  Initially emerged in the Chinese city Wuhan and subsequently spread almost
worldwide causing a pandemic, the SARS-CoV-2 virus follows reasonably well the
SIR (Susceptible-Infectious-Recovered) epidemic model on contact networks in
the Chinese case. In this paper, we investigate the prediction accuracy of the
SIR model on networks also for Italy. Specifically, the Italian regions are a
metapopulation represented by network nodes and the network links are the
interactions between those regions. Then, we modify the network-based SIR model
in order to take into account the different lockdown measures adopted by the
Italian Government in the various phases of the spreading of the COVID-19. Our
results indicate that the network-based model better predicts the daily
cumulative infected individuals when time-varying lockdown protocols are
incorporated in the classical SIR model.
