Department of Mathematics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Department of Ecology & Evolutionary Biology, University of California, Los Angeles, California, United States of America.
PLoS Comput Biol. 2022 Nov 21;18(11):e1010670. doi: 10.1371/journal.pcbi.1010670. eCollection 2022 Nov.
Levels of sociality in nature vary widely. Some species are solitary; others live in family groups; some form complex multi-family societies. Increased levels of social interaction can allow for the spread of useful innovations and beneficial information, but can also facilitate the spread of harmful contagions, such as infectious diseases. It is natural to assume that these contagion processes shape the evolution of complex social systems, but an explicit account of the dynamics of sociality under selection pressure imposed by contagion remains elusive. We consider a model for the evolution of sociality strategies in the presence of both a beneficial and costly contagion. We study the dynamics of this model at three timescales: using a susceptible-infectious-susceptible (SIS) model to describe contagion spread for given sociality strategies, a replicator equation to study the changing fractions of two different levels of sociality, and an adaptive dynamics approach to study the long-time evolution of the population level of sociality. For a wide range of assumptions about the benefits and costs of infection, we identify a social dilemma: the evolutionarily-stable sociality strategy (ESS) is distinct from the collective optimum-the level of sociality that would be best for all individuals. In particular, the ESS level of social interaction is greater (respectively less) than the social optimum when the good contagion spreads more (respectively less) readily than the bad contagion. Our results shed light on how contagion shapes the evolution of social interaction, but reveals that evolution may not necessarily lead populations to social structures that are good for any or all.
自然界中的社交水平差异很大。有些物种是独居的；有些则生活在家庭群体中；有些则形成复杂的多家族社会。社交互动水平的提高可以促进有用的创新和有益信息的传播，但也可以促进有害传染病的传播，如传染病。人们自然会认为这些传染病过程塑造了复杂社会系统的进化，但对于传染病选择压力下的社交性动态的明确解释仍然难以捉摸。我们考虑了在存在有益和有代价的传染病的情况下，社交策略的进化模型。我们在三个时间尺度上研究了这个模型的动态：使用易感染-感染-易感染（SIS）模型来描述给定社交策略的传染病传播，使用复制者方程来研究两种不同社交水平的变化分数，以及使用自适应动态方法来研究社交水平的种群水平的长期进化。对于感染的收益和成本的各种假设，我们确定了一个社会困境：进化稳定的社交策略（ESS）与集体最优不同——这是对所有个体都最好的社交水平。特别是，当好的传染病比坏的传染病更容易传播时，社交互动的 ESS 水平大于（分别小于）社交最优水平。我们的结果阐明了传染病如何塑造社交互动的进化，但揭示了进化不一定会导致种群形成对任何或所有个体都有利的社会结构。
