An Epidemic Model for SARS-CoV-2 with Self-Adaptive Containment Measures

During the COVID-19 pandemic, several countries have resorted to self-adaptive mechanisms that allow non-pharmaceutical interventions to be tailored to local epidemiological and health care indicators. These mechanisms reinforce the interdependence between containment measures and the evolution of the epidemic, mostly overlooked by existing epidemiological models. In our innovative approach, we instead develop a model that embeds an algorithm mimicking the self-adaptive policy mechanism, effective in Italy since November 2020, and allows us to track the historical evolution of both health outcomes and restrictions in the country. By focusing on the epidemic wave triggered by the onset of the Delta variant, we compare the functioning of alternative mechanisms to show how the policy framework may affect the trade-off between health outcomes and the restrictiveness of mitigation measures. This trade-off varies considerably depending on specific conditions (e.g. vaccination coverage), with less reactive mechanisms (e.g. those based on occupancy rates) becoming more advantageous in favourable contexts.