Nunn Charles L, Jordán Ferenc, McCabe Collin M, Verdolin Jennifer L, Fewell Jennifer H
Department of Evolutionary Anthropology, Duke University, Box 90383, Durham, NC 27708, USA Duke Global Health Institute, Duke University, 310 Trent Drive, Durham, NC 27710, USA
The Microsoft Research-University of Trento COSBI, Piazza Manifattura 1, 38068 Rovereto, Italy Balaton Limnological Institute, Centre for Ecological Research HAS, Klebelsberg K. u. 3, 8237 Tihany, Hungary.
Philos Trans R Soc Lond B Biol Sci. 2015 May 26;370(1669). doi: 10.1098/rstb.2014.0111.
Increased risk of infectious disease is assumed to be a major cost of group living, yet empirical evidence for this effect is mixed. We studied whether larger social groups are more subdivided structurally. If so, the social subdivisions that form in larger groups may act as barriers to the spread of infection, weakening the association between group size and infectious disease. To investigate this 'social bottleneck' hypothesis, we examined the association between group size and four network structure metrics in 43 vertebrate and invertebrate species. We focused on metrics involving modularity, clustering, distance and centralization. In a meta-analysis of intraspecific variation in social networks, modularity showed positive associations with network size, with a weaker but still positive effect in cross-species analyses. Network distance also showed a positive association with group size when using intraspecific variation. We then used a theoretical model to explore the effects of subgrouping relative to other effects that influence disease spread in socially structured populations. Outbreaks reached higher prevalence when groups were larger, but subgrouping reduced prevalence. Subgrouping also acted as a 'brake' on disease spread between groups. We suggest research directions to understand the conditions under which larger groups become more subdivided, and to devise new metrics that account for subgrouping when investigating the links between sociality and infectious disease risk.
传染病风险增加被认为是群居生活的一项主要代价,但这一效应的实证证据并不一致。我们研究了较大的社会群体在结构上是否更具细分性。如果是这样,在较大群体中形成的社会细分可能会成为感染传播的障碍,从而削弱群体规模与传染病之间的关联。为了探究这一“社会瓶颈”假说,我们考察了43种脊椎动物和无脊椎动物物种的群体规模与四种网络结构指标之间的关联。我们关注的指标包括模块性、聚类性、距离和中心性。在对社会网络种内变异的荟萃分析中,模块性与网络规模呈正相关,在跨物种分析中效应较弱但仍为正相关。使用种内变异时,网络距离也与群体规模呈正相关。然后,我们使用一个理论模型来探究相对于影响社会结构种群中疾病传播的其他效应而言,亚分组的效应。群体规模较大时,疫情的患病率更高,但亚分组会降低患病率。亚分组还对群体间的疾病传播起到了“刹车”作用。我们提出了研究方向,以了解在何种条件下较大群体变得更具细分性,并在研究社会性与传染病风险之间的联系时设计出新的指标来考虑亚分组情况。