ANALYSIS OF SPATIAL RELATIONSHIPS OF CONFIRMED COVID-19 CASES AND DEATHS FROM MARCH TO AUGUST 2020 IN THE STATE OF PERNAMBUCO, BRAZIL

Detalhes bibliográficos
Autor(a) principal: Candeia, Bruna Araujo
Data de Publicação: 2023
Outros Autores: Candeias, Ana Lúcia Bezerra, Tavares Junior, João Rodrigues
Tipo de documento: Artigo
Idioma: por
Título da fonte: Caminhos de Geografia
Texto Completo: https://seer.ufu.br/index.php/caminhosdegeografia/article/view/62229
Resumo: By modeling COVID-19 data, and drawing up thematic maps, it was possible to analyze spatiotemporal behavior patterns of the new coronavirus in Pernambuco. It is possible to identify: 01- The highest numbers of cases and deaths are related to the cities with the highest GDP per capita; 02- The spread of the disease follows the directions of the main network of federal highways; 03- The thematic maps of municipalities added to the numbers of cases and deaths have repercussions on the articulated and intense propagation of patterns in blocks of municipalities connected by highways in the timeline, as the cases of Serra Talhada, São José de Belmonte, Mirandiba, Salgueiro and Parnamirim; 04- Other municipalities such as Santa Maria da Boa Vista and Orocó are isolated with fewer cases, as well as Belém do São Francisco and Carnaubeira da Penha, small isolated blocks with fewer cases and deaths, similarly to Ibimirim and Custódia; Águas Belas and Serra Talhada are outside the propagation block, the “island-municipalities”, thus revealing a behavior of propagation of the disease, of isolated or articulated municipalities around and along federal road axes. BR-104 and 232 assume regional influence and state and local roads may have contributed to greater "capillarity" of the spread of COVID-19.
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spelling ANALYSIS OF SPATIAL RELATIONSHIPS OF CONFIRMED COVID-19 CASES AND DEATHS FROM MARCH TO AUGUST 2020 IN THE STATE OF PERNAMBUCO, BRAZILANÁLISE DAS RELAÇÕES ESPACIAIS DOS CASOS CONFIRMADOS E ÓBITOS DA COVID-19 NO PERÍODO DE MARÇO A AGOSTO DE 2020 NO ESTADO DE PERNAMBUCO, BRASILCOVID-19PandemiaCartografia TemáticaCOVID-19PandemicThematic CartographyBy modeling COVID-19 data, and drawing up thematic maps, it was possible to analyze spatiotemporal behavior patterns of the new coronavirus in Pernambuco. It is possible to identify: 01- The highest numbers of cases and deaths are related to the cities with the highest GDP per capita; 02- The spread of the disease follows the directions of the main network of federal highways; 03- The thematic maps of municipalities added to the numbers of cases and deaths have repercussions on the articulated and intense propagation of patterns in blocks of municipalities connected by highways in the timeline, as the cases of Serra Talhada, São José de Belmonte, Mirandiba, Salgueiro and Parnamirim; 04- Other municipalities such as Santa Maria da Boa Vista and Orocó are isolated with fewer cases, as well as Belém do São Francisco and Carnaubeira da Penha, small isolated blocks with fewer cases and deaths, similarly to Ibimirim and Custódia; Águas Belas and Serra Talhada are outside the propagation block, the “island-municipalities”, thus revealing a behavior of propagation of the disease, of isolated or articulated municipalities around and along federal road axes. BR-104 and 232 assume regional influence and state and local roads may have contributed to greater "capillarity" of the spread of COVID-19.Modelando os dados da COVID-19 e elaborando mapas temáticos, foi possível analisar padrões de comportamento espaço-temporal do novo coronavírus