Diabetes is one of the most common chronic diseases in childhood and young adulthood and requires lifelong treatment, management, and care. Better understanding of the burden of diabetes in these populations can improve healthcare planning and inform prevention strategies. Previous studies have yielded valuable information on the incidence and prevalence of diabetes in children, adolescents, and young adults; however, ongoing accurate and timely surveillance is needed to monitor trends and anticipate future needs. As the NYU Coordinating Center (NYU CoC) for this Cooperative Agreement, we will provide the infrastructure and expertise to guide development and validation of harmonized and standardized surveillance measures and develop analytical methods to provide unbiased estimates of diabetes trends among children, adolescents, and young adults. Specifically, the NYU CoC aims to: 1) develop and maintain a central data repository and provide the infrastructure for secure transmission and management of data; 2) develop and maintain a study website for data entry and dissemination of information among study investigators and to the public; 3) provide required training for clinical staff and facilitate their interaction with study materials, documentation, and data collection; 4) provide expertise and leadership in developing, implementing, and evaluating a network of surveillance systems designed for population-based estimation; 5) provide statistical, epidemiologic, and analytic expertise and support for all aspects of the study; and 6) support the timely dissemination of study results. The NYU CoC leadership has significant experience leading multi-center studies and data coordinating centers, as well as specific expertise in designing surveillance systems based on electronic health records (EHRs) that integrate sound epidemiologic and study design principles to ensure completeness, appropriate representativeness, and generalizability of results. The NYU CoC will also provide strong expertise in analyzing and integrating data from complex surveys and administrative databases with EHR data to generate unbiased estimates of prevalence, incidence, and trends in type 1 and type 2 diabetes. Finally, the team has demonstrated expertise in advanced statistical methods for bias correction and in combining geographic information systems with new advances in small-area estimation to identify and characterize neighborhood-level characteristics that drive observed disparities in diabetes incidence and diabetes-related complications. With this combination of skills, the NYU CoC is poised to deliver an unrivaled system for surveillance of diabetes in youth and young adults that provides accurate, representative, timely, and stable data over time to help determine trends.