  Touristic cities will suffer from COVID-19 emergency because of its economic
impact on their communities. The first emergency phases involved a wide closure
of such areas to support "social distancing" measures (i.e. travels limitation;
lockdown of (over)crowd-prone activities). In the second phase, individual's
risk-mitigation strategies (facial masks) could be properly linked to "social
distancing" to ensure re-opening touristic cities to visitors. Simulation tools
could support the effectiveness evaluation of risk-mitigation measures to look
for an economic and social optimum for activities restarting. This work
modifies an existing Agent-Based Model to estimate the virus spreading in
touristic areas, including tourists and residents' behaviours, movement and
virus effects on them according to a probabilistic approach. Consolidated
proximity-based and exposure-time-based contagion spreading rules are included
according to international health organizations and previous calibration
through experimental data. Effects of tourists' capacity (as "social
distancing"-based measure) and other strategies (i.e. facial mask
implementation) are evaluated depending on virus-related conditions (i.e.
initial infector percentages). An idealized scenario representing a significant
case study has been analysed to demonstrate the tool capabilities and compare
the effectiveness of those solutions. Results show that "social distancing"
seems to be more effective at the highest infectors' rates, although represents
an extreme measure with important economic effects. This measure loses its full
effectiveness (on the community) as the infectors' rate decreases and
individuals' protection measures become predominant (facial masks). The model
could be integrated to consider other recurring issues on tourist-related
fruition and schedule of urban spaces and facilities (e.g. cultural/leisure
buildings).
