Individual Altruism Cannot Overcome Congestion Effects in a Global Pandemic Game

• Main Authors: Brown, Philip N, Collins, Brandon, Hill, Colton, Barboza, Gia, Hines, Lisa
• Format: Journal Article
• Language: English
• Published: 24.03.2021
• Subjects: Computer Science - Computer Science and Game Theory; Computer Science - Systems and Control
• DOI: 10.48550/arxiv.2103.14538

A key challenge in responding to public health crises such as COVID-19 is the difficulty of predicting the results of feedback interconnections between the disease and society. As a step towards understanding these interconnections, we pose a simple game-theoretic model of a global pandemic in which individuals can choose where to live, and we investigate the global behavior that may emerge as a result of individuals reacting locally to the competing costs of isolation and infection. We study the game-theoretic equilibria that emerge from this setup when the population is composed of either selfish or altruistic individuals. First, we demonstrate that as is typical in these types of games, selfish equilibria are in general not optimal, but that all stable selfish equilibria are within a constant factor of optimal. Second, there exist infinitely-many stable altruistic equilibria; all but finitely-many of these are worse than the worst selfish equilibrium, and the social cost of altruistic equilibria is unbounded. Our work is in sharp contrast to recent work in network congestion games in which all altruistic equilibria are socially optimal. This suggests that a population without central coordination may react very poorly to a pandemic, and that individual altruism could even exacerbate the problem.