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

In this work we propose and test a generalized framework to study an epidemic contagion through a compartmental model based on geographical groups and age classes. We reveal how the promptness of lockdown measures has only a main effect on the timing of the contagion. More specifically, we show that strict social distancing policies reduce the extent of contagion during the lockdown period, but full recover occurs once such measures are relaxed. Interestingly, our study also contributes to uncover how local dynamics at regional level can be masked by observing the aggregate national system. Such regional heterogeneity, in fact, lowers and widens the curve of the contagion thus determining a shift forward in time for its peak at the aggregate national level. Moreover, by employing mobility data, we find that, due to the sparsity of interconnections across regions, contagion develops independently within each region once the epidemic is started. This, in turn, contributes to explain the delays observed in the alignment of the contagion curves across different geographical areas. Finally, we rely on the structure of social contacts to emphasize the role played by different age classes in the spreading of contagion. We notice that both young people (0-19) and elderly people (70+) are the most interconnected classes and therefore can have a greater influence on the post-lockdown phase. We show that while confirming quarantine policies to only elderly people can limit the possibility of a renewed upward phase in the contagion dynamics, relaxing the lockdown measures to only the middle age class can be enough to smooth and lessen the propagation of contagion in the post-lockdown phase.