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Towards a stochastic SEIR model for the COVID-19 post-pandemic scenario

2023Conference paper Open access
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dc.contributor.authorBalsa, Carlos
dc.contributor.authorPadua, Everaldo Junior Borges Garcia de
dc.contributor.authorPinto, Luan Crisostomo
dc.contributor.authorRufino, José
dc.date.accessioned2024-01-15T17:29:50Z
dc.date.available2024-01-15T17:29:50Z
dc.date.issued2023
dc.description.abstractWith the current recession of the global COVID-19 pandemic, the corresponding epidemic models need to be adapted to reflect this new reality and continue assisting public health authorities in the definition of policies and decision making. With that aim, this paper presents a SEIR epidemic model for the representation of the COVID-19 pos-pandemic scenario. The model considers the effect of countermeasures such as vaccination and quarantine, and the consequences of the progressive loss of immunity. A deterministic formulation and a first stochastic version of the model are presented, and their implementation in MATLAB is evaluated and compared. To cope with the computational demands of the application of the Monte Carlo method, the implementation of the stochastic version follows a parallel approach that proved to be highly scalable and efficient in a multi-core computational system. The preliminary evaluation results, with fixed parameters, point to a cyclic evolution of the pandemic and a tendency for stabilization in the future.pt_PT
dc.description.sponsorshipThe authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBalsa, Carlos; Padua, Everaldo Junior Borges Garcia de; Pinto, Luan Crisostomo; Rufino, José (2023). Towards a stochastic SEIR model for the COVID-19 post-pandemic scenario. In 18th Iberian Conference on Information Systems and Technologies (CISTI). p. 1-6. ISBN 978-989-33-4792-8pt_PT
dc.identifier.doi10.23919/CISTI58278.2023.10212021pt_PT
dc.identifier.isbn978-989-33-4792-8
dc.identifier.urihttp://hdl.handle.net/10198/29218
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherIEEEpt_PT
dc.relationLA/P/0007/2021pt_PT
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectCOVID-19pt_PT
dc.subjectPost-pandemic scenariopt_PT
dc.subjectStochastic SEIR modelpt_PT
dc.subjectMATLABpt_PT
dc.subjectParallel simulationspt_PT
dc.titleTowards a stochastic SEIR model for the COVID-19 post-pandemic scenariopt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT
oaire.citation.endPage6pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.title18th Iberian Conference on Information Systems and Technologies (CISTI)pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameBalsa
person.familyNameRufino
person.givenNameCarlos
person.givenNameJosé
person.identifier1721518
person.identifier.ciencia-idDE1E-2F7A-AAB1
person.identifier.ciencia-idC414-F47F-6323
person.identifier.orcid0000-0003-2431-8665
person.identifier.orcid0000-0002-1344-8264
person.identifier.ridM-8735-2013
person.identifier.scopus-author-id23391719100
person.identifier.scopus-author-id55947199100
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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