Risk-based resource allocation for management and pandemic response: The COVID-19 Case in Bogotá, Colombia

ilustraciones, gráficas, mapas, tablas

Autores:: Prieto Velandia, Jeisson Andres

Tipo de recurso:

Fecha de publicación:: 2022

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: eng

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repository_id_str
dc.title.eng.fl_str_mv	Risk-based resource allocation for management and pandemic response: The COVID-19 Case in Bogotá, Colombia
dc.title.translated.spa.fl_str_mv	Asignación de recursos basada en riesgo para la gestión y respuesta ante una pandemia: El Caso del COVID-19 en Bogotá, Colombia Español
title	Risk-based resource allocation for management and pandemic response: The COVID-19 Case in Bogotá, Colombia
spellingShingle	Risk-based resource allocation for management and pandemic response: The COVID-19 Case in Bogotá, Colombia 510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas Infecciones por Coronavirus Gestión de Riesgos Gestión de Recursos Coronavirus Infections Risk Management Resources Management Risk management Risk-based optimization Resource allocation Pandemic response Multi-objective optimization Complex systems COVID-19 Urban spatial analysis Gestión del riesgo Optimización basada en riesgos Asignación de recursos Respuesta a pandemias Optimización multiobjetivo Sistemas complejos COVID-19 Análisis espacial urbano
title_short	Risk-based resource allocation for management and pandemic response: The COVID-19 Case in Bogotá, Colombia
title_full	Risk-based resource allocation for management and pandemic response: The COVID-19 Case in Bogotá, Colombia
title_fullStr	Risk-based resource allocation for management and pandemic response: The COVID-19 Case in Bogotá, Colombia
title_full_unstemmed	Risk-based resource allocation for management and pandemic response: The COVID-19 Case in Bogotá, Colombia
title_sort	Risk-based resource allocation for management and pandemic response: The COVID-19 Case in Bogotá, Colombia
dc.creator.fl_str_mv	Prieto Velandia, Jeisson Andres
dc.contributor.advisor.none.fl_str_mv	Gómez Perdomo, Jonatan
dc.contributor.author.none.fl_str_mv	Prieto Velandia, Jeisson Andres
dc.contributor.researchgroup.spa.fl_str_mv	Alife: Grupo de Investigación en Vida Artificial
dc.contributor.subjectmatterexpert.none.fl_str_mv	León Guzmán, Elizabeth Malagon Oviedo, Rafael Antonio
dc.subject.ddc.spa.fl_str_mv	510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas
topic	510 - Matemáticas::519 - Probabilidades y matemáticas aplicadas Infecciones por Coronavirus Gestión de Riesgos Gestión de Recursos Coronavirus Infections Risk Management Resources Management Risk management Risk-based optimization Resource allocation Pandemic response Multi-objective optimization Complex systems COVID-19 Urban spatial analysis Gestión del riesgo Optimización basada en riesgos Asignación de recursos Respuesta a pandemias Optimización multiobjetivo Sistemas complejos COVID-19 Análisis espacial urbano
dc.subject.decs.spa.fl_str_mv	Infecciones por Coronavirus Gestión de Riesgos Gestión de Recursos
dc.subject.decs.eng.fl_str_mv	Coronavirus Infections Risk Management Resources Management
dc.subject.proposal.eng.fl_str_mv	Risk management Risk-based optimization Resource allocation Pandemic response Multi-objective optimization Complex systems COVID-19 Urban spatial analysis
dc.subject.proposal.spa.fl_str_mv	Gestión del riesgo Optimización basada en riesgos Asignación de recursos Respuesta a pandemias Optimización multiobjetivo Sistemas complejos COVID-19 Análisis espacial urbano
description	ilustraciones, gráficas, mapas, tablas
publishDate	2022
dc.date.accessioned.none.fl_str_mv	2022-03-22T13:13:36Z
dc.date.available.none.fl_str_mv	2022-03-22T13:13:36Z
dc.date.issued.none.fl_str_mv	2022-01-17
dc.type.spa.fl_str_mv	Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv	info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv	Text
dc.type.redcol.spa.fl_str_mv	http://purl.org/redcol/resource_type/TM
status_str	acceptedVersion
dc.identifier.uri.none.fl_str_mv	https://repositorio.unal.edu.co/handle/unal/81293
