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.
| Original language | English |
|---|---|
| Article number | 109548 |
| Journal | Chaos, solitons and fractals |
| Volume | 132 |
| DOIs | |
| Publication status | Published - Mar 2020 |
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All Science Journal Classification (ASJC) codes
- Statistical and Nonlinear Physics
- Mathematics(all)
- Physics and Astronomy(all)
- Applied Mathematics
Cite this
The impact of information spreading on epidemic vaccination game dynamics in a heterogeneous complex network- A theoretical approach. / Kabir, KM Ariful; Kuga, Kazuki; Tanimoto, Jun.
In: Chaos, solitons and fractals, Vol. 132, 109548, 03.2020.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - The impact of information spreading on epidemic vaccination game dynamics in a heterogeneous complex network- A theoretical approach
AU - Kabir, KM Ariful
AU - Kuga, Kazuki
AU - Tanimoto, Jun
PY - 2020/3
Y1 - 2020/3
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=85075982317&partnerID=8YFLogxK
U2 - 10.1016/j.chaos.2019.109548
DO - 10.1016/j.chaos.2019.109548
M3 - Article
AN - SCOPUS:85075982317
VL - 132
JO - Chaos, Solitons and Fractals
JF - Chaos, Solitons and Fractals
SN - 0960-0779
M1 - 109548
ER -