In this article, we apply the stability theory of differential equations, based on the improved infectious disease transmission model SEIS, to describe the change in the number of infections when the lurker is a non-staff. In the process of the spread of infectious diseases, we establish the relationship between various groups, and establish the equation data solving algorithm. On this basis, a complex network model is established to describe the influence of the movement of various groups of people in the system on the number of infections when the lurker is a staff member. At the same time, the cellular automata simulation in accordance with the complex network models is carried out through the collected data. Finally, using the probabilistic model of the spread of infectious diseases, the impact of the protective effect on the spread of infectious diseases is analyzed when staff in public places take appropriate protective measures. Through the establishment of the probabilistic model and the curve fitted by the python program, we conclude that at the beginning of the spread of infectious diseases, the fastest and best protective measures can not only slow down the speed of the spread of infectious diseases, but also effectively reduce the infection in the later stages of transmission the proportion of the people.