dc.identifier.instname.spa.fl_str_mv	Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv	https://repositorio.unal.edu.co/
url	https://repositorio.unal.edu.co/handle/unal/81293 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	eng
language	eng
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repository.name.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
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spelling	Reconocimiento 4.0 InternacionalDerechos reservados al autor, 2021http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Gómez Perdomo, Jonatan2f9d2cf2487ee9d391eb9f4ab72124edPrieto Velandia, Jeisson Andreseefaf29a018590528fe786e97d5880deAlife: Grupo de Investigación en Vida ArtificialLeón Guzmán, ElizabethMalagon Oviedo, Rafael Antonio2022-03-22T13:13:36Z2022-03-22T13:13:36Z2022-01-17https://repositorio.unal.edu.co/handle/unal/81293Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, gráficas, mapas, tablasIn any serious disaster, a gap develops between resource needs and resource availability. In a severe pandemic, this gap will be worse due to global supply chain disruptions or delays and the fact that governments and aid organizations will be overwhelmed responding to all who need assistance. Then, determining the locations of the resources (i.e., budget for antivirals and preventive vaccinations, Intensive Care Unit (ICU), ventilators, non-intensive Care Unit (non-ICU), doctors) to be used during a pandemic is a strategic decision that directly affects the success of pandemic response operations. The resource allocation could be done using a risk management perspective, where a demand point has one (or more) associated risk (i.e., geographic spread, overall poverty, medical preconditions) and the objective is to choose the amount to be invested in several interventions such that the overall risk exposed by the demand points is minimized according to budget constraints and health benefits. Due to the randomness and uncertainty of conditions, not only one but a set of risks may adversely affect the allocation of resources in the geographical space. Then, the objectives (one objective for each risk exposed) must be optimized simultaneously. However, there exists a trade-off among objectives, i.e., an improvement gained for one objective is only achieved by making concessions to another objective. This thesis aims to build a mathematically and computational grounded solution to the Multi-objective risk-based Resource Allocation problem suitable to be used for supporting decision making in the formulation of management and response policies during a pandemic. The risk management is studied in a complex network located in some space (city or town being studied). The risk in some specific place (demand point) is modeled not only by the vulnerability factor related to the severity of infection but also by the infectious disease transmission dynamics that emerged from the local interactions between people. The solution is framed in the current COVID-19 pandemic in Bogotá, the largest and most crowded city in Colombia.En cualquier desastre grave, se desarrolla una brecha entre la necesidad y la disponibilidad de recursos. En una pandemia, esta brecha se agravará debido a las interrupciones o retrasos de la cadena de suministro global y al hecho de que los gobiernos y las organizaciones de ayuda se ven abrumados para responder a todos los que necesitan asistencia. Entonces, determinar la ubicación de los recursos (por ejemplo, presupuesto para antivirales y vacunas preventivas, Unidad de Cuidados Intensivos (UCI), ventiladores, Unidad de Cuidados No Intensivos (no UCI), médicos) que se utilizarán durante una pandemia es una decisión estratégica que afecta directamente el éxito de las operaciones de respuesta ante una pandemia. La asignación de recursos se puede realizar utilizando una perspectiva de gestión de riesgos, donde un lugar de demanda tiene uno (o más) riesgos asociados (por ejemplo, propagación del virus, pobreza, precondiciones médicas) y el objetivo es escoger la cantidad que se invertirá