School of Life Sciences, Faculty of Science and Engineering, Anglia Ruskin University, Cambridge, CB1 1PT, UK.
Department of Population Health and Reproduction, School of Veterinary Medicine (SVM), University of California at Davis, Davis, CA, 95616, USA.
Sci Rep. 2022 Jul 8;12(1):11600. doi: 10.1038/s41598-022-15713-6.
Pandemics caused by pathogens that originate in wildlife highlight the importance of understanding the behavioral ecology of disease outbreaks at human-wildlife interfaces. Specifically, the relative effects of human-wildlife and wildlife-wildlife interactions on disease outbreaks among wildlife populations in urban and peri-urban environments remain unclear. We used social network analysis and epidemiological Susceptible-Infected-Recovered models to simulate zooanthroponotic outbreaks, through wild animals' joint propensities to co-interact with humans, and their social grooming of conspecifics. On 10 groups of macaques (Macaca spp.) in peri-urban environments in Asia, we collected behavioral data using event sampling of human-macaque interactions within the same time and space, and focal sampling of macaques' social interactions with conspecifics and overall anthropogenic exposure. Model-predicted outbreak sizes were related to structural features of macaques' networks. For all three species, and for both anthropogenic (co-interactions) and social (grooming) contexts, outbreak sizes were positively correlated to the network centrality of first-infected macaques. Across host species and contexts, the above effects were stronger through macaques' human co-interaction networks than through their grooming networks, particularly for rhesus and bonnet macaques. Long-tailed macaques appeared to show intraspecific variation in these effects. Our findings suggest that among wildlife in anthropogenically-impacted environments, the structure of their aggregations around anthropogenic factors makes them more vulnerable to zooanthroponotic outbreaks than their social structure. The global features of these networks that influence disease outbreaks, and their underlying socio-ecological covariates, need further investigation. Animals that consistently interact with both humans and their conspecifics are important targets for disease control.
由野生动物源病原体引起的大流行突出表明，了解人类-野生动物界面上疾病爆发的行为生态学非常重要。具体而言，在城市和城郊环境中，野生动物种群中疾病爆发的人类-野生动物和野生动物-野生动物相互作用的相对影响仍不清楚。我们使用社会网络分析和流行病学易感-感染-恢复模型，通过野生动物与人类共同的相互作用倾向，以及它们对同类的社交梳理，模拟人畜共患暴发。在亚洲城郊环境中的 10 组猕猴（Macaca spp.）中，我们通过在同一时间和空间内对人类-猕猴相互作用进行事件抽样，以及对猕猴与同类的社交互动和整体人为暴露进行焦点抽样，收集行为数据。模型预测的暴发规模与猕猴网络的结构特征有关。对于所有三个物种，以及对于人为（共同相互作用）和社会（梳理）背景，暴发规模与首次感染猕猴的网络中心度呈正相关。在宿主物种和背景下，通过猕猴的人类共同相互作用网络，这些影响比通过梳理网络更为强烈，特别是对于恒河猴和戴帽猕猴。长尾猕猴在这些影响中表现出种内变异。我们的研究结果表明，在受人为影响的环境中的野生动物中，它们围绕人为因素聚集的结构使它们比社会结构更容易受到人畜共患暴发的影响。影响疾病暴发的这些网络的全球特征及其潜在的社会生态协变量需要进一步研究。那些与人类和同类动物都有持续相互作用的动物是疾病控制的重要目标。
