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Public Goods Games in Disease Evolution and Spread

Christo Morison et al.

Dynamic Games and Applications2025https://doi.org/10.1007/s13235-025-00619-5article
AJG 1ABDC B
Weight
0.44

Abstract

Cooperation arises in nature at every scale, from within cells to entire ecosystems. Public goods games (PGGs) are used to represent scenarios characterised by the conflict/dilemma between choosing cooperation as a socially optimal strategy and defection as an individually optimal strategy. Evolutionary game theory is often used to analyse the dynamics of behaviour emergence in this context. Here, we focus on PGGs arising in the disease modelling of cancer evolution and the spread of infectious diseases. We use these two systems as case studies for the development of the theory and applications of PGGs, which we succinctly review. We also posit that applications of evolutionary game theory to decision-making in cancer, such as interactions between a clinician and a tumour, can learn from the PGGs studied in epidemiology, where cooperative behaviours such as quarantine and vaccination compliance have been more thoroughly investigated. Furthermore, instances of cellular-level cooperation observed in cancers point to a corresponding area of potential interest for modellers of other diseases, be they viral, bacterial or otherwise. We aim to demonstrate the breadth of applicability of PGGs in disease modelling while providing a starting point for those interested in quantifying cooperation arising in healthcare.

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https://doi.org/https://doi.org/10.1007/s13235-025-00619-5

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@article{christo2025,
  title        = {{Public Goods Games in Disease Evolution and Spread}},
  author       = {Christo Morison et al.},
  journal      = {Dynamic Games and Applications},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1007/s13235-025-00619-5},
}

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Evidence weight

0.44

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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