Stochastic resonance effect observed in a vaccination game with effectiveness framework obeying the SIR process on a scale-free network

Kouki Okita, Yuichi Tatsukawa, Shinobu Utsumi, Md. Rajib Arefin, Md. Anowar Hossain and Jun Tanimoto

Chaos, Solitons & Fractals, 2023, vol. 167, issue C

Abstract: This study investigates a standard vaccination game presuming the repeated-season framework, in which we mutually merge the dynamics of disease spread, which obeys the SIR process, and human decision-making as regards whether or not to get vaccinated at the beginning of each season with reference to the evolutionary game theory. We herein presume the Barabási–Albert scale-free (BA-SF) graph as an underlying network. Accordingly, we explore whether or not an additive noise to the transmission rate brings an advantageous stochastic resonance effect for confining a disease's spread. The results show that with a higher vaccination cost and/or a lower vaccine efficacy, the stochastic noise has no gap in vaccination coverage (VC) with the default without noise case, but brings a smaller final epidemic size (FES). In contrast, at a lower vaccination cost and a higher vaccine efficacy, the additive stochastic noise brings a smaller VC that consequently results in a larger FES than the default without noise case. This phenomenon is completely different from our previously reported bolstered enhancement effect of network reciprocity, in which each element of a payoff matrix is exposed to stochastic noise.

Keywords: Mathematical epidemiology; SIR process; Vaccination game; Evolutionary game theory; Multi agent simulation (MAS) (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:167:y:2023:i:c:s0960077922012085

DOI: 10.1016/j.chaos.2022.113029

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