Exploring voluntary vaccination with bounded rationality through reinforcement learning

Benyun SHI, Guangliang Liu, Hongjun Qiu*, Zhen Wang, Yizhi Ren, Dan Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Evidence shows that there exists a complex interaction between human vaccinating behaviors and disease prevalence during an epidemic. Usually, rational individuals make vaccinating decisions by strategically evaluating the cost of vaccination and the risk of infection. While in reality, individuals’ decisions can also be influenced by their social acquaintances. In this paper, we present a reinforcement learning-based mechanism to characterize human decision-making process with bounded rationality, which takes into consideration both individuals’ rational decisions and social influence from their neighbors. Specifically, we investigate human voluntary vaccinating behaviors in the face of flu-like seasonal diseases in locally-mixed social networks, where each individual together with his/her neighbors forms a well-mixed environment. Through carrying out simulations, we evaluate the performance of decision-making mechanisms with/without reinforcement learning in terms of vaccine coverage, final epidemic size, average payoff and vaccine effectiveness under different settings of relative cost of vaccination and infection. Simulation results show that reinforcement learning can improve the vaccine effectiveness through balancing individuals’ rationality and social influence. This emphasizes the importance of appropriately utilizing human bounded rationality in preventing disease epidemics through voluntary vaccination policies.

Original languageEnglish
Pages (from-to)171-182
Number of pages12
JournalPhysica A: Statistical Mechanics and its Applications
Volume515
DOIs
Publication statusPublished - 1 Feb 2019

Scopus Subject Areas

  • Statistics and Probability
  • Condensed Matter Physics

User-Defined Keywords

  • Bounded rationality
  • Disease epidemics
  • Reinforcement learning
  • Social influence
  • Voluntary vaccination

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