  We propose a multi-layer network model for the spread of COVID-19 that
accounts for interactions within the family, between schoolmates, and casual
contacts in the population. We utilize the proposed model-calibrated on
epidemiological and demographic data-to investigate current questions
concerning the implementation of non-pharmaceutical interventions (NPIs) during
the vaccination campaign. Specifically, we consider scenarios in which the most
fragile population has already received the vaccine, and we focus our analysis
on the role of schools as drivers of the contagions and on the implementation
of targeted intervention policies oriented to children and their families. We
perform our analysis by means of a campaign of Monte Carlo simulations. Our
findings suggest that, in a phase with NPIs enacted but in-person education,
children play a key role in the spreading of COVID-19. Interestingly, we show
that children's testing might be an important tool to flatten the epidemic
curve, in particular when combined with enacting temporary online education for
classes in which infected students are detected. Finally, we test a vaccination
strategy that prioritizes the members of large families and we demonstrate its
good performance. We believe that our modeling framework and our findings could
be of help for public health authorities for planning their current and future
interventions, as well as to increase preparedness for future epidemic
outbreaks.
