A Model-Based Architecture for Supporting Situational Diagnosis in Real-Time Surveillance Systems

Real-time syndromic surveillance systems require adapted dataflow organization and tools for supporting data processing in real time, from their acquisition until the counter-measure building process. This work explores the capabilities of a specific model based architecture for fulfilling these requisites and its results during a real-size international disease surveillance exercise.