en varias intervenciones tal que el riesgo expuesto por los puntos de demanda se minimiza de acuerdo con las limitaciones presupuestarias y los beneficios para la salud. Debido a la aleatoriedad y a la incertidumbre de las condiciones, no solo uno, sino un conjunto de riesgos pueden afectar negativamente la asignación de recursos en el espacio geográfico. Entonces, los objetivos (un objetivo por cada riesgo expuesto) deben optimizarse simultáneamente. Sin embargo, existe una compensación entre los objetivos, es decir, una mejora obtenida para un objetivo solo se logra haciendo concesiones en otro objetivo. Esta tesis tiene como proposito construir una solución con base matemática y computacional para el problema de la asignación de recursos basado en múltiples riesgos adecuada para apoyar a la toma de decisiones en la formulación de políticas de gestión y respuesta a pandemias. La gestión de riesgo es estudiada en una red compleja ubicada en algún espacio (ciudad o pueblo en estudio). El riesgo en algún lugar específico (punto de demanda) se modela no solo por factores de vulnerabilidad relacionados con la gravedad de la infección, sino también por las dinámicas de transmisión de la enfermedad que surgen por la interacción entre personas. La solución se enmarca en la actual pandemia de COVID-19 en Bogotá, la ciudad más grande y densamente poblada de Colombia. (Texto tomado de la fuente)MaestríaMagíster en Ciencias - Matemática AplicadaRisk-based OptimizationOptimización basada en riesgosx, 63 páginasapplication/pdfengUniversidad Nacional de ColombiaBogotá - Ciencias - Maestría en Ciencias - Matemática AplicadaDepartamento de MatemáticasFacultad de CienciasBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá510 - Matemáticas::519 - Probabilidades y matemáticas aplicadasInfecciones por CoronavirusGestión de RiesgosGestión de RecursosCoronavirus InfectionsRisk ManagementResources ManagementRisk managementRisk-based optimizationResource allocationPandemic responseMulti-objective optimizationComplex systemsCOVID-19Urban spatial analysisGestión del riesgoOptimización basada en riesgosAsignación de recursosRespuesta a pandemiasOptimización multiobjetivoSistemas complejosCOVID-19Análisis espacial urbanoRisk-based resource allocation for management and pandemic response: The COVID-19 Case in Bogotá, ColombiaAsignación de recursos basada en riesgo para la gestión y respuesta ante una pandemia: El Caso del COVID-19 en Bogotá, Colombia EspañolTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMRajib Acharya and Akash Porwal. 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Risk analysis, 35(3):434–458, 2015.EstudiantesInvestigadoresMaestrosPúblico generalResponsables políticosORIGINAL1014258959.2022.pdf1014258959.2022.pdfTesis de Maestría en Ciencias - Matemática Aplicadaapplication/pdf10336667https://repositorio.unal.edu.co/bitstream/unal/81293/1/1014258959.2022.pdfe64c06672af3a3ae713929233ed24a00MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-84074https://repositorio.unal.edu.co/bitstream/unal/81293/2/license.txt8153f7789df02f0a4c9e079953658ab2MD52THUMBNAIL1014258959.2022.pdf.jpg1014258959.2022.pdf.jpgGenerated Thumbnailimage/jpeg4502https://repositorio.unal.edu.co/bitstream/unal/81293/3/1014258959.2022.pdf.jpg8dbbe37af30ff59cb7029b9a0b0c8c22MD53unal/81293oai:repositorio.unal.edu.co:unal/812932024-08-04 23:10:30.499Repositorio Institucional Universidad Nacional de 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EVESURBIFBPUiBMQSBTRUNSRVRBUsONQSBHRU5FUkFMLiAqTEEgVEVTSVMgQSBQVUJMSUNBUiBERUJFIFNFUiBMQSBWRVJTScOTTiBGSU5BTCBBUFJPQkFEQS4gCgpBbCBoYWNlciBjbGljIGVuIGVsIHNpZ3VpZW50ZSBib3TDs24sIHVzdGVkIGluZGljYSBxdWUgZXN0w6EgZGUgYWN1ZXJkbyBjb24gZXN0b3MgdMOpcm1pbm9zLiBTaSB0aWVuZSBhbGd1bmEgZHVkYSBzb2JyZSBsYSBsaWNlbmNpYSwgcG9yIGZhdm9yLCBjb250YWN0ZSBjb24gZWwgYWRtaW5pc3RyYWRvciBkZWwgc2lzdGVtYS4KClVOSVZFUlNJREFEIE5BQ0lPTkFMIERFIENPTE9NQklBIC0gw5psdGltYSBtb2RpZmljYWNpw7NuIDE5LzEwLzIwMjEK

Risk-based resource allocation for management and pandemic response: The COVID-19 Case in Bogotá, Colombia

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