Evans Julian C, Hodgson David J, Boogert Neeltje J, Silk Matthew J
Deparment of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.
Centre for Ecology and Conservation, University of Exeter Penryn Campus, Penryn, UK.
Behav Ecol Sociobiol. 2021;75(12):163. doi: 10.1007/s00265-021-03102-4. Epub 2021 Nov 27.
Social interactions between animals can provide many benefits, including the ability to gain useful environmental information through social learning. However, these social contacts can also facilitate the transmission of infectious diseases through a population. Animals engaging in social interactions therefore face a trade-off between the potential informational benefits and the risk of acquiring disease. Theoretical models have suggested that modular social networks, associated with the formation of groups or sub-groups, can slow spread of infection by trapping it within particular groups. However, these social structures will not necessarily impact the spread of information in the same way if its transmission follows a "complex contagion", e.g. through individuals disproportionally copying the majority (conformist learning). Here we use simulation models to demonstrate that modular networks can promote the spread of information relative to the spread of infection, but only when the network is fragmented and group sizes are small. We show that the difference in transmission between information and disease is maximised for more well-connected social networks when the likelihood of transmission is intermediate. Our results have important implications for understanding the selective pressures operating on the social structure of animal societies, revealing that highly fragmented networks such as those formed in fission-fusion social groups and multilevel societies can be effective in modulating the infection-information trade-off for individuals within them.
The online version contains supplementary material available at 10.1007/s00265-021-03102-4.
动物之间的社会互动能带来诸多益处，包括通过社会学习获取有用环境信息的能力。然而，这些社会接触也会促进传染病在种群中的传播。因此，参与社会互动的动物面临着潜在信息益处与患病风险之间的权衡。理论模型表明，与群体或子群体形成相关的模块化社会网络，可通过将感染限制在特定群体内来减缓感染传播。然而，如果信息传播遵循“复杂传播”，例如个体不成比例地模仿多数行为（从众学习），这些社会结构不一定会以同样方式影响信息传播。在此，我们使用模拟模型证明，模块化网络相对于感染传播能促进信息传播，但前提是网络碎片化且群体规模较小。我们表明，当传播可能性处于中等水平时，对于连接性更强的社会网络，信息与疾病传播的差异最大。我们的研究结果对于理解作用于动物社会结构的选择压力具有重要意义，揭示出高度碎片化的网络，如裂变融合社会群体和多层次社会中形成的网络，可有效调节其中个体的感染 - 信息权衡。
在线版本包含可在10.1007/s00265 - 021 - 03102 - 4获取的补充材料。
