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.

An ensemble approach to short‐term forecast of COVID‐19 intensive care occupancy in Italian regions / Farcomeni, Alessio; Maruotti, Antonello; Divino, Fabio; Jona‐Lasinio, Giovanna; Lovison, Gianfranco. - In: BIOMETRICAL JOURNAL. - ISSN 0323-3847. - (2020), pp. 1-11. [10.1002/bimj.202000189]

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

Farcomeni, Alessio
Primo
Methodology
;
Maruotti, Antonello
Secondo
Conceptualization
;
Divino, Fabio
Conceptualization
;
Jona‐Lasinio, Giovanna
Penultimo
Membro del Collaboration Group
;
2020

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.
2020
clustered data; COVID-19; generalized linear mixed model; integer autoregressive; integer autoregressive model; panel data; SARS-CoV-2; weighted ensemble
01 Pubblicazione su rivista::01a Articolo in rivista
An ensemble approach to short‐term forecast of COVID‐19 intensive care occupancy in Italian regions / Farcomeni, Alessio; Maruotti, Antonello; Divino, Fabio; Jona‐Lasinio, Giovanna; Lovison, Gianfranco. - In: BIOMETRICAL JOURNAL. - ISSN 0323-3847. - (2020), pp. 1-11. [10.1002/bimj.202000189]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1476913
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