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Optimal time-profiles of public health intervention to shape voluntary vaccination for childhood diseases.
Buonomo, Bruno; Manfredi, Piero; d'Onofrio, Alberto.
Afiliação
  • Buonomo B; Department of Mathematics and Applications, University of Naples Federico II, via Cintia, 80126, Naples, Italy.
  • Manfredi P; Department of Economics and Management, University of Pisa, Via Ridolfi 1, 56124, Pisa, Italy.
  • d'Onofrio A; International Prevention Research Institute, 95 cours Lafayette, 69006, Lyon, France. alberto.donofrio@i-pri.org.
J Math Biol ; 78(4): 1089-1113, 2019 03.
Article em En | MEDLINE | ID: mdl-30390103
In order to seek the optimal time-profiles of public health systems (PHS) Intervention to favor vaccine propensity, we apply optimal control (OC) to a SIR model with voluntary vaccination and PHS intervention. We focus on short-term horizons, and on both continuous control strategies resulting from the forward-backward sweep deterministic algorithm, and piecewise-constant strategies (which are closer to the PHS way of working) investigated by the simulated annealing (SA) stochastic algorithm. For childhood diseases, where disease costs are much larger than vaccination costs, the OC solution sets at its maximum for most of the policy horizon, meaning that the PHS cannot further improve perceptions about the net benefit of immunization. Thus, the subsequent dynamics of vaccine uptake stems entirely from the declining perceived risk of infection (due to declining prevalence) which is communicated by direct contacts among parents, and unavoidably yields a future decline in vaccine uptake. We find that for relatively low communication costs, the piecewise control is close to the continuous control. For large communication costs the SA algorithm converges towards a non-monotone OC that can have oscillations.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Saúde Pública / Vacinação Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adult / Child / Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Saúde Pública / Vacinação Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adult / Child / Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article