A comparative network approach to assess the social-ecological underpinnings of zoonotic outbreaks at human-wildlife interfaces
Pandemics caused by wildlife-origin pathogens, like COVID-19, highlight the importance of understanding the ecology of zoonosis at human-wildlife interfaces. To-date, the relative effects of human-wildlife and wildlife-wildlife interactions on zoonotic outbreaks among wildlife populations remain unclear. In this study, we used social network analysis and epidemiological Susceptible Infected Recovered (SIR) models, to track zoonotic outbreaks through wild animals social-ecological co-interactions with humans and their social grooming interactions with conspecifics, for 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. Outbreak 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. Our findings, independent of pathogen-transmissibility, suggest that for wildlife populations in the Anthropocene, vulnerability to zoonotic outbreaks may outweigh the potential/perceived benefits of interacting with humans to procure anthropogenic food. From One Health perspectives, animals that consistently interact with humans (and their own conspecifics) across time and space are useful targets for disease-control.