An ensemble approach to short-term forecast of COVID-19 intensive care occupancy in Italian regions

Gianfranco Lovison, Gianfranco Lovison, Alessio Farcomeni, Antonello Maruotti, Fabio Divino, Giovanna Jona-Lasinio

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The availability of intensive care beds during the COVID-19 epidemic is crucial to guarantee the best possible treatment to severely affected patients. In this work we show a simple strategy for short-term prediction of COVID-19 intensive care unit (ICU) beds, that has proved very effective during the Italian outbreak in February to May 2020. Our approach is based on an optimal ensemble of two simple methods: a generalized linear mixed regression model, which pools information over different areas, and an area-specific nonstationary integer autoregressive methodology. Optimal weights are estimated using a leave-last-out rationale. The approach has been set up and validated during the first epidemic wave in Italy. A report of its performance for predicting ICU occupancy at regional level is included.
Original languageEnglish
Pages (from-to)503-513
Number of pages11
JournalBiometrical Journal
Volume63
Publication statusPublished - 2020

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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