The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Cadernos de Saúde Pública |
Texto Completo: | https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/7432 |
Resumo: | The inter-cities mobility network is of great importance in understanding outbreaks, especially in Brazil, a continental-dimension country. We adopt the data from the Brazilian Ministry of Health and the terrestrial flow of people between cities from the Brazilian Institute of Geography and Statistics database in two scales: cities from Brazil, without the North region, and from the São Paulo State. Grounded on the complex networks approach, and considering that the mobility network serves as a proxy for the SARS-CoV-2 spreading, the nodes and edges represent cities and flows, respectively. Network centrality measures such as strength and degree are ranked and compared to the list of cities, ordered according to the day that they confirmed the first case of COVID-19. The strength measure captures the cities with a higher vulnerability of receiving new cases. Besides, it follows the interiorization process of SARS-CoV-2 in the São Paulo State when the network flows are above specific thresholds. Some countryside cities such as Feira de Santana (Bahia State), Ribeirão Preto (São Paulo State), and Caruaru (Pernambuco State) have strength comparable to states’ capitals. Our analysis offers additional tools for understanding and decision support to inter-cities mobility interventions regarding the SARS-CoV-2 and other epidemics. |
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The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in BrazilCOVID-19Public Health SurveillanceEpidemicsThe inter-cities mobility network is of great importance in understanding outbreaks, especially in Brazil, a continental-dimension country. We adopt the data from the Brazilian Ministry of Health and the terrestrial flow of people between cities from the Brazilian Institute of Geography and Statistics database in two scales: cities from Brazil, without the North region, and from the São Paulo State. Grounded on the complex networks approach, and considering that the mobility network serves as a proxy for the SARS-CoV-2 spreading, the nodes and edges represent cities and flows, respectively. Network centrality measures such as strength and degree are ranked and compared to the list of cities, ordered according to the day that they confirmed the first case of COVID-19. The strength measure captures the cities with a higher vulnerability of receiving new cases. Besides, it follows the interiorization process of SARS-CoV-2 in the São Paulo State when the network flows are above specific thresholds. Some countryside cities such as Feira de Santana (Bahia State), Ribeirão Preto (São Paulo State), and Caruaru (Pernambuco State) have strength comparable to states’ capitals. Our analysis offers additional tools for understanding and decision support to inter-cities mobility interventions regarding the SARS-CoV-2 and other epidemics.La red de movilidad entre ciudades es de vital importancia para la comprensión de los brotes, especialmente en Brasil, un país con dimensiones continentales. Conseguimos los datos del Ministerio de Salud Brasileño y el flujo terrestre de gente entre ciudades a partir de la base de datos del Instituto Brasileño de Geografía y Estadística en dos escalas: ciudades de Brasil, sin la región Norte, y Estado de São Paulo. Basado en un planteamiento de redes complejas, y considerando que la movilidad de la red sirve como un proxy para la propagación del SARS-CoV-2, los nodos y extremos representan ciudades y flujos, respectivamente. Las medidas de centralidad de la red como la fuerza y el grado se clasificaron y compararon con la lista de ciudades, ordenadas según el día en que confirmaron el primer caso de COVID-19. La medida de fuerza captura las ciudades con la mayor vulnerabilidad en recibir nuevos casos. Asimismo, le sigue la interiorización del proceso de SARS-CoV-2 en el Estado de São Paulo, cuando los flujos de la red están por encima de determinados umbrales. Algunas ciudades en áreas rurales como Feira de Santana (Estado de Bahía), Ribeirão Preto (Estado de São Paulo), y Caruaru (Estado de Pernambuco) poseen una fuerza comparable a las capitales de los estados. Nuestro análisis ofrece herramientas adicionales para la compresión y apoyo en la toma de decisiones, respecto a las intervenciones de movilidad entre ciudades, en relación con el SARS-CoV-2 y otras epidemias.A rede de mobilidade intermunicipal é de suma importância para a compreensão de surtos, sobretudo no Brasil, um país com dimensões continentais. Os autores adotaram os dados do Ministério da Saúde e informações sobre o fluxo de pessoas entre cidades, da base de dados do Instituto Brasileiro de Geografia e Estatística, em duas escalas: cidades brasileiras, sem a região Norte, e do Estado de São Paulo. Com base na abordagem de redes complexas, e considerando que a rede de mobilidade serve como proxy para a propagação do SARS-CoV-2, os nós e arestas representam cidades e fluxos, respectivamente. As medidas de centralidade de rede, como força e grau, são ranqueadas e comparadas à lista das cidades, de acordo com o dia da confirmação do primeiro caso de COVID-19. A medida de força capta as cidades com maior vulnerabilidade à pandemia, além de acompanhar o processo de interiorização do SARS-CoV-2 no Estado de São Paulo quando os fluxos de rede estão acima de limiares