Influence of socio-economic indicators and territorial networks at the spatiotemporal spread dynamics of Covid-19 in Brazil

Dados Bibliográficos

ID4331340
AutoresMiguel Guia Albuquerque (0000-0002-2063-492X, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul), Jefferson Rodrigues Dos Santos (0000-0002-4938-9577, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul), Angelita Fialho Silveira (0000-0002-8565-9466, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul), Dardo Lorenzo Bornia Junior (0000-0002-3316-404X, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul), Rojane Brum Nunes (0000-0001-8560-7685, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul), Tiago Borges Ribeiro Gandra (0000-0002-7165-770X, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul), André Luis Corrêa Da Silva (0000-0001-7190-6406, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul), Gustavo Borba De Miranda (0000-0003-4029-8334, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul), Alessandra Ruiz Trevisol (0000-0003-2934-5531, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul)
Ano2021
Volume33
Data de publicação2021-04-16
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoSociedade & natureza (JOURNAL)
Identificadores do periódicoISSN: 0103-1570 • E-ISSN: 1982-4513
EditoraPPUFU - Portal de Periódicos da Universidade Federal de Uberlândia (PUBLISHER)
DOI10.14393/sn-v33-2021-59688
OpenAlexW3152691055
IdiomaEN
Citações recebidas1
Referências citadas11

This work aims to provide an overview of the territorial evolution of COVID-19 (SARS-CoV-2) in Brazil using socio-demographic variables, for the time span between February 26, 2020 until January 24, 2021. Socio-demographic indicators, basic sanitation infrastructure data, and epidemiological bulletins were integrated using Principal Components Analysis (PCA) to develop a social vulnerability index (SVI), to estimate the degree of exposure risk of the Brazilian population to COVID-19. The results indicate that the majority of confirmed cases were reported from the main Brazilian capitals, linked to well-developed port and airport modes. In terms of deaths, the states of São Paulo, Rio de Janeiro, Ceará and Pernambuco were at the top of the ranking. On the contrary, there were some states of the mid-west (Mato Grosso do Sul) and the north (Acre, Amapá, Roraima, Rondônia and Tocantins), that recorded low mortality indexes. The SVI reveals that the states of the north and north-east are the most vulnerable. Regarding the metropolitan areas, it was observed that the main capitals of the north and north-east, with the exception of Salvador, present significantly more critical numbers in terms of dissemination and deaths by COVID-19 than the capitals of the south-southeast, where the SVI is lower. The comparative exception was Santa Catarina state metropolitan areas. Finally, as the virus does not strike everyone in the same way, one of the great challenges is to search for solutions to cope with COVID-19 in the face of very unequal realities. Thus, a reflection on the strategies adopted by the Brazilian government is relevant, while considering the continental dimensions and the diversity of the Brazilian regions, to obtain a better analysis of the more vulnerable populations and social groups

2019-20 coronavirus outbreak · Biology · Coronavirus disease 2019 (COVID-19 · Dynamics (music · Econometrics · Economic geography · Economics · Geography · Outbreak · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Sociology · COVID-19 epidemiological studies · COVID-19 impact on air quality · COVID-19 Pandemic Impacts · Medicine · Virology