A comparative network approach to assess the social-ecological underpinnings of zoonotic outbreaks at human-wildlife interfaces
O_LIPandemics caused by wildlife-origin pathogens, like COVID-19, highlight the importance of understanding the ecology of zoonotic transmission and outbreaks among wildlife populations at human-wildlife interfaces. To-date, the relative effects of human-wildlife and wildlife-wildlife interactions on the likelihood of such outbreaks remain unclear. C_LIO_LIIn this study, we used social network analysis and epidemiological Susceptible Infected Recovered (SIR) models, to track zoonotic outbreaks through wild animals joint propensities to engage in social-ecological co-interactions with humans, and their social grooming interactions with conspecifics. C_LIO_LIWe collected behavioral and demographic data on 10 groups of macaques (Macaca spp.) living in (peri)urban environments across Asia. Outbreak sizes predicted by the SIR models were related to structural features of the social networks, and particular properties of individual animals connectivity within those networks. C_LIO_LIOutbreak sizes were larger when the first-infected animal was highly central, in both types of networks. Across host-species, particularly for rhesus and bonnet macaques, the effects of network centrality on outbreak sizes were stronger through macaques human co-interaction networks compared to grooming networks. C_LIO_LIOur findings, independent of pathogen-transmissibility, suggest that wildlife populations in the Anthropocene are vulnerable to zoonosis more so due to their propensities to aggregate around anthropogenic factors than their gregariousness with conspecifics. Thus, the costs of zoonotic outbreaks may outweigh the potential/perceived benefits of jointly interacting with humans to procure anthropogenic food. From One Health perspectives, animals that consistently interact with both humans and conspecifics across time and space are useful targets for disease spillover assessments and control. C_LI