específicos. Algumas cidades do interior, como Feira de Santana (Bahia), Ribeirão Preto (São Paulo) e Caruaru (Pernambuco) mostram forças comparáveis às capitais estaduais. Nossa análise oferece ferramentas adicionais para a compreensão e o apoio para a tomada de decisões sobre intervenções na mobilidade intermunicipal em relação ao SARS-CoV-2 e outras epidemias.Reports in Public HealthCadernos de Saúde Pública2020-10-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlapplication/pdfhttps://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/7432Reports in Public Health; Vol. 36 No. 9 (2020): SeptemberCadernos de Saúde Pública; v. 36 n. 9 (2020): Setembro1678-44640102-311Xreponame:Cadernos de Saúde Públicainstname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZenghttps://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/7432/16428https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/7432/16429Vander Luis de Souza FreitasThais Cláudia Roma de Oliveira KonstantynerJeferson Feitosa MendesCátia Souza do Nascimento SepetauskasLeonardo Bacelar Lima Santosinfo:eu-repo/semantics/openAccess2024-03-06T15:29:57Zoai:ojs.teste-cadernos.ensp.fiocruz.br:article/7432Revistahttps://cadernos.ensp.fiocruz.br/ojs/index.php/csphttps://cadernos.ensp.fiocruz.br/ojs/index.php/csp/oaicadernos@ensp.fiocruz.br||cadernos@ensp.fiocruz.br1678-44640102-311Xopendoar:2024-03-06T13:08:32.437592Cadernos de Saúde Pública - Fundação Oswaldo Cruz (FIOCRUZ)true |
dc.title.none.fl_str_mv |
The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil |
title |
The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil |
spellingShingle |
The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil Vander Luis de Souza Freitas COVID-19 Public Health Surveillance Epidemics |
title_short |
The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil |
title_full |
The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil |
title_fullStr |
The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil |
title_full_unstemmed |
The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil |
title_sort |
The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil |
author |
Vander Luis de Souza Freitas |
author_facet |
Vander Luis de Souza Freitas Thais Cláudia Roma de Oliveira Konstantyner Jeferson Feitosa Mendes Cátia Souza do Nascimento Sepetauskas Leonardo Bacelar Lima Santos |
author_role |
author |
author2 |
Thais Cláudia Roma de Oliveira Konstantyner Jeferson Feitosa Mendes Cátia Souza do Nascimento Sepetauskas Leonardo Bacelar Lima Santos |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Vander Luis de Souza Freitas Thais Cláudia Roma de Oliveira Konstantyner Jeferson Feitosa Mendes Cátia Souza do Nascimento Sepetauskas Leonardo Bacelar Lima Santos |
dc.subject.por.fl_str_mv |
COVID-19 Public Health Surveillance Epidemics |
topic |
COVID-19 Public Health Surveillance Epidemics |
description |
The inter-cities mobility network is of great importance in understanding outbreaks, especially in Brazil, a continental-dimension country. We adopt the data from the Brazilian Ministry of Health and the terrestrial flow of people between cities from the Brazilian Institute of Geography and Statistics database in two scales: cities from Brazil, without the North region, and from the São Paulo State. Grounded on the complex networks approach, and considering that the mobility network serves as a proxy for the SARS-CoV-2 spreading, the nodes and edges represent cities and flows, respectively. Network centrality measures such as strength and degree are ranked and compared to the list of cities, ordered according to the day that they confirmed the first case of COVID-19. The strength measure captures the cities with a higher vulnerability of receiving new cases. Besides, it follows the interiorization process of SARS-CoV-2 in the São Paulo State when the network flows are above specific thresholds. Some countryside cities such as Feira de Santana (Bahia State), Ribeirão Preto (São Paulo State), and Caruaru (Pernambuco State) have strength comparable to states’ capitals. Our analysis offers additional tools for understanding and decision support to inter-cities mobility interventions regarding the SARS-CoV-2 and other epidemics. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-10-05 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/7432 |
url |
https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/7432 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/7432/16428 https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/7432/16429 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html application/pdf |
dc.publisher.none.fl_str_mv |
Reports in Public Health Cadernos de Saúde Pública |
publisher.none.fl_str_mv |
Reports in Public Health Cadernos de Saúde Pública |
dc.source.none.fl_str_mv |
Reports in Public Health; Vol. 36 No. 9 (2020): September Cadernos de Saúde Pública; v. 36 n. 9 (2020): Setembro 1678-4464 0102-311X reponame:Cadernos de Saúde Pública instname:Fundação Oswaldo Cruz (FIOCRUZ) instacron:FIOCRUZ |
instname_str |
Fundação Oswaldo Cruz (FIOCRUZ) |
instacron_str |
FIOCRUZ |
institution |
FIOCRUZ |
reponame_str |
Cadernos de Saúde Pública |
collection |
Cadernos de Saúde Pública |
repository.name.fl_str_mv |
Cadernos de Saúde Pública - Fundação Oswaldo Cruz (FIOCRUZ) |
repository.mail.fl_str_mv |
cadernos@ensp.fiocruz.br||cadernos@ensp.fiocruz.br |
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1798943392330153984 |