AGENT-BASED MODEL FOR LARGE (URBAN) SCALE SIMULATION OF PANDEMIC SPREAD

The ongoing worldwide COVID-19 pandemic has changed the world significantly since its outbreak in January 2020. Most governments across the world imposed different containment measures to minimize the spread of the virus. Moreover, public health experts and administrations highlighted the importance of planning these intervention strategies because they have heavy economic and social consequences. Agent-based simulations can be useful tools to evaluate the impact of the epidemic under different containment policies. This thesis project focuses on the development of a urban scale agent-based model parameterized for the city of Turin. Unity DOTS (Data Oriented Technology Stack) has been used to simulate the behaviour of a large number of agents, which move across a 2D tile-map environment following a BDI (Belief, Desire, Intention) routine model. Different intervention policies have been implemented, both non-pharmaceutical and pharmaceutical, to evaluate various scenarios that trying to keep a low infection rate, such as partial or total lockdown and vaccination policy.