An SEIR Epidemic Model of Fractional Order to Analyze the Evolution of the Covid-19 Epidemic in Argentina

Autores
Santos, Juan Enrique; Carcione, José M.; Savioli, Gabriela B.; Gauzellino, Patricia Mercedes
Año de publicación
2021
Idioma
inglés
Tipo de recurso
parte de libro
Estado
versión publicada
Descripción
A pandemic caused by a new coronavirus (Covid-19) has spread worldwide, inducing an epidemic still active in Argentina. In this chapter, we present a case study using an SEIR (Susceptible-Exposed-Infected-Recovered) diffusion model of fractional order in time to analyze the evolution of the epidemic in Buenos Aires and neighboring areas (Region Metropolitana de Buenos Aires, (RMBA)) comprising about 15 million inhabitants. In the SEIR model, individuals are divided into four classes, namely, susceptible (S), exposed (E), infected (I) and recovered (R). The SEIR model of fractional order allows for the incorporation of memory, with hereditary properties of the system, being a generalization of the classic SEIR first-order system, where such effects are ignored. Furthermore, the fractional model provides one additional parameter to obtain a better fit of the data. The parameters of the model are calibrated by using as data the number of casualties officially reported. Since infinite solutions honour the data, we show a set of cases with different values of the lockdown parameters, fatality rate, and incubation and infectious periods. The different reproduction ratios \(R_0\) and infection fatality rates (IFR) so obtained indicate the results may differ from recent reported values, constituting possible alternative solutions. A comparison with results obtained with the classic SEIR model is also included. The analysis allows us to study how isolation and social distancing measures affect the time evolution of the epidemic.
Facultad de Ciencias Astronómicas y Geofísicas
Materia
Ciencias Exactas
Ciencias Médicas
Fractional Differential Equations
Numerical investigation of stability of solutions
Medical epidemiology
Medical epidemiology
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/146433
Acceder
id SEDICI_8d1617e6e80ff7786ac3a48ced60acda
oai_identifier_str oai:sedici.unlp.edu.ar:10915/146433
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling An SEIR Epidemic Model of Fractional Order to Analyze the Evolution of the Covid-19 Epidemic in ArgentinaSantos, Juan EnriqueCarcione, José M.Savioli, Gabriela B.Gauzellino, Patricia MercedesCiencias ExactasCiencias MédicasFractional Differential EquationsNumerical investigation of stability of solutionsMedical epidemiologyMedical epidemiologyA pandemic caused by a new coronavirus (Covid-19) has spread worldwide, inducing an epidemic still active in Argentina. In this chapter, we present a case study using an SEIR (Susceptible-Exposed-Infected-Recovered) diffusion model of fractional order in time to analyze the evolution of the epidemic in Buenos Aires and neighboring areas (Region Metropolitana de Buenos Aires, (RMBA)) comprising about 15 million inhabitants. In the SEIR model, individuals are divided into four classes, namely, susceptible (S), exposed (E), infected (I) and recovered (R). The SEIR model of fractional order allows for the incorporation of memory, with hereditary properties of the system, being a generalization of the classic SEIR first-order system, where such effects are ignored. Furthermore, the fractional model provides one additional parameter to obtain a better fit of the data. The parameters of the model are calibrated by using as data the number of casualties officially reported. Since infinite solutions honour the data, we show a set of cases with different values of the lockdown parameters, fatality rate, and incubation and infectious periods. The different reproduction ratios \(R_0\) and infection fatality rates (IFR) so obtained indicate the results may differ from recent reported values, constituting possible alternative solutions. A comparison with results obtained with the classic SEIR model is also included. The analysis allows us to study how isolation and social distancing measures affect the time evolution of the epidemic.Facultad de Ciencias Astronómicas y GeofísicasSpringer2021-09-30info:eu-repo/semantics/bookPartinfo:eu-repo/semantics/publishedVersionCapitulo de librohttp://purl.org/coar/resource_type/c_3248info:ar-repo/semantics/parteDeLibroapplication/pdf539-557http://sedici.unlp.edu.ar/handle/10915/146433enginfo:eu-repo/semantics/altIdentifier/isbn/978-981-16-2450-6info:eu-repo/semantics/altIdentifier/issn/2363-6149info:eu-repo/semantics/altIdentifier/issn/2363-6157info:eu-repo/semantics/altIdentifier/doi/10.1007/978-981-16-2450-6_25info:eu-repo/semantics/altIdentifier/arxiv/2104.02853v1info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:32:17Zoai:sedici.unlp.edu.ar:10915/146433Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:32:18.111SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv An SEIR Epidemic Model of Fractional Order to Analyze the Evolution of the Covid-19 Epidemic in Argentina
title An SEIR Epidemic Model of Fractional Order to Analyze the Evolution of the Covid-19 Epidemic in Argentina
spellingShingle An SEIR Epidemic Model of Fractional Order to Analyze the Evolution of the Covid-19 Epidemic in Argentina
Santos, Juan Enrique
Ciencias Exactas
Ciencias Médicas
Fractional Differential Equations
Numerical investigation of stability of solutions
Medical epidemiology
Medical epidemiology
title_short An SEIR Epidemic Model of Fractional Order to Analyze the Evolution of the Covid-19 Epidemic in Argentina
title_full An SEIR Epidemic Model of Fractional Order to Analyze the Evolution of the Covid-19 Epidemic in Argentina
title_fullStr An SEIR Epidemic Model of Fractional Order to Analyze the Evolution of the Covid-19 Epidemic in Argentina
title_full_unstemmed An SEIR Epidemic Model of Fractional Order to Analyze the Evolution of the Covid-19 Epidemic in Argentina
title_sort An SEIR Epidemic Model of Fractional Order to Analyze the Evolution of the Covid-19 Epidemic in Argentina
dc.creator.none.fl_str_mv Santos, Juan Enrique
Carcione, José M.
