Characterization of the epidemiological curve of the 1st wave of the pandemic: study of the determinants for death and hospitalization due to COVID-19 in Portugal
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: | http://hdl.handle.net/10773/32788 |
Resumo: | COVID-19 is an infectious disease caused by the SARS-CoV-2 virus that emerged in China and has since spread rapidly to all countries in the world. The aim of this study is to characterize the peak of the first wave of the pandemic in Portugal using some demographic and clinical determinants. The database studied contains epidemiological surveillance data of COVID-19 from Portugal until June 30, 2020. The peak of the pandemic was determined considering the number of diagnoses, deaths, and hospitalizations over time, and the estimated period for the first wave was between March 19 and April 24. Multivariable logistic regression models were performed to estimate the Odds Ratio (OR) and the respective 95% confidence intervals (95% CI) for this period and for each of the variables considered in relation to both study outcomes: mortality (5.8%) and hospitalization (18.8%). The main risk factors considered for the mortality outcome were: Age Group (≥ 80 years: OR = 11.98; 65-79 years: OR = 4.06; reference group: <64 years), Hospitalization (OR = 6.48) and Comorbidities (OR = 5.74). For the outcome hospitalization, the main risk factors were: Age Group (≥ 80 years: OR = 8.54; 65-79 years: OR = 3.90; reference group: <64 years), male gender (OR= 1.58) and Comorbidities (OR = 5.19). The proposed models presented high area under the curve (AUC) results (mortality: AUC=91.1%; and hospitalization: AUC=84.5%), with small amplitudes in the 95% CI. The present study demonstrated that, overall, the major risk factors associated with worse prognostics of COVID-19 were advanced age (over 65 years), and the existence of comorbidities. For the risk of hospitalizations, the male gender was also a significant risk factor. |
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Characterization of the epidemiological curve of the 1st wave of the pandemic: study of the determinants for death and hospitalization due to COVID-19 in PortugalCOVID-19PortugalMortality, Hospitalization, Comorbidities.Logistic regressionDemographic factorsCOVID-19 is an infectious disease caused by the SARS-CoV-2 virus that emerged in China and has since spread rapidly to all countries in the world. The aim of this study is to characterize the peak of the first wave of the pandemic in Portugal using some demographic and clinical determinants. The database studied contains epidemiological surveillance data of COVID-19 from Portugal until June 30, 2020. The peak of the pandemic was determined considering the number of diagnoses, deaths, and hospitalizations over time, and the estimated period for the first wave was between March 19 and April 24. Multivariable logistic regression models were performed to estimate the Odds Ratio (OR) and the respective 95% confidence intervals (95% CI) for this period and for each of the variables considered in relation to both study outcomes: mortality (5.8%) and hospitalization (18.8%). The main risk factors considered for the mortality outcome were: Age Group (≥ 80 years: OR = 11.98; 65-79 years: OR = 4.06; reference group: <64 years), Hospitalization (OR = 6.48) and Comorbidities (OR = 5.74). For the outcome hospitalization, the main risk factors were: Age Group (≥ 80 years: OR = 8.54; 65-79 years: OR = 3.90; reference group: <64 years), male gender (OR= 1.58) and Comorbidities (OR = 5.19). The proposed models presented high area under the curve (AUC) results (mortality: AUC=91.1%; and hospitalization: AUC=84.5%), with small amplitudes in the 95% CI. The present study demonstrated that, overall, the major risk factors associated with worse prognostics of COVID-19 were advanced age (over 65 years), and the existence of comorbidities. For the risk of hospitalizations, the male gender was also a significant risk factor.UA/CHBV2021-12-23T12:19:10Z2021-12-14T00:00:00Z2021-12-14info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/32788eng2184-579410.34624/jshd.v3i2.24208Freire, Francisca MonteiroAfreixo, VeraSá Couto, Pedroinfo: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:RCAAP2024-02-22T12:03:02Zoai:ria.ua.pt:10773/32788Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:04:19.015882Repositório 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 |
