With the COVID-19 pandemic, the role of infectious disease spreading in public places has
been brought into focus more than ever. Places that are of particular interest regarding the spread of
infectious diseases are international airport terminals, not only for the protection of staff and ground
crew members but also to help minimize the risk of the spread of infectious entities such as COVID-19
around the globe. Computational modelling and simulation can help in understanding and predicting
the spreading of infectious diseases in any such scenario. In this paper, we propose a model, which
combines a simulation of high geometric detail regarding virus spreading with an account of the
temporal progress of infection dynamics. We, thus, introduce an agent-based social force model for
tracking the spread of infectious diseases by modelling aerosol traces and concentration of virus load
in the air. We complement this agent-based model to have consistency over a period of several days.
We then apply this model to investigate simulations in a realistic airport setting with multiple virus
variants of varying contagiousness. According to our experiments, a virus variant has to be at least
twelve times more contagious than the respective control to result in a level of infection of more than
30%. Combinations of agent-based models with temporal components can be valuable tools in an
attempt to assess the risk of infection attributable to a particular virus and its variants