Much progress has been made on the development of novel systems for influenza surveillance (1, 2) or explored the choices of algorithms for detecting the start of a peak season. The use of multiple streams of surveillance data has been shown to improve performance (3) but few studies have explored its use in situational awareness to quantify level or trend of disease activity. In this study, we propose a multivariate statistical approach, which describes overall influenza activity and handles interrupted or drop-in surveillance systems.