Modelling and predicting the effect of social distancing and travel restrictions on COVID-19 spreading
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Publication:6351115
arXiv2010.05968MaRDI QIDQ6351115
Lorenzo Zino, Alessandro Rizzo, Francesco Parino, Maurizio Porfiri
Publication date: 12 October 2020
Abstract: To date, the only effective means to respond to the spreading of COVID-19 pandemic are non-pharmaceutical interventions (NPIs), which entail policies to reduce social activity and mobility restrictions. Quantifying their effect is difficult, but it is key to reduce their social and economical consequences. Here, we introduce a meta-population model based on temporal networks, calibrated on the COVID-19 outbreak data in Italy and apt to evaluate the outcomes of these two types of NPIs. Our approach combines the advantages of granular spatial modelling of meta-population models with the ability to realistically describe social contacts via activity-driven networks. We provide a valuable framework to assess the viability of different NPIs, varying with respect to their timing and severity. Results suggest that the effects of mobility restrictions largely depend on the possibility to implement timely NPIs in the early phases of the outbreak, whereas activity reduction policies should be prioritised afterwards.
Has companion code repository: https://gitlab.com/PoliToComplexSystemLab/adn-metapopulation-2020
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