We propose to use complex systems science methods to understand how social connectedness influences the utilization of dental care by young children and their caregivers. The overall goal of our research program is to address disparities in Early Childhood Caries (ECC) as it remains the most prevalent disease afflicting children, the consequences of which can be serious and long lasting. Social influence is an important moderator of the causes of disease, the population distribution of disease (e.g. disparities), and health-related behavior change via social networks. Understanding the role of social influence provides a potent perspective on why behavioral interventions aimed solely at individuals have often failed to produce meaningful results. For these reasons, interest in the development of social network interventions has grown, but much of the information necessary to develop and adequately tailor interventions to the underlying mechanisms responsible for disease production is severely lacking, especially for populations facing the greatest burdens of disease. Complex systems science approaches, such as agent-based modeling and social network analysis, can provide critical insights into the mechanisms responsible for the production of health disparities. Yet, applications to oral health are minimal. We propose to apply complex systems science methods to understand the mechanisms underlying population distributions of ECC. We propose the following specific aims: (1) Characterize the pathways by which social connectedness of caregivers interacts with individual-level perceptions of oral health status, behaviors and dental care practices to shape population patterns of ECC. (2) Evaluate social network structure and composition of caregivers of young children in relation to individual- level dental care utilization behaviors among a sample of Boston public housing residents. (3) Identify and test hypothetical interventions aimed at modifying the social-behavioral and caries risk mechanisms through the use of in silico experimentation (i.e., simulations). Outcomes of our research will inform the design of targeted interventions that respond to complex system dynamics of populations affected by health disparities. ECC prevalence and severity are disproportionately higher among children from disadvantaged groups, including the poor and certain racial/ethnic minority groups. Importantly, ECC is one of the largest unmet healthcare needs of children in the US, and significant disparities in care utilization exist. Public housing residents are a high impact population for the study of disparities. As a population group, they are characterized by spatial clustering of poverty and poor health and are ideally suited for the proposed work. Our results are expected to yield important insights into the strength of the interactions responsible for producing behavioral patterns and their consequences, and provided the necessary data for using social relation...