Logotipo do repositório
 

Publicação:
COVID Health Structure Index: The Vulnerability of Brazilian Microregions

dc.contributor.authorFerraz, Diogo [UNESP]
dc.contributor.authorMariano, Enzo Barberio [UNESP]
dc.contributor.authorManzine, Patricia Regina
dc.contributor.authorMoralles, Herick Fernando
dc.contributor.authorMorceiro, Paulo César
dc.contributor.authorTorres, Bruno Guimarães
dc.contributor.authorde Almeida, Mariana Rodrigues
dc.contributor.authorSoares de Mello, João Carlos
dc.contributor.authorRebelatto, Daisy Aparecida do Nascimento
dc.contributor.institutionUniversity of Hohenheim
dc.contributor.institutionFederal University of Ouro Preto (UFOP)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade Federal de São Carlos (UFSCar)
dc.contributor.institutionUniversity of Johannesburg
dc.contributor.institutionFluminense Federal University (UFF)
dc.contributor.institutionFederal University of Rio Grande do Norte (UFRN)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.date.accessioned2021-06-25T11:15:46Z
dc.date.available2021-06-25T11:15:46Z
dc.date.issued2021-01-01
dc.description.abstractMany developing countries have highly unequal health systems across their regions. The pandemic of COVID-19 brought an additional challenge, as hospital structures equipped with doctors, intensive care units and respirators are not available to a sufficient extent in all regions. Using Data Envelopment Analysis, we create a COVID Index to verify whether the hospital structures in 543 Brazilian microregions are adequate to deal with COVID-19 and to verify whether public policies were implemented in the right direction. The results indicate that hospital structures in the poorest microregions were the most vulnerable, although the peak of COVID-19 occurred in the richest microregions (Sao Paulo). The Southeast states could relocate hospital resources or even patients between their regions. The relocation was not possible in many states in the Northeast, as the health system poorly assisted the interior of these states. These findings reveal that the heterogeneity of microregions’ hospital structures follows the patterns of socioeconomic inequalities. We conclude that it is easier for the wealthier regions to reallocate hospital resources internally than for the poorest regions. By using the COVID Index, policymakers and hospital managers have straightforward information to decide which regions must receive new investments and reallocate underutilized resources.en
dc.description.affiliationDepartment of Innovation Economics University of Hohenheim, Wollgrasweg 23, 2nd floor, Room 520i
dc.description.affiliationDepartment of Economics Federal University of Ouro Preto (UFOP), Rua do Catete 166 Centro
dc.description.affiliationDepartment of Production Engineering São Paulo State University (UNESP) Núcleo Residencial Presidente Geisel, Avenida Engenheiro Luiz Edmundo Carrijo Coube, 14-01
dc.description.affiliationDepartment of Gerontology Federal University of São Carlos (UFSCar), Rod. Washington Luiz, s/n
dc.description.affiliationDepartment of Production Engineering Federal University of São Carlos (UFSCar), Rod. Washington Luiz, s/n
dc.description.affiliationDST/NRF South African Chair in Industrial Development College of Business and Economics University of Johannesburg, 31 Henley Road
dc.description.affiliationDepartment of Production Engineering Fluminense Federal University (UFF), Rua Passo da Pátria, Campus Praia Vermelha, Bloco D - sala 309
dc.description.affiliationDepartment of Production Engineering Federal University of Rio Grande do Norte (UFRN), Av. Senador Salgado Filho, n° 3000, Campus Universitário Lagoa Nova - Centro de Tecnologia
dc.description.affiliationDepartment of Production Engineering University of São Paulo (EESC/USP), Av. Trab. São Carlense, 400 - Parque Arnold Schimidt
dc.description.affiliationUnespDepartment of Production Engineering São Paulo State University (UNESP) Núcleo Residencial Presidente Geisel, Avenida Engenheiro Luiz Edmundo Carrijo Coube, 14-01
dc.identifierhttp://dx.doi.org/10.1007/s11205-021-02699-3
dc.identifier.citationSocial Indicators Research.
dc.identifier.doi10.1007/s11205-021-02699-3
dc.identifier.issn1573-0921
dc.identifier.issn0303-8300
dc.identifier.scopus2-s2.0-85105443727
dc.identifier.urihttp://hdl.handle.net/11449/208656
dc.language.isoeng
dc.relation.ispartofSocial Indicators Research
dc.sourceScopus
dc.subjectCoronavirus pandemic. health service. decision index. Brazilian microregions. Data Envelopment Analysis (DEA)
dc.titleCOVID Health Structure Index: The Vulnerability of Brazilian Microregionsen
dc.typeArtigo
dspace.entity.typePublication
unesp.author.orcid0000-0003-4037-7171[1]
unesp.author.orcid0000-0002-9577-3297[2]
unesp.author.orcid0000-0003-3460-9300[3]
unesp.author.orcid0000-0002-5521-9443[4]
unesp.author.orcid0000-0002-9548-0996[5]
unesp.author.orcid0000-0003-2095-7937[6]
unesp.author.orcid0000-0001-7491-0742[7]
unesp.author.orcid0000-0002-6507-2721[8]
unesp.author.orcid0000-0003-0611-1492[9]
unesp.departmentEngenharia de Produção - FEBpt

Arquivos