  Restarting public buildings activities in the "second phase" of COVID-19
emergency should be supported by operational measures to avoid a second virus
spreading. Buildings hosting the continuous presence of the same users and
significant overcrowd conditions over space/time (e.g. large offices,
universities) are critical scenarios due to the prolonged contact with
infectors. Beside individual's risk-mitigation strategies performed (facial
masks), stakeholders should promote additional strategies, i.e. occupants' load
limitation (towards "social distancing") and access control. Simulators could
support the measures effectiveness evaluation. This work provides an
Agent-Based Model to estimate the virus spreading in the closed built
environment. The model adopts a probabilistic approach to jointly simulate
occupants' movement and virus transmission according to proximity-based and
exposure-time-based rules proposed by international health organizations.
Scenarios can be defined in terms of building occupancy, mitigation strategies
and virus-related aspects. The model is calibrated on experimental data
("Diamond Princess" cruise) and then applied to a relevant case-study (a part
of a university campus). Results demonstrate the model capabilities. Concerning
the case-study, adopting facial masks seems to be a paramount strategy to
reduce virus spreading in each initial condition, by maintaining an acceptable
infected people's number. The building capacity limitation could support such
measure by potentially moving from FFPk masks to surgical masks use by
occupants (thus improving users' comfort issues). A preliminary model to
combine acceptable mask filters-occupants' density combination is proposed. The
model could be modified to consider other recurring scenarios in other public
buildings (e.g. tourist facilities, cultural buildings).