Savioli, Gabriela B.
Gauzellino, Patricia Mercedes
author Santos, Juan Enrique
author_facet Santos, Juan Enrique
Carcione, José M.
Savioli, Gabriela B.
Gauzellino, Patricia Mercedes
author_role author
author2 Carcione, José M.
Savioli, Gabriela B.
Gauzellino, Patricia Mercedes
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Exactas
Ciencias Médicas
Fractional Differential Equations
Numerical investigation of stability of solutions
Medical epidemiology
Medical epidemiology
topic Ciencias Exactas
Ciencias Médicas
Fractional Differential Equations
Numerical investigation of stability of solutions
Medical epidemiology
Medical epidemiology
dc.description.none.fl_txt_mv A pandemic caused by a new coronavirus (Covid-19) has spread worldwide, inducing an epidemic still active in Argentina. In this chapter, we present a case study using an SEIR (Susceptible-Exposed-Infected-Recovered) diffusion model of fractional order in time to analyze the evolution of the epidemic in Buenos Aires and neighboring areas (Region Metropolitana de Buenos Aires, (RMBA)) comprising about 15 million inhabitants. In the SEIR model, individuals are divided into four classes, namely, susceptible (S), exposed (E), infected (I) and recovered (R). The SEIR model of fractional order allows for the incorporation of memory, with hereditary properties of the system, being a generalization of the classic SEIR first-order system, where such effects are ignored. Furthermore, the fractional model provides one additional parameter to obtain a better fit of the data. The parameters of the model are calibrated by using as data the number of casualties officially reported. Since infinite solutions honour the data, we show a set of cases with different values of the lockdown parameters, fatality rate, and incubation and infectious periods. The different reproduction ratios \(R_0\) and infection fatality rates (IFR) so obtained indicate the results may differ from recent reported values, constituting possible alternative solutions. A comparison with results obtained with the classic SEIR model is also included. The analysis allows us to study how isolation and social distancing measures affect the time evolution of the epidemic.
Facultad de Ciencias Astronómicas y Geofísicas
description A pandemic caused by a new coronavirus (Covid-19) has spread worldwide, inducing an epidemic still active in Argentina. In this chapter, we present a case study using an SEIR (Susceptible-Exposed-Infected-Recovered) diffusion model of fractional order in time to analyze the evolution of the epidemic in Buenos Aires and neighboring areas (Region Metropolitana de Buenos Aires, (RMBA)) comprising about 15 million inhabitants. In the SEIR model, individuals are divided into four classes, namely, susceptible (S), exposed (E), infected (I) and recovered (R). The SEIR model of fractional order allows for the incorporation of memory, with hereditary properties of the system, being a generalization of the classic SEIR first-order system, where such effects are ignored. Furthermore, the fractional model provides one additional parameter to obtain a better fit of the data. The parameters of the model are calibrated by using as data the number of casualties officially reported. Since infinite solutions honour the data, we show a set of cases with different values of the lockdown parameters, fatality rate, and incubation and infectious periods. The different reproduction ratios \(R_0\) and infection fatality rates (IFR) so obtained indicate the results may differ from recent reported values, constituting possible alternative solutions. A comparison with results obtained with the classic SEIR model is also included. The analysis allows us to study how isolation and social distancing measures affect the time evolution of the epidemic.
publishDate 2021
dc.date.none.fl_str_mv 2021-09-30
dc.type.none.fl_str_mv info:eu-repo/semantics/bookPart
info:eu-repo/semantics/publishedVersion
Capitulo de libro
http://purl.org/coar/resource_type/c_3248
info:ar-repo/semantics/parteDeLibro
format bookPart
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/146433
url http://sedici.unlp.edu.ar/handle/10915/146433
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-981-16-2450-6
info:eu-repo/semantics/altIdentifier/issn/2363-6149
info:eu-repo/semantics/altIdentifier/issn/2363-6157
info:eu-repo/semantics/altIdentifier/doi/10.1007/978-981-16-2450-6_25
info:eu-repo/semantics/altIdentifier/arxiv/2104.02853v1
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
539-557
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1844616202695999488
score 13.070432

Publicaciones similares