Lyme disease and other diseases carried by ticks are generally linked to suburban and rural areas, but they are increasingly found in urban parks and other natural habitats in and around cities. The germs that cause these diseases are maintained by wildlife that ticks also depend on for survival, as they are their main source of blood meals. Therefore, areas with the greatest chance for humans to get sick occur where there are enough greenspaces to support wildlife and many human visitors. The project will identify these risky settings by collecting and combining wildlife, tick, and human movement information using advanced computational models. The findings of this investigation will be directly translated into disease prevention by empowering the community to improve their own health through the use of The Tick App smartphone app, a research and educational tool created by the research team. The App includes AI functions to identify ticks and provide information on risk factors and human movement; wildlife will be identified using AI identification of trail cam photos. Furthermore, the project’s outcomes equip city planners, park managers, and health officials with science-based information and practical tools to design urban green spaces that support wildlife while reducing tick encounters in urban areas. This work offers training for students and a skilled future workforce—from elementary students to postdoctoral researchers—in research methods with real-world application