tommcandrew
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influenza
FluSight Network Ensemble
We present three combination forecasting techniques. The FluSight Network (FSN) ensemble model is a multimodel ensemble; a convex combination of component predictive densities. The adaptive ensemble is a multimodel ensemble, but unlike the FSN ensemble, recomputes component model weights every week.
Aug 20, 2019 12:00 AM
Atlanta, Georgia
Slides
Adaptively stacked ensembles for influenza forecasting with incomplete data
Seasonal Influenza infects an average 30 million people in the United States every year, overburdening hospitals during weeks of peak incidence.Named by the CDC as an important tool to fight the damaging effects of these epidemics, accurate forecasts of influenza and influenza like illness (ILI) forewarn public health officials about when, and where, seasonal influenza outbreaks will hit hardest.
May 31, 2019 12:00 AM
Bellevue, Washington
Slides
Adaptively stacked ensembles for influenza forecasting with incomplete data
Influenza prediction can better prepare public health officials for seasonal outbreaks. We propose an adaptive multi-model ensemble forecast method that changes model weights week-by-week throughout the flu season. Without historical training data or when models do not have a track-record, an adaptive model can enhance the public health impact of ensemble forecasts.
May 20, 2019 12:00 AM
Bethesda, Maryland
Slides
Adaptively stacked ensembles for influenza forecasting with incomplete data
Seasonal Influenza infects an average 30 million people in the United States every year, overburdening hospitals during weeks of peak incidence.Named by the CDC as an important tool to fight the damaging effects of these epidemics, accurate forecasts of influenza and influenza like illness (ILI) forewarn public health officials about when, and where, seasonal influenza outbreaks will hit hardest.
May 16, 2019 12:00 AM
Hartford, CT
Slides
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