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Modeling the effect of observational social learning on parental decision-making for childhood vaccination and diseases spread over household networks.
Oraby, Tamer; Balogh, Andras.
Afiliação
  • Oraby T; School of Mathematical and Statistical Sciences, The University of Texas Rio Grande Valley, Edinburg, TX, United States.
  • Balogh A; School of Mathematical and Statistical Sciences, The University of Texas Rio Grande Valley, Edinburg, TX, United States.
Front Epidemiol ; 3: 1177752, 2023.
Article em En | MEDLINE | ID: mdl-38455928
ABSTRACT
In this paper, we introduce a novel model for parental decision-making about vaccinations against a childhood disease that spreads through a contact network. This model considers a bilayer network comprising two overlapping networks, which are either Erdos-Rényi (random) networks or Barabási-Albert networks. The model also employs a Bayesian aggregation rule for observational social learning on a social network. This new model encompasses other decision models, such as voting and DeGroot models, as special cases. Using our model, we demonstrate how certain levels of social learning about vaccination preferences can converge opinions, influencing vaccine uptake and ultimately disease spread. In addition, we explore how two different cultures of social learning affect the establishment of social norms of vaccination and the uptake of vaccines. In every scenario, the interplay between the dynamics of observational social learning and disease spread is influenced by the network's topology, along with vaccine safety and availability.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article