A multivariate spatio-temporal model for the incidence of imported COVID-19 cases and COVID-19 deaths in Cuba.

Autor: De Witte D; L-BioStat, KU Leuven, Leuven, 3000, Belgium. Electronic address: dries.dewitte@kuleuven.be., Abad AA; L-BioStat, KU Leuven, Leuven, 3000, Belgium; I-BioStat, Hasselt University, Diepenbeek, 3590, Belgium., Molenberghs G; L-BioStat, KU Leuven, Leuven, 3000, Belgium; I-BioStat, Hasselt University, Diepenbeek, 3590, Belgium., Verbeke G; L-BioStat, KU Leuven, Leuven, 3000, Belgium; I-BioStat, Hasselt University, Diepenbeek, 3590, Belgium., Sanchez L; Cuban National Group of Epidemiology and Modeling of the COVID-19 Pandemic, Center of Molecular Immunology, Havana, 11 600, Cuba., Mas-Bermejo P; Cuban National Group of Epidemiology and Modeling of the COVID-19 Pandemic, Institute 'Pedro Kouri', Havana, 11 600, Cuba., Neyens T; L-BioStat, KU Leuven, Leuven, 3000, Belgium; I-BioStat, Hasselt University, Diepenbeek, 3590, Belgium.
Jazyk: angličtina
Zdroj: Spatial and spatio-temporal epidemiology [Spat Spatiotemporal Epidemiol] 2023 Jun; Vol. 45, pp. 100588. Date of Electronic Publication: 2023 May 10.
DOI: 10.1016/j.sste.2023.100588
Abstrakt: To monitor the COVID-19 epidemic in Cuba, data on several epidemiological indicators have been collected on a daily basis for each municipality. Studying the spatio-temporal dynamics in these indicators, and how they behave similarly, can help us better understand how COVID-19 spread across Cuba. Therefore, spatio-temporal models can be used to analyze these indicators. Univariate spatio-temporal models have been thoroughly studied, but when interest lies in studying the association between multiple outcomes, a joint model that allows for association between the spatial and temporal patterns is necessary. The purpose of our study was to develop a multivariate spatio-temporal model to study the association between the weekly number of COVID-19 deaths and the weekly number of imported COVID-19 cases in Cuba during 2021. To allow for correlation between the spatial patterns, a multivariate conditional autoregressive prior (MCAR) was used. Correlation between the temporal patterns was taken into account by using two approaches; either a multivariate random walk prior was used or a multivariate conditional autoregressive prior (MCAR) was used. All models were fitted within a Bayesian framework.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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