Epidemic prevalence information on social networks can mediate emergent collective outcomes in voluntary vaccine schemes
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DOI: 10.1371/journal.pcbi.1006977
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Cited by:
- Pathak, Shraddha & Kulkarni, Ankur A., 2025. "A scalable Bayesian persuasion framework for epidemic containment on heterogeneous networks," Journal of Mathematical Economics, Elsevier, vol. 119(C).
- 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).
- Shraddha Pathak & Ankur A. Kulkarni, 2022. "A Scalable Bayesian Persuasion Framework for Epidemic Containment on Heterogeneous Networks," Papers 2207.11578, arXiv.org.
- 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.
- 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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