COMPRIME - COnhecer Mais PaRa Intervir MElhor: Preliminary Mapping of Municipal Level Determinants of COVID-19 Transmission in Portugal at Different Moments of the 1st Epidemic Wave
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/149521 |
Resumo: | Background: The role of demographic and socio-economic determinants of COVID-19 transmission is still unclear and is expected to vary in different contexts and epidemic periods. Exploring such determinants may generate a hypothesis about transmission and aid the definition of prevention strategies. Objectives: To identify municipality-level demographic and socio-economic determinants of COVID-19 in Portugal. Methods: We assessed determinants of COVID-19 daily cases at 4 moments of the first COVID-19 epidemic wave in Portugal, related with lockdown and post-lockdown measures. We selected 60 potential determinants from 5 dimensions: population and settlement, disease, economy, social context, and mobility. We conducted a multiple linear regression (MLR) stepwise analysis (p < 0.05) and an artificial neural network (ANN) analysis with the variables to identify predictors of the number of daily cases. Results: For MLR, some of the identified variables were: resident population and population density, exports, overnight stays in touristic facilities, the location quotient of employment in accommodation, catering and similar activities, education, restaurants and lodging, some industries and building construction, the share of the population working outside the municipality, the net migration rate, income, and renting. In ANN, some of the identified variables were: population density and resident population, urbanization, students in higher education, income, exports, social housing buildings, production services employment, and the share of the population working outside the municipality of residence. Conclusions: Several factors were identified as possible determinants of COVID-19 transmission at the municipality level. Despite limitations to the study, we believe that this information should be considered to promote communication and prevention approaches. Further research should be conducted. |
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COMPRIME - COnhecer Mais PaRa Intervir MElhor: Preliminary Mapping of Municipal Level Determinants of COVID-19 Transmission in Portugal at Different Moments of the 1st Epidemic WaveCOMPRIME - COnhecer Mais PaRa Intervir MElhor: Análise preliminar de fatores determinantes da transmissão da COVID-19 em Portugal, a nível municipal, em diferentes momentos da 1a onda epidémicaMunicipal levelCOVID-19PandemicsLinear modelNon-linear modelNível municipalCOVID-19PandemiaModelo linearModelo não linearBackground: The role of demographic and socio-economic determinants of COVID-19 transmission is still unclear and is expected to vary in different contexts and epidemic periods. Exploring such determinants may generate a hypothesis about transmission and aid the definition of prevention strategies. Objectives: To identify municipality-level demographic and socio-economic determinants of COVID-19 in Portugal. Methods: We assessed determinants of COVID-19 daily cases at 4 moments of the first COVID-19 epidemic wave in Portugal, related with lockdown and post-lockdown measures. We selected 60 potential determinants from 5 dimensions: population and settlement, disease, economy, social context, and mobility. We conducted a multiple linear regression (MLR) stepwise analysis (p < 0.05) and an artificial neural network (ANN) analysis with the variables to identify predictors of the number of daily cases. Results: For MLR, some of the identified variables were: resident population and population density, exports, overnight stays in touristic facilities, the location quotient of employment in accommodation, catering and similar activities, education, restaurants and lodging, some industries and building construction, the share of the population working outside the municipality, the net migration rate, income, and renting. In ANN, some of the identified variables were: population density and resident population, urbanization, students in higher education, income, exports, social housing buildings, production services employment, and the share of the population working outside the municipality of residence. Conclusions: Several factors were identified as possible determinants of COVID-19 transmission at the municipality level. Despite limitations to the study, we believe that this information should be considered to promote communication and prevention approaches. Further research should be conducted.Contexto: O papel dos determinantes demográficos e socioeconómicos na transmissão do vírus SARS Cov2 ainda não é claro e acredita-se que varie em diferentes contextos e períodos da pandemia. A análise desses determinantes pode ajudar a gerar hipóteses sobre a transmissão e apoiar na definição de estratégias de prevenção. Objetivos: Identificar os determinantes demográficos e socioeconómicos que podem estar associados a maior transmissibilidade da COVID-19 ao nível do município em Portugal. Métodos: Pretende-se avaliar quais os determinantes que mais influenciam o número de casos diários de COVID-19 em 4 momentos entre março e junho (corresponde à primeira vaga da pandemia) em Portugal. Foram selecionados 60 indicadores de 5 dimensões: populacional, prevalência de doenças, economia, contexto social e mobilidade. Realizamos análises de regressão linear múltipla (RLM) (p < 0,05) e análise de rede neural artificial (RNA) para identificar preditores do número de casos diários. Resultados: Para RML, algumas das variáveis identificadas foram: população residente e densidade populacional, exportações, dormidas em instalações turísticas, educação, restauração e alojamento, algumas indústrias e construção civil, proporção da população que trabalha fora do município, taxa de migração, entre outros. Na RNA, algumas das variáveis identificadas foram: densidade populacional e população residente, urbanização, alunos do ensino superior, exportações, edifícios de habitação social, emprego nos serviços de produção e parcela da população que trabalha fora do município de residência. Conclusões: Vários fatores foram identificados como possíveis determinantes da transmissibilidade da COVID-19 ao nível municipal. Apesar das limitações do estudo, acreditamos que estes resultados podem contribuir para apoiar tomadas de decisão e abordagens de comunicação e prevenção.Karger Publishers20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10216/149521eng2504-31372504-314510.1159/000514334Sousa, PDa, Costa, NMDa Costa, EMRocha, JRicoca Peixoto, VCampos Fernandes, AGaspar, RDuarte-Ramos, FAbrantes, PLeite, Ainfo: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:RCAAP2023-11-29T12:37:32Zoai:repositorio-aberto.up.pt:10216/149521Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:23:42.207242Repositório 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 |
