Forecasting Covid-19 Outbreak Progression in Italian Regions: A model based on neural network training from Chinese data

Cosimo Distante; Igor Gadelha Pereira; Luiz Marcos Garcia Goncalves; Prisco Piscitelli; Alessandro Miani

is the (which was not peer-reviewed) The copyright holder for this preprint with the mean average precision between official Italian data and the forecast. SEIR model can gain advantage on modeling epidemic since the compartments are based on the complete curve dynamic (the portion of the real data and those forecasted). We showed the validity of the method since the predictive model learns from the dynamics of Covid-19 in China and exploits its learned knowledge to predict future daily cases in Italy. As shown in Figure 9 and in Table 2 , the expected peak of SEIR model was . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.