Estimation of COVID-19 dynamics "on a back-of-envelope": Does the simplest SIR model provide quantitative parameters and predictions?. (June 2020)

• Record Type: Journal Article
• Authors: Postnikov, Eugene B.
• Is Part Of: Chaos, solitons and fractals. Volume 135(2020)
• Publication Date: 2020-06
• Subjects: Covid-19 -- Compartmental epidemic model -- SIR model -- Logistic regression; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2020.109841
• Languages: English
• ISSNs: 0960-0779

Abstract

Highlights: COVID-19. SIR-model reducible to logistic regression. Forecast uncertainty quantification. Revealing effect of epidemic prevention measures. Abstract: 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.