Estimation of COVID-19 dynamics “on a back-of-envelope”: Does the simplest SIR model provide quantitative parameters and predictions?

• Published in: Chaos, solitons and fractals Vol. 135; p. 109841
• Main Author: Postnikov, Eugene B.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.06.2020
• Subjects: Compartmental epidemic model; Covid-19; Logistic regression; SIR model; Logistic regression; Covid-19; Compartmental epidemic model; SIR model
• ISSN: 0960-0779; 1873-2887; 0960-0779
• DOI: 10.1016/j.chaos.2020.109841

•COVID-19.•SIR-model reducible to logistic regression.•Forecast uncertainty quantification.•Revealing effect of epidemic prevention measures. Basing on existence of the mathematically sequential reduction of the three-compartmental (Susceptible-Infected-Recovered/Removed) model to the Verhulst (logistic) equation with the parameters determined by the basic characteristic of epidemic process, this model is tested in application to the recent data on COVID-19 outbreak reported by the European Centre for Disease Prevention and Control. It is shown that such a simple model adequately reproduces the epidemic dynamics not only qualitatively but for a number of countries quantitatively with a high degree of correlation that allows to use it for predictive estimations. In addition, some features of SIR model are discussed in the context, how its parameters and conditions reflect measures attempted for the disease growth prevention that is also clearly indicated by deviations from such model solutions.