Abstract: Objective To compare predictive capacity and fitting efficiency of autoregressive integrated moving average model (ARIMA),radical basis function model (RBF),and ARIMA-RBF combined model for monthly incidence of hand-foot-mouth disease (HFMD) in China and to explore an optimized model.Methods Data on monthly incidence of HFMD from January 2008 to December 2014 in China were collected and ARIMA,RBF,and ARIMA-RBF combined models were established based on the data;then the data for the period from July to December 2014 were introduced back to the established models to evaluate their predictive capacity.The indexes of fitting efficiency of the models included relative error (RE),mean relative error (MRE),mean square error (MSE),root mean square error (RMSE),and mean absolute error (MAE).Results The MRE,MSE,RMSE,and MAE were 14.006,4.689,2.165,and 0.916 for ARIMA fitting model;13.565,4.416,2.101,and 0.577 for ARIMA predictive model;9.031,1.559,1.249,and 0.508 for RBF fitting model;8.964,1.504,1.226,and 0.503 for RBF predictive model;6.397,1.357,1.165,and 0.416 for ARIMA-RBF combined fitting model;and 6.655,1.485,1.218,and 0.433 for ARIMA-RBF combined predictive model,respectively.For the three established models,the fitting and predictive values of ARIMA-RBF combined model were closest to the original data.Conclusion The ARIMA-RBF combination model is superior to ARIMA model and RBF model in fitting and prediction of HFMD monthly incidence in China.