Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/35166
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dc.contributor.authorMachado, Pedropt_PT
dc.contributor.authorPinheiro, Sofia J.pt_PT
dc.contributor.authorAfreixo, Verapt_PT
dc.contributor.authorSilva, Cristiana J.pt_PT
dc.contributor.authorLeitão, Ruipt_PT
dc.date.accessioned2022-11-10T11:50:31Z-
dc.date.available2022-11-10T11:50:31Z-
dc.date.issued2022-10-
dc.identifier.issn1300-686Xpt_PT
dc.identifier.urihttp://hdl.handle.net/10773/35166-
dc.description.abstractThe COVID-19 pandemic remains a global problem that affects the health of millions of people and the world economy. Identifying how the movement of people between regions of the world, countries, and municipalities and how the close contact between individuals of different age groups promotes the spread of infectious diseases is a pressing concern for society, during epidemic outbreaks and pandemics, such as COVID-19. Networks and Graph Theory provide adequate and powerful tools to study the spread of communicable diseases. In this work, we use Graph Theory to analyze COVID-19 transmission dynamics between municipalities of Aveiro district, in Portugal, and between different age groups, considering data from 2020 and 2021, in order to better understand the spread of this disease, as well as preparing actions for possible future pandemics. We used a digraph structure that models the transmission of SARS-CoV-2 virus between Aveiro’s municipalities and between age groups. To understand how a node fits over the contact digraphs, we studied centrality measures, namely eigencentrality, closeness, degree, and betweenness. Transmission ratios were also considered to determine whether there were certain age groups or municipals that were more responsible for the virus’s spread. According to the results of this research, transmissions mostly occur within the same social groupings, that is, within the same municipalities and age groups. However, the study of centrality measures, eliminating loops, reveals that municipalities such as Aveiro, Estarreja and Ovar are relevant nodes in the transmission network of municipalities as well as the age group of 40–49 in the transmission network of age groups. Furthermore, we conclude that vaccination is effective in reducing the virus.pt_PT
dc.language.isoengpt_PT
dc.publisherMDPIpt_PT
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04106%2F2020/PTpt_PT
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F04106%2F2020/PTpt_PT
dc.relationinfo:eu-repo/grantAgreement/FCT/CEEC IND 2018/CEECIND%2F00564%2F2018%2FCP1559%2FCT0001/PTpt_PT
dc.rightsopenAccesspt_PT
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectGraph theorypt_PT
dc.subjectCentrality measurespt_PT
dc.subjectCOVID-19pt_PT
dc.subjectBetweenness centralitypt_PT
dc.subjectCloseness centralitypt_PT
dc.subjectDegree centralitypt_PT
dc.subjectEigencentralitypt_PT
dc.subjectAge groupspt_PT
dc.subjectMunicipalspt_PT
dc.titleGraph Theory approach to COVID-19 transmission by municipalities and age groupspt_PT
dc.typearticlept_PT
dc.description.versionpublishedpt_PT
dc.peerreviewedyespt_PT
degois.publication.issue5pt_PT
degois.publication.titleMathematical and Computational Applicationspt_PT
degois.publication.volume27pt_PT
dc.relation.publisherversionhttps://www.mdpi.com/2297-8747/27/5/86/htmpt_PT
dc.identifier.doi10.3390/mca27050086pt_PT
dc.identifier.essn2297-8747pt_PT
dc.identifier.articlenumber86pt_PT
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DMat - Artigos
OGTCG - Artigos

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