The present work deals with an Ordinary Differential Equation (ODE) model specifically designed to describe the COVID-19 evolution in Italy. The model is particularised on the basis of National data about the infection status of the Italian population to obtain numerical solutions that effectively reproduce the real data. Our epidemic model is a classical SEIR model that incorporates two compartments of infected subpopulations, representing diagnosed and undiagnosed individuals respectively, and an additional quarantine compartment. Possible control actions representing social, political, and medical interventions are also included. The numerical results of the proposed model identification by least square fitting are analysed and commented with special emphasis on the estimation of the number of asymptomatic infective individuals. Our fitting results are in good agreement with the epidemiological data. Short and long-term predictions on the evolution of the disease are also given.
2021, IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, Pages 1326-1332 (volume: 25)
Dynamical evolution of COVID-19 in Italy with an evaluation of the size of the asymptomatic infective population (01a Articolo in rivista)
Giamberardino P. D., Iacoviello D., Papa F., Sinisgalli C.
Gruppo di ricerca: Nonlinear Systems and Control