Irrational behaviour-induced suppression, enhancement and oscillations of voluntary vaccination: A stochastic model with delays

We investigate how human irrationality and memory shapes voluntary vaccine uptake in the absence of disease. Building on a deterministic imitation game framework, after providing its analytical solution, we show that finite-population stochasticity alone produces either vaccine-free or full-coverage states, but with fixation times so long that the mean-field ODE model remains valid for large population sizes. To capture rapid irrational swings in public sentiment, we model them using white noise, deriving an SDE whose stationary density undergoes noise-induced transitions as noise intensity crosses critical thresholds. Larger noise can switch the population to either disease-free or full-coverage regimes, and very strong noise yields stochastic bistability reminiscent of phase transitions. Numerical simulations reveal very slow transients and rich behaviors when delays and noise interact. In particular, noise-induced quasi-cycles can onset. Generalizing to fat-tailed Cauchy noise, we find that heavy-tailed fluctuations increase the probability of fixation at zero or full coverage. Fluctuations in the imitation rate parameter produce large amplitude cycle distortions, occasionally destroying cyclic patterns. Finally, we show that a public health campaign term with ‘intensity’ exceeding a noise-dependent threshold eliminates the vaccine-free attractor and stabilizes full coverage.

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Publication Details

Journal
Physica D Nonlinear Phenomena
Published
2026-02-18
DOI
https://doi.org/10.1016/j.physd.2026.135143
Primary Topic
stochastic dynamics and bifurcation
Type
article
Field-Weighted Citation Impact
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article

Irrational behaviour-induced suppression, enhancement and oscillations of voluntary vaccination: A stochastic model with delays

Fabio Anselmi, P.F. Manfredi, Alberto d’Onofrio, Chris T. Bauch et al.
Physica D Nonlinear Phenomena
stochastic dynamics and bifurcation
article

Irrational behaviour-induced suppression, enhancement and oscillations of voluntary vaccination: A stochastic model with delays

Fabio Anselmi, P.F. Manfredi, Alberto d’Onofrio, Chris T. Bauch, Lorenzo Cabriel
article en

Abstract

We investigate how human irrationality and memory shapes voluntary vaccine uptake in the absence of disease. Building on a deterministic imitation game framework, after providing its analytical solution, we show that finite-population stochasticity alone produces either vaccine-free or full-coverage states, but with fixation times so long that the mean-field ODE model remains valid for large population sizes. To capture rapid irrational swings in public sentiment, we model them using white noise, deriving an SDE whose stationary density undergoes noise-induced transitions as noise intensity crosses critical thresholds. Larger noise can switch the population to either disease-free or full-coverage regimes, and very strong noise yields stochastic bistability reminiscent of phase transitions. Numerical simulations reveal very slow transients and rich behaviors when delays and noise interact. In particular, noise-induced quasi-cycles can onset. Generalizing to fat-tailed Cauchy noise, we find that heavy-tailed fluctuations increase the probability of fixation at zero or full coverage. Fluctuations in the imitation rate parameter produce large amplitude cycle distortions, occasionally destroying cyclic patterns. Finally, we show that a public health campaign term with ‘intensity’ exceeding a noise-dependent threshold eliminates the vaccine-free attractor and stabilizes full coverage.

Physica D Nonlinear PhenomenaVol. 489
University of Pisa (IT), University of Trieste (IT), University of Waterloo (CA)
Good health and well-being
Openalex Percentile: Top 49%
stochastic dynamics and bifurcation
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Irrational behaviour-induced suppression, enhancement and oscillations of voluntary vaccination: A stochastic model with delays — Fabio Anselmi, P.F. Manfredi, et al. · Physica D Nonlinear Phenomena (2026) | TGRS Research Map | TGRS