SARS-CoV-2 spread forecast dynamic model validation through digital twin approach, Catalonia case study

The spread of the SARS-CoV-2 modeling is a challenging problem because of its complex nature and lack of information regarding certain aspects. In this paper, we explore a Digital Twin approach to model the pandemic situation in Catalonia. The Digital Twin is composed of three different dynamic mode...

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Detalles Bibliográficos
Autores: Fonseca Casas, Pau|||0000-0002-6747-9736, Garcia Subirana, Joan, García Carrasco, Víctor, Pi Palomés, Xavier
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/360998
Acceso en línea:https://hdl.handle.net/2117/360998
https://dx.doi.org/10.3390/math9141660
Access Level:acceso abierto
Palabra clave:Multivariate analysis
Biomathematics
SARS-CoV-2
COVID-19
SEIRD (Susceptible
Exposed
Infected and Recovered and Death)
SDL
Catalonia
Anàlisi multivariable
Biomatemàtica
Classificació AMS::62 Statistics::62H Multivariate analysis
Classificació AMS::92 Biology and other natural sciences::92B Mathematical biology in general
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística aplicada::Estadística biosanitària
Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
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repository_id_str
spelling SARS-CoV-2 spread forecast dynamic model validation through digital twin approach, Catalonia case studyFonseca Casas, Pau|||0000-0002-6747-9736Garcia Subirana, JoanGarcía Carrasco, VíctorPi Palomés, XavierMultivariate analysisBiomathematicsSARS-CoV-2COVID-19SEIRD (SusceptibleExposedInfected and Recovered and Death)SDLCataloniaAnàlisi multivariableBiomatemàticaClassificació AMS::62 Statistics::62H Multivariate analysisClassificació AMS::92 Biology and other natural sciences::92B Mathematical biology in generalÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística aplicada::Estadística biosanitàriaÀrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciènciesThe spread of the SARS-CoV-2 modeling is a challenging problem because of its complex nature and lack of information regarding certain aspects. In this paper, we explore a Digital Twin approach to model the pandemic situation in Catalonia. The Digital Twin is composed of three different dynamic models used to perform the validations by a Model Comparison approach. We detail how we use this approach to obtain knowledge regarding the effects of the nonpharmaceutical interventions and the problems we faced during the modeling process. We use Specification and Description Language (SDL) to represent the compartmental forecasting model for the SARS-CoV-2. Its graphical notation simplifies the different specialists’ understanding of the model hypotheses, which must be validated continuously following a Solution Validation approach. This model allows the successful forecasting of different scenarios for Catalonia. We present some formalization details, discuss the validation process and present some results obtained from the validation model discussion, which becomes a digital twin of the pandemic in Catalonia.Peer ReviewedMultidisciplinary Digital Publishing Institute (MDPI)20212021-07-1420222022-01-28journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/360998https://dx.doi.org/10.3390/math9141660reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3609982026-05-27T15:37:01Z
dc.title.none.fl_str_mv SARS-CoV-2 spread forecast dynamic model validation through digital twin approach, Catalonia case study
title SARS-CoV-2 spread forecast dynamic model validation through digital twin approach, Catalonia case study
spellingShingle SARS-CoV-2 spread forecast dynamic model validation through digital twin approach, Catalonia case study
Fonseca Casas, Pau|||0000-0002-6747-9736
Multivariate analysis
Biomathematics
SARS-CoV-2
COVID-19
SEIRD (Susceptible
Exposed
Infected and Recovered and Death)
SDL
Catalonia
Anàlisi multivariable
Biomatemàtica
Classificació AMS::62 Statistics::62H Multivariate analysis
Classificació AMS::92 Biology and other natural sciences::92B Mathematical biology in general
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística aplicada::Estadística biosanitària
Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
title_short SARS-CoV-2 spread forecast dynamic model validation through digital twin approach, Catalonia case study
title_full SARS-CoV-2 spread forecast dynamic model validation through digital twin approach, Catalonia case study
title_fullStr SARS-CoV-2 spread forecast dynamic model validation through digital twin approach, Catalonia case study
title_full_unstemmed SARS-CoV-2 spread forecast dynamic model validation through digital twin approach, Catalonia case study
title_sort SARS-CoV-2 spread forecast dynamic model validation through digital twin approach, Catalonia case study
dc.creator.none.fl_str_mv Fonseca Casas, Pau|||0000-0002-6747-9736
Garcia Subirana, Joan
García Carrasco, Víctor
Pi Palomés, Xavier
author Fonseca Casas, Pau|||0000-0002-6747-9736
author_facet Fonseca Casas, Pau|||0000-0002-6747-9736
Garcia Subirana, Joan
García Carrasco, Víctor
Pi Palomés, Xavier
author_role author
author2 Garcia Subirana, Joan
García Carrasco, Víctor
Pi Palomés, Xavier
author2_role author
author
author
dc.subject.none.fl_str_mv Multivariate analysis
Biomathematics
SARS-CoV-2
COVID-19
SEIRD (Susceptible
Exposed
Infected and Recovered and Death)
SDL
Catalonia
Anàlisi multivariable
Biomatemàtica
Classificació AMS::62 Statistics::62H Multivariate analysis
Classificació AMS::92 Biology and other natural sciences::92B Mathematical biology in general
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística aplicada::Estadística biosanitària
Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
topic Multivariate analysis
Biomathematics
SARS-CoV-2
COVID-19
SEIRD (Susceptible
Exposed
Infected and Recovered and Death)
SDL
Catalonia
Anàlisi multivariable
Biomatemàtica
Classificació AMS::62 Statistics::62H Multivariate analysis
Classificació AMS::92 Biology and other natural sciences::92B Mathematical biology in general
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística aplicada::Estadística biosanitària
Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
description The spread of the SARS-CoV-2 modeling is a challenging problem because of its complex nature and lack of information regarding certain aspects. In this paper, we explore a Digital Twin approach to model the pandemic situation in Catalonia. The Digital Twin is composed of three different dynamic models used to perform the validations by a Model Comparison approach. We detail how we use this approach to obtain knowledge regarding the effects of the nonpharmaceutical interventions and the problems we faced during the modeling process. We use Specification and Description Language (SDL) to represent the compartmental forecasting model for the SARS-CoV-2. Its graphical notation simplifies the different specialists’ understanding of the model hypotheses, which must be validated continuously following a Solution Validation approach. This model allows the successful forecasting of different scenarios for Catalonia. We present some formalization details, discuss the validation process and present some results obtained from the validation model discussion, which becomes a digital twin of the pandemic in Catalonia.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-07-14
2022
2022-01-28
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/360998
https://dx.doi.org/10.3390/math9141660
url https://hdl.handle.net/2117/360998
https://dx.doi.org/10.3390/math9141660
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute (MDPI)
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute (MDPI)
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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