Probabilistic forecasting of prefecture-level influenza in Japan accounting for surveillance data release histories

Background. Public-health use of influenza surveillance - situational awareness, planning for clinical surge, and issuing advisories or warnings - needs more than an accurate point estimate of next week's count. What matters operationally is whether a rise is caught early, whether the direction of change is right, and whether an alert threshold is about to be crossed, all with honest uncertainty. For such use a forecast must also respect reporting delay, later data revision, and the calibration of its prediction intervals. Using Japan's sentinel surveillance, we evaluated short-term probabilis

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