Spatial analysis of determinants of COVID-19 vaccine hesitancy in Portugal
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/164714 |
Resumo: | ABSTRACT - Background: Vaccine hesitancy tends to exhibit geographical patterns and is often associated with social deprivation and migrant status. Objectives: We aim to estimate the COVID-19 vaccination hesitancy in a high vaccination acceptance country, Portugal, and its association with sociodemographic risk factors. Methods: We used the Registry of National Health System Users to determine the eligible population for vaccination and the Vaccination Registry to determine the individuals without COVID-19 vaccine doses. Individuals older than five with no COVID 19 vaccine dose administered on March 31, 2022 were considered hesitant. We calculated hesitancy rates by the municipality, sex and age group for all municipalities in mainland Portugal. We modeled vaccine hesitancy rates with the spatial statistical scan method to identify the spatial clusters and the Besag, York, and Mollié (BYM) model to estimate the effect of age, sex, social deprivation, and migrant proportion across all the municipalities of mainland Portugal. Results: The eligible population was 9,852,283, with 1,212,565 (12%) COVID-19 vaccine-hesitant individuals. We found high hesitancy spatial clusters in the Lisbon metropolitan area and the country's southwest. Our model showed that municipalities with higher proportions of migrants are associated with an increased relative risk (RR) of vaccine hesitancy (RR = 8.0; CI 95% 4.6; 14.0). Social deprivation and gender were not associated with vaccine hesitancy rates. Conclusion: We found clusters of COVID-19 vaccine hesitancy in Portugal and a strong association with the proportion of migrants per municipality. |
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Spatial analysis of determinants of COVID-19 vaccine hesitancy in PortugalCOVID-19SARS-CoV-2Vaccine hesitancySocial DeprivationMigrant Healthhesitação vacinalprivação socialsaúde do migranteDomínio/Área Científica::Ciências Sociais::Outras Ciências SociaisABSTRACT - Background: Vaccine hesitancy tends to exhibit geographical patterns and is often associated with social deprivation and migrant status. Objectives: We aim to estimate the COVID-19 vaccination hesitancy in a high vaccination acceptance country, Portugal, and its association with sociodemographic risk factors. Methods: We used the Registry of National Health System Users to determine the eligible population for vaccination and the Vaccination Registry to determine the individuals without COVID-19 vaccine doses. Individuals older than five with no COVID 19 vaccine dose administered on March 31, 2022 were considered hesitant. We calculated hesitancy rates by the municipality, sex and age group for all municipalities in mainland Portugal. We modeled vaccine hesitancy rates with the spatial statistical scan method to identify the spatial clusters and the Besag, York, and Mollié (BYM) model to estimate the effect of age, sex, social deprivation, and migrant proportion across all the municipalities of mainland Portugal. Results: The eligible population was 9,852,283, with 1,212,565 (12%) COVID-19 vaccine-hesitant individuals. We found high hesitancy spatial clusters in the Lisbon metropolitan area and the country's southwest. Our model showed that municipalities with higher proportions of migrants are associated with an increased relative risk (RR) of vaccine hesitancy (RR = 8.0; CI 95% 4.6; 14.0). Social deprivation and gender were not associated with vaccine hesitancy rates. Conclusion: We found clusters of COVID-19 vaccine hesitancy in Portugal and a strong association with the proportion of migrants per municipality.RESUMO - Contexto: A hesitação vacinal tem tendência a exibir padrões geográficos e está frequentemente associada a privação social e estatuto de migrante. Objetivos: Estimar a hesitação vacinal na COVID-19 num país com elevada cobertura vacinal, Portugal, e a sua associação com fatores de risco sociodemográficos. Métodos: Usou-se o Registo Nacional de Utentes (RNU) para determinar a população elegível e o VACINAS para determinar o número de indivíduos sem qualquer inoculação vacinal para a COVID-19. Consideram-se hesitantes os indivíduos com mais de 5 anos de idade sem doses de vacina COVID-19 à data de 31 de março de 2022. Calcularam se proporções por município, sexo e grupo etário para todos os municípios de Portugal Continental. Usou-se a metodologia SaTScan para identificar clusters espaciais e o modelo Besag, York, and Mollié (BYM) para estimar o efeito das variáveis explicativas. Resultados: A população elegível totalizou 9 852 283 indivíduos, dos quais 1 212 565 (12%) eram hesitantes para as vacinas da COVID-19. Foram encontrados clusters de hesitação vacinal na área da