ArticleJournal of theoretical biology2022
A behavioural modelling approach to assess the impact of COVID-19 vaccine hesitancy.
Article in Journal of theoretical biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.
- Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review.Systematic reviews · 2024Pooled it
- Bayesian uncertainty quantification to identify population level vaccine hesitancy behaviours.PloS one · 2026Article
- Modelling behavioural changes and vaccination in the transmission of respiratory viruses with co-infection.Journal of mathematical biology · 2025Article
- Article
- Evaluating vaccination timing, hesitancy and effectiveness to prevent future outbreaks: insights from COVID-19 modelling and transmission dynamics.Royal Society open science · 2024Article
- Predicting Covid-19 pandemic waves with biologically and behaviorally informed universal differential equations.Heliyon · 2024Article
- Exploring epidemic voluntary vaccinating behavior based on information-driven decisions and benefit-cost analysis.Applied mathematics and computation · 2023Article
- Kinetic Models for Epidemic Dynamics in the Presence of Opinion Polarization.Bulletin of mathematical biology · 2023Article
- A Fractional Order Model Studying the Role of Negative and Positive Attitudes towards Vaccination.Vaccines · 2022Article
- Analysis of COVID-19 Spread in Tokyo through an Agent-Based Model with Data Assimilation.Journal of clinical medicine · 2022Article
- Effects of Vaccination Efficacy on Wealth Distribution in Kinetic Epidemic Models.Entropy (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We introduce a compartmental epidemic model to describe the spread of COVID-19 within a population, assuming that a vaccine is available, but vaccination is not mandatory. The model takes into account vaccine hesitancy and the refusal of vaccination by individuals, which take their decision on vaccination based on both the present and past information about the spread of the disease. Theoretical analysis and simulations show that voluntary vaccination can certainly reduce the impact of the disease but is unable to eliminate it. We also demonstrate how the information-related parameters affect the dynamics of the disease. In particular, vaccine hesitancy and refusal are better contained in case of widespread information coverage and short-term memory. Finally, the possible impact of seasonality on the spread of the disease is investigated.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.