Flutrack.org: Open-source and linked data for epidemiology

Abstract

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.

Keywords: Application Programming Interface; Twitter; contagious; linked data; open source; social media; visualization.