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Robust Optimal Control of Compartmental Models in Epidemiology: Application to the COVID-19 Pandemic

dc.contributor.authorOlivares, Alberto
dc.contributor.authorStaffetti, Ernesto
dc.date.accessioned2023-09-21T08:22:45Z
dc.date.available2023-09-21T08:22:45Z
dc.date.issued2022
dc.identifier.citationAlberto Olivares, Ernesto Staffetti, Robust optimal control of compartmental models in epidemiology: Application to the COVID-19 pandemic, Communications in Nonlinear Science and Numerical Simulation, Volume 111, 2022, 106509, ISSN 1007-5704, https://doi.org/10.1016/j.cnsns.2022.106509es
dc.identifier.issn1878-7274
dc.identifier.urihttps://hdl.handle.net/10115/24433
dc.description.abstractIn this paper, a spectral approach is used to formulate and solve robust optimal control problems for compartmental epidemic models, allowing the uncertainty propagation through the optimal control model to be represented by a polynomial expansion of its stochastic state variables. More specifically, a statistical moment-based polynomial chaos expansion is employed. The spectral expansion of the stochastic state variables allows the computation of their main statistics to be carried out, resulting in a compact and efficient representation of the variability of the optimal control model with respect to its random parameters. The proposed robust formulation provides the designers of the optimal control strategy of the epidemic model the capability to increase the predictability of the results by simply adding upper bounds on the variability of the state variables. Moreover, this approach yields a way to efficiently estimate the probability distributions of the stochastic state variables and conduct a global sensitivity analysis. To show the practical implementation of the proposed approach, a mathematical model of COVID-19 transmission is considered. The numerical results show that the spectral approach proposed to formulate and solve robust optimal control problems for compartmental epidemic models provides healthcare systems with a valuable tool to mitigate and control the impact of infectious diseases.es
dc.language.isoenges
dc.publisherElsevieres
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectRobust optimal controles
dc.subjectEpidemic compartmental modelses
dc.subjectPolynomial chaos expansiones
dc.subjectUncertainty quantificationes
dc.subjectCOVID-19 transmission dynamicses
dc.titleRobust Optimal Control of Compartmental Models in Epidemiology: Application to the COVID-19 Pandemices
dc.typeinfo:eu-repo/semantics/articlees
dc.identifier.doi10.1016/j.cnsns.2022.106509es
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses


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Attribution-NonCommercial-NoDerivatives 4.0 InternacionalExcept where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional