In recent years， respiratory infectious diseases break out in crowded places frequently. How to restore transmission path of the virus between people has become a key issue in epidemic prevention and control. However， the existing methods have problems such as the difficulty in describing the crowd movement trajectory in crowded places and the difficulty in simulating spread of the virus caused by contact between people. To this end， a virus transmission’s visual analysis system of Agent-Based Modeling （ABM） was proposed to simulate dynamically and visualize the virus transmission process as well as show individual contact relationships and transmission paths. Firstly， a multi-head rapidly-exploring random tree algorithm was combined with movement statistical data to generate crowd movement trajectories conforming to actual laws. Secondly， by refining the contact rules of people and the virus transmission mechanism， a transmission model based on ABM was constructed to simulate the impact of crowd interaction on virus transmission. Case analysis shows that the virus transmission’s visual analysis system restores the contact relationship between people and the process of virus transmission between people， the transmission chain simulated by the system is highly similar to the actual chain， the number of simulated cases is basically consistent with the actual number of cases， and the multi-head rapidly-exploring random tree algorithm can generate highly realistic trajectories efficiently. The case verifies the decision support value of the system in the optimization of epidemic prevention and control strategies.