This award will provide support for the annual Clinic on Dynamic Approaches to Infectious Disease Data (DAIDD) to be held in December, 2017. DAIDD will train U.S. scientists in the mathematical modeling of infectious disease dynamics. Mathematics and simulation are essential tools in infectious disease control, enabling decision-makers to explore control policies before implementing them, interpret trends, plan empirical studies, and predict emerging threats. Over the past decade, integration of the fields of mathematical epidemiology and biomedical epidemiology has increased in research practice; however, training options provide few opportunities for integration in the classroom. This clinic addresses this gap by offering participants exposure to a broad range of concepts and techniques from both epidemiological traditions. The clinic will provide a conceptual foundation for integrating dynamic modeling approaches with empirical infectious diseases research. It is aimed at participants without substantial experience in scientific computing or in mathematical modeling. Training will focus on how the complex dynamics of pathogen transmission influence study design and data collection for applied problems in infectious disease research. Training will also prepare participants to pursue their research goals after the clinic. Participants will develop the skills necessary to identify which research questions can and cannot benefit from a dynamic modeling approach. In addition, because the Clinic will also include scientists from Africa, it will provide opportunities for U.S. scientists to build a network of international collaborators. All pedagogic material will be made publicly available online so that they can be used for self-instruction by those unable to attend the Clinic or to be incorporated into teaching materials for other courses.