Sustainable and resilient strategies for touristic cities against COVID-19: an agent-based approach
Marco D'Orazio, Gabriele Bernardini, Enrico Quagliarini

TL;DR
This paper develops an agent-based simulation model to evaluate COVID-19 mitigation strategies in touristic cities, analyzing the effectiveness of social distancing and mask-wearing on virus spread and economic impact.
Contribution
It introduces a modified agent-based model incorporating probabilistic contagion rules and evaluates mitigation strategies' effectiveness in touristic urban settings.
Findings
Social distancing is most effective at high infection rates.
Mask-wearing becomes more effective as infection rates decrease.
The model demonstrates the trade-off between health measures and economic impact.
Abstract
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…
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