A data-driven epidemic model with social structure for understanding the COVID-19 infection on a heavily affected Italian province

@article{Zanella2021ADE,
  title={A data-driven epidemic model with social structure for understanding the COVID-19 infection on a heavily affected Italian province},
  author={Mattia Zanella and Chiara Bardelli and Giacomo Dimarco and Silvia Deandrea and Pietro Perotti and Mar{\'i}a Susana Azzi and Silvia Figini and Giuseppe Toscani},
  journal={Mathematical Models and Methods in Applied Sciences},
  year={2021}
}
In this work, using a detailed dataset furnished by National Health Authorities concerning the Province of Pavia (Lombardy, Italy), we propose to determine the essential features of the ongoing COVID-19 pandemic in terms of contact dynamics. Our contribution is devoted to provide a possible planning of the needs of medical infrastructures in the Pavia Province and to suggest different scenarios about the vaccination campaign which possibly help in reducing the fatalities and/or reducing the… 
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