abstract: Understanding the consequences of changes in social networks is an important an- thropological research goal. This dissertation looks at the role of data-driven social networks on infectious disease transmission and evolution. The dissertation has two projects. The first project is an examination of the effects of the superspreading phenomenon, wherein a relatively few individuals are responsible for a dispropor- tionate number of secondary cases, on the patterns of an infectious disease. The second project examines the timing of the initial introduction of tuberculosis (TB) to the human population. The results suggest that TB has a long evolutionary history with hunter-gatherers. Both of these projects demonstrate the consequences of social networks for infectious disease transmission and evolution. The introductory chapter provides a review of social network-based studies in an- thropology and epidemiology. Particular emphasis is paid to the concept and models of superspreading and why to consider it, as this is central to the discussion in chapter 2. The introductory chapter also reviews relevant epidemic mathematical modeling studies. In chapter 2, social networks are connected with superspreading events, followed by an investigation of how social networks can provide greater understanding of in- fectious disease transmission through mathematical models. Using the example of SARS, the research shows how heterogeneity in transmission rate impacts super- spreading which, in turn, can change epidemiological inference on model parameters for an epidemic. Chapter 3 uses a different mathematical model to investigate the evolution of TB in hunter-gatherers. The underlying question is the timing of the introduction of TB to the human population. Chapter 3 finds that TB’s long latent period is consistent with the evolutionary pressure which would be exerted by transmission on a hunter- igatherer social network. Evidence of a long coevolution with humans indicates an early introduction of TB to the human population. Both of the projects in this dissertation are demonstrations of the impact of var- ious characteristics and types of social networks on infectious disease transmission dynamics. The projects together force epidemiologists to think about networks and their context in nontraditional ways. / Dissertation/Thesis / Doctoral Dissertation Anthropology 2019