Modeling and simulation of disease spreading in pedestrian crowds have recently become a topic of increasing relevance. In this paper, we consider the influence of the crowd motion in a complex dynamical environment on the course of infection of the pedestrians. To model the pedestrian dynamics, we consider a kinetic equation for multi-group pedestrian flow based on a social force model coupled with an Eikonal equation. This model is coupled with a non-local SEIS contagion model for disease spread, where besides the description of local contacts, the influence of contact times has also been modeled. Hydrodynamic approximations of the coupled system are derived. Finally, simulations of the hydrodynamic model are carried out using a mesh-free particle method. Different numerical test cases are investigated, including uni- and bi-directional flow in a passage with and without obstacles.
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Univ Paris Saclay, INRAE, AgroParisTech, UMR SayFood 0782, F-91300 Massy, FranceUniv Paris Saclay, INRAE, AgroParisTech, UMR SayFood 0782, F-91300 Massy, France
Jenkinson, William J.
Flick, Denis
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Univ Paris Saclay, INRAE, AgroParisTech, UMR SayFood 0782, F-91300 Massy, FranceUniv Paris Saclay, INRAE, AgroParisTech, UMR SayFood 0782, F-91300 Massy, France
Flick, Denis
Vitrac, Olivier
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Univ Paris Saclay, INRAE, AgroParisTech, UMR SayFood 0782, F-91300 Massy, FranceUniv Paris Saclay, INRAE, AgroParisTech, UMR SayFood 0782, F-91300 Massy, France
Vitrac, Olivier
Guthrie, Brian
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Cargill Global Core Res, Minneapolis, MN USAUniv Paris Saclay, INRAE, AgroParisTech, UMR SayFood 0782, F-91300 Massy, France
Guthrie, Brian
12TH INTERNATIONAL CONFERENCE ON SIMULATION AND MODELLING IN THE FOOD AND BIO-INDUSTRY 2022 (FOODSIM'2022),
2022,
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