A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagions

Autores
Lanzarotti, Esteban Omar; Roslan, Francisco; Groisman, Leandro; Santi, Lucio Emilio; Castro, Rodrigo Daniel
Año de publicación
2021
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In the quest to better understand the epidemic dynamics of COVID-19 and possible strategies to mitigate its impact, a wide range of simulation models have been developed for various purposes. Faced with a novel disease with little-known characteristics and an unprecedented impact, the need arises to model multiple aspects with very dissimilar dynamics in a consistent, formal, yet flexible and quick way, in order to then study the combined interaction of these dynamics. We present an agent-based model combining kinematic movement of agents, interaction between them and their surrounding space and a top-down control over the entire population. To achieve this, we extend the retQSS framework to model and simulate particle systems interacting with geometries. In this work, we study different contact tracing strategies and their efficacy in a population undergoing an epidemic process driven mainly by airborne infections in indoor environments.
Fil: Lanzarotti, Esteban Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina
Fil: Roslan, Francisco. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina
Fil: Groisman, Leandro. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina
Fil: Santi, Lucio Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina
Fil: Castro, Rodrigo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina
Winter Simulation Conference 2021: Simulation for a Smart World: From Smart Devices to Smart Cities
Phoenix
Estados Unidos
Organizing Committee of Simulation Conference
Materia
Agent Based Models
COVID-19
Hybrid Models
Particle Systems
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/154351
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagionsLanzarotti, Esteban OmarRoslan, FranciscoGroisman, LeandroSanti, Lucio EmilioCastro, Rodrigo DanielAgent Based ModelsCOVID-19Hybrid ModelsParticle Systemshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1In the quest to better understand the epidemic dynamics of COVID-19 and possible strategies to mitigate its impact, a wide range of simulation models have been developed for various purposes. Faced with a novel disease with little-known characteristics and an unprecedented impact, the need arises to model multiple aspects with very dissimilar dynamics in a consistent, formal, yet flexible and quick way, in order to then study the combined interaction of these dynamics. We present an agent-based model combining kinematic movement of agents, interaction between them and their surrounding space and a top-down control over the entire population. To achieve this, we extend the retQSS framework to model and simulate particle systems interacting with geometries. In this work, we study different contact tracing strategies and their efficacy in a population undergoing an epidemic process driven mainly by airborne infections in indoor environments.Fil: Lanzarotti, Esteban Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Roslan, Francisco. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; ArgentinaFil: Groisman, Leandro. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; ArgentinaFil: Santi, Lucio Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Castro, Rodrigo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaWinter Simulation Conference 2021: Simulation for a Smart World: From Smart Devices to Smart CitiesPhoenixEstados UnidosOrganizing Committee of Simulation ConferenceACMKim, S.Feng, B.Smith, K.Masoud, S.Zheng, Z.Szabo, C.Loper, M.2021info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectConferenciaBookhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/154351A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagions; Winter Simulation Conference 2021: Simulation for a Smart World: From Smart Devices to Smart Cities; Phoenix; Estados Unidos; 2021; 1-12CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://ssl.linklings.net/conferences/wsc/wsc2021_program/views/at_a_glance.htmlInternacionalinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:34:20Zoai:ri.conicet.gov.ar:11336/154351instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:34:20.952CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagions
title A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagions
spellingShingle A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagions
Lanzarotti, Esteban Omar
Agent Based Models
COVID-19
Hybrid Models
Particle Systems
title_short A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagions
title_full A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagions
title_fullStr A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagions
title_full_unstemmed A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagions
title_sort A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagions
dc.creator.none.fl_str_mv Lanzarotti, Esteban Omar
Roslan, Francisco
Groisman, Leandro
Santi, Lucio Emilio
Castro, Rodrigo Daniel
author Lanzarotti, Esteban Omar
author_facet Lanzarotti, Esteban Omar
Roslan, Francisco
Groisman, Leandro
Santi, Lucio Emilio
Castro, Rodrigo Daniel
author_role author
author2 Roslan, Francisco
Groisman, Leandro
Santi, Lucio Emilio
Castro, Rodrigo Daniel
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Kim, S.
Feng, B.
Smith, K.
Masoud, S.
Zheng, Z.
Szabo, C.
Loper, M.
dc.subject.none.fl_str_mv Agent Based Models
COVID-19
Hybrid Models
Particle Systems
topic Agent Based Models
COVID-19
Hybrid Models
Particle Systems
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In the quest to better understand the epidemic dynamics of COVID-19 and possible strategies to mitigate its impact, a wide range of simulation models have been developed for various purposes. Faced with a novel disease with little-known characteristics and an unprecedented impact, the need arises to model multiple aspects with very dissimilar dynamics in a consistent, formal, yet flexible and quick way, in order to then study the combined interaction of these dynamics. We present an agent-based model combining kinematic movement of agents, interaction between them and their surrounding space and a top-down control over the entire population. To achieve this, we extend the retQSS framework to model and simulate particle systems interacting with geometries. In this work, we study different contact tracing strategies and their efficacy in a population undergoing an epidemic process driven mainly by airborne infections in indoor environments.
Fil: Lanzarotti, Esteban Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina
Fil: Roslan, Francisco. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina
Fil: Groisman, Leandro. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina
Fil: Santi, Lucio Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina
Fil: Castro, Rodrigo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; Argentina
Winter Simulation Conference 2021: Simulation for a Smart World: From Smart Devices to Smart Cities
Phoenix
Estados Unidos
Organizing Committee of Simulation Conference
description In the quest to better understand the epidemic dynamics of COVID-19 and possible strategies to mitigate its impact, a wide range of simulation models have been developed for various purposes. Faced with a novel disease with little-known characteristics and an unprecedented impact, the need arises to model multiple aspects with very dissimilar dynamics in a consistent, formal, yet flexible and quick way, in order to then study the combined interaction of these dynamics. We present an agent-based model combining kinematic movement of agents, interaction between them and their surrounding space and a top-down control over the entire population. To achieve this, we extend the retQSS framework to model and simulate particle systems interacting with geometries. In this work, we study different contact tracing strategies and their efficacy in a population undergoing an epidemic process driven mainly by airborne infections in indoor environments.
publishDate 2021
dc.date.none.fl_str_mv 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
Conferencia
Book
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
status_str publishedVersion
format conferenceObject
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/154351
A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagions; Winter Simulation Conference 2021: Simulation for a Smart World: From Smart Devices to Smart Cities; Phoenix; Estados Unidos; 2021; 1-12
CONICET Digital
CONICET
url http://hdl.handle.net/11336/154351
identifier_str_mv A multi-aspect agent-based model of covid-19: disease dynamics, contact tracing interventions and shared space-driven contagions; Winter Simulation Conference 2021: Simulation for a Smart World: From Smart Devices to Smart Cities; Phoenix; Estados Unidos; 2021; 1-12
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://ssl.linklings.net/conferences/wsc/wsc2021_program/views/at_a_glance.html
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.coverage.none.fl_str_mv Internacional
dc.publisher.none.fl_str_mv ACM
publisher.none.fl_str_mv ACM
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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