In this paper we model and predict the spread of COVID-19 infection at a provincial (i.e. EU NUTS-3) level in Italy by using official data from the Italian Ministry of Health integrated with data extracted from daily official press conferences of regional authorities and from local newspaper websites. This integration is mainly concerned with  death data which are not available at NUTS-3 level from official data channels. An adjusted time-dependent SIRD model is used to predict the behaviour of the epidemics , specifically the number of susceptible, infected, deceased and recovered people. Model performance is evaluated using comparison with real data.
In this paper we develop a predictive model for the spread of COVID-19 infection at a provincial (i.e. EU NUTS-3) level in Italy by using official data from the Italian Ministry of Health integrated with data extracted from daily official press conferences of regional authorities and from local newspaper websites. This integration is mainly concerned with COVID-19 cause specific death data which are not available at NUTS-3 level from open official data data channels. An adjusted time-dependent SIRD model is used to predict the behavior of the epidemic , specifically the number of susceptible, infected, deceased and recovered people. Predictive model performance is evaluated using comparison with real data.
R
model and predict
develop a predictive model for
A
COVID-19 cause specific
R
official
open official data
R
behaviour of the epidemics
behavior of the epidemic
R
Model
Predictive model