In this paper, we develop a forecasting 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 local newspaper websites. This data integration is needed as COVID-19 death data are not available at the NUTS-3 level from official open data channels. An adjusted time-dependent SIRD model is used to predict the behavior of the epidemic; specifically, the number of susceptible, infected, deceased, recovered people and epidemiological parameters. Predictive model performance is evaluated using comparison with real data.

Modeling provincial Covid-19 epidemic data using an adjusted time-dependent sird model / L. Ferrari, G. Gerardi, G. Manzi, A. Micheletti, F. Nicolussi, E. Biganzoli, S. Salini. - In: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH. - ISSN 1661-7827. - 18:12(2021 Jun 18), pp. 6563.1-6563.20. [10.3390/ijerph18126563]

Modeling provincial Covid-19 epidemic data using an adjusted time-dependent sird model

G. Gerardi
Secondo
;
G. Manzi
;
A. Micheletti;F. Nicolussi;E. Biganzoli
Penultimo
;
S. Salini
Ultimo
2021-06-18

Abstract

In this paper, we develop a forecasting 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 local newspaper websites. This data integration is needed as COVID-19 death data are not available at the NUTS-3 level from official open data channels. An adjusted time-dependent SIRD model is used to predict the behavior of the epidemic; specifically, the number of susceptible, infected, deceased, recovered people and epidemiological parameters. Predictive model performance is evaluated using comparison with real data.
COVID-19; Epidemic data; EU NUTS-3 regions; Italy; SIRD-derived models
Settore SECS-S/01 - Statistica
Settore MED/01 - Statistica Medica
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/853245
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