A Fractional Order Model to Study the Effectiveness of Government Measures and Public Behaviours in COVID-19 Pandemic

In this work, we emphasise the dynamical study of spreading COVID-19 in Bangladesh. Considering the uncertainty caused by the limited coronavirus (COVID-19) information, we have taken the modified Susceptible-Asymptomatic-Infectious-Hospitalised-Recovered (SAIHR) compartmental model in a Caputo frac...

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Autores: Das, Meghadri, Samanta, Guruprasad, De la Sen Parte, Manuel
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/57353
Acceso en línea:http://hdl.handle.net/10810/57353
Access Level:acceso abierto
Palabra clave:Caputo fractional differential equation
COVID-19
SAIHR compartmental model
stability
sensitivity index
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spelling A Fractional Order Model to Study the Effectiveness of Government Measures and Public Behaviours in COVID-19 PandemicDas, MeghadriSamanta, GuruprasadDe la Sen Parte, ManuelCaputo fractional differential equationCOVID-19SAIHR compartmental modelstabilitysensitivity indexIn this work, we emphasise the dynamical study of spreading COVID-19 in Bangladesh. Considering the uncertainty caused by the limited coronavirus (COVID-19) information, we have taken the modified Susceptible-Asymptomatic-Infectious-Hospitalised-Recovered (SAIHR) compartmental model in a Caputo fractional order system. We have also introduced public behavioural and government policy dynamics in our model. The dynamical nature of the solutions of the system is analysed and we have also calculated the sensitivity index of different parameters. It has been observed that public behaviour and government measures play an important role in controlling the pandemic situation. The government measures (social distance, vaccination, hospitalisation, awareness programme) are more helpful than only public responses to the eradication of the COVID-19 pandemic.This research was funded by the Spanish Government for its support through grant RTI2018-094336-B-100 (MCIU/AEI/FEDER, UE) and to the Basque Government for its support through grant IT1555-22.MDPI2022202220222022info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/57353reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoInglésinfo:eu-repo/grantAgreement/MICIU/RTI2018-094336-B-100/https://www.mdpi.com/2227-7390/10/16/3020info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/© 2022 by the authors.Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).oai:addi.ehu.eus:10810/573532026-06-18T09:23:17Z
dc.title.none.fl_str_mv A Fractional Order Model to Study the Effectiveness of Government Measures and Public Behaviours in COVID-19 Pandemic
title A Fractional Order Model to Study the Effectiveness of Government Measures and Public Behaviours in COVID-19 Pandemic
spellingShingle A Fractional Order Model to Study the Effectiveness of Government Measures and Public Behaviours in COVID-19 Pandemic
Das, Meghadri
Caputo fractional differential equation
COVID-19
SAIHR compartmental model
stability
sensitivity index
title_short A Fractional Order Model to Study the Effectiveness of Government Measures and Public Behaviours in COVID-19 Pandemic
title_full A Fractional Order Model to Study the Effectiveness of Government Measures and Public Behaviours in COVID-19 Pandemic
title_fullStr A Fractional Order Model to Study the Effectiveness of Government Measures and Public Behaviours in COVID-19 Pandemic
title_full_unstemmed A Fractional Order Model to Study the Effectiveness of Government Measures and Public Behaviours in COVID-19 Pandemic
title_sort A Fractional Order Model to Study the Effectiveness of Government Measures and Public Behaviours in COVID-19 Pandemic
dc.creator.none.fl_str_mv Das, Meghadri
Samanta, Guruprasad
De la Sen Parte, Manuel
author Das, Meghadri
author_facet Das, Meghadri
Samanta, Guruprasad
De la Sen Parte, Manuel
author_role author
author2 Samanta, Guruprasad
De la Sen Parte, Manuel
author2_role author
author
dc.subject.none.fl_str_mv Caputo fractional differential equation
COVID-19
SAIHR compartmental model
stability
sensitivity index
topic Caputo fractional differential equation
COVID-19
SAIHR compartmental model
stability
sensitivity index
description In this work, we emphasise the dynamical study of spreading COVID-19 in Bangladesh. Considering the uncertainty caused by the limited coronavirus (COVID-19) information, we have taken the modified Susceptible-Asymptomatic-Infectious-Hospitalised-Recovered (SAIHR) compartmental model in a Caputo fractional order system. We have also introduced public behavioural and government policy dynamics in our model. The dynamical nature of the solutions of the system is analysed and we have also calculated the sensitivity index of different parameters. It has been observed that public behaviour and government measures play an important role in controlling the pandemic situation. The government measures (social distance, vaccination, hospitalisation, awareness programme) are more helpful than only public responses to the eradication of the COVID-19 pandemic.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022
2022
2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/57353
url http://hdl.handle.net/10810/57353
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/MICIU/RTI2018-094336-B-100/
https://www.mdpi.com/2227-7390/10/16/3020
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Addi. Archivo Digital para la Docencia y la Investigación
instname:Universidad del País Vasco
instname_str Universidad del País Vasco
reponame_str Addi. Archivo Digital para la Docencia y la Investigación
collection Addi. Archivo Digital para la Docencia y la Investigación
repository.name.fl_str_mv
repository.mail.fl_str_mv
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