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

KM Ariful Kabir, Kazuki Kuga, Jun Tanimoto

Research output: Contribution to journalArticle

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 languageEnglish
Article number109548
JournalChaos, solitons and fractals
Volume132
DOIs
Publication statusPublished - Mar 2020

Fingerprint

Dynamic Games
Vaccination
Heterogeneous networks
Heterogeneous Networks
games
Complex networks
Complex Networks
Risk assessment
Scale-free Networks
Epidemic Model
Spatial Structure
Risk Assessment
risk assessment
Random Graphs
Topology
Game
Network Topology
Imperfect
infectious diseases
Updating

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 journalArticle

@article{08c85a9c74844898a755a2240dcea1be,
title = "The impact of information spreading on epidemic vaccination game dynamics in a heterogeneous complex network- A theoretical approach",
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.",
author = "Kabir, {KM Ariful} and Kazuki Kuga and Jun Tanimoto",
year = "2020",
month = "3",
doi = "10.1016/j.chaos.2019.109548",
language = "English",
volume = "132",
journal = "Chaos, Solitons and Fractals",
issn = "0960-0779",
publisher = "Elsevier Limited",

}

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.

UR - http://www.scopus.com/inward/record.url?scp=85075982317&partnerID=8YFLogxK

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 -