Objective: Hot events often lead to rampant online rumor spread. To prevent the incitement of public sentiment and the exacerbation of social contradictions, government departments must conduct timely and accurate situation assessment and response efficiency analysis before the outbreak of an online rumor crisis. In this regard, this paper investigates the trigger mechanism and congestion effects of online rumor crises. Methods: By analyzing the evolution system of online rumors, a model for the trigger mechanism and congestion effects of online rumor crises is constructed using the improved susceptible exposed infectious recovered (SEIR) model and the stochastic Petri net (SPN). The constructed trigger model, SE(ER)IR-SPN, is refined by delineating the involved latent population group into exaggerators or rational spreaders. The equilibrium system state and precise trigger timing are obtained by analyzing transmission equilibrium points, trigger thresholds, and the density change trends of different characteristic groups. The congestion effects of emergency responses to crisis events after the outbreak of rumors are analyzed based on the busy rates of places and the utilization rates of transitions. Finally, the model applicability is verified using a medical and health event in City A as a case study. Results: The research indicates that the SE(ER)IR-SPN model can detect high-risk online rumor events early, providing decision support for government departments during the disposal phase based on the busy rates of places and the utilization rates of transitions. The model effectively captures the dynamics of rumor spread and the subsequent congestion effects in emergency response processes. Conclusions: The SE(ER)IR-SPN model is a valuable tool for the early identification of online rumor crises, enabling government departments to make informed decisions during the disposal phase. Detailed analysis of the model components, including the busy rates of places and the utilization rates of transitions, offers insights into the optimization of emergency response workflows. The case study considered herein confirms the practical utility of the model, highlighting the potential for broad application in managing and mitigating the impact of online rumor crises.irms the practical utility of the model, highlighting the potential for broad application in managing and mitigating the impact of online rumor crises.