Assessment of COVID-19 Hospitalization Forecasts from a Simplified SIR Model

Authors

  • P.-A. Absil ICTEAM Institute, UCLouvain, B-1348 Louvain-la-Neuve, Belgium Author
  • Ousmane Diao ICTEAM Institute, UCLouvain, B-1348 Louvain-la-Neuve, Belgium Author
  • Mouhamadou Diallo Molecular Biology Unit/Bacteriology-Virology Lab, CNHU A. Le Dantec / Université Cheikh Anta Diop, Dakar, Sénégal Author

DOI:

https://doi.org/10.30707/LiB8.1.1682013528.154572

Keywords:

COVID-19 prediction, COVID-19 forecast, SARS-CoV-2, coronavirus, SIR model, hospitalization prediction

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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Published

2021-10-05

Issue

Section

Research

How to Cite

Assessment of COVID-19 Hospitalization Forecasts from a Simplified SIR Model. (2021). Letters in Biomathematics, 8(1), 215-228. https://doi.org/10.30707/LiB8.1.1682013528.154572

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