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

Detalhes bibliográficos
Autor(a) principal: Sousa, P
Data de Publicação: 2021
Outros Autores: Da, Costa, NM, Da Costa, EM, Rocha, J, Ricoca Peixoto, V, Campos Fernandes, A, Gaspar, R, Duarte-Ramos, F, Abrantes, P, Leite, A
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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spelling 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
dc.relation.none.fl_str_mv 2504-3137
2504-3145
10.1159/000514334
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 Karger Publishers
publisher.none.fl_str_mv Karger Publishers
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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