Game Theory : A Case of Infectious Diseases

Authors

  • Prof. Adekunle A. Yinka  Department of Computer Science, Babcock University, Ilishan-Remo, Nigeria
  • Dr. Seun Ebiesuwa  Department of Computer Science, Babcock University, Ilishan-Remo, Nigeria
  • Ohwo Onome Blaise  Department of Computer Science, Babcock University, Ilishan-Remo, Nigeria

DOI:

https://doi.org/10.32628/CSEIT20647

Keywords:

Game Theory, Epidemiology, Pandemic, Healthcare

Abstract

Game theory is a mathematical model which deals with interactions between various entities by analyzing the strategies and choices. In today’s world, Game Theory is being extensively used in fields like computer science, economics, sociology, political science, and so on, due to its versatile nature and applications in numerous conflicts and problems. The application of game theory has been extended to real life problems also due to its versatility and robustness. In this research, various game theory methodologies applied during pandemic was reviewed. Various aspects of these methodologies were highlighted such as methods applied, description, expected result and limitation. This research will act as a reliable and efficient way of understanding the concept of game theory and its application in combating infectious diseases, analyze and eventually understand different strategic scenarios. The main importance of game theory is to formulate the alternative strategy to compete with one another and in the same sense it is an essential tool for decision making process according to fluctuations in relevant contents. These reviewed methodologies would be further categorized into prevent, control or both based on the application they favour most.

References

  1. Alexis, D., & Maciej, F. B. (2020). Game theory of vaccination and depopulation for managing livestock diseases and zoonoses on small-scale farms. Epidemics, 1-13. doi:10.1016/j.epidem.2019.100370
  2. Bellal, A. B. (2016). AN OVERVIEW OF GAME THEORY AND SOME APPLICATIONS. Philosophy and Progress, 112-128. doi:10.3329/pp.v59i1-2.36683
  3. Ceyhun, E., Jeff, S. S., & Joshua, S. W. (2017). Disease dynamics in a stochastic network game: a little empathy goes a long way in averting outbreaks. Scientific Reports, 1-13. doi:10.1038/srep44122
  4. Cui, J., Takeuchi, Y., & Saito, Y. (2006). Spreading disease with transport-related infection. Journal of Theoretical Biology, 376–390. doi:10.1016/j.jtbi.2005.08.005
  5. Gérvas, J., Starfield, B., & Heath, I. (2008). Is clinical prevention better than cure? The Lancet, 372(9654), 1997–1999. doi:10.1016/S0140-6736(08)61843-7
  6. Gholamreza, A., Madjid, E. G., & Choonkil, P. (2019). The behavioral model and game theory. PALGRAVE COMMUNICATIONS, 1-8. doi:10.1057/s41599-019-0265-2
  7. Gordon, G. M., & Ray, D. (2013). Game theory and plant ecology. Ecology Letters, 1-11. doi:10.1111/ele.12071
  8. Gregory, D., & Bryan, C. M. (27 de June de 2019). Psychological game theory in public choice. Public Choice, 1-22. doi:10.1007/s11127-019-00676-6
  9. Joseph, Y. H., & Rafael, P. (7 de May de 2018). Game theory with translucent players. International Journal Game Theory, 1-28. doi:10.1007/s00182-018-0626-x
  10. Kostić-Ljubisavljević, A., Radonjić, V., Mladenović, S., & Aćimović-Raspopović, V. (2011). An Application of Game Theory for the Selection of Traffic Routing Method in Interconnected NGN. En V. Snasel, J. Platos, & E. El-Qawasmeh, ICDIPC 2011, Part II, CCIS 189 (págs. 107-122). Berlin Heidelberg: Springer-Verlag .
  11. Marios, M., Vicky, P., & Paul, S. (2007). Algorithmic Game Theory and Applications. 285-313.
  12. Mark, T., Mike, B., Denis, R., & Somasundaram, R. (2017). Game Theory for Computer Games Design. Games and Culture, 1-13. doi:10.1177/1555412017740497
  13. Muntasir, A., Ariful, K. K., & Jun, T. (2020). Based on mathematical epidemiology and evolutionary game theory, which is more effective: quarantine or isolation policy? Journal of Statistical Mechanics: Theory and Experiment, 1-29. doi:10.1088/1742-5468/ab75ea
  14. Sajjan, S., Sankardas, R., & Dipankar, D. (2010). Game Theory for Cyber Security. 1-4.
  15. Sasmita, P. A., Sha, M., Yu-Ju, W., Yu-Ping, M., Rui-Xue, Y., Qing-Zhi, W., . . . Huan, Z. (2020). Epidemiology, causes, clinical manifestation and diagnosis, prevention and control of coronavirus disease (COVID-19) during the early outbreak period: a scoping review. Infectious Diseases of Poverty, 1-12. doi:10.1186/s40249-020-00646-x
  16. Shi, Z., Chris, T. B., & Daihai, H. (2018). Strategic decision making about travel during disease outbreaks: a game theoretical approach. J. Royal Society Interface, 1-10.
  17. Simon, M. H., & Kevin, J. S. (2013). Methodology in Biological Game Theory. Britain Journal of Philosophical Sciences, 637–658.
  18. Sofía, J., Virginie, S., & Romulus, B. (2017). Prevention of treatable infectious diseases: A game-theoretic approach. Vaccine, 1-7.
  19. Timothy, C. R. (2010). Game Theory of Social Distancing in Response to an Epidemic. PLoS Computational Biology, 6(5), 1-10. doi:10.1371/journal.pcbi.1000793

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

Downloads

Published

2020-08-30

Issue

Volume 6, Issue 4, July-August-2020

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Prof. Adekunle A. Yinka, Dr. Seun Ebiesuwa, Ohwo Onome Blaise, " Game Theory : A Case of Infectious Diseases" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 4, pp.202-213, July-August-2020. Available at doi : https://doi.org/10.32628/CSEIT20647