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

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. Foll...

Descripción completa

Detalles Bibliográficos
Autores principales: Vitale, Vincenzina, D’Urso, Pierpaolo, De Giovanni, Livia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8277433/
https://www.ncbi.nlm.nih.gov/pubmed/34277332
http://dx.doi.org/10.1016/j.spasta.2021.100529
Descripción
Sumario: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.

Ejemplares similares