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The emergence of a new influenza virus strain setting off a global epidemic can put considerable strain on the current hospital capacity. The task of estimating hospital load during an influenza pandemic event remains difficult, despite a number of tools that are publicly available for decision makers today. The estimate depends on a multitude of parameters, each with associated uncertainties. We provide a new tool, StatFlu, combining advances in static modelling using historic influenza data with a pedagogical interface designed to highlight propagation of parameter settings and uncertaintiesin the output. StatFlu provides graphs of the load on hospital wards as well as primary care units as a function of time, aiding the user in decision making. Here we present the model and software. We also demonstrate it with an example and compare the results with a similar tool.


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