Optimization model for planning the logistical response to COVID-19 vaccination

Descripción del Articulo

The health crisis that our country is going through is very difficult to manage and vaccination is of utmost importance to counteract it; however, the logistical process of purchasing and distributing vaccines is very complex. Objective: Therefore, the present research article aims to design a predi...

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Detalles Bibliográficos
Autores: Cobos Valdéz, Hugo Fabrizzio, Arellano Alcaide, Migue Angel
Formato: tesis de grado
Fecha de Publicación:2024
Institución:Universidad de Lima
Repositorio:ULIMA-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.ulima.edu.pe:20.500.12724/21272
Enlace del recurso:https://hdl.handle.net/20.500.12724/21272
Nivel de acceso:acceso abierto
Materia:Vacunas
Hospitales móviles
COVID-19
Sistemas de información geográfica
https://purl.org/pe-repo/ocde/ford#2.11.04
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dc.title.en_EN.fl_str_mv Optimization model for planning the logistical response to COVID-19 vaccination
title Optimization model for planning the logistical response to COVID-19 vaccination
spellingShingle Optimization model for planning the logistical response to COVID-19 vaccination
Cobos Valdéz, Hugo Fabrizzio
Vacunas
Hospitales móviles
COVID-19
Sistemas de información geográfica
https://purl.org/pe-repo/ocde/ford#2.11.04
title_short Optimization model for planning the logistical response to COVID-19 vaccination
title_full Optimization model for planning the logistical response to COVID-19 vaccination
title_fullStr Optimization model for planning the logistical response to COVID-19 vaccination
title_full_unstemmed Optimization model for planning the logistical response to COVID-19 vaccination
title_sort Optimization model for planning the logistical response to COVID-19 vaccination
author Cobos Valdéz, Hugo Fabrizzio
author_facet Cobos Valdéz, Hugo Fabrizzio
Arellano Alcaide, Migue Angel
author_role author
author2 Arellano Alcaide, Migue Angel
author2_role author
dc.contributor.advisor.fl_str_mv Taquía Gutiérrez, José Antonio
dc.contributor.author.fl_str_mv Cobos Valdéz, Hugo Fabrizzio
Arellano Alcaide, Migue Angel
dc.subject.es_PE.fl_str_mv Vacunas
Hospitales móviles
COVID-19
Sistemas de información geográfica
topic Vacunas
Hospitales móviles
COVID-19
Sistemas de información geográfica
https://purl.org/pe-repo/ocde/ford#2.11.04
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.11.04
description The health crisis that our country is going through is very difficult to manage and vaccination is of utmost importance to counteract it; however, the logistical process of purchasing and distributing vaccines is very complex. Objective: Therefore, the present research article aims to design a predictive model that influences the logistic response planning for COVID 19 vaccination in the district of San Juan de Lurigancho. Methods: This can be achieved using geographic information systems technology and the implementation of mobile vaccination centers. Results: The results obtained showed the lack of vaccination sites in the district and how this measure generates a great benefit in the most vulnerable population of the study district. In addition, it is positive the results obtained compared to the results of other articles. Conclusions: It is confirmed that the logistic process of vaccination can be improved from the implementation of mobile vaccination centers.
publishDate 2024
dc.date.accessioned.none.fl_str_mv 2024-10-03T14:40:22Z
dc.date.available.none.fl_str_mv 2024-10-03T14:40:22Z
dc.date.issued.fl_str_mv 2024
dc.type.none.fl_str_mv info:eu-repo/semantics/bachelorThesis
dc.type.other.none.fl_str_mv Tesis
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dc.identifier.citation.es_PE.fl_str_mv Cobos Valdéz, H. F. , & Arellano Alcaide, M. A.(2024). Optimization model for planning the logistical response to COVID-19 vaccination [Tesis para optar el Título Profesional de Ingeniero Industrial, Universidad de Lima]. Repositorio Institucional de la Universidad de Lima. https://hdl.handle.net/20.500.12724/21272
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12724/21272
dc.identifier.isni.none.fl_str_mv 121541816
