Influence of Contact Network Topology on the Spread of Tuberculosis
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1007/978-3-030-36636-0_6 http://hdl.handle.net/11449/198310 |
Resumo: | This paper presents the influence of the complex networks topology on the spread of Tuberculosis with the use of the Individual-Based Model (IBM). Five complex network models were used with the IBM, namely, random, small world, scale-free, modular and hierarchical models. For every model, we applied the usual topological properties available in literature for the characterization of complex networks. Afterwards, we verified the topological effect of the contact networks in the evolution of tuberculosis and it was observed that different contact networks result in different epidemic thresholds for the spread of tuberculosis. More specifically, we noted that networks that have greater heterogeneity of connections need a lower, however when the value of the infection rate is large, the number of individuals infected are similar. It is believed that this observation may contribute to actions to reduce and eradicate the disease. |
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Influence of Contact Network Topology on the Spread of TuberculosisComplex networksComplex systemsIndividual-Based ModelTopological effectTuberculosisThis paper presents the influence of the complex networks topology on the spread of Tuberculosis with the use of the Individual-Based Model (IBM). Five complex network models were used with the IBM, namely, random, small world, scale-free, modular and hierarchical models. For every model, we applied the usual topological properties available in literature for the characterization of complex networks. Afterwards, we verified the topological effect of the contact networks in the evolution of tuberculosis and it was observed that different contact networks result in different epidemic thresholds for the spread of tuberculosis. More specifically, we noted that networks that have greater heterogeneity of connections need a lower, however when the value of the infection rate is large, the number of individuals infected are similar. It is believed that this observation may contribute to actions to reduce and eradicate the disease.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Institute of Biosciences Postgraduate Program in Biometrics São Paulo State University (UNESP)Department of Electrical Engineering Federal University of São João del-Rei (UFSJ)Institute of Biosciences Department of Biostatistics São Paulo State University (UNESP)Institute of Biosciences Postgraduate Program in Biometrics São Paulo State University (UNESP)Institute of Biosciences Department of Biostatistics São Paulo State University (UNESP)CAPES: 1770124FAPESP: 2018/25358-9Universidade Estadual Paulista (Unesp)Universidade Federal de Sergipe (UFS)Pinto, Eduardo R. [UNESP]Nepomuceno, Erivelton G.Campanharo, Andriana S. L. O. [UNESP]2020-12-12T01:09:20Z2020-12-12T01:09:20Z2019-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject81-88http://dx.doi.org/10.1007/978-3-030-36636-0_6Communications in Computer and Information Science, v. 1068 CCIS, p. 81-88.1865-09371865-0929http://hdl.handle.net/11449/19831010.1007/978-3-030-36636-0_62-s2.0-85076905088Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCommunications in Computer and Information Scienceinfo:eu-repo/semantics/openAccess2021-10-23T08:39:01Zoai:repositorio.unesp.br:11449/198310Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:23:33.467668Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Influence of Contact Network Topology on the Spread of Tuberculosis |
title |
Influence of Contact Network Topology on the Spread of Tuberculosis |
spellingShingle |
Influence of Contact Network Topology on the Spread of Tuberculosis Pinto, Eduardo R. [UNESP] Complex networks Complex systems Individual-Based Model Topological effect Tuberculosis |
title_short |
Influence of Contact Network Topology on the Spread of Tuberculosis |
title_full |
Influence of Contact Network Topology on the Spread of Tuberculosis |
title_fullStr |
Influence of Contact Network Topology on the Spread of Tuberculosis |
title_full_unstemmed |
Influence of Contact Network Topology on the Spread of Tuberculosis |
title_sort |
Influence of Contact Network Topology on the Spread of Tuberculosis |
author |
Pinto, Eduardo R. [UNESP] |
author_facet |
Pinto, Eduardo R. [UNESP] Nepomuceno, Erivelton G. Campanharo, Andriana S. L. O. [UNESP] |
author_role |
author |
author2 |
Nepomuceno, Erivelton G. Campanharo, Andriana S. L. O. [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Universidade Federal de Sergipe (UFS) |
dc.contributor.author.fl_str_mv |
Pinto, Eduardo R. [UNESP] Nepomuceno, Erivelton G. Campanharo, Andriana S. L. O. [UNESP] |
dc.subject.por.fl_str_mv |
Complex networks Complex systems Individual-Based Model Topological effect Tuberculosis |
topic |
Complex networks Complex systems Individual-Based Model Topological effect Tuberculosis |
description |
This paper presents the influence of the complex networks topology on the spread of Tuberculosis with the use of the Individual-Based Model (IBM). Five complex network models were used with the IBM, namely, random, small world, scale-free, modular and hierarchical models. For every model, we applied the usual topological properties available in literature for the characterization of complex networks. Afterwards, we verified the topological effect of the contact networks in the evolution of tuberculosis and it was observed that different contact networks result in different epidemic thresholds for the spread of tuberculosis. More specifically, we noted that networks that have greater heterogeneity of connections need a lower, however when the value of the infection rate is large, the number of individuals infected are similar. It is believed that this observation may contribute to actions to reduce and eradicate the disease. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-01 2020-12-12T01:09:20Z 2020-12-12T01:09:20Z |
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 |
http://dx.doi.org/10.1007/978-3-030-36636-0_6 Communications in Computer and Information Science, v. 1068 CCIS, p. 81-88. 1865-0937 1865-0929 http://hdl.handle.net/11449/198310 10.1007/978-3-030-36636-0_6 2-s2.0-85076905088 |
url |
http://dx.doi.org/10.1007/978-3-030-36636-0_6 http://hdl.handle.net/11449/198310 |
identifier_str_mv |
Communications in Computer and Information Science, v. 1068 CCIS, p. 81-88. 1865-0937 1865-0929 10.1007/978-3-030-36636-0_6 2-s2.0-85076905088 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Communications in Computer and Information Science |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
81-88 |
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 |
|
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1808129515331780608 |