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: | |
---|---|
Data de Publicação: | 2020 |
Outros Autores: | , , , , , , , , |
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. |
id |
RCAP_34213f46ca20ea4503778de7173f00ff |
---|---|
oai_identifier_str |
oai:scielo:S2504-31452020000400018 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
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 |
url |
http://scielo.pt/scielo.php?script=sci_arttext&pid=S2504-31452020000400018 |
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 instacron:RCAAP |
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 |
|
_version_ |
1799137416103067648 |