This study aims to investigate the advantages and actual forecast efficiency of the hybrid model in the early stage after the earthquake,improve the accuracy of strong aftershocks space-time forecast,so as to provide a model basis for the construction of operational earthquake forecasting research. We have developed the Coulomb-ETAS hybrid model,capitalizing on the Coulomb failure stress change to delineate the spatial stress distribution subsequent to an earthquake,and the ETAS model to characterize the decay pattern of aftershock sequences,recognized for its superior fit. The model's premise is anchored in the observation that strong aftershocks predominantly emerge in regions of stress concentration. It recalibrates the forecast probabilities,shifting emphasis from areas of stress release to those of stress accumulation,by leveraging the event occurrence ratios within the stress-loading regions during the model's training phase. The hybrid model's performance was rigorously tested and evaluated using data from four significant earthquakes(M≥6.0) in mainland China from 2021 to 2022:the Yunnan Yangbi M_S6.5,Qinghai Maduo M_S7.4,Qinghai Menyuan M_S6.9,and Sichuan Luding M_S6.8 earthquakes. These instances served to benchmark the hybrid model against both the standalone ETAS model and the C-RS model. Our findings indicate that all three models demonstrate commendable predictive performance for strong aftershocks in the post-earthquake phase,closely mirroring the observed decay characteristics with minimal predictive discrepancies. The Coulomb-ETAS model outperforms the C-RS model in frequency sliding forecasts,underscoring the pronounced advantage of incorporating statistical methodologies. Furthermore,it surpasses the ETAS model in spatial occurrence rate forecasting by integrating Coulomb stress,which effectively diminishes the rate of false alarms and augments the precision of spatial predictions. The comparative analysis across the four earthquake cases suggests that the hybrid model surpasses both the singular statistical and physical models in terms of spatio-temporal forecasting of strong aftershocks. It is well-suited for application post-mainshock and offers valuable insights for the integration of multiple models and the expansion of earthquake forecasting applications beyond the scope of strong aftershocks.