COMPRIME - COnhecer Mais PaRa Intervir MElhor: Preliminary Mapping of Municipal Level Determinants of COVID-19 Transmission in Portugal at Different Moments of the 1st Epidemic Wave COMPRIME - COnhecer Mais PaRa Intervir MElhor: Análise preliminar de fatores determinantes da transmissão da COVID-19 em Portugal, a nível municipal, em diferentes momentos da 1a onda epidémica |
title |
COMPRIME - COnhecer Mais PaRa Intervir MElhor: Preliminary Mapping of Municipal Level Determinants of COVID-19 Transmission in Portugal at Different Moments of the 1st Epidemic Wave |
spellingShingle |
COMPRIME - COnhecer Mais PaRa Intervir MElhor: Preliminary Mapping of Municipal Level Determinants of COVID-19 Transmission in Portugal at Different Moments of the 1st Epidemic Wave Sousa, P Municipal level COVID-19 Pandemics Linear model Non-linear model Nível municipal COVID-19 Pandemia Modelo linear Modelo não linear |
title_short |
COMPRIME - COnhecer Mais PaRa Intervir MElhor: Preliminary Mapping of Municipal Level Determinants of COVID-19 Transmission in Portugal at Different Moments of the 1st Epidemic Wave |
title_full |
COMPRIME - COnhecer Mais PaRa Intervir MElhor: Preliminary Mapping of Municipal Level Determinants of COVID-19 Transmission in Portugal at Different Moments of the 1st Epidemic Wave |
title_fullStr |
COMPRIME - COnhecer Mais PaRa Intervir MElhor: Preliminary Mapping of Municipal Level Determinants of COVID-19 Transmission in Portugal at Different Moments of the 1st Epidemic Wave |
title_full_unstemmed |
COMPRIME - COnhecer Mais PaRa Intervir MElhor: Preliminary Mapping of Municipal Level Determinants of COVID-19 Transmission in Portugal at Different Moments of the 1st Epidemic Wave |
title_sort |
COMPRIME - COnhecer Mais PaRa Intervir MElhor: Preliminary Mapping of Municipal Level Determinants of COVID-19 Transmission in Portugal at Different Moments of the 1st Epidemic Wave |
author |
Sousa, P |
author_facet |
Sousa, P Da, Costa, NM Da Costa, EM Rocha, J Ricoca Peixoto, V Campos Fernandes, A Gaspar, R Duarte-Ramos, F Abrantes, P Leite, A |
author_role |
author |
author2 |
Da, Costa, NM Da Costa, EM Rocha, J Ricoca Peixoto, V Campos Fernandes, A Gaspar, R Duarte-Ramos, F Abrantes, P Leite, A |
author2_role |
author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Sousa, P Da, Costa, NM Da Costa, EM Rocha, J Ricoca Peixoto, V Campos Fernandes, A Gaspar, R Duarte-Ramos, F Abrantes, P Leite, A |
dc.subject.por.fl_str_mv |
Municipal level COVID-19 Pandemics Linear model Non-linear model Nível municipal COVID-19 Pandemia Modelo linear Modelo não linear |
topic |
Municipal level COVID-19 Pandemics Linear model Non-linear model Nível municipal COVID-19 Pandemia Modelo linear Modelo não linear |
description |
Background: The role of demographic and socio-economic determinants of COVID-19 transmission is still unclear and is expected to vary in different contexts and epidemic periods. Exploring such determinants may generate a hypothesis about transmission and aid the definition of prevention strategies. Objectives: To identify municipality-level demographic and socio-economic determinants of COVID-19 in Portugal. Methods: We assessed determinants of COVID-19 daily cases at 4 moments of the first COVID-19 epidemic wave in Portugal, related with lockdown and post-lockdown measures. We selected 60 potential determinants from 5 dimensions: population and settlement, disease, economy, social context, and mobility. We conducted a multiple linear regression (MLR) stepwise analysis (p < 0.05) and an artificial neural network (ANN) analysis with the variables to identify predictors of the number of daily cases. Results: For MLR, some of the identified variables were: resident population and population density, exports, overnight stays in touristic facilities, the location quotient of employment in accommodation, catering and similar activities, education, restaurants and lodging, some industries and building construction, the share of the population working outside the municipality, the net migration rate, income, and renting. In ANN, some of the identified variables were: population density and resident population, urbanization, students in higher education, income, exports, social housing buildings, production services employment, and the share of the population working outside the municipality of residence. Conclusions: Several factors were identified as possible determinants of COVID-19 transmission at the municipality level. Despite limitations to the study, we believe that this information should be considered to promote communication and prevention approaches. Further research should be conducted. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021 2021-01-01T00:00:00Z |
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 |
https://hdl.handle.net/10216/149521 |
url |
https://hdl.handle.net/10216/149521 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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2504-3137 2504-3145 10.1159/000514334 |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Karger Publishers |
publisher.none.fl_str_mv |
Karger Publishers |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799135539733987328 |