Dengue fever is a vector-borne infectious disease responsible for a large health burden in Asia, Africa, and the Americas. Although statistical and mathematical models have been developed to understand and to predict dengue fever outbreaks, many aspects of the underlying transmission mechanisms remain unknown, such as the roles of built vs. environment, virus type distributions, and population immunity. This project will develop models that explore these aspects using the observed trajectories of dengue outbreaks from San Juan, Puerto Rico, Iquitos, Peru and other tropical cities with high-quality surveillance data. The ability of the developed models to predict dengue incidence in real-time will be evaluated, with the ultimate goal of informing relevant outbreak control policies and decisions.