Living Along COVID-19: Assessing Contention Policies Through Agent-Based Models

SARS-CoV-2 has become an endemic disease, and we will have to face the continuous rise of new variants. Designing and evaluating the effects of new containment policies is of primary importance to keep social activities going as safely as possible according to the different stages of the pandemic. Therefore, we propose an Agent-Based Model to study the evolution of SARS-CoV-2 spread in a well-defined environment (of small/medium size, like a shop, a restaurant, an office, a school, with fewer than a hundred or a few hundred people) to assess the efficacy of different non-pharmaceutical interventions and vaccination strategies. Specifically, we focused on schools, given that the COVID-19 quarantine has resulted in substantial disruptions to education, leading to a transition to remote learning and worsening educational inequalities. We consider using face masks and several real-world testing protocols combined with quarantine policies. All protocols/policies have been evaluated at various stages of the pandemic evolution. Results show that testing campaigns are effective as far as the testing process is faster than the virus diffusion. Also, vaccination campaigns covering less than 40% of the susceptible population provide poor results in protecting from a major outbreak, even if the circulation of the virus is low. Our empirical findings reveal a decreasing effectiveness of various policy implementations as viral circulation intensifies. Additionally, our analysis shows a consistent reduction in infection rates due to the continued use of facial protective measures, regardless of the level of viral circulation.