em Pernambuco. Sendo possível identificar: 01- Os maiores números de casos e óbitos estão relacionados aos municípios de maior PIB per capita; 02- A dispersão da doença acompanha as direções da rede principal de rodovias federais; 03- Os mapas temáticos dos municípios agregados aos números de casos e óbitos repercutem na propagação articulada e intensa de padrões em blocos de municípios conectados por rodovias na linha do tempo, vide Serra Talhada, São José de Belmonte, Mirandiba, Salgueiro e Parnamirim; 04- Outros municípios como Santa Maria da Boa Vista e Orocó se apresentam isolados com menos casos, assim como Belém do São Francisco e Carnaubeira da Penha, pequenos blocos isolados com menos casos e óbitos, analogamente a Ibimirim e Custódia; já Águas Belas e Serra Talhada apresentam-se fora da propagação em bloco, os  “municípios-ilhas”. Revelando, assim, um comportamento de propagação da doença, de municípios isolados ou articulados em torno e ao longo de eixos viários federais. As BR-104 e 232 assumem influência regional e as estradas estaduais e vicinais podem ter contribuído para maior "capilaridade" da disseminação da COVID-19.EDUFU - Editora da Universidade Federal de Uberlândia2023-02-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado pelos paresapplication/pdfhttps://seer.ufu.br/index.php/caminhosdegeografia/article/view/6222910.14393/RCG249162229Caminhos de Geografia; Vol. 24 No. 91 (2023): Fevereiro; 208-223Caminhos de Geografia; Vol. 24 Núm. 91 (2023): Fevereiro; 208-223Caminhos de Geografia; v. 24 n. 91 (2023): Fevereiro; 208-2231678-6343reponame:Caminhos de Geografiainstname:Universidade Federal de Uberlândia (UFU)instacron:UFUporhttps://seer.ufu.br/index.php/caminhosdegeografia/article/view/62229/35618Copyright (c) 2023 Bruna Araujo Candeia, Ana Lúcia Bezerra Candeias, João Rodrigues Tavares Juniorhttp://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessCandeia, Bruna AraujoCandeias, Ana Lúcia BezerraTavares Junior, João Rodrigues2023-02-22T20:06:05Zoai:ojs.www.seer.ufu.br:article/62229Revistahttps://seer.ufu.br/index.php/caminhosdegeografia/indexPUBhttp://www.seer.ufu.br/index.php/caminhosdegeografia/oaiflaviasantosgeo@gmail.com1678-63431678-6343opendoar:2023-02-22T20:06:05Caminhos de Geografia - Universidade Federal de Uberlândia (UFU)false
dc.title.none.fl_str_mv ANALYSIS OF SPATIAL RELATIONSHIPS OF CONFIRMED COVID-19 CASES AND DEATHS FROM MARCH TO AUGUST 2020 IN THE STATE OF PERNAMBUCO, BRAZIL
ANÁLISE DAS RELAÇÕES ESPACIAIS DOS CASOS CONFIRMADOS E ÓBITOS DA COVID-19 NO PERÍODO DE MARÇO A AGOSTO DE 2020 NO ESTADO DE PERNAMBUCO, BRASIL
title ANALYSIS OF SPATIAL RELATIONSHIPS OF CONFIRMED COVID-19 CASES AND DEATHS FROM MARCH TO AUGUST 2020 IN THE STATE OF PERNAMBUCO, BRAZIL
spellingShingle ANALYSIS OF SPATIAL RELATIONSHIPS OF CONFIRMED COVID-19 CASES AND DEATHS FROM MARCH TO AUGUST 2020 IN THE STATE OF PERNAMBUCO, BRAZIL
Candeia, Bruna Araujo
COVID-19
Pandemia
Cartografia Temática
COVID-19
Pandemic
Thematic Cartography
title_short ANALYSIS OF SPATIAL RELATIONSHIPS OF CONFIRMED COVID-19 CASES AND DEATHS FROM MARCH TO AUGUST 2020 IN THE STATE OF PERNAMBUCO, BRAZIL
title_full ANALYSIS OF SPATIAL RELATIONSHIPS OF CONFIRMED COVID-19 CASES AND DEATHS FROM MARCH TO AUGUST 2020 IN THE STATE OF PERNAMBUCO, BRAZIL
title_fullStr ANALYSIS OF SPATIAL RELATIONSHIPS OF CONFIRMED COVID-19 CASES AND DEATHS FROM MARCH TO AUGUST 2020 IN THE STATE OF PERNAMBUCO, BRAZIL
title_full_unstemmed ANALYSIS OF SPATIAL RELATIONSHIPS OF CONFIRMED COVID-19 CASES AND DEATHS FROM MARCH TO AUGUST 2020 IN THE STATE OF PERNAMBUCO, BRAZIL
