  In the present work, we study how the number of simulated clients (occupancy)
affects the social distance in an ideal supermarket. For this, we account for
realistic typical dimensions and process time (picking products and checkout).
From the simulated trajectories, we measure events of social distance less than
2 m and its duration. Between other observables, we define a social distance
coefficient that informs how many events (of a given duration) suffer each
agent in the system. These kinds of outputs could be useful for building
procedures and protocols in the context of a pandemic allowing to keep low
health risks while setting a maximum operating capacity.