grande Lisboa e no sudoeste do país. O modelo ajustado sugere uma forte associação positiva entre hesitação vacinal e a proporção de migrantes (RR = 8; IC 95% 4,6; 14). A privação social e o género não evidenciaram associação com as proporções de hesitação vacinal. Conclusão: Foram encontrados clusters de hesitação vacinal para a COVID-19 em Portugal e uma forte associação com a proporção de migrantes por município.Peralta-Santos, AndréRUNCarvalho, Constança Pinto de2024-03-11T11:49:26Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/164714TID:203533607enginfo: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:RCAAP2024-03-18T01:44:30Zoai:run.unl.pt:10362/164714Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T04:01:57.695980Repositório 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 analysis of determinants of COVID-19 vaccine hesitancy in Portugal |
title |
Spatial analysis of determinants of COVID-19 vaccine hesitancy in Portugal |
spellingShingle |
Spatial analysis of determinants of COVID-19 vaccine hesitancy in Portugal Carvalho, Constança Pinto de COVID-19 SARS-CoV-2 Vaccine hesitancy Social Deprivation Migrant Health hesitação vacinal privação social saúde do migrante Domínio/Área Científica::Ciências Sociais::Outras Ciências Sociais |
title_short |
Spatial analysis of determinants of COVID-19 vaccine hesitancy in Portugal |
title_full |
Spatial analysis of determinants of COVID-19 vaccine hesitancy in Portugal |
title_fullStr |
Spatial analysis of determinants of COVID-19 vaccine hesitancy in Portugal |
title_full_unstemmed |
Spatial analysis of determinants of COVID-19 vaccine hesitancy in Portugal |
title_sort |
Spatial analysis of determinants of COVID-19 vaccine hesitancy in Portugal |
author |
Carvalho, Constança Pinto de |
author_facet |
Carvalho, Constança Pinto de |
author_role |
author |
dc.contributor.none.fl_str_mv |
Peralta-Santos, André RUN |
dc.contributor.author.fl_str_mv |
Carvalho, Constança Pinto de |
dc.subject.por.fl_str_mv |
COVID-19 SARS-CoV-2 Vaccine hesitancy Social Deprivation Migrant Health hesitação vacinal privação social saúde do migrante Domínio/Área Científica::Ciências Sociais::Outras Ciências Sociais |
topic |
COVID-19 SARS-CoV-2 Vaccine hesitancy Social Deprivation Migrant Health hesitação vacinal privação social saúde do migrante Domínio/Área Científica::Ciências Sociais::Outras Ciências Sociais |
description |
ABSTRACT - Background: Vaccine hesitancy tends to exhibit geographical patterns and is often associated with social deprivation and migrant status. Objectives: We aim to estimate the COVID-19 vaccination hesitancy in a high vaccination acceptance country, Portugal, and its association with sociodemographic risk factors. Methods: We used the Registry of National Health System Users to determine the eligible population for vaccination and the Vaccination Registry to determine the individuals without COVID-19 vaccine doses. Individuals older than five with no COVID 19 vaccine dose administered on March 31, 2022 were considered hesitant. We calculated hesitancy rates by the municipality, sex and age group for all municipalities in mainland Portugal. We modeled vaccine hesitancy rates with the spatial statistical scan method to identify the spatial clusters and the Besag, York, and Mollié (BYM) model to estimate the effect of age, sex, social deprivation, and migrant proportion across all the municipalities of mainland Portugal. Results: The eligible population was 9,852,283, with 1,212,565 (12%) COVID-19 vaccine-hesitant individuals. We found high hesitancy spatial clusters in the Lisbon metropolitan area and the country's southwest. Our model showed that municipalities with higher proportions of migrants are associated with an increased relative risk (RR) of vaccine hesitancy (RR = 8.0; CI 95% 4.6; 14.0). Social deprivation and gender were not associated with vaccine hesitancy rates. Conclusion: We found clusters of COVID-19 vaccine hesitancy in Portugal and a strong association with the proportion of migrants per municipality. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023 2023-01-01T00:00:00Z 2024-03-11T11:49:26Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/164714 TID:203533607 |
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http://hdl.handle.net/10362/164714 |
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TID:203533607 |
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eng |
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eng |
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openAccess |
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application/pdf |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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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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