Several models for the spread of disease exist, but the physical spread of disease in a crowd is still poorly understood even though greater insight could help reduce the risks of pandemics. This work reviews some of the existing epidemic models before presenting a coupling of an SIR epidemic model and the Vadere crowd simulation model developed by a research group at the Munich University of Applied Sciences. The resulting model is then validated against predicted results from previous epidemic models and the implementation is verified by individually checking several of the methods involved, to ensure there is no unexpected behaviour. A visualization of the results of the simulations is also presented. The impact of individual parameters of the model are then measured by modifying these parameters one at a time while keeping the others constant, and an interpretation of these results is given. Once the model is validated, it is applied on a larger example scenario to demonstrate its behavior in a more realistic setting. The results, as well as possible improvements are then discussed at the end of the thesis.
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Several models for the spread of disease exist, but the physical spread of disease in a crowd is still poorly understood even though greater insight could help reduce the risks of pandemics. This work reviews some of the existing epidemic models before presenting a coupling of an SIR epidemic model and the Vadere crowd simulation model developed by a research group at the Munich University of Applied Sciences. The resulting model is then validated against predicted results from previous epidemic...
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