Models for optimally controlling varicella and herpes zoster by varicella vaccination: a comparative study.


Journal

Medical & biological engineering & computing
ISSN: 1741-0444
Titre abrégé: Med Biol Eng Comput
Pays: United States
ID NLM: 7704869

Informations de publication

Date de publication:
May 2019
Historique:
received: 12 09 2017
accepted: 04 12 2018
pubmed: 18 1 2019
medline: 19 9 2019
entrez: 18 1 2019
Statut: ppublish

Résumé

The introduction of mass vaccination against Varicella-Zoster-Virus (VZV) is being delayed in many European countries mainly because of the "fear" of a subsequent boom in natural herpes zoster (HZ) incidence in the first decades after the initiation of vaccination, caused by the expected decline in the protective effect of natural immunity boosting due to reduced virus circulation. Optimal control theory has proven to be a successful tool in understanding ways to curtail the spread of infectious diseases by devising the optimal disease intervention strategies. In this paper, we describe how a reduced 'toy' model can extract the essentials of the dynamics of the VZV transmission and reactivation in case of the study of optimal paths of varicella immunization programs. Results obtained using different optimization approaches are compared with the ones of a more realistic age-structured model. The reduced model shows some unreliable predictions in regards of model time scales about herpes zoster dynamic; nevertheless, it is able to reproduce the main qualitative dynamic of the more realistic model to the different optimization problems, while requiring a minimal number of parameters to be identified. Graphical abstract ᅟ.

Identifiants

pubmed: 30652233
doi: 10.1007/s11517-018-1938-5
pii: 10.1007/s11517-018-1938-5
doi:

Substances chimiques

Chickenpox Vaccine 0

Types de publication

Comparative Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1121-1132

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Auteurs

Monica Betta (M)

IMT School for Advanced Studies, Piazza S. Francesco 19, 55100, Lucca, Italy. monica.betta@imtlucca.it.
Department of Information Engineering (DIE), University of Pisa, Via G. Caruso 16, 56122, Pisa, Italy. monica.betta@imtlucca.it.

Alberto Landi (A)

Department of Information Engineering (DIE), University of Pisa, Via G. Caruso 16, 56122, Pisa, Italy.

Piero Manfredi (P)

Department of Economics and Management, University of Pisa, Via Cosimo Ridolfi 10, 56124, Pisa, Italy.

Marco Laurino (M)

Institute of Clinical Physiology, National Research Council, Via Giuseppe Moruzzi 1, 56124, Pisa, Italy.

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Classifications MeSH