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A time-varying SIRD model for the COVID-19 contagion in Italy

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-Deceased (SIRD) model for the contagion, and we used official data of the pandemic for identifying the parameters of this mo...

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Autores principales: Calafiore, Giuseppe C., Novara, Carlo, Possieri, Corrado
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7587010/
https://www.ncbi.nlm.nih.gov/pubmed/33132739
http://dx.doi.org/10.1016/j.arcontrol.2020.10.005
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author Calafiore, Giuseppe C.
Novara, Carlo
Possieri, Corrado
author_facet Calafiore, Giuseppe C.
Novara, Carlo
Possieri, Corrado
author_sort Calafiore, Giuseppe C.
collection PubMed
description 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-Deceased (SIRD) model for the contagion, and we used official data of the pandemic for identifying the parameters of this model. Our approach features two main non-standard aspects. The first one is that model parameters can be time-varying, allowing us to capture possible changes of the epidemic behavior, due for example to containment measures enforced by authorities or modifications of the epidemic characteristics and to the effect of advanced antiviral treatments. The time-varying parameters are written as linear combinations of basis functions and are then inferred from data using sparse identification techniques. The second non-standard aspect resides in the fact that we consider 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 model parameters amounts to a non-convex identification problem that we solve by means of a nested approach, consisting in a one-dimensional grid search in the outer loop, with a Lasso optimization problem in the inner step.
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spelling pubmed-75870102020-10-27 A time-varying SIRD model for the COVID-19 contagion in Italy Calafiore, Giuseppe C. Novara, Carlo Possieri, Corrado Annu Rev Control Article 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-Deceased (SIRD) model for the contagion, and we used official data of the pandemic for identifying the parameters of this model. Our approach features two main non-standard aspects. The first one is that model parameters can be time-varying, allowing us to capture possible changes of the epidemic behavior, due for example to containment measures enforced by authorities or modifications of the epidemic characteristics and to the effect of advanced antiviral treatments. The time-varying parameters are written as linear combinations of basis functions and are then inferred from data using sparse identification techniques. The second non-standard aspect resides in the fact that we consider 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 model parameters amounts to a non-convex identification problem that we solve by means of a nested approach, consisting in a one-dimensional grid search in the outer loop, with a Lasso optimization problem in the inner step. Elsevier Ltd. 2020 2020-10-26 /pmc/articles/PMC7587010/ /pubmed/33132739 http://dx.doi.org/10.1016/j.arcontrol.2020.10.005 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Calafiore, Giuseppe C.
Novara, Carlo
Possieri, Corrado
A time-varying SIRD model for the COVID-19 contagion in Italy
title A time-varying SIRD model for the COVID-19 contagion in Italy
title_full A time-varying SIRD model for the COVID-19 contagion in Italy
title_fullStr A time-varying SIRD model for the COVID-19 contagion in Italy
title_full_unstemmed A time-varying SIRD model for the COVID-19 contagion in Italy
title_short A time-varying SIRD model for the COVID-19 contagion in Italy
title_sort time-varying sird model for the covid-19 contagion in italy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7587010/
https://www.ncbi.nlm.nih.gov/pubmed/33132739
http://dx.doi.org/10.1016/j.arcontrol.2020.10.005
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