The purpose of this work is to give a contribution to the understanding of the COVID-19 contagion in Italy. To this end, we developed a modified Susceptible-Infected-Recovered (SIR) model for the contagion, and we used official data of the pandemic up to March 30th, 2020 for identifying the parameters of this model. The non standard part of our approach resides in the fact that we considered as model parameters also the initial number of susceptible individuals, as well as the proportionality factor relating the detected number of positives with the actual (and unknown) number of infected individuals. Identifying the contagion, recovery and death rates as well as the mentioned parameters amounts to a non-convex identification problem that we solved by means of a two-dimensional grid search in the outer loop, with a standard weighted least-squares optimization problem as the inner step.
A Modified SIR Model for the COVID-19 Contagion in Italy / Calafiore, G. C.; Novara, C.; Possieri, C.. - (2020), pp. 3889-3894. (Intervento presentato al convegno 59th IEEE Conference on Decision and Control, CDC 2020 tenutosi a Jeju, Korea (South) nel 14-18 Dec. 2020) [10.1109/CDC42340.2020.9304142].
A Modified SIR Model for the COVID-19 Contagion in Italy
Calafiore G. C.;Novara C.;Possieri C.
2020
Abstract
The purpose of this work is to give a contribution to the understanding of the COVID-19 contagion in Italy. To this end, we developed a modified Susceptible-Infected-Recovered (SIR) model for the contagion, and we used official data of the pandemic up to March 30th, 2020 for identifying the parameters of this model. The non standard part of our approach resides in the fact that we considered as model parameters also the initial number of susceptible individuals, as well as the proportionality factor relating the detected number of positives with the actual (and unknown) number of infected individuals. Identifying the contagion, recovery and death rates as well as the mentioned parameters amounts to a non-convex identification problem that we solved by means of a two-dimensional grid search in the outer loop, with a standard weighted least-squares optimization problem as the inner step.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2933554