""Inﬂuenza recurs seasonally in temperate regions of the world; however, our ability to predict the timing, duration, and magnitude of local seasonal outbreaks of inﬂuenza remains limited. Here we develop a framework for initializing real-time forecasts of seasonal inﬂuenza outbreaks, using a data assimilation technique commonly applied in numerical weather prediction. The availability of realtime, web-based estimates of local inﬂuenza infection rates makes this type of quantitative forecasting possible. Retrospective ensemble forecasts are generated on a weekly basis following assimilation of these web-based estimates for the 2003–2008 inﬂuenza seasons in New York City. The ﬁndings indicate that real-time skillful predictions of peak timing can be made more than 7 wk in advance of the actual peak. In addition, conﬁdence in those predictions can be inferred from the spread of the forecast ensemble. This work represents an initial step in the development of a statistically rigorous system for real-time forecast of seasonal inﬂuenza." ."