title_sort ANALYSIS OF SPATIAL RELATIONSHIPS OF CONFIRMED COVID-19 CASES AND DEATHS FROM MARCH TO AUGUST 2020 IN THE STATE OF PERNAMBUCO, BRAZIL
author Candeia, Bruna Araujo
author_facet Candeia, Bruna Araujo
Candeias, Ana Lúcia Bezerra
Tavares Junior, João Rodrigues
author_role author
author2 Candeias, Ana Lúcia Bezerra
Tavares Junior, João Rodrigues
author2_role author
author
dc.contributor.author.fl_str_mv Candeia, Bruna Araujo
Candeias, Ana Lúcia Bezerra
Tavares Junior, João Rodrigues
dc.subject.por.fl_str_mv COVID-19
Pandemia
Cartografia Temática
COVID-19
Pandemic
Thematic Cartography
topic COVID-19
Pandemia
Cartografia Temática
COVID-19
Pandemic
Thematic Cartography
description By modeling COVID-19 data, and drawing up thematic maps, it was possible to analyze spatiotemporal behavior patterns of the new coronavirus in Pernambuco. It is possible to identify: 01- The highest numbers of cases and deaths are related to the cities with the highest GDP per capita; 02- The spread of the disease follows the directions of the main network of federal highways; 03- The thematic maps of municipalities added to the numbers of cases and deaths have repercussions on the articulated and intense propagation of patterns in blocks of municipalities connected by highways in the timeline, as the cases of Serra Talhada, São José de Belmonte, Mirandiba, Salgueiro and Parnamirim; 04- Other municipalities such as Santa Maria da Boa Vista and Orocó are isolated with fewer cases, as well as Belém do São Francisco and Carnaubeira da Penha, small isolated blocks with fewer cases and deaths, similarly to Ibimirim and Custódia; Águas Belas and Serra Talhada are outside the propagation block, the “island-municipalities”, thus revealing a behavior of propagation of the disease, of isolated or articulated municipalities around and along federal road axes. BR-104 and 232 assume regional influence and state and local roads may have contributed to greater "capillarity" of the spread of COVID-19.
publishDate 2023
dc.date.none.fl_str_mv 2023-02-22
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Avaliado pelos pares
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://seer.ufu.br/index.php/caminhosdegeografia/article/view/62229
10.14393/RCG249162229
url https://seer.ufu.br/index.php/caminhosdegeografia/article/view/62229
identifier_str_mv 10.14393/RCG249162229
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://seer.ufu.br/index.php/caminhosdegeografia/article/view/62229/35618
dc.rights.driver.fl_str_mv Copyright (c) 2023 Bruna Araujo Candeia, Ana Lúcia Bezerra Candeias, João Rodrigues Tavares Junior
http://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 Bruna Araujo Candeia, Ana Lúcia Bezerra Candeias, João Rodrigues Tavares Junior
http://creativecommons.org/licenses/by-nc-nd/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv EDUFU - Editora da Universidade Federal de Uberlândia
publisher.none.fl_str_mv EDUFU - Editora da Universidade Federal de Uberlândia
dc.source.none.fl_str_mv Caminhos de Geografia; Vol. 24 No. 91 (2023): Fevereiro; 208-223
Caminhos de Geografia; Vol. 24 Núm. 91 (2023): Fevereiro; 208-223
Caminhos de Geografia; v. 24 n. 91 (2023): Fevereiro; 208-223
1678-6343
reponame:Caminhos de Geografia
instname:Universidade Federal de Uberlândia (UFU)
instacron:UFU
instname_str Universidade Federal de Uberlândia (UFU)
instacron_str UFU
institution UFU
reponame_str Caminhos de Geografia
collection Caminhos de Geografia
repository.name.fl_str_mv Caminhos de Geografia - Universidade Federal de Uberlândia (UFU)
repository.mail.fl_str_mv flaviasantosgeo@gmail.com
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