Explicit formulae for the peak time of an epidemic from the SIR model. Which approximant to use?

Martin Kröger; Mustafa Turkyilmazoglu; Reinhard Schlickeiser

doi:10.1016/j.physd.2021.132981

Explicit formulae for the peak time of an epidemic from the SIR model. Which approximant to use?

Physica D. 2021 Nov:425:132981. doi: 10.1016/j.physd.2021.132981. Epub 2021 Jun 24.

Authors

Martin Kröger¹, Mustafa Turkyilmazoglu^{2

3}, Reinhard Schlickeiser^{4

5}

Affiliations

¹ Polymer Physics, Department of Materials, ETH Zurich, Leopold-Ruzicka-Weg 4, 8093 Zurich, Switzerland.
² Department of Mathematics, Hacettepe University, Beytepe, 06532, Ankara, Turkey.
³ Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan.
⁴ Institut für Theoretische Physik, Lehrstuhl IV: Weltraum- und Astrophysik, Ruhr-Universität Bochum, 44780 Bochum, Germany.
⁵ Institut für Theoretische Physik und Astrophysik, Christian-Albrechts-Universität zu Kiel, Leibnizstr. 15, 24118 Kiel, Germany.

Abstract

An analytic evaluation of the peak time of a disease allows for the installment of effective epidemic precautions. Recently, an explicit analytic, approximate expression (MT) for the peak time of the fraction of infected persons during an outbreak within the susceptible-infectious-recovered/removed (SIR) model had been presented and discussed (Turkyilmazoglu, 2021). There are three existing approximate solutions (SK-I, SK-II, and CG) of the semi-time SIR model in its reduced formulation that allow one to come up with different explicit expressions for the peak time of the infected compartment (Schlickeiser and Kröger, 2021; Carvalho and Gonçalves, 2021). Here we compare the four expressions for any choice of SIR model parameters and find that SK-I, SK-II and CG are more accurate than MT as long as the amount of population to which the SIR model is applied exceeds hundred by far (countries, ss, cities). For small populations with less than hundreds of individuals (families, small towns), however, the approximant MT outperforms the other approximants. To be able to compare the various approaches, we clarify the equivalence between the four-parametric dimensional SIR equations and their two-dimensional dimensionless analogue. Using Covid-19 data from various countries and sources we identify the relevant regime within the parameter space of the SIR model.

Keywords: COVID-19; Epidemic; Peak thresholds; Peak time; SIR model.