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Game Theory of Social Distancing in Response to an Epidemic
Open accessAbstract
Social distancing practices are changes in behavior that prevent disease transmission by reducing contact rates between susceptible individuals and infected individuals who may transmit the disease. Social distancing practices can reduce the severity of an epidemic, but the benefits of social distancing depend on the extent to which it is used by individuals. Individuals are sometimes reluctant to pay the costs inherent in social distancing, and this can limit its effectiveness as a control measure. This paper formulates a differential-game to identify how individuals would best use social distancing and related self-protective behaviors during an epidemic. The epidemic is described by a simple, well-mixed ordinary differential equation model. We use the differential game to study potential value of social distancing as a mitigation measure by calculating the equilibrium behaviors under a variety of cost-functions. Numerical methods are used to calculate the total costs of an epidemic under equilibrium behaviors as a function of the time to mass vaccination, following epidemic identification. The key parameters in the analysis are the basic reproduction number and the baseline efficiency of social distancing. The results show that social distancing is most beneficial to individuals for basic reproduction numbers around 2. In the absence of vaccination or other intervention measures, optimal social distancing never recovers more than 30% of the cost of infection. We also show how the window of opportunity for vaccine development lengthens as the efficiency of social distancing and detection improve.
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Statistical physics of vaccination
Wang, Z., Bauch, C. T., Bhattacharyya, S., d'Onofrio, A., Manfredi, P., Perc, M., Perra, N., Salathé, M., & Zhao, D. (2016) · Physics Reports · doi:10.1016/j.physrep.2016.10.006 · Cited by 872
Behavioural change models for infectious disease transmission: a systematic review (2010–2015)
Verelst, F., Willem, L., & Beutels, P. (2016) · Journal of The Royal Society Interface · doi:10.1098/rsif.2016.0820 · Cited by 382
Xie, W., Campbell, S., & Zhang, W. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2008868117 · Cited by 109
Schnyder, S. K., Molina, J. J., Yamamoto, R., & Turner, M. S. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2409362122 · Cited by 12
Metadata
- Authors
- Reluga, T. C.
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2010-05-27
- Volume
- 6
- Issue
- 5
- Pages
- e1000793
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- OpenAlex
- W1970112752
- Cited by
- 507
- References
- 0
- FWCI
- 10.73
- Type
- journal article
- Language
- en
- Open access
- gold
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- Reluga, T. C. (2010). Game Theory of Social Distancing in Response to an Epidemic. PLoS Computational Biology. https://doi.org/10.1371/journal.pcbi.1000793
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