  Wireless networks are commonly used in public spaces, universities and public
institutions and provide accurate and easily accessible information to monitor
the mobility and behavior of users. Following the application of containment
measures during the recent pandemic, we analyse extensive data from the WiFi
network in a University Campus in Italy during three periods, corresponding to
partial lockdown, partial opening, and almost complete opening. We measure the
probability distributions of groups and link activation at Wi-Fi Access Points,
investigating how different areas are used in the presence of restrictions. We
rank the hotspots and the area they cover according to their crowding and to
the probability of link formation, which is the relevant variable in
determining potential outbreaks. We consider a recently proposed epidemic model
on simplicial temporal networks and we use the measured distributions to infer
the change in the reproduction number in the three phases. Our data show that
additional measures are necessary to limit the epidemic spreading in the total
opening phase, due to the dramatic increase in the number of contacts.
