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Article Dans Une Revue Nature Communications Année : 2023

A network model of Italy shows that intermittent regional strategies can alleviate the COVID-19 epidemic

Fabio Della Rossa
  • Fonction : Auteur
Davide Salzano
  • Fonction : Auteur
Anna Di Meglio
  • Fonction : Auteur
Francesco de Lellis
  • Fonction : Auteur
Marco Coraggio
  • Fonction : Auteur
Agostino Guarino
  • Fonction : Auteur
Ricardo Cardona-Rivera
  • Fonction : Auteur
Pietro de Lellis
  • Fonction : Auteur
Davide Liuzza
  • Fonction : Auteur
Francesco Lo Iudice
  • Fonction : Auteur
Giovanni Russo
  • Fonction : Auteur
Mario Di Bernardo
  • Fonction : Auteur

Résumé

The COVID-19 epidemic hit Italy particularly hard, yielding the implementation of strict national lockdown rules. Previous modelling studies at the national level overlooked the fact that Italy is divided into administrative regions which can independently oversee their own share of the Italian National Health Service. Here, we show that heterogeneity between regions is essential to understand the spread of the epidemic and to design effective strategies to control the disease. We model Italy as a network of regions and parameterize the model of each region on real data spanning over two months from the initial outbreak. We confirm the effectiveness at the regional level of the national lockdown strategy and propose coordinated regional interventions to prevent future national lockdowns, while avoiding saturation of the regional health systems and mitigating impact on costs. Our study and methodology can be easily extended to other levels of granularity to support policy- and decision-makers.

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Neurosciences
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Dates et versions

hal-03598263 , version 1 (11-06-2023)

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Fabio Della Rossa, Davide Salzano, Anna Di Meglio, Francesco de Lellis, Marco Coraggio, et al.. A network model of Italy shows that intermittent regional strategies can alleviate the COVID-19 epidemic. Nature Communications, 2023, 11 (1), pp.5106. ⟨10.1038/s41467-020-18827-5⟩. ⟨hal-03598263⟩
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