Subsidy policy with punishment mechanism can promote voluntary vaccination behaviors in structured populations

Wang, Jingrui; Zhang, Huizhen; Jin, Xing; Ma, Leyu; Chen, Yueren; Wang, Chao; Zhao, Jian; An, Tianbo

doi:10.1016/j.chaos.2023.113863

Cited by 7 publications

(2 citation statements)

References 44 publications

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“…The rapid development of network science has led more and more researchers to analyze the structure and dynamic processes in various complex systems from the perspective of network science [1][2][3][4][5][6][7][8]. In particular, the synchronization of complex networks has attracted many scholars to undertake in-depth research [9][10][11][12][13][14]. There are two key issues that have attracted widespread interest in this field: (1) how to analyze the stability of network synchronization dynamics; (2) how network structure affects synchronization dynamics.…”

Section: Introductionmentioning

confidence: 99%

Network Synchronization via Pinning Control from an Attacker-Defender Game Perspective

Pei,

Zhang,

Zhang

et al. 2024

Mathematics

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The pinning control of complex networks is a hot topic of research in network science. However, most studies on pinning control ignore the impact of external interference on actual control strategies. To more comprehensively evaluate network synchronizability via pinning control in the attack–defense confrontation scenario, the paper constructs an attacker-defender game model. In the model, the attacker needs to control nodes in the network as much as possible. The defender will do their best to interfere with the attacker’s control of the network. Through a series of experiments, we find that the random attack strategy is always the dominant strategy of the attacker in various equilibriums. On the other hand, the defender needs to constantly change dominant strategy in equilibrium according to the set of defense strategies and cost constraints. In addition, scale-free networks with different network metrics can also influence the payoff matrix of the game. In particular, the average degree of the network has an obvious impact on the attacker’s payoff. Moreover, we further verify the correctness of the proposed attacker-defender game through a simulation based on the specific network synchronization dynamics. Finally, we conduct a sensitivity analysis in different network structures, such as the WS small-world network, the ER random network, and the Google network, to comprehensively evaluate the performance of the model.

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Section: Introductionmentioning

confidence: 99%

Network Synchronization via Pinning Control from an Attacker-Defender Game Perspective

Pei,

Zhang,

Zhang

et al. 2024

Mathematics

Self Cite

View full text Add to dashboard Cite

show abstract

“…Their findings indicate that the network structure can improve vaccination coverage when cost of vaccination is small; conversely, the network structure inhibits vaccination coverage when cost of vaccination is large [12]. Recently, a great deal of study has also focused on the impacts of various factors on individual vaccination behavior, such as perception [21], stubborn [22], social influence [23], different subsidy strategies [16,24,25], strategy conformity [15,26], anti-social behavior [27], hypergraph structure [28] and so on.…”

Section: Introductionmentioning

confidence: 99%

Double-edged sword role of reinforcement learning based decision-makings on vaccination behavior

Kan,

Zhang,

Zhang

2023

Front. Phys.

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Pre-emptive vaccination has been proven to be the most effective measure to control influenza outbreaks. However, when vaccination behavior is voluntary, individuals may face the vaccination dilemma owing to the two sides of vaccines. In view of this, many researchers began to use evolutionary game theory to model the vaccination decisions of individuals. Many existing models assume that individuals in networks use the Fermi function based strategy to update their vaccination decisions. As we know, human beings have strong learning capability and they may continuously search for the optimal strategy based on the surrounding environments. Hence, it is reasonable to use the reinforcement learning (RL) strategy to reflect the vaccination decisions of individuals. To this end, we here explore a mixed updating strategy for the vaccination decisions, specifically, some individuals called intelligent agents update their vaccination decisions based on the RL strategy, and the other individuals called regular agents update their decisions based on the Fermi function. We then investigate the impact of RL strategy on the vaccination behavior and the epidemic dynamics. Through extensive experiments, we find that the RL strategy plays a double-edged sword role: when the vaccination cost is not so high, more individuals are willing to choose vaccination if more individuals adopt the RL strategy, leading to the significant suppression of epidemics. On the contrary, when the vaccination cost is extremely high, the vaccination coverage is dramatically reduced, inducing the outbreak of the epidemic. We also analyze the underlying reasons for the double-edged sword role of the RL strategy.

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Effect of vaccine efficacy on vaccination behavior with adaptive perception

Wang,

Zhang,

et al. 2024

Applied Mathematics and Computation

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Subsidy policy with punishment mechanism can promote voluntary vaccination behaviors in structured populations

Cited by 7 publications

References 44 publications

Network Synchronization via Pinning Control from an Attacker-Defender Game Perspective

Network Synchronization via Pinning Control from an Attacker-Defender Game Perspective

Double-edged sword role of reinforcement learning based decision-makings on vaccination behavior

Effect of vaccine efficacy on vaccination behavior with adaptive perception

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