Brazilian states in the context of covid-19 pandemic: An Index Proposition using Network Data Envelopment Analysis
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/TLA.2021.9451236 http://hdl.handle.net/11449/229635 |
Resumo: | This study aims to evaluate comparatively the situation of the federal units and the Brazilian states in relation to the pandemic of new coronaviruses (COVID19) through the technique of Network Data Envelopment Analysis (Network DEA - NDEA). For the development of research, data were collected on the Ministry of Health website, for all regions that register cases of virus cases notified until April 27, 2020. The purpose of the analysis is to assess regional discrepancies in the country. The model consists of the following structure: three inputs (number of doctors, number of respirators and number of clinical beds), an intermediate variable (number of reported cases) and one output (number of deaths). The results indicated that the federative unit with the worst performance overall was Amazonas, while the worst capital was Manaus. With two-dimensional representation, managers can visualize better which locations have the worst performance and assess which locations require more assistance. Depending on the results, managers can develop regional action plans, which can take steps to prevent the collapse of the health system. |
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Brazilian states in the context of covid-19 pandemic: An Index Proposition using Network Data Envelopment AnalysisCOVID-19HealthcareNetwork data envelopment analysis (NDEA)Two-dimensional frontier representationThis study aims to evaluate comparatively the situation of the federal units and the Brazilian states in relation to the pandemic of new coronaviruses (COVID19) through the technique of Network Data Envelopment Analysis (Network DEA - NDEA). For the development of research, data were collected on the Ministry of Health website, for all regions that register cases of virus cases notified until April 27, 2020. The purpose of the analysis is to assess regional discrepancies in the country. The model consists of the following structure: three inputs (number of doctors, number of respirators and number of clinical beds), an intermediate variable (number of reported cases) and one output (number of deaths). The results indicated that the federative unit with the worst performance overall was Amazonas, while the worst capital was Manaus. With two-dimensional representation, managers can visualize better which locations have the worst performance and assess which locations require more assistance. Depending on the results, managers can develop regional action plans, which can take steps to prevent the collapse of the health system.Departamento de Engenharia de Produção (DEP) Universidade Estadual Paulista (UNESP), BauruUniversidade Federal Fluminense (UFF), NiteróiDepartamento de Engenharia de Produção (DEP) Universidade Federal do Rio Grande do Norte, NatalUniversidade Federal Rural da Amazônia (UFRA), ParauapebasEscola de Engenharia de São Carlos (EESC) Universidade de São Paulo, São CarlosDepartamento de Engenharia de Produção (TEP) Universidade Federal Fluminense (UFF), NiteróiDepartamento de Engenharia de Produção (DEP) Universidade Estadual Paulista (UNESP), BauruUniversidade Estadual Paulista (UNESP)Universidade Federal Fluminense (UFF)Universidade Federal do Rio Grande do NorteUniversidade Federal Rural da Amazônia (UFRA)Universidade de São Paulo (USP)Mariano, Enzo B. [UNESP]Torres, Bruno G.de Almeida, Mariana RodriguesFerraz, DiogoRebelatto, Daisy A.N.de Mello, João Carlos Soares2022-04-29T08:34:54Z2022-04-29T08:34:54Z2021-06-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article917-924http://dx.doi.org/10.1109/TLA.2021.9451236IEEE Latin America Transactions, v. 19, n. 6, p. 917-924, 2021.1548-0992http://hdl.handle.net/11449/22963510.1109/TLA.2021.94512362-s2.0-85116331180Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporIEEE Latin America Transactionsinfo:eu-repo/semantics/openAccess2024-06-28T13:17:58Zoai:repositorio.unesp.br:11449/229635Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:17:44.942819Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Brazilian states in the context of covid-19 pandemic: An Index Proposition using Network Data Envelopment Analysis |
title |
Brazilian states in the context of covid-19 pandemic: An Index Proposition using Network Data Envelopment Analysis |
spellingShingle |
Brazilian states in the context of covid-19 pandemic: An Index Proposition using Network Data Envelopment Analysis Mariano, Enzo B. [UNESP] COVID-19 Healthcare Network data envelopment analysis (NDEA) Two-dimensional frontier representation |
title_short |
Brazilian states in the context of covid-19 pandemic: An Index Proposition using Network Data Envelopment Analysis |
title_full |
Brazilian states in the context of covid-19 pandemic: An Index Proposition using Network Data Envelopment Analysis |
title_fullStr |
Brazilian states in the context of covid-19 pandemic: An Index Proposition using Network Data Envelopment Analysis |
title_full_unstemmed |
Brazilian states in the context of covid-19 pandemic: An Index Proposition using Network Data Envelopment Analysis |
title_sort |
Brazilian states in the context of covid-19 pandemic: An Index Proposition using Network Data Envelopment Analysis |
author |
Mariano, Enzo B. [UNESP] |
author_facet |
Mariano, Enzo B. [UNESP] Torres, Bruno G. de Almeida, Mariana Rodrigues Ferraz, Diogo Rebelatto, Daisy A.N. de Mello, João Carlos Soares |
author_role |
author |
author2 |
Torres, Bruno G. de Almeida, Mariana Rodrigues Ferraz, Diogo Rebelatto, Daisy A.N. de Mello, João Carlos Soares |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Universidade Federal Fluminense (UFF) Universidade Federal do Rio Grande do Norte Universidade Federal Rural da Amazônia (UFRA) Universidade de São Paulo (USP) |
dc.contributor.author.fl_str_mv |
Mariano, Enzo B. [UNESP] Torres, Bruno G. de Almeida, Mariana Rodrigues Ferraz, Diogo Rebelatto, Daisy A.N. de Mello, João Carlos Soares |
dc.subject.por.fl_str_mv |
COVID-19 Healthcare Network data envelopment analysis (NDEA) Two-dimensional frontier representation |
topic |
COVID-19 Healthcare Network data envelopment analysis (NDEA) Two-dimensional frontier representation |
description |
This study aims to evaluate comparatively the situation of the federal units and the Brazilian states in relation to the pandemic of new coronaviruses (COVID19) through the technique of Network Data Envelopment Analysis (Network DEA - NDEA). For the development of research, data were collected on the Ministry of Health website, for all regions that register cases of virus cases notified until April 27, 2020. The purpose of the analysis is to assess regional discrepancies in the country. The model consists of the following structure: three inputs (number of doctors, number of respirators and number of clinical beds), an intermediate variable (number of reported cases) and one output (number of deaths). The results indicated that the federative unit with the worst performance overall was Amazonas, while the worst capital was Manaus. With two-dimensional representation, managers can visualize better which locations have the worst performance and assess which locations require more assistance. Depending on the results, managers can develop regional action plans, which can take steps to prevent the collapse of the health system. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-01 2022-04-29T08:34:54Z 2022-04-29T08:34:54Z |
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://dx.doi.org/10.1109/TLA.2021.9451236 IEEE Latin America Transactions, v. 19, n. 6, p. 917-924, 2021. 1548-0992 http://hdl.handle.net/11449/229635 10.1109/TLA.2021.9451236 2-s2.0-85116331180 |
url |
http://dx.doi.org/10.1109/TLA.2021.9451236 http://hdl.handle.net/11449/229635 |
identifier_str_mv |
IEEE Latin America Transactions, v. 19, n. 6, p. 917-924, 2021. 1548-0992 10.1109/TLA.2021.9451236 2-s2.0-85116331180 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
IEEE Latin America Transactions |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
917-924 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
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1808128630425911296 |