Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/101650
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dc.contributorDepartment of Applied Mathematics-
dc.contributorSchool of Nursing-
dc.creatorLiu, Yen_US
dc.creatorWang, Ken_US
dc.creatorYang, Len_US
dc.creatorHe, Den_US
dc.date.accessioned2023-09-18T07:41:02Z-
dc.date.available2023-09-18T07:41:02Z-
dc.identifier.issn2468-0427en_US
dc.identifier.urihttp://hdl.handle.net/10397/101650-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2022 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rightsThe following publication Liu, Y., Wang, K., Yang, L., & He, D. (2022). Regional heterogeneity of in-hospital mortality of COVID-19 in Brazil. Infectious Disease Modelling, 7(3), 364-373 is available at https://doi.org/10.1016/j.idm.2022.06.005.en_US
dc.subjectBrazilen_US
dc.subjectCOVID-19en_US
dc.subjectIn-hospital mortalityen_US
dc.subjectVaccineen_US
dc.titleRegional heterogeneity of in-hospital mortality of COVID-19 in Brazilen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage364en_US
dc.identifier.epage373en_US
dc.identifier.volume7en_US
dc.identifier.issue3en_US
dc.identifier.doi10.1016/j.idm.2022.06.005en_US
dcterms.abstractBackground: The ongoing Coronavirus disease of 2019 (COVID-19) pandemic has hit Brazil hard in period of different dominant variants. Different COIVD-19 variants have swept through the region, resulting that the total number of cases in Brazil is the third highest in the world. This study is aimed at investigating the regional heterogeneity of in-hospital mortality of COVID-19 in Brazil and the effects of vaccination and social inequality.-
dcterms.abstractMethods: We fitted a multivariate mixed-effects Cox model to a national database of inpatient data in Brazil who were admitted for COVID-19 from February 27, 2020 to March 15, 2022. The in-hospital mortality risks of vaccinated and unvaccinated patients were compared, with adjustment for age, state, ethnicity, education and comorbidities. And the effects of variables to in-hospital mortality were also compared. Stratified analysis was conducted across different age groups and vaccine types.-
dcterms.abstractResults: By fitting the multivariate mixed-effects Cox model, we concluded that age was the most important risk factor for death. With regards to educational level, illiterate patients (hazard ratio: 1.63, 95% CI: 1.56–1.70) had a higher risk than those with a university or college degree. Some common comorbidities were more dangerous for hospitalized patients, such as liver disease (HR: 1.46, 95% CI: 1.34–1.59) and immunosuppression (HR:1.32, 95% CI: 1.26–1.40). In addition, the states involving Sergipe (HR: 1.75, 95% CI: 1.46–2.11), Roraima (HR: 1.65, 95% CI: 1.43–1.92), Maranhão (HR: 1.57, 95% CI: 1.38–1.79), Acre (HR: 1.44, 95% CI: 1.12–1.86), and Rondônia (HR: 1.26, 95% CI: 1.10–1.44) in the north and the northeast region tended to have higher hazard ratios than other area. In terms of vaccine protection, vaccination did not significantly reduce mortality among hospitalized patients. Sinovac and AstraZeneca offered different protection in different regions, and no vaccine provided high protection in all regions.-
dcterms.abstractConclusion: The study revealed the regional heterogeneity of in-hospital mortality of Covid-19 in Brazil and the effects of vaccination and social inequality. We found that ethnic concentrations were consistent with higher proportion of death cases relative to population size. White Brazilians had more frequent international travel opportunities. As race revealed the intersection of social connections, we speculated that uneven interactions with residential communities partially contribute to the spread of the epidemic. Additionally, the vaccine showed different protection in different regions. In the northern and northeastern regions, AstraZeneca was much more protective than Sinovac, while Sinovac was more protective for hospitalized patients with varying numbers of comorbidities in the Central-west, Southeast and South regions.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInfectious Disease Modelling, Sept. 2022, v. 7, no. 3, p. 364-373en_US
dcterms.isPartOfInfectious disease modellingen_US
dcterms.issued2022-09-
dc.identifier.scopus2-s2.0-85133945260-
dc.description.validate202309 bcvc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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