Effects of mobility restrictions during COVID19 in Italy
Alex Smolyak, Giovanni Bonaccorsi, Andrea Flori, Fabio Pammolli, Shlomo Havlin
Abstract
To reduce the spread and the effect of the COVID-19 global pandemic, non-pharmaceutical\ninterventions have been adopted on multiple occasions by governments. In particular lockdown\npolicies, i.e., generalized mobility restrictions, have been employed to fight the first wave of the\npandemic. We analyze data reflecting mobility levels over time in Italy before, during and after the\nnational lockdown, in order to assess some direct and indirect effects. By applying methodologies\nbased on percolation and network science approaches, we find that the typical network\ncharacteristics, while very revealing, do not tell the whole story. In particular, the Italian mobility\nnetwork during lockdown has been damaged much more than node- and edge-level metrics indicate.\nAdditionally, many of the main Provinces of Italy are affected by the lockdown in a surprisingly similar\nfashion, despite their geographical and economic dissimilarity. Based on our findings we offer an\napproach to estimate unavailable high-resolution economic dimensions, such as real time Provincelevel\nGDP, based on easily measurable mobility information.