Runway risk identification is crucial for ensuring airport safety and operational efficiency. However, existing studies mainly focus on causal analysis of runway safety incidents while neglecting the dynamic mechanism of risk propagation. To address this gap, an integrated model combining event tree analysis (ETA) and complex network theory was proposed. Accident chain information was extracted to construct a runway safety risk network encompassing four dimensions including personnel, equipment, environment, and management. Considering the delay effect of safety control measures, the susceptible-infectious-recovered-susceptible (SIRS) model was employed to simulate the processes of risk occurrence, diffusion, mitigation, and recurrence. Simulation results demonstrate that the proposed model can reproduce the underlying mechanisms and patterns of runway risk propagation. Personnel and management factors serve as key nodes in risk transmission, particularly “insufficient organizational training” and “inadequate training/experience,” which exhibit the highest diffusion intensities with peak infection rates of 0.595 238 and 0.571 429, respectively. Targeted safety management for these key nodes can effectively suppress risk propagation. This study provides a new methodological framework for enhancing airport operational safety management.