Analysis of mobility network metrics in the spread of COVID-19 in the Metropolitan Region of Vale do Paraíba and Litoral Norte (RMVPLN)
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/247352 |
Resumo: | In 2019, a pandemic of the so-called new coronavirus (SARS-COV-II) began, which causes the disease COVID-19. In a short time after the first case appeared, hundreds of countries began to register new cases every day. Mapping and analyzing the flow of people, regardless of the mode of transport, can help us to understand and prevent several phenomena that can affect our society in different ways. Graphs are complex networks made up of points and edges. The (geo)graphs are graphs with known spatial location and, in the case of our study, the edges represent the flow between them. The (geo)graphs proved to be a promising tool for such analyses. In the study region, municipalities that first registered their COVID-19 cases are also municipalities that have the highest mobility indices analyzed: degree, betweenness and weight of edges. |
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Analysis of mobility network metrics in the spread of COVID-19 in the Metropolitan Region of Vale do Paraíba and Litoral Norte (RMVPLN)In 2019, a pandemic of the so-called new coronavirus (SARS-COV-II) began, which causes the disease COVID-19. In a short time after the first case appeared, hundreds of countries began to register new cases every day. Mapping and analyzing the flow of people, regardless of the mode of transport, can help us to understand and prevent several phenomena that can affect our society in different ways. Graphs are complex networks made up of points and edges. The (geo)graphs are graphs with known spatial location and, in the case of our study, the edges represent the flow between them. The (geo)graphs proved to be a promising tool for such analyses. In the study region, municipalities that first registered their COVID-19 cases are also municipalities that have the highest mobility indices analyzed: degree, betweenness and weight of edges.Institute of Science and Technology Paulista State University (UNESP), SPNational Center for Monitoring and Natural Disaster Alerts (CEMADEN), SPNational Institute of Spatial Researches (INPE), SPInstitute of Science and Technology Paulista State University (UNESP), SPUniversidade Estadual Paulista (UNESP)National Center for Monitoring and Natural Disaster Alerts (CEMADEN)National Institute of Spatial Researches (INPE)Cabral, Leticia da S. [UNESP]Santos, Leonardo Bacelar L.Monteiro, Antonio Miguel Vieira2023-07-29T13:13:44Z2023-07-29T13:13:44Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject360-365Proceedings of the Brazilian Symposium on GeoInformatics, p. 360-365.2179-4847http://hdl.handle.net/11449/2473522-s2.0-85159081780Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the Brazilian Symposium on GeoInformaticsinfo:eu-repo/semantics/openAccess2023-07-29T13:13:45Zoai:repositorio.unesp.br:11449/247352Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:27:34.984463Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Analysis of mobility network metrics in the spread of COVID-19 in the Metropolitan Region of Vale do Paraíba and Litoral Norte (RMVPLN) |
title |
Analysis of mobility network metrics in the spread of COVID-19 in the Metropolitan Region of Vale do Paraíba and Litoral Norte (RMVPLN) |
spellingShingle |
Analysis of mobility network metrics in the spread of COVID-19 in the Metropolitan Region of Vale do Paraíba and Litoral Norte (RMVPLN) Cabral, Leticia da S. [UNESP] |
title_short |
Analysis of mobility network metrics in the spread of COVID-19 in the Metropolitan Region of Vale do Paraíba and Litoral Norte (RMVPLN) |
title_full |
Analysis of mobility network metrics in the spread of COVID-19 in the Metropolitan Region of Vale do Paraíba and Litoral Norte (RMVPLN) |
title_fullStr |
Analysis of mobility network metrics in the spread of COVID-19 in the Metropolitan Region of Vale do Paraíba and Litoral Norte (RMVPLN) |
title_full_unstemmed |
Analysis of mobility network metrics in the spread of COVID-19 in the Metropolitan Region of Vale do Paraíba and Litoral Norte (RMVPLN) |
title_sort |
Analysis of mobility network metrics in the spread of COVID-19 in the Metropolitan Region of Vale do Paraíba and Litoral Norte (RMVPLN) |
author |
Cabral, Leticia da S. [UNESP] |
author_facet |
Cabral, Leticia da S. [UNESP] Santos, Leonardo Bacelar L. Monteiro, Antonio Miguel Vieira |
author_role |
author |
author2 |
Santos, Leonardo Bacelar L. Monteiro, Antonio Miguel Vieira |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) National Center for Monitoring and Natural Disaster Alerts (CEMADEN) National Institute of Spatial Researches (INPE) |
dc.contributor.author.fl_str_mv |
Cabral, Leticia da S. [UNESP] Santos, Leonardo Bacelar L. Monteiro, Antonio Miguel Vieira |
description |
In 2019, a pandemic of the so-called new coronavirus (SARS-COV-II) began, which causes the disease COVID-19. In a short time after the first case appeared, hundreds of countries began to register new cases every day. Mapping and analyzing the flow of people, regardless of the mode of transport, can help us to understand and prevent several phenomena that can affect our society in different ways. Graphs are complex networks made up of points and edges. The (geo)graphs are graphs with known spatial location and, in the case of our study, the edges represent the flow between them. The (geo)graphs proved to be a promising tool for such analyses. In the study region, municipalities that first registered their COVID-19 cases are also municipalities that have the highest mobility indices analyzed: degree, betweenness and weight of edges. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 2023-07-29T13:13:44Z 2023-07-29T13:13:44Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Proceedings of the Brazilian Symposium on GeoInformatics, p. 360-365. 2179-4847 http://hdl.handle.net/11449/247352 2-s2.0-85159081780 |
identifier_str_mv |
Proceedings of the Brazilian Symposium on GeoInformatics, p. 360-365. 2179-4847 2-s2.0-85159081780 |
url |
http://hdl.handle.net/11449/247352 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceedings of the Brazilian Symposium on GeoInformatics |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
360-365 |
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 |
|
_version_ |
1808128655411380224 |