Graduate Program on Bioinformatics and Computational Biology, Iowa State University, Ames, Iowa, United States of America.
Department of Mathematics, Iowa State University, Ames, Iowa, United States of America.
PLoS One. 2021 Aug 2;16(8):e0255543. doi: 10.1371/journal.pone.0255543. eCollection 2021.
Since the outbreak of the global COVID-19 pandemic, social distancing has been known to everyone and recommended almost everywhere everyday. Social distancing has been and will be one of the most effective measures and sometimes, the only available one for fighting epidemics and saving lives. However, it has not been so clear how social distancing should be practiced or managed, especially when it comes to regulating everyone's otherwise normal social activities. The debate on how to implement social distancing often leads to a heated political argument, while research on the subject is lacking. This paper is to provide a theoretical basis for the understanding of the scientific nature of social distancing by considering it as a social dilemma game played by every individual against his/her population. From this perspective, every individual needs to make a decision on how to engage in social distancing, or risk being trapped into a dilemma either exposing to deadly diseases or getting no access to necessary social activities. As the players of the game, the individual's decisions depend on the population's actions and vice versa, and an optimal strategy can be found when the game reaches an equilibrium. The paper shows how an optimal strategy can be determined for a population with either closely related or completely separated social activities and with either single or multiple social groups, and how the collective behaviors of social distancing can be simulated by following every individual's actions as the distancing game progresses. The simulation results for populations of varying sizes and complexities are presented, which not only justify the choices of the strategies based on the theoretical analysis, but also demonstrate the convergence of the individual actions to an optimal distancing strategy in silico and possibly in natura as well, if every individual makes rational distancing decisions.
自全球 COVID-19 大流行爆发以来，社交距离已广为人知，几乎每天都在世界各地被推荐。社交距离一直是且将是对抗流行病和拯救生命的最有效措施之一，有时甚至是唯一可用的措施。然而，如何实施社交距离措施尚不清楚，特别是在规范每个人的正常社交活动方面。关于如何实施社交距离的争论往往会引发激烈的政治争论，而关于这个主题的研究却很少。本文通过将其视为每个人针对其所在人群进行的社会困境博弈，为理解社交距离的科学性提供了理论依据。从这个角度来看，每个人都需要决定如何进行社交距离措施，否则将面临暴露于致命疾病或无法获得必要社交活动的困境。作为博弈的参与者，个人的决策取决于人群的行动，反之亦然，当博弈达到平衡时，可以找到最佳策略。本文展示了如何为具有密切相关或完全分离的社交活动以及具有单个或多个社会团体的人群确定最佳策略，以及如何通过随着距离博弈的进行跟踪每个个体的行为来模拟社交距离的集体行为。本文还呈现了不同规模和复杂度的人群的模拟结果，这些结果不仅证明了基于理论分析的策略选择是合理的，而且还表明如果每个个体都做出理性的距离决策，个体行为将在计算机模拟中并可能在现实中收敛到最佳的距离策略。
