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dc.contributor.authorSaldaña, F. 
dc.contributor.authorKebir, A. 
dc.contributor.authorCamacho-Gutiérrez, J. A.
dc.contributor.authorAguiar, M. 
dc.date2024-12-01en_US
dc.date.accessioned2023-11-02T10:51:31Z
dc.date.available2023-11-02T10:51:31Z
dc.date.issued2023-12
dc.identifier.issn0025-5564
dc.identifier.urihttp://hdl.handle.net/20.500.11824/1706
dc.description.abstractThe choice of the objective functional in optimization problems coming from biomedical and epidemiological applications plays a key role in optimal control outcomes. In this study, we investigate the role of the objective functional on the structure of the optimal control solution for an epidemic model for sexually transmitted infections that includes a core group with higher sexual activity levels than the rest of the population. An optimal control problem is formulated to find a targeted vaccination program able to control the spread of the infection with minimum vaccine deployment. Both $L_{1}-$ and $L_{2}-$objectives are considered as an attempt to explore the trade-offs between control dynamics and the functional form characterizing optimality. The results show that the optimal vaccination policies for both the $L_{1}-$ and the $L_{2}-$formulation share one important qualitative property, that is, immunization of the core group should be prioritized by policymakers to achieve a fast reduction of the epidemic. However, quantitative aspects of this result can be significantly affected depending on the choice of the control weights between formulations. Overall, the results suggest that with appropriate weight constants, the optimal control outcomes are reasonably robust with respect to the $L_{1}-$ or $L_{2}-$formulation. This is particularly true when the monetary cost of the control policy is substantially lower than the cost associated with the disease burden. Under these conditions, even if the $L_{1}-$formulation is more realistic from a modeling perspective, the $L_{2}-$formulation can be used as an approximation and yield qualitatively comparable outcomes.en_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.subjectOptimal controlen_US
dc.subjectEpidemic modelsen_US
dc.subjectMathematical modelingen_US
dc.subjectVaccine allocationen_US
dc.titleOptimal vaccination strategies for a heterogenous population using multiple objectives: The case of L1 and L2-formulationsen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.identifier.doihttps://doi.org/10.1016/j.mbs.2023.109103en_US
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0025556423001438en_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/CEX2021-001142-Sen_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/Gobierno Vasco/BERC/BERC.2022-2025en_US
dc.rights.accessRightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.type.hasVersioninfo:eu-repo/semantics/submittedVersionen_US
dc.journal.titleMathematical Biosciencesen_US
dc.volume.number366en_US


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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España