Given the pressure on healthcare authorities to assess whether hospital capacity allows properly responding to outbreaks such as COVID-19, there is a need for simple, data-driven methods that may provide accurate forecasts of hospital bed demand. This study applies growth models to forecast the demand for Intensive Care Unit admissions in Italy during COVID-19. We show that, with only some mild assumptions on the functional form and using short time-series, the model fits past data well and can accurately forecast demand fourteen days ahead (the mean absolute percentage error (MAPE) of the cumulative fourteen days forecasts is 7.64). The model is then applied to derive regional-level forecasts by adopting hierarchical methods that ensure the consistency between national and regional level forecasts. Predictions are compared with current hospital capacity in the different Italian regions, with the aim to evaluate the adequacy of the expansion in the number of beds implemented during the COVID-19 crisis.

Gitto, S., Di Mauro, C., Ancarani, A., Mancuso, P. (2021). Forecasting national and regional level intensive care unit bed demand during COVID-19: The case of Italy. PLOS ONE, 16(2), e0247726 [10.1371/journal.pone.0247726].

Forecasting national and regional level intensive care unit bed demand during COVID-19: The case of Italy

Gitto, S;Mancuso, P
2021-01-01

Abstract

Given the pressure on healthcare authorities to assess whether hospital capacity allows properly responding to outbreaks such as COVID-19, there is a need for simple, data-driven methods that may provide accurate forecasts of hospital bed demand. This study applies growth models to forecast the demand for Intensive Care Unit admissions in Italy during COVID-19. We show that, with only some mild assumptions on the functional form and using short time-series, the model fits past data well and can accurately forecast demand fourteen days ahead (the mean absolute percentage error (MAPE) of the cumulative fourteen days forecasts is 7.64). The model is then applied to derive regional-level forecasts by adopting hierarchical methods that ensure the consistency between national and regional level forecasts. Predictions are compared with current hospital capacity in the different Italian regions, with the aim to evaluate the adequacy of the expansion in the number of beds implemented during the COVID-19 crisis.
2021
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-IND/35 - INGEGNERIA ECONOMICO-GESTIONALE
English
COVID-19
Forecasting
Humans
Italy
Hospital Bed Capacity
Intensive Care Units
Gitto, S., Di Mauro, C., Ancarani, A., Mancuso, P. (2021). Forecasting national and regional level intensive care unit bed demand during COVID-19: The case of Italy. PLOS ONE, 16(2), e0247726 [10.1371/journal.pone.0247726].
Gitto, S; Di Mauro, C; Ancarani, A; Mancuso, P
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/294011
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