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
OAI Identifier:
oai:repositorio.unal.edu.co:unal/81293
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/81293
https://repositorio.unal.edu.co/
Palabra clave:
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
Rights
openAccess
License
Reconocimiento 4.0 Internacional
id UNACIONAL2_eb772619e5882212996f6265dd60115e
oai_identifier_str oai:repositorio.unal.edu.co:unal/81293
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
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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dc.rights.license.spa.fl_str_mv Reconocimiento 4.0 Internacional
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rights_invalid_str_mv Reconocimiento 4.0 Internacional
Derechos reservados al autor, 2021
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dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv Bogotá - Ciencias - Maestría en Ciencias - Matemática Aplicada
dc.publisher.department.spa.fl_str_mv Departamento de Matemáticas
dc.publisher.faculty.spa.fl_str_mv Facultad de Ciencias
dc.publisher.place.spa.fl_str_mv Bogotá, Colombia
dc.publisher.branch.spa.fl_str_mv Universidad Nacional de Colombia - Sede Bogotá
institution 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

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