Between Geography and Demography: Key Interdependencies and Exit Mechanisms for Covid-19

Antonio Scala; Andrea Flori; Alessandro Spelta; Emanuele Brugnoli; Matteo Cinelli; Walter Quattrociocchi; Fabio Pammolli

Starting from such premises, we apply a model-based scenario analysis for Covid-19, highlighting the role non-medical variables play in the epidemic spreading and how those dimensions are likely to impact on lockdown policies and exit (from lockdown) strategies [8] . In particular, we study how to schedule shortterm interventions in response to an emerging epidemic when geographic and demographic variables are accounted in the model. We are indeed interested in analyzing how mobility restriction measures and the timing of the lockdown release might affect the total fraction of infected, the peak prevalence, and, possibly, the delay of the epidemic when model heterogeneity is driven by regional boundaries and age classes [8] . To such an end, we use a very general compartmental model, minimally adapted to describe Italian data, and we analyze the effect of disregarding regional compartmentalization and age classes. Notice that our results are general for the vast class of epidemic models where transmission rate is proportional to the number of susceptible people times the density of infected. In a nutshell, our scope is to understand which dimensions, beside medical ones, should be considered and available to leverage strategies for containing epidemic even before having detailed quantitative predictions. Secondly, we also aim to point out how disregarding such dimensions in epidemic models could seriously affect exit scenarios.