TY - JOUR
T1 - Impact of imperfect vaccination and defense against contagion on vaccination behavior in complex networks
AU - Kuga, Kazuki
AU - Tanimoto, Jun
N1 - Funding Information:
This study was partially supported by Grant-in-Aid for Scientific Research from JSPS, Japan, KAKENHI (Grant No. 18K18924) and Kakihara Foundation awarded to Professor Tanimoto. We would like to express our gratitude to them.
PY - 2018/11/15
Y1 - 2018/11/15
N2 - We explore a mathematical framework of the vaccination game taking into account spatial structure, say, and degree distribution amid individuals. The framework presumes SIR/V dynamics in a season, which is followed by a strategy update process that estimates whether an individual will take a protecting measure, considering imperfect vaccination or defense against contagion. The numerical result based on multi-agent simulations (MAS) validates our theory, suggesting that a more heterogeneous spatial structure is vulnerable to an epidemic. This conclusion is consistent with the qualitative knowledge that a pandemic arises more easily in a scale-free network than in homogeneous networks because of the negative contribution of hub agents acting as super spreaders. Highlights - A new theoretical model is established for the vaccination game with a SIR/V model and either imperfect vaccination or intermediate measures. - The model considers degree distribution amid individuals, which significantly influences disease spreading. - The model is validated by simulation results. - The results prove that a more heterogeneous network is disadvantageous to prevent disease spreading.
AB - We explore a mathematical framework of the vaccination game taking into account spatial structure, say, and degree distribution amid individuals. The framework presumes SIR/V dynamics in a season, which is followed by a strategy update process that estimates whether an individual will take a protecting measure, considering imperfect vaccination or defense against contagion. The numerical result based on multi-agent simulations (MAS) validates our theory, suggesting that a more heterogeneous spatial structure is vulnerable to an epidemic. This conclusion is consistent with the qualitative knowledge that a pandemic arises more easily in a scale-free network than in homogeneous networks because of the negative contribution of hub agents acting as super spreaders. Highlights - A new theoretical model is established for the vaccination game with a SIR/V model and either imperfect vaccination or intermediate measures. - The model considers degree distribution amid individuals, which significantly influences disease spreading. - The model is validated by simulation results. - The results prove that a more heterogeneous network is disadvantageous to prevent disease spreading.
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U2 - 10.1088/1742-5468/aae84f
DO - 10.1088/1742-5468/aae84f
M3 - Article
AN - SCOPUS:85057621653
SN - 1742-5468
VL - 2018
JO - Journal of Statistical Mechanics: Theory and Experiment
JF - Journal of Statistical Mechanics: Theory and Experiment
IS - 11
M1 - 113402
ER -