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...
Autores principales: | , , , |
---|---|
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 |