InSTEDD Evolve: An Integrated Global Early Warning and Response System

We present on the anticipated contribution of social networking, machine learning and collaboration techniques to address public health events (e.g., an emerging infectious disease outbreak or a pandemic). We describe a hybrid (event-based and indicator-based) surveillance system (InSTEDD Evolve) designed to streamline the collaboration between domain experts and machine learning algorithms for linking detection to an effective response. Presently, Evolve and its associated modules are being piloted in the Mekong Basin region of Southeast Asia.