order differences. All further statistical procedures were performed on the transformed HFRS incidence. Based on the distribution characteristics, we conducted five models, ARIMA(0, 2, 1), ARIMA(1,2,1), ARIMA(0,3,1), ARIMA(1, 3, 1), and ARIMA (2, 3, 1) . Of all the models tested, the ARIMA (0,3,1) model was the best fit for the data ( Table 1 ). The transformation series by taking third-order differences is shown in Figure 2 . The plots of ACF and PACF ( Figure  3 ) described the temporal dependence structure in HFRS incidence. The slow decay in the PACF, associated with a ACF cutoff at lag 1 suggested a MA(q = 1).