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Comparative assessment of methods for short-term forecasts of COVID-19 admissions in England at the local level.

Sophie R MeakinSam AbbottNikos I BosseJames D MundayHugo GrusonJoel HellewellKatharine Sherratnull nullSebastian Funk
Published in: medRxiv : the preprint server for health sciences (2021)
Assuming no change in current admissions is rarely better than including at least a trend. Using confirmed COVID-19 cases as a predictor can improve admissions forecasts in some scenarios, but this is variable and depends on the ability to make consistently good case forecasts. However, ensemble forecasts can make forecasts that make consistently more accurate forecasts across time and locations. Given minimal requirements on data and computation, our admissions forecasting ensemble could be used to anticipate healthcare needs in future epidemic or pandemic settings.
Keyphrases
  • coronavirus disease
  • sars cov
  • healthcare
  • climate change
  • respiratory syndrome coronavirus
  • convolutional neural network
  • machine learning
  • big data
  • health information
  • health insurance