Cargando…

A model-based opinion dynamics approach to tackle vaccine hesitancy

Uncovering the mechanisms underlying the diffusion of vaccine hesitancy is crucial in fighting epidemic spreading. Toward this ambitious goal, we treat vaccine hesitancy as an opinion, whose diffusion in a social group can be shaped over time by the influence of personal beliefs, social pressure, an...

Descripción completa

Detalles Bibliográficos
Autores principales: Ancona, Camilla, Iudice, Francesco Lo, Garofalo, Franco, De Lellis, Pietro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9276809/
https://www.ncbi.nlm.nih.gov/pubmed/35821508
http://dx.doi.org/10.1038/s41598-022-15082-0
_version_ 1784745809822089216
author Ancona, Camilla
Iudice, Francesco Lo
Garofalo, Franco
De Lellis, Pietro
author_facet Ancona, Camilla
Iudice, Francesco Lo
Garofalo, Franco
De Lellis, Pietro
author_sort Ancona, Camilla
collection PubMed
description Uncovering the mechanisms underlying the diffusion of vaccine hesitancy is crucial in fighting epidemic spreading. Toward this ambitious goal, we treat vaccine hesitancy as an opinion, whose diffusion in a social group can be shaped over time by the influence of personal beliefs, social pressure, and other exogenous actions, such as pro-vaccine campaigns. We propose a simple mathematical model that, calibrated on survey data, can predict the modification of the pre-existing individual willingness to be vaccinated and estimate the fraction of a population that is expected to adhere to an immunization program. This work paves the way for enabling tools from network control towards the simulation of different intervention plans and the design of more effective targeted pro-vaccine campaigns. Compared to traditional mass media alternatives, these model-based campaigns can exploit the structural properties of social networks to provide a potentially pivotal advantage in epidemic mitigation.
format Online
Article
Text
id pubmed-9276809
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-92768092022-07-14 A model-based opinion dynamics approach to tackle vaccine hesitancy Ancona, Camilla Iudice, Francesco Lo Garofalo, Franco De Lellis, Pietro Sci Rep Article Uncovering the mechanisms underlying the diffusion of vaccine hesitancy is crucial in fighting epidemic spreading. Toward this ambitious goal, we treat vaccine hesitancy as an opinion, whose diffusion in a social group can be shaped over time by the influence of personal beliefs, social pressure, and other exogenous actions, such as pro-vaccine campaigns. We propose a simple mathematical model that, calibrated on survey data, can predict the modification of the pre-existing individual willingness to be vaccinated and estimate the fraction of a population that is expected to adhere to an immunization program. This work paves the way for enabling tools from network control towards the simulation of different intervention plans and the design of more effective targeted pro-vaccine campaigns. Compared to traditional mass media alternatives, these model-based campaigns can exploit the structural properties of social networks to provide a potentially pivotal advantage in epidemic mitigation. Nature Publishing Group UK 2022-07-12 /pmc/articles/PMC9276809/ /pubmed/35821508 http://dx.doi.org/10.1038/s41598-022-15082-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ancona, Camilla
Iudice, Francesco Lo
Garofalo, Franco
De Lellis, Pietro
A model-based opinion dynamics approach to tackle vaccine hesitancy
title A model-based opinion dynamics approach to tackle vaccine hesitancy
title_full A model-based opinion dynamics approach to tackle vaccine hesitancy
title_fullStr A model-based opinion dynamics approach to tackle vaccine hesitancy
title_full_unstemmed A model-based opinion dynamics approach to tackle vaccine hesitancy
title_short A model-based opinion dynamics approach to tackle vaccine hesitancy
title_sort model-based opinion dynamics approach to tackle vaccine hesitancy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9276809/
https://www.ncbi.nlm.nih.gov/pubmed/35821508
http://dx.doi.org/10.1038/s41598-022-15082-0
work_keys_str_mv AT anconacamilla amodelbasedopiniondynamicsapproachtotacklevaccinehesitancy
AT iudicefrancescolo amodelbasedopiniondynamicsapproachtotacklevaccinehesitancy
AT garofalofranco amodelbasedopiniondynamicsapproachtotacklevaccinehesitancy
AT delellispietro amodelbasedopiniondynamicsapproachtotacklevaccinehesitancy
AT anconacamilla modelbasedopiniondynamicsapproachtotacklevaccinehesitancy
AT iudicefrancescolo modelbasedopiniondynamicsapproachtotacklevaccinehesitancy
AT garofalofranco modelbasedopiniondynamicsapproachtotacklevaccinehesitancy
AT delellispietro modelbasedopiniondynamicsapproachtotacklevaccinehesitancy