Background Xinjiang is the second largest pastoral areas, and the main arid and semi-arid regions in China. The echinococcosis in Xinjiang has been brought serious challenge and large pressure for the disease control and prevention.Methods We comprehensively investigated the echinococcosis temporal variations at multiple time scales in Xinjiang during the period of 2004-2020. The relationships between the echinococcosis and the impact factors (i.e., Tmp: temperature, Pre: precipitation, RH: relative humidity, and SD: sunshine duration), and MR (medicine rate accounting in gross domestic product) are detected. Moreover, the echinococcosis is predicted by the combined model: ARIMA (autoregressive integrated moving average) and RF(random forest) hybrid model using the five factors.Results The results indicate the echinococcosis has a significant increased trend for both confirmed cases and incidence rates with the annual trend values of 94.48 cases per year, and 0.339 new cases per 100,000 population per year. Moreover, the echinococcosis in Xinjiang has the nonlinear characteristics with the multiple periods of the 3-, 6-, 13-, 40-, and 67-month for the confirmed cases, and 3-, 6-, 12-, 34-, and 73-month for the incidence rates. In terms of the impact factors, Tmp has the positive impacts on echinococcosis, and SD has the negative impact at annual and seasonal scales. Pre has the positive impact on echinococcosis at annual, June, July and August (JJA), and September, October, and November (SON). RH has the positive relationship at JJA. MR has the significant positive relationship with echinococcosis. The ARIMA-RF hybrid model has high performance in predicting the echinococcosis variations.Conclusions Echinococcosis in Xinjiang has a significant increased trend during the period of 2004-2020. Tmp and MR have the positive impact on the echinococcosis. The ARIMA-RF hybrid model can well predict the disease variations. Our finding can provide more characteristics about the echinococcosis variations in Xinjiang, which is the basic and important information for the disease control and prevision.