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,Paulo
Data de Publicação: 2020
Outros Autores: Costa,Nuno Marques da, Costa,Eduarda Marques da, Rocha,Jorge, Peixoto,Vasco Ricoca, Fernandes,Adalberto Campos, Gaspar,Rogério, Duarte-Ramos,Filipa, Abrantes,Patrícia, Leite,Andreia
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://scielo.pt/scielo.php?script=sci_arttext&pid=S2504-31452020000400018
Resumo: Abstract 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 wave.Municipal levelCOVID-19PandemicsLinear modelNon-linear modelAbstract 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.Escola Nacional de Saúde Pública2020-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articletext/htmlhttp://scielo.pt/scielo.php?script=sci_arttext&pid=S2504-31452020000400018Portuguese Journal of Public Health v.38 suppl.1 2020reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttp://scielo.pt/scielo.php?script=sci_arttext&pid=S2504-31452020000400018Sousa,PauloCosta,Nuno Marques daCosta,Eduarda Marques daRocha,JorgePeixoto,Vasco RicocaFernandes,Adalberto CamposGaspar,RogérioDuarte-Ramos,FilipaAbrantes,PatríciaLeite,Andreiainfo:eu-repo/semantics/openAccess2024-02-06T17:34:32Zoai:scielo:S2504-31452020000400018Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:36:28.183583Repositório 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.
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,Paulo
Municipal level
COVID-19
Pandemics
Linear model
Non-linear model
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,Paulo
author_facet Sousa,Paulo
Costa,Nuno Marques da
Costa,Eduarda Marques da
Rocha,Jorge
Peixoto,Vasco Ricoca
Fernandes,Adalberto Campos
Gaspar,Rogério
Duarte-Ramos,Filipa
Abrantes,Patrícia
Leite,Andreia
author_role author
author2 Costa,Nuno Marques da
Costa,Eduarda Marques da
Rocha,Jorge
Peixoto,Vasco Ricoca
Fernandes,Adalberto Campos
Gaspar,Rogério
Duarte-Ramos,Filipa
Abrantes,Patrícia
Leite,Andreia
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Sousa,Paulo
Costa,Nuno Marques da
Costa,Eduarda Marques da
Rocha,Jorge
Peixoto,Vasco Ricoca
Fernandes,Adalberto Campos
Gaspar,Rogério
Duarte-Ramos,Filipa
Abrantes,Patrícia
Leite,Andreia
dc.subject.por.fl_str_mv Municipal level
COVID-19
Pandemics
Linear model
Non-linear model
topic Municipal level
COVID-19
Pandemics
Linear model
Non-linear model
description Abstract 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 2020
dc.date.none.fl_str_mv 2020-12-01
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://scielo.pt/scielo.php?script=sci_arttext&pid=S2504-31452020000400018
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://scielo.pt/scielo.php?script=sci_arttext&pid=S2504-31452020000400018
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Escola Nacional de Saúde Pública
publisher.none.fl_str_mv Escola Nacional de Saúde Pública
dc.source.none.fl_str_mv Portuguese Journal of Public Health v.38 suppl.1 2020
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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instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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
repository.mail.fl_str_mv
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