A mathematical model of the transmission dynamics of tuberculosis with exogenous reinfection in the infection-free state

Descripción del Articulo

In the present work, a perturbation of the model presented by Feng, Castillo-Chávez and Capurro (2000) will be carried out, where the dynamics of tuberculosis transmission will be described, where recovery from the disease will be incorporated. The model will include four epidemiological populations...

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Detalles Bibliográficos
Autores: Pino Romero, Neisser, Pérez-Núñez, Jhelly-Reynaluz, Vásquez-Serpa, Luis-Javier, Haya-Enríquez, Erwin-Fernando, Bravo-Orellana, Miriam
Formato: artículo
Fecha de Publicación:2022
Institución:Universidad Tecnológica del Perú
Repositorio:UTP-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.utp.edu.pe:20.500.12867/6222
Enlace del recurso:https://hdl.handle.net/20.500.12867/6222
Nivel de acceso:acceso abierto
Materia:Mathematical model
Tuberculosis
Computational simulation
https://purl.org/pe-repo/ocde/ford#2.00.00
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dc.title.es_PE.fl_str_mv A mathematical model of the transmission dynamics of tuberculosis with exogenous reinfection in the infection-free state
title A mathematical model of the transmission dynamics of tuberculosis with exogenous reinfection in the infection-free state
spellingShingle A mathematical model of the transmission dynamics of tuberculosis with exogenous reinfection in the infection-free state
Pino Romero, Neisser
Mathematical model
Tuberculosis
Computational simulation
https://purl.org/pe-repo/ocde/ford#2.00.00
title_short A mathematical model of the transmission dynamics of tuberculosis with exogenous reinfection in the infection-free state
title_full A mathematical model of the transmission dynamics of tuberculosis with exogenous reinfection in the infection-free state
title_fullStr A mathematical model of the transmission dynamics of tuberculosis with exogenous reinfection in the infection-free state
title_full_unstemmed A mathematical model of the transmission dynamics of tuberculosis with exogenous reinfection in the infection-free state
title_sort A mathematical model of the transmission dynamics of tuberculosis with exogenous reinfection in the infection-free state
author Pino Romero, Neisser
author_facet Pino Romero, Neisser
Pérez-Núñez, Jhelly-Reynaluz
Vásquez-Serpa, Luis-Javier
Haya-Enríquez, Erwin-Fernando
Bravo-Orellana, Miriam
author_role author
author2 Pérez-Núñez, Jhelly-Reynaluz
Vásquez-Serpa, Luis-Javier
Haya-Enríquez, Erwin-Fernando
Bravo-Orellana, Miriam
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Pino Romero, Neisser
Pérez-Núñez, Jhelly-Reynaluz
Vásquez-Serpa, Luis-Javier
Haya-Enríquez, Erwin-Fernando
Bravo-Orellana, Miriam
dc.subject.es_PE.fl_str_mv Mathematical model
Tuberculosis
Computational simulation
topic Mathematical model
Tuberculosis
Computational simulation
https://purl.org/pe-repo/ocde/ford#2.00.00
dc.subject.ocde.es_PE.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.00.00
description In the present work, a perturbation of the model presented by Feng, Castillo-Chávez and Capurro (2000) will be carried out, where the dynamics of tuberculosis transmission will be described, where recovery from the disease will be incorporated. The model will include four epidemiological populations: Susceptible (S), Exposed (E), Infected (I) and Infected with treatment (T). This will allow to know how the interaction that exists with the infected can cause the permanence of the individuals with the disease. For which, its qualitative behavior will be analyzed as its evolution in time of the epidemiological populations for the model by the ordinary differential equations (ODE) and its perturbation to the dalay differential equations (DDE). In this way, it will allow us to know how the parameters influence the spread of the disease at the point free of infection and with a computational extension to evaluate an endemic situation.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-11-14T19:23:17Z
dc.date.available.none.fl_str_mv 2022-11-14T19:23:17Z
dc.date.issued.fl_str_mv 2022
dc.type.es_PE.fl_str_mv info:eu-repo/semantics/article
dc.type.version.es_PE.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.issn.none.fl_str_mv 2277-212X
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12867/6222
dc.identifier.journal.es_PE.fl_str_mv International Journal of Applied Engineering & Technology
identifier_str_mv 2277-212X
International Journal of Applied Engineering & Technology
url https://hdl.handle.net/20.500.12867/6222
dc.language.iso.es_PE.fl_str_mv eng
language eng
dc.relation.ispartofseries.none.fl_str_mv International Journal of Applied Engineering & Technology;vol. 4, n° 2, pp. 38-45
dc.rights.es_PE.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.uri.es_PE.fl_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
dc.format.es_PE.fl_str_mv application/pdf
dc.publisher.es_PE.fl_str_mv The Roman Science Publications and Distributions
dc.publisher.country.es_PE.fl_str_mv GB
dc.source.es_PE.fl_str_mv Repositorio Institucional - UTP
Universidad Tecnológica del Perú
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instname_str Universidad Tecnológica del Perú
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spelling Pino Romero, NeisserPérez-Núñez, Jhelly-ReynaluzVásquez-Serpa, Luis-JavierHaya-Enríquez, Erwin-FernandoBravo-Orellana, Miriam2022-11-14T19:23:17Z2022-11-14T19:23:17Z20222277-212Xhttps://hdl.handle.net/20.500.12867/6222International Journal of Applied Engineering & TechnologyIn the present work, a perturbation of the model presented by Feng, Castillo-Chávez and Capurro (2000) will be carried out, where the dynamics of tuberculosis transmission will be described, where recovery from the disease will be incorporated. The model will include four epidemiological populations: Susceptible (S), Exposed (E), Infected (I) and Infected with treatment (T). This will allow to know how the interaction that exists with the infected can cause the permanence of the individuals with the disease. For which, its qualitative behavior will be analyzed as its evolution in time of the epidemiological populations for the model by the ordinary differential equations (ODE) and its perturbation to the dalay differential equations (DDE). 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