Epidemiology has made advances, thanks to the availability of real-time surveillance data and by leveraging the geographic analysis of incidents. There are many health information systems that visualize the symptoms of influenza-like illness on a digital map, which is suitable for end-users, but it does not afford further processing and analysis. Existing systems have emphasized the collection, analysis, and visualization of surveillance data, but they have neglected a modular and interoperable design that integrates high-resolution geo-location with real-time data. As a remedy, we have built an open-source project and we have been operating an open service that detects flu-related symptoms and shares the data in real-time with anyone who wants to built upon this system. An analysis of a small number of precisely geo-located status updates (e.g. Twitter) correlates closely with the Google Flu Trends and the Centers for Disease Control and Prevention flu-positive reports. We suggest that public health information systems should embrace an open-source approach and offer linked data, in order to facilitate the development of an ecosystem of applications and services, and in order to be transparent to the general public interest.