The spatial epidemic dynamics of COVID-19 outbreak in Italy were modelled by means of an Object-Oriented Bayesian Network in order to explore the dependence relationships, in a static and a dynamic way, among the weekly incidence rate, the intensive care units occupancy rate and that of deaths. Following an autoregressive approach, both spatial and time components have been embedded in the model by means of spatial and time lagged variables. The model could be a valid instrument to support or validate policy makers’ decisions strategies.

Spatio-temporal Object-Oriented Bayesian Network modelling of the COVID-19 Italian outbreak data / Vitale, Vincenzina; D'Urso, Pierpaolo; De Giovanni, Livia. - In: SPATIAL STATISTICS. - ISSN 2211-6753. - 49:June(2022), pp. 1-18. [10.1016/j.spasta.2021.100529]

Spatio-temporal Object-Oriented Bayesian Network modelling of the COVID-19 Italian outbreak data

D’Urso, Pierpaolo;De Giovanni, Livia
2022

Abstract

The spatial epidemic dynamics of COVID-19 outbreak in Italy were modelled by means of an Object-Oriented Bayesian Network in order to explore the dependence relationships, in a static and a dynamic way, among the weekly incidence rate, the intensive care units occupancy rate and that of deaths. Following an autoregressive approach, both spatial and time components have been embedded in the model by means of spatial and time lagged variables. The model could be a valid instrument to support or validate policy makers’ decisions strategies.
2022
Object-Oriented Bayesian Network, Spatial correlation, Time series, COVID-19 Italian outbreak
Spatio-temporal Object-Oriented Bayesian Network modelling of the COVID-19 Italian outbreak data / Vitale, Vincenzina; D'Urso, Pierpaolo; De Giovanni, Livia. - In: SPATIAL STATISTICS. - ISSN 2211-6753. - 49:June(2022), pp. 1-18. [10.1016/j.spasta.2021.100529]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11385/211716
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