identifier_str_mv Cobos Valdéz, H. F. , & Arellano Alcaide, M. A.(2024). Optimization model for planning the logistical response to COVID-19 vaccination [Tesis para optar el Título Profesional de Ingeniero Industrial, Universidad de Lima]. Repositorio Institucional de la Universidad de Lima. https://hdl.handle.net/20.500.12724/21272
121541816
url https://hdl.handle.net/20.500.12724/21272
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.fl_str_mv SUNEDU
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
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eu_rights_str_mv openAccess
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dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidad de Lima
dc.publisher.country.none.fl_str_mv PE
publisher.none.fl_str_mv Universidad de Lima
dc.source.none.fl_str_mv Repositorio Institucional - Ulima
Universidad de Lima
reponame:ULIMA-Institucional
instname:Universidad de Lima
instacron:ULIMA
instname_str Universidad de Lima
instacron_str ULIMA
institution ULIMA
reponame_str ULIMA-Institucional
collection ULIMA-Institucional
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spelling Taquía Gutiérrez, José AntonioCobos Valdéz, Hugo FabrizzioArellano Alcaide, Migue Angel2024-10-03T14:40:22Z2024-10-03T14:40:22Z2024Cobos Valdéz, H. F. , & Arellano Alcaide, M. A.(2024). Optimization model for planning the logistical response to COVID-19 vaccination [Tesis para optar el Título Profesional de Ingeniero Industrial, Universidad de Lima]. Repositorio Institucional de la Universidad de Lima. https://hdl.handle.net/20.500.12724/21272https://hdl.handle.net/20.500.12724/21272121541816The health crisis that our country is going through is very difficult to manage and vaccination is of utmost importance to counteract it; however, the logistical process of purchasing and distributing vaccines is very complex. Objective: Therefore, the present research article aims to design a predictive model that influences the logistic response planning for COVID 19 vaccination in the district of San Juan de Lurigancho. Methods: This can be achieved using geographic information systems technology and the implementation of mobile vaccination centers. Results: The results obtained showed the lack of vaccination sites in the district and how this measure generates a great benefit in the most vulnerable population of the study district. In addition, it is positive the results obtained compared to the results of other articles. Conclusions: It is confirmed that the logistic process of vaccination can be improved from the implementation of mobile vaccination centers.La crisis sanitaria que atraviesa nuestro país es muy difícil de manejar y la vacunación es de suma importancia para poder contrarrestarla; sin embargo, el proceso logístico de compra y distribución de las vacunas es muy compleja. Objetivo: Por ello, el presente artículo de investigación tiene como objetivo diseñar un modelo predictivo que influya en la planificación de respuesta logística ante la vacunación contra el COVID 19 en el distrito de San Juan de Lurigancho. Métodos: Esto se puede lograr a partir del uso de la Tecnología GIS y la implementación de centros de vacunación móviles. Resultados: Los resultados obtenidos demostraban la falta de locales de vacunación en el distrito y como esta medida genera un gran beneficio en la población más vulnerable del distrito de estudio. Además, es positivo los resultados que se obtuvieron en comparación a los resultados de otros artículos. Conclusiones: Se confirma que el proceso logístico de vacunación puede mejorar a partir de la implementación de centros de vacunación móviles.application/pdfengUniversidad de LimaPEinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/4.0/Repositorio Institucional - UlimaUniversidad de Limareponame:ULIMA-Institucionalinstname:Universidad de Limainstacron:ULIMAVacunasHospitales móvilesCOVID-19Sistemas de información geográficahttps://purl.org/pe-repo/ocde/ford#2.11.04Optimization model for planning the logistical response to COVID-19 vaccinationinfo:eu-repo/semantics/bachelorThesisTesisSUNEDUTítulo ProfesionalIngeniería IndustrialUniversidad de Lima. 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Optimization model for planning the logistical response to COVID-19 vaccination
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