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A multivariate spatio-temporal model for the incidence of imported COVID-19 cases and COVID-19 deaths in Cuba.
De Witte, Dries; Abad, Ariel Alonso; Molenberghs, Geert; Verbeke, Geert; Sanchez, Lizet; Mas-Bermejo, Pedro; Neyens, Thomas.
Afiliação
  • 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.
Spat Spatiotemporal Epidemiol ; 45: 100588, 2023 06.
Article em En | MEDLINE | ID: mdl-37301587
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Incidence_studies / Prognostic_studies / Risk_factors_studies Limite: Humans País/Região como assunto: Caribe / Cuba Idioma: En Revista: Spat Spatiotemporal Epidemiol Ano de publicação: 2023 Tipo de documento: Article País de publicação: Holanda
Texto completo
Adicionar na Minha BVS
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Incidence_studies / Prognostic_studies / Risk_factors_studies Limite: Humans País/Região como assunto: Caribe / Cuba Idioma: En Revista: Spat Spatiotemporal Epidemiol Ano de publicação: 2023 Tipo de documento: Article País de publicação: Holanda