Title
SIR model for assessing the impact of the advent of Omicron and mitigating measures on infection pressure and hospitalization needs - Preprint
Author
van Wees, J.D.
van der Kuip, M.
Osinga, S.
Keijser, B.
van Westerloo, D.
Hanegraaf, M.
Pluymaekers, M.
Leeuwenburgh, O.
Brunner, L.
Tutu van Furth, M.
Publication year
2021
Abstract
Background: On 26 November 2021, the world health organization (WHO) designated the coronavirus SARS-CoV-2 B.1.1.529 a variant of concern, named Omicron (WHO, 2021a). As of December 16, Omicron has been detected in 89 countries (WHO, 2021b). The thread posed by Omicron is highly uncertain. Methods and findings: For the analysis of the impact of Omicron on infection pressure and hospitalization needs we developed an open-source stochastic SIR (Susceptible-Infectious-Removed) fast-model for simulating the transmission in the transition stage from the prevailing variant (most often Delta) to Omicron. The model is capable to predict trajectories of infection pressure and hospitalization needs, considering (a) uncertainties for the (Omicron) parametrization, (b) pre-existing vaccination and/or partial immunity status of the population, and demographic specific aspects regarding reference hospitalization needs, (c) effects of mitigating measures including social distancing and accelerated vaccination (booster) campaigns. Conclusions: The SIR model approach yields results in fair agreement with Omicron transmission characteristics observed in South Africa and prognosis results in Europe (UK and Netherlands). The equations underlying the SIR formulation allows to effectively explore the effect of Omicron parametrization on anticipated infection growth rates and hospitalization rates relative to the prevailing variant. The models are online available as open source on GitHub.
Subject
Epidemiology
To reference this document use:
http://resolver.tudelft.nl/uuid:59bfb9df-1883-4098-a839-d4cacd5a2139
DOI
https://doi.org/10.1101/2021.12.25.21268394
TNO identifier
962715
Source
Paper in collection: COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxiv, 1-22
Document type
article