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.
Modeling provincial Covid-19 epidemic data in Italy using an adjusted time-dependent SIRD model / L. Ferrari, G. Gerardi, G. Manzi, A. Micheletti, F. Nicolussi, E. Biganzoli, S. Salini. - (2020 Jun 02).
|Titolo:||Modeling provincial Covid-19 epidemic data in Italy using an adjusted time-dependent SIRD model|
MANZI, GIANCARLO (Corresponding)
|Parole Chiave:||COVID-19; SIRD-derived model; Italy; EU NUTS-3 regions; scraped epidemic data|
|Settore Scientifico Disciplinare:||Settore SECS-S/01 - Statistica|
Settore MAT/06 - Probabilita' e Statistica Matematica
Settore MED/01 - Statistica Medica
|Data di pubblicazione:||2020-06-02|
|Appare nelle tipologie:||24 - Pre-print|