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The aim of this paper consists in the application of a recent epidemiologicalmodel, namely SEIR with Social Distancing (SEIR--SD), extended here through thedefinition of a social distancing function varying over time, to assess thesituation related to the spreading of the coronavirus Covid--19 in Italy and intwo of its most important regions, i.e., Lombardy and Campania. To profitablyuse this model, the most suitable values of its parameters must be found. Theestimation of the SEIR--SD model parameters takes place here through the use ofDifferential Evolution, a heuristic optimization technique. In this way, we areable to evaluate for each of the three above-mentioned scenarios the dailynumber of infectious cases from today until the end of virus spreading, theday(s) in which this number will be at its highest peak, and the day in whichthe infected cases will become very close to zero.

Coronavirus Covid-19 spreading in Italy: optimizing an epidemiological model with dynamic social distancing through Differential Evolution