A Modified SIR Model for the COVID-19 Contagion in Italy

Giuseppe C. Calafiore, Carlo Novara, Corrado Possieri

2020Cineca Institutional Research Information System (Tor Vergata University)153 citationsDOI

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.

Topics & Concepts

Coronavirus disease 2019 (COVID-19)Epidemic modelIdentification (biology)PandemicFalse positive paradoxConvex optimization2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)EconometricsRegular polygonComputer scienceStatisticsMathematicsVirologyMedicineBiologyInfectious disease (medical specialty)PopulationPathologyGeometryOutbreakEnvironmental healthDiseaseBotanyCOVID-19 epidemiological studiesSARS-CoV-2 and COVID-19 ResearchAdvanced Statistical Methods and Models