UC Davis

This dissertation addresses the escalating threat of anthropozoonosis at human-wildlife interfaces by investigating the social dynamics of disease transmission among wildlife populations, focusing particularly on long-tailed macaques (Macaca fascicularis) inhabiting human-wildlife interface areas. Tuberculosis (TB) serves as the model infectious disease due to its high prevalence in Southeast Asia, air-borne transmission and its zoonosis nature. Although concerns about disease risks to these macaques have been raised, the role of individual variation, encompassing social network attributes and human exposures, has remained unexplored. To address these questions, this project utilizes non-invasive techniques for sample collection from a population of free-ranging macaques in Thailand. I adopt a network approach to examine the intricate relationship between social attributes and TB infection status. Furthermore, an epidemiological model, Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS), is integrated to monitor changes in individuals' disease states and explore hypothetical scenarios of disease spread within social networks, with parameters tailored to each individual.Chapter One investigates the factors driving pathogen infection by identifying infected animals and examining how sociodemographic attributes, combined with interactions with conspecifics, humans, and responses to stress and sickness, influence TB infection patterns within social groups. Notably, it reveals that the likelihood of TB infection increases among individuals with high human interaction and those engaging in less grooming activity. Chapter Two explores the influence of social network positions on TB transmission. By implementing a social network approach to locate infected individuals, this chapter explores the interplay between contact-transmission and social buffering. It highlights the significance of individual macaques' social network positions in their infection status, emphasizing that monkeys with fewer grooming interactions and living periphery are more likely to have TB. Chapter Three employs mathematical modeling within the network to investigate transmission dynamics and the persistence of TB, taking into account variations in transmissibility and latency periods. SEIRS models reveal that over half of the population remains in the latent stage of TB infection. It elucidates that social buffering, specifically the adjustment of the latency period from latency to active TB, plays a pivotal role in explaining the presence of infected individuals in the social network periphery. In contrast, adjusting transmissibility fails to accurately represent observed relationships in this population. Overall, this dissertation aims to uncover the social and demographic factors that influence the acquisition and transmission of TB among free-ranging long-tailed macaques inhabiting human-wildlife interface areas. Understanding the attributes of social network components in wildlife populations at the human-wildlife interface contributes to mitigating infectious disease transmission, reducing zoonotic risks, and promoting the well-being of both humans and wildlife. These insights play a crucial role in clarifying steps to prevent potential future pandemics.