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Vaccination Decisions in Triadic Interactions: A Coupled ODE Approach

DOI: 10.4236/jamp.2026.142041, PP. 785-803

Keywords: Triadic Game Theory, Vaccination Decision-Making, Coupled Ordinary Differential Equations, Emergent Behavior, Decision Anchor

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Abstract:

This paper presents a mathematical model of vaccination decision-making in small social groups using triadic game theory. It employs coupled ordinary differential equations to illustrate the evolution of vaccination intensities among three individuals, influenced by interaction coefficients that reflect their interconnected decisions. The analysis explores scenarios in which one individual’s vaccination stance remains fixed. When the first individual maintains a constant stance, the system exhibits exponential growth or decay. Conversely, if the second individual is fixed, the system displays oscillatory behavior with declining vaccination rates. Additionally, the model is extended to include two coupled triads involving five individuals, revealing emergent behaviors that are not present in isolated groups. The findings emphasize differences in group stability based on which member serves as the decision anchor. This research establishes a mathematical foundation for understanding collective behavior in small social clusters and suggests potential avenues for future studies on vaccination decision-making in families, friend groups, and workplaces.

References

[1]  Fine, P.E.M. and Clarkson, J.A. (1986) Individual versus Public Priorities in the Determination of Optimal Vaccination Policies. American Journal of Epidemiology, 124, 1012-1020.
https://doi.org/10.1093/oxfordjournals.aje.a114471

[2]  Geoffard, P. and Philipson, T. (1997) Disease Eradication: Private versus Public Vaccination. American Economic Review, 87, 222-230.
[3]  Xin, Y., Gerberry, D. and Just, W. (2019) Open-Minded Imitation Can Achieve Near-Optimal Vaccination Coverage. Journal of Mathematical Biology, 79, 1491-1514.
https://doi.org/10.1007/s00285-019-01401-z

[4]  Perisic, A. and Bauch, C.T. (2009) Social Contact Networks and Disease Eradicability under Voluntary Vaccination. PLOS Computational Biology, 5, e1000280.
https://doi.org/10.1371/journal.pcbi.1000280

[5]  Bauch, C.T., Galvani, A.P. and Earn, D.J.D. (2003) Group Interest versus Self-Interest in Smallpox Vaccination Policy. Proceedings of the National Academy of Sciences, 100, 10564-10567.
https://doi.org/10.1073/pnas.1731324100

[6]  Kumar, V., Bauch, C.T. and Bhattacharyya, S. (2024) A Game Theoretic Complex Network Model to Estimate the Epidemic Threshold under Individual Vaccination Behaviour and Adaptive Social Connections. Scientific Reports, 14, Article No. 29148.
https://doi.org/10.1038/s41598-024-79771-8

[7]  Oraby, T., Thampi, V. and Bauch, C.T. (2014) The Influence of Social Norms on the Dynamics of Vaccinating Behaviour for Paediatric Infectious Diseases. Proceedings of the Royal Society B: Biological Sciences, 281, Article ID: 20133172.
https://doi.org/10.1098/rspb.2013.3172

[8]  Chang, J.J., Chen, M.K., Alatas, V., et al. (2022) The Influence of Social Norms Varies with “Others” Groups: Evidence from COVID-19 Vaccination Intentions. Proceedings of the National Academy of Sciences, 119, e2118770119.
[9]  Wu, J., Liao, H., Wang, J.W. and Chen, T. (2023) Behavioral Change Models for Infectious Disease Transmission: A Systematic Review. Journal of Biomedical Informatics, 120, Article ID: 104070.
[10]  Granell, C., Gómez, S. and Arenas, A. (2013) Dynamical Interplay between Awareness and Epidemic Spreading in Multiplex Networks. Physical Review Letters, 111, Article ID: 128701.
https://doi.org/10.1103/physrevlett.111.128701

[11]  Salathé, M. and Bonhoeffer, S. (2008) The Effect of Opinion Clustering on Disease Outbreaks. Journal of The Royal Society Interface, 5, 1505-1508.
https://doi.org/10.1098/rsif.2008.0271

[12]  Sartori, F., Turchetto, M., Bellingeri, M., Scotognella, F., Alfieri, R., et al. (2022) A Comparison of Node Vaccination Strategies to Halt SIR Epidemic Spreading in Real-World Complex Networks. Scientific Reports, 12, Article No. 21355.
https://doi.org/10.1038/s41598-022-24652-1

[13]  Fügenschuh, M. and Fu, F. (2023) Overcoming Vaccine Hesitancy by Multiplex Social Network Targeting: An Analysis of Targeting Algorithms and Implications. Applied Network Science, 8, Article No. 67.
https://doi.org/10.1007/s41109-023-00595-y

[14]  Reluga, T.C. (2010) Game Theory of Social Distancing in Response to an Epidemic. PLOS Computational Biology, 6, e1000793.
https://doi.org/10.1371/journal.pcbi.1000793

[15]  Cardillo, A., Reyes-SuArez, C., Naranjo, F. and Gamez-Gardeales, J. (2020) Evolutionary Vaccination Dilemma in Complex Networks. Physical Review E, 101, Article ID: 012301.
[16]  Manfredi, P. and D’Onofrio, A. (2013) Modeling the Interplay between Human Behavior and the Spread of Infectious Diseases. Springer.
[17]  Teslya, A., Pham, T.M., Godijk, N.G., Kretzschmar, M.E., Bootsma, M.C.J. and Rozhnova, G. (2020) Impact of Self-Imposed Prevention Measures and Short-Term Government-Imposed Social Distancing on Mitigating and Delaying a COVID-19 Epidemic: A Modelling Study. PLOS Medicine, 17, e1003166.
https://doi.org/10.1371/journal.pmed.1003166

[18]  Kabir, K.M.A., Kuga, K. and Tanimoto, J. (2019) Analysis of SIR Epidemic Model with Information Spreading of Awareness. Chaos, Solitons & Fractals, 119, 118-125.
https://doi.org/10.1016/j.chaos.2018.12.017

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