Characterization of the epidemiological curve of the 1st wave of the pandemic: study of the determinants for death and hospitalization due to COVID-19 in Portugal |
title |
Characterization of the epidemiological curve of the 1st wave of the pandemic: study of the determinants for death and hospitalization due to COVID-19 in Portugal |
spellingShingle |
Characterization of the epidemiological curve of the 1st wave of the pandemic: study of the determinants for death and hospitalization due to COVID-19 in Portugal Freire, Francisca Monteiro COVID-19 Portugal Mortality, Hospitalization, Comorbidities. Logistic regression Demographic factors |
title_short |
Characterization of the epidemiological curve of the 1st wave of the pandemic: study of the determinants for death and hospitalization due to COVID-19 in Portugal |
title_full |
Characterization of the epidemiological curve of the 1st wave of the pandemic: study of the determinants for death and hospitalization due to COVID-19 in Portugal |
title_fullStr |
Characterization of the epidemiological curve of the 1st wave of the pandemic: study of the determinants for death and hospitalization due to COVID-19 in Portugal |
title_full_unstemmed |
Characterization of the epidemiological curve of the 1st wave of the pandemic: study of the determinants for death and hospitalization due to COVID-19 in Portugal |
title_sort |
Characterization of the epidemiological curve of the 1st wave of the pandemic: study of the determinants for death and hospitalization due to COVID-19 in Portugal |
author |
Freire, Francisca Monteiro |
author_facet |
Freire, Francisca Monteiro Afreixo, Vera Sá Couto, Pedro |
author_role |
author |
author2 |
Afreixo, Vera Sá Couto, Pedro |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Freire, Francisca Monteiro Afreixo, Vera Sá Couto, Pedro |
dc.subject.por.fl_str_mv |
COVID-19 Portugal Mortality, Hospitalization, Comorbidities. Logistic regression Demographic factors |
topic |
COVID-19 Portugal Mortality, Hospitalization, Comorbidities. Logistic regression Demographic factors |
description |
COVID-19 is an infectious disease caused by the SARS-CoV-2 virus that emerged in China and has since spread rapidly to all countries in the world. The aim of this study is to characterize the peak of the first wave of the pandemic in Portugal using some demographic and clinical determinants. The database studied contains epidemiological surveillance data of COVID-19 from Portugal until June 30, 2020. The peak of the pandemic was determined considering the number of diagnoses, deaths, and hospitalizations over time, and the estimated period for the first wave was between March 19 and April 24. Multivariable logistic regression models were performed to estimate the Odds Ratio (OR) and the respective 95% confidence intervals (95% CI) for this period and for each of the variables considered in relation to both study outcomes: mortality (5.8%) and hospitalization (18.8%). The main risk factors considered for the mortality outcome were: Age Group (≥ 80 years: OR = 11.98; 65-79 years: OR = 4.06; reference group: <64 years), Hospitalization (OR = 6.48) and Comorbidities (OR = 5.74). For the outcome hospitalization, the main risk factors were: Age Group (≥ 80 years: OR = 8.54; 65-79 years: OR = 3.90; reference group: <64 years), male gender (OR= 1.58) and Comorbidities (OR = 5.19). The proposed models presented high area under the curve (AUC) results (mortality: AUC=91.1%; and hospitalization: AUC=84.5%), with small amplitudes in the 95% CI. The present study demonstrated that, overall, the major risk factors associated with worse prognostics of COVID-19 were advanced age (over 65 years), and the existence of comorbidities. For the risk of hospitalizations, the male gender was also a significant risk factor. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12-23T12:19:10Z 2021-12-14T00:00:00Z 2021-12-14 |
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://hdl.handle.net/10773/32788 |
url |
http://hdl.handle.net/10773/32788 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2184-5794 10.34624/jshd.v3i2.24208 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
UA/CHBV |
publisher.none.fl_str_mv |
UA/CHBV |
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 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 |
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1799137698840051712 |