Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/24498
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dc.contributor.authorRosa, Silvériopt_PT
dc.contributor.authorTorres, Delfim F. M.pt_PT
dc.date.accessioned2018-10-29T16:12:45Z-
dc.date.available2018-10-29T16:12:45Z-
dc.date.issued2018-
dc.identifier.issn0960-0779pt_PT
dc.identifier.urihttp://hdl.handle.net/10773/24498-
dc.description.abstractA human respiratory syncytial virus surveillance system was implemented in Florida in 1999, to support clinical decision-making for prophylaxis of premature newborns. Recently, a local periodic SEIRS mathematical model was proposed in [Stat. Optim. Inf. Comput. 6 (2018), no.1, 139--149] to describe real data collected by Florida's system. In contrast, here we propose a non-local fractional (non-integer) order model. A fractional optimal control problem is then formulated and solved, having treatment as the control. Finally, a cost-effectiveness analysis is carried out to evaluate the cost and the effectiveness of proposed control measures during the intervention period, showing the superiority of obtained results with respect to previous ones.pt_PT
dc.language.isoengpt_PT
dc.publisherElsevierpt_PT
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147206/PTpt_PT
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147328/PTpt_PT
dc.rightsrestrictedAccesspt_PT
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectHuman respiratory syncytial virus (HRSV)pt_PT
dc.subjectCompartmental mathematical modelspt_PT
dc.subjectFractional optimal controlpt_PT
dc.titleOptimal control of a fractional order epidemic model with application to human respiratory syncytial virus infectionpt_PT
dc.typearticlept_PT
dc.description.versionpublishedpt_PT
dc.peerreviewedyespt_PT
degois.publication.firstPage142pt_PT
degois.publication.lastPage149pt_PT
degois.publication.titleChaos, Solitons & Fractalspt_PT
degois.publication.volume117pt_PT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0960077918306878pt_PT
dc.identifier.doi10.1016/j.chaos.2018.10.021pt_PT
Appears in Collections:CIDMA - Artigos
SCG - Artigos

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