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Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes

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  • Anupama Sharma
  • Shakti N Menon
  • V Sasidevan
  • Sitabhra Sinha

Abstract

The effectiveness of a mass vaccination program can engender its own undoing if individuals choose to not get vaccinated believing that they are already protected by herd immunity. This would appear to be the optimal decision for an individual, based on a strategic appraisal of her costs and benefits, even though she would be vulnerable during subsequent outbreaks if the majority of the population argues in this manner. We investigate how voluntary vaccination can nevertheless emerge in a social network of rational agents, who make informed decisions whether to be vaccinated, integrated with a model of epidemic dynamics. The information available to each agent includes the prevalence of the disease in their local network neighborhood and/or globally in the population, as well as the fraction of their neighbors that are protected against the disease. Crucially, the payoffs governing the decision of agents vary with disease prevalence, resulting in the vaccine uptake behavior changing in response to contagion spreading. The collective behavior of the agents responding to local prevalence can lead to a significant reduction in the final epidemic size, particularly for less contagious diseases having low basic reproduction number R 0. Near the epidemic threshold (R 0 ≈ 1) the use of local prevalence information can result in divergent responses in the final vaccine coverage. Our results suggest that heterogeneity in the risk perception resulting from the spatio-temporal evolution of an epidemic differentially affects agents’ payoffs, which is a critical determinant of the success of voluntary vaccination schemes.Author summary: A major factor underlying the success of voluntary vaccination schemes is the public perception about the costs and benefits associated with vaccines. Individuals may avoid vaccination if they perceive the risk of infection to be low compared to the potential hazards and inconveniences associated with getting vaccinated. However, in the course of an epidemic outbreak individuals may opt to vaccinate because of the associated higher risk perception. Modeling individual decision-making in the presence of an evolving epidemic using games, we show that spatial heterogeneity in the vaccine-uptake behavior emerges with the spread of disease on social networks. Our results highlight the crucial importance of the information source shaping an individual’s risk perception for achieving high vaccine coverage.

Suggested Citation

  • Anupama Sharma & Shakti N Menon & V Sasidevan & Sitabhra Sinha, 2019. "Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes," PLOS Computational Biology, Public Library of Science, vol. 15(5), pages 1-18, May.
  • Handle: RePEc:plo:pcbi00:1006977
    DOI: 10.1371/journal.pcbi.1006977
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    References listed on IDEAS

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    Cited by:

    1. Shraddha Pathak & Ankur A. Kulkarni, 2022. "A Scalable Bayesian Persuasion Framework for Epidemic Containment on Heterogeneous Networks," Papers 2207.11578, arXiv.org.
    2. Rastko Jovanović & Miloš Davidović & Ivan Lazović & Maja Jovanović & Milena Jovašević-Stojanović, 2021. "Modelling Voluntary General Population Vaccination Strategies during COVID-19 Outbreak: Influence of Disease Prevalence," IJERPH, MDPI, vol. 18(12), pages 1-18, June.
    3. Zuo, Chao & Ling, Yuting & Zhu, Fenping & Ma, Xinyu & Xiang, Guochun, 2023. "Exploring epidemic voluntary vaccinating behavior based on information-driven decisions and benefit-cost analysis," Applied Mathematics and Computation, Elsevier, vol. 447(C).
    4. Panicker, Akhil & Sasidevan, V., 2024. "Social adaptive behavior and oscillatory prevalence in an epidemic model on evolving random geometric graphs," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).

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