Spatial-temporal generalized additive model for modeling COVID-19 mortality risk in Toronto, Canada

This article presents a spatial–temporal generalized additive model for modeling geo-referenced COVID-19 mortality data in Toronto, Canada. A range of factors and spatial–temporal terms are incorporated into the model. The non-linear and interactive effects of the neighborhood-level factors, i.e., p...

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Detalles Bibliográficos
Autor principal: Feng, Cindy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8257405/
https://www.ncbi.nlm.nih.gov/pubmed/34249608
http://dx.doi.org/10.1016/j.spasta.2021.100526

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8257405/
https://www.ncbi.nlm.nih.gov/pubmed/34249608
http://dx.doi.org/10.1016/j.spasta.2021.100526

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