Paper ID sheet UCL-INMA-2020.05

Title

Assessment of COVID-19 hospitalization forecasts from a simplified SIR model

Authors

P.-A. Absil, Ousmane Diao, Mouhamadou Diallo

Abstract

We propose the SH model, a simplified version of the well-known SIR compartmental model of infectious diseases. With optimized parameters and initial conditions, this time-invariant two-parameter two-dimensional model is able to fit COVID-19 hospitalization data over several months with high accuracy (e.g., the root relative squared error is below 10% for Belgium over the period from 2020-03-15 to 2020-07-15). Moreover, we observed that, when the model is trained on a suitable three-week period around the hospitalization peak for Belgium, it forecasts the subsequent two months with mean absolute percentage error (MAPE) under 4%. We repeated the experiment for each French department and found 14 of them where the MAPE was below 20%. However, when the model is trained in the increase phase, it is less successful at forecasting the subsequent evolution.

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Status

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BibTeX entry

@techreport{Absil_Diao_Diallo_2021,
author={Absil, P.-A. and Diao, Ousmane and Diallo, Mouhamadou},
title={Assessment of COVID-19 Hospitalization Forecasts from a Simplified SIR Model},
url={https://arxiv.org/abs/2007.10492},
year={2021},
month={Oct.},
}