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Optimizing Disease Outbreak Forecast Ensembles.

Spencer J FoxMinsu KimLauren Ancel MeyersNicholas G ReichEvan L Ray
Published in: Emerging infectious diseases (2024)
On the basis of historical influenza and COVID-19 forecasts, we found that more than 3 forecast models are needed to ensure robust ensemble accuracy. Additional models can improve ensemble performance, but with diminishing accuracy returns. This understanding will assist with the design of current and future collaborative infectious disease forecasting efforts.
Keyphrases
  • infectious diseases
  • coronavirus disease
  • quality improvement
  • sars cov
  • convolutional neural network
  • neural network
  • current status
  • deep learning