The impact of information spreading on epidemic vaccination game dynamics in a heterogeneous complex network- A theoretical approach

KM Ariful Kabir, Kazuki Kuga and Jun Tanimoto

Chaos, Solitons & Fractals, 2020, vol. 132, issue C

Abstract: A modified susceptible-vaccinated-infected-recovered (SIR/V) with unaware-aware (UA) epidemic model in heterogeneous networks is presented to study the effect of information spreading in the spatial structure of the vaccination game on epidemic dynamics. Two layers SIR/V epidemic model is considered to elucidate information spreading, where the fraction of susceptible, vaccinated and infected individuals are parted as unaware and aware state as each susceptible and vaccinated persons are allied with their infected neighbors by a spatial structure, say, an underlying network. The context deduces epidemic vaccination game with awareness influence dynamics in one single season followed by a strategy update process that refer an individual to take imperfect vaccination or not. We considered two different strategy updating rules: individual based risk assessment (IB-RA) and strategy-based risk assessment (SB-RA) to explore how different underlying network topologies, say, random graph and scale free networks, subsequently giving impact on the final epidemic size, vaccination coverage and average social payoff through the effect of information spreading on epidemic. Thus, it can be seen that, awareness can enhance the epidemic threshold effectiveness and lessen the spreading of infection in a scale free network other than random graph and homogeneous network.

Keywords: Social dilemma; Vaccination game; SIR model; Information spreading; Heterogeneous network (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (24)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:132:y:2020:i:c:s0960077919305053

DOI: 10.1016/j.chaos.2019.109548

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