Cargando…
A joint hierarchical model for the number of cases and deaths due to COVID-19 across the boroughs of Montreal
As of July 2021, Montreal is the epicentre of the COVID-19 pandemic in Canada with highest number of deaths. We aim to investigate the spatial distribution of the number of cases and deaths due to COVID-19 across the boroughs of Montreal. To this end, we propose that the cumulative numbers of cases...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9126618/ https://www.ncbi.nlm.nih.gov/pubmed/35934331 http://dx.doi.org/10.1016/j.sste.2022.100518 |
_version_ | 1784712165387665408 |
---|---|
author | Michal, Victoire Vanciu, Leo Schmidt, Alexandra M. |
author_facet | Michal, Victoire Vanciu, Leo Schmidt, Alexandra M. |
author_sort | Michal, Victoire |
collection | PubMed |
description | As of July 2021, Montreal is the epicentre of the COVID-19 pandemic in Canada with highest number of deaths. We aim to investigate the spatial distribution of the number of cases and deaths due to COVID-19 across the boroughs of Montreal. To this end, we propose that the cumulative numbers of cases and deaths in the 33 boroughs of Montreal are modelled through a bivariate hierarchical Bayesian model using Poisson distributions. The Poisson means are decomposed in the log scale as the sums of fixed effects and latent effects. The areal median age, the educational level, and the number of beds in long-term care homes are included in the fixed effects. To explore the correlation between cases and deaths inside and across areas, three different bivariate models are considered for the latent effects, namely an independent one, a conditional autoregressive model, and one that allows for both spatially structured and unstructured sources of variability. As the inclusion of spatial effects change some of the fixed effects, we extend the Spatial+ approach to a Bayesian areal set up to investigate the presence of spatial confounding. We find that the model which includes independent latent effects across boroughs performs the best among the ones considered, there appears to be spatial confounding with the diploma and median age variables, and the correlation between the cases and deaths across and within boroughs is always negative. |
format | Online Article Text |
id | pubmed-9126618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91266182022-05-24 A joint hierarchical model for the number of cases and deaths due to COVID-19 across the boroughs of Montreal Michal, Victoire Vanciu, Leo Schmidt, Alexandra M. Spat Spatiotemporal Epidemiol Case Study As of July 2021, Montreal is the epicentre of the COVID-19 pandemic in Canada with highest number of deaths. We aim to investigate the spatial distribution of the number of cases and deaths due to COVID-19 across the boroughs of Montreal. To this end, we propose that the cumulative numbers of cases and deaths in the 33 boroughs of Montreal are modelled through a bivariate hierarchical Bayesian model using Poisson distributions. The Poisson means are decomposed in the log scale as the sums of fixed effects and latent effects. The areal median age, the educational level, and the number of beds in long-term care homes are included in the fixed effects. To explore the correlation between cases and deaths inside and across areas, three different bivariate models are considered for the latent effects, namely an independent one, a conditional autoregressive model, and one that allows for both spatially structured and unstructured sources of variability. As the inclusion of spatial effects change some of the fixed effects, we extend the Spatial+ approach to a Bayesian areal set up to investigate the presence of spatial confounding. We find that the model which includes independent latent effects across boroughs performs the best among the ones considered, there appears to be spatial confounding with the diploma and median age variables, and the correlation between the cases and deaths across and within boroughs is always negative. Elsevier Ltd. 2022-08 2022-05-23 /pmc/articles/PMC9126618/ /pubmed/35934331 http://dx.doi.org/10.1016/j.sste.2022.100518 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Case Study Michal, Victoire Vanciu, Leo Schmidt, Alexandra M. A joint hierarchical model for the number of cases and deaths due to COVID-19 across the boroughs of Montreal |
title | A joint hierarchical model for the number of cases and deaths due to COVID-19 across the boroughs of Montreal |
title_full | A joint hierarchical model for the number of cases and deaths due to COVID-19 across the boroughs of Montreal |
title_fullStr | A joint hierarchical model for the number of cases and deaths due to COVID-19 across the boroughs of Montreal |
title_full_unstemmed | A joint hierarchical model for the number of cases and deaths due to COVID-19 across the boroughs of Montreal |
title_short | A joint hierarchical model for the number of cases and deaths due to COVID-19 across the boroughs of Montreal |
title_sort | joint hierarchical model for the number of cases and deaths due to covid-19 across the boroughs of montreal |
topic | Case Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9126618/ https://www.ncbi.nlm.nih.gov/pubmed/35934331 http://dx.doi.org/10.1016/j.sste.2022.100518 |
work_keys_str_mv | AT michalvictoire ajointhierarchicalmodelforthenumberofcasesanddeathsduetocovid19acrosstheboroughsofmontreal AT vanciuleo ajointhierarchicalmodelforthenumberofcasesanddeathsduetocovid19acrosstheboroughsofmontreal AT schmidtalexandram ajointhierarchicalmodelforthenumberofcasesanddeathsduetocovid19acrosstheboroughsofmontreal AT michalvictoire jointhierarchicalmodelforthenumberofcasesanddeathsduetocovid19acrosstheboroughsofmontreal AT vanciuleo jointhierarchicalmodelforthenumberofcasesanddeathsduetocovid19acrosstheboroughsofmontreal AT schmidtalexandram jointhierarchicalmodelforthenumberofcasesanddeathsduetocovid19acrosstheboroughsofmontreal |