Spatial correlates of COVID-19 first wave across continental Portugal

Detalhes bibliográficos
Autor(a) principal: Barbosa, Bruno
Data de Publicação: 2022
Outros Autores: Silva, Melissa, Capinha, César, Garcia, Ricardo, Rocha, Jorge
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10451/53588
Resumo: The first case of COVID-19 in continental Portugal was documented on the 2nd of March 2020 and about seven months later more than 75 thousand infections had been reported. Although several factors correlate significantly with the spatial incidence of COVID-19 worldwide, the drivers of spatial incidence of this virus remain poorly known and need further exploration. In this study, we analyse the spatiotemporal patterns of COVID-19 incidence in the at the municipality level and test for significant relationships between these patterns and environmental, socioeconomic, demographic and human mobility factors to identify the mains drivers of COVID-19 incidence across time and space. We used a generalized liner mixed model, which accounts for zero inflated cases and spatial autocorrelation to identify significant relationships between the spatiotemporal incidence and the considered set of driving factors. Some of these relationships were particularly consistent across time, including the ‘percentage of employment in services’; ‘average time of commuting using individual transportation’; ‘percentage of employment in the agricultural sector’; and ‘average family size’. Comparing the preventive measures in Portugal (e.g., restrictions on mobility and crowd around) with the model results clearly show that COVID-19 incidence fluctuates as those measures are imposed or relieved. This shows that our model can be a useful tool to help decision-makers in defining prevention and/or mitigation policies.
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spelling Spatial correlates of COVID-19 first wave across continental PortugalCOVID-19Drivers of transmissionSocio-economic conditionsSpatial incidencePortugalThe first case of COVID-19 in continental Portugal was documented on the 2nd of March 2020 and about seven months later more than 75 thousand infections had been reported. Although several factors correlate significantly with the spatial incidence of COVID-19 worldwide, the drivers of spatial incidence of this virus remain poorly known and need further exploration. In this study, we analyse the spatiotemporal patterns of COVID-19 incidence in the at the municipality level and test for significant relationships between these patterns and environmental, socioeconomic, demographic and human mobility factors to identify the mains drivers of COVID-19 incidence across time and space. We used a generalized liner mixed model, which accounts for zero inflated cases and spatial autocorrelation to identify significant relationships between the spatiotemporal incidence and the considered set of driving factors. Some of these relationships were particularly consistent across time, including the ‘percentage of employment in services’; ‘average time of commuting using individual transportation’; ‘percentage of employment in the agricultural sector’; and ‘average family size’. Comparing the preventive measures in Portugal (e.g., restrictions on mobility and crowd around) with the model results clearly show that COVID-19 incidence fluctuates as those measures are imposed or relieved. This shows that our model can be a useful tool to help decision-makers in defining prevention and/or mitigation policies.PAGEPressRepositório da Universidade de LisboaBarbosa, BrunoSilva, MelissaCapinha, CésarGarcia, RicardoRocha, Jorge2022-07-01T09:10:10Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/53588engBarbosa, B., Silva, M., Capinha, C., Garcia, R. A., & Rocha, J. (2022). Spatial correlates of COVID-19 first wave across continental Portugal. Geospatial Health, 17(s1):1073. https://doi.org/10.4081/gh.2022.10731827-19871970-7096info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-08T16:59:31Zoai:repositorio.ul.pt:10451/53588Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:04:32.692093Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Spatial correlates of COVID-19 first wave across continental Portugal
title Spatial correlates of COVID-19 first wave across continental Portugal
spellingShingle Spatial correlates of COVID-19 first wave across continental Portugal
Barbosa, Bruno
COVID-19
Drivers of transmission
Socio-economic conditions
Spatial incidence
Portugal
title_short Spatial correlates of COVID-19 first wave across continental Portugal
title_full Spatial correlates of COVID-19 first wave across continental Portugal
title_fullStr Spatial correlates of COVID-19 first wave across continental Portugal
title_full_unstemmed Spatial correlates of COVID-19 first wave across continental Portugal
title_sort Spatial correlates of COVID-19 first wave across continental Portugal
author Barbosa, Bruno
author_facet Barbosa, Bruno
Silva, Melissa
Capinha, César
Garcia, Ricardo
Rocha, Jorge
author_role author
author2 Silva, Melissa
Capinha, César
Garcia, Ricardo
Rocha, Jorge
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Barbosa, Bruno
Silva, Melissa
Capinha, César
Garcia, Ricardo
Rocha, Jorge
dc.subject.por.fl_str_mv COVID-19
Drivers of transmission
Socio-economic conditions
Spatial incidence
Portugal
topic COVID-19
Drivers of transmission
Socio-economic conditions
Spatial incidence
Portugal
description The first case of COVID-19 in continental Portugal was documented on the 2nd of March 2020 and about seven months later more than 75 thousand infections had been reported. Although several factors correlate significantly with the spatial incidence of COVID-19 worldwide, the drivers of spatial incidence of this virus remain poorly known and need further exploration. In this study, we analyse the spatiotemporal patterns of COVID-19 incidence in the at the municipality level and test for significant relationships between these patterns and environmental, socioeconomic, demographic and human mobility factors to identify the mains drivers of COVID-19 incidence across time and space. We used a generalized liner mixed model, which accounts for zero inflated cases and spatial autocorrelation to identify significant relationships between the spatiotemporal incidence and the considered set of driving factors. Some of these relationships were particularly consistent across time, including the ‘percentage of employment in services’; ‘average time of commuting using individual transportation’; ‘percentage of employment in the agricultural sector’; and ‘average family size’. Comparing the preventive measures in Portugal (e.g., restrictions on mobility and crowd around) with the model results clearly show that COVID-19 incidence fluctuates as those measures are imposed or relieved. This shows that our model can be a useful tool to help decision-makers in defining prevention and/or mitigation policies.
publishDate 2022
dc.date.none.fl_str_mv 2022-07-01T09:10:10Z
2022
2022-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10451/53588
url http://hdl.handle.net/10451/53588
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Barbosa, B., Silva, M., Capinha, C., Garcia, R. A., & Rocha, J. (2022). Spatial correlates of COVID-19 first wave across continental Portugal. Geospatial Health, 17(s1):1073. https://doi.org/10.4081/gh.2022.1073
1827-1987
1970-7096
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv PAGEPress
publisher.none.fl_str_mv PAGEPress
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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