Modeling and simulation of SARS-CoV-2 transmission in dynamic crowds

This work presents a modeling approach for the transmission of pathogens such as the coronavirus. A transmission model is integrated into agent-based crowd models, which permits the analysis of specific spreading events. The simulator is open-source. Reenacting superspreading events and predicting individual exposure risks for various scenarios using uncertainty quantification methods support the model's validity.