Use este identificador para citar ou linkar para este item: http://www.repositorio.ufop.br/jspui/handle/123456789/14974
Título: Brazilian states in the context of COVID-19 pandemic : an index proposition using network data envelopment analysis.
Autor(es): Mariano, Enzo Barberio
Torres, Bruno G.
Almeida, Mariana Rodrigues de
Ferraz, Diogo
Rebelatto, Daisy Aparecida do Nascimento
Mello, João Carlos Soares de
Palavras-chave: Healthcare
Two-dimensional frontier representation
Data do documento: 2021
Referência: MARIANO, E. B. et al. Brazilian states in the context of COVID-19 pandemic: an index proposition using network data envelopment analysis. IEEE Latin America Transactions, v. 19, n. 6, jun. 2021. Disponível em: <https://latamt.ieeer9.org/index.php/transactions/article/view/4274>. Acesso em: 24 maio 2022.
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.
URI: http://www.repositorio.ufop.br/jspui/handle/123456789/14974
Link para o artigo: https://latamt.ieeer9.org/index.php/transactions/article/view/4274
ISSN:  1548-0992
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