Modeling the multifractal dynamics of COVID-19 pandemic

V.P. Tsvetkov, S.A. Mikheev, I.V. Tsvetkov, V.L. Derbov, A.A. Gusev and S.I. Vinitsky

Chaos, Solitons & Fractals, 2022, vol. 161, issue C

Abstract: To describe the COVID-19 pandemic, we propose to use a mathematical model of multifractal dynamics, which is alternative to other models and free of their shortcomings. It is based on the fractal properties of pandemics only and allows describing their time behavior using no hypotheses and assumptions about the structure of the disease process. The model is applied to describe the dynamics of the COVID-19 pandemic from day 1 to day 699 from the beginning of the pandemic. The calculated parameters of the model accurately determine the parameters of the trend and the large jump in daily diseases in this time interval. Within the framework of this model and finite-difference parametric nonlinear equations of the reduced SIR (Susceptible-Infected-Removed) model, the fractal dimensions of various segments of daily incidence in the world and variations in the main reproduction number of COVID-19 were calculated based on the data of COVID-19 world statistics