Dipartimento di Ingegneria informatica, automatica e gestionale

A new measles epidemic model is proposed and identified by using real data relative to the number of confirmed infected patients in Italy in the period 1970-2018. The possibility of predicting the number of new infection is important for an efficient resource scheduling. Only in the last years great attention has been devoted to reliable data collection; therefore, in general, the model parameters identification is not an easy task. Moreover, the available data are 'corrupted' by human intervention, such as prevention campaign, or, whenever possible, vaccination. In this paper, the measles model parameters are identified referring to the data of the period in which there wasn't a significant vaccination coverage; successively, the vaccination action has been identified. The results obtained appear encouraging, confirming the importance of available consistent data.