On Epidemic Spreading Mitigation via Heuristic Macro-Control of People Flow

We provide numerical investigation results of employment of macro-control measures towards epidemic spreading mitigation in closed spaces, via control of people transport dynamics. In particular, we construct heuristic, feedback control laws via manipulation of the average distance or maximum speed (or both) of pedestrians, whose movement is described by a crowd flow Partial Differential Equation (PDE). Towards this, we numerically implement a macroscopic PDE model consisting of a coupled crowd flow - epidemic transport process, with variable pressure coefficient or free-flow speed, which are manipulated depending on the maximum density within the space considered. The simulation results provide first evidence on how to systematically manipulate, in a feedback manner, people transport dynamics, towards epidemic spreading mitigation, demonstrating that the heuristic control measures developed can reduce the total number of individuals exposed in a disease.