Modelling the epidemiological trend and behavior of COVID-19 in Italy

Alessandro Rovetta; Akshaya Srikanth Bhagavathula

To obtain a more realistic trend and assuming true the probable "non-relapse patients", and we applied S.E.I.R. model to predict the virus progress in Italy. As a note, it is not possible to estimate the containment measures taken by the government. However, at the same time, assuming that only half of the population was susceptible to the virus precisely due to the above containment measures. Thanks to the comparison between real and theoretical evolution, it is likely to estimate the presence of essential mutations and/or the limitation strategy effectiveness through similarities, anomalies, or substantial deviations from each other. We used S.E.I.R. differential equations and non-linear methods to resolve the gaps analytically. An interactive algorithm was developed using C++ software (version) to find a solution through a finite discretization method. The total population number has been considered constant because of the very low deaths/population ratio.