Optimal control of epidemic size and duration with limited resources.


Journal

Mathematical biosciences
ISSN: 1879-3134
Titre abrégé: Math Biosci
Pays: United States
ID NLM: 0103146

Informations de publication

Date de publication:
09 2019
Historique:
received: 20 08 2018
revised: 18 07 2019
accepted: 18 07 2019
pubmed: 23 7 2019
medline: 21 4 2020
entrez: 23 7 2019
Statut: ppublish

Résumé

The total number of infections (epidemic size) and the time needed for the infection to go extinct (epidemic duration) represent two of the main indicators for the severity of infectious disease epidemics in human and livestock. However, few attempts have been made to address the problem of minimizing at the same time the epidemic size and duration from a theoretical point of view by using optimal control theory. Here, we investigate the multi-objective optimal control problem aiming to minimize, through either vaccination or isolation, a suitable combination of epidemic size and duration when both maximum control effort and total amount of resources available during the entire epidemic period are limited. Application of Pontryagin's Maximum Principle to a Susceptible-Infected-Removed epidemic model, shows that, when the resources are not sufficient to maintain the maximum control effort for the entire duration of the epidemic, the optimal vaccination control admits only bang-bang solutions with one or two switches, while the optimal isolation control admits only bang-bang solutions with one switch. We also find that, especially when the maximum control effort is low, there may exist a trade-off between the minimization of the two objectives. Consideration of this conflict among objectives can be crucial in successfully tackling real-world problems, where different stakeholders with potentially different objectives are involved. Finally, the particular case of the minimum time optimal control problem with limited resources is discussed.

Identifiants

pubmed: 31330135
pii: S0025-5564(18)30511-X
doi: 10.1016/j.mbs.2019.108232
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

108232

Informations de copyright

Copyright © 2019 Elsevier Inc. All rights reserved.

Auteurs

Luca Bolzoni (L)

Risk Analysis and Genomic Epidemiology Unit, Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna, Via dei Mercati 13, Parma 43126, Italy. Electronic address: luca.bolzoni@izsler.it.

Elena Bonacini (E)

Department of Mathematical, Physical and Computer Sciences, University of Parma, Parco Area delle Scienze 53/A, Parma 43124, Italy.

Rossella Della Marca (R)

Department of Mathematical, Physical and Computer Sciences, University of Parma, Parco Area delle Scienze 53/A, Parma 43124, Italy.

Maria Groppi (M)

Department of Mathematical, Physical and Computer Sciences, University of Parma, Parco Area delle Scienze 53/A, Parma 43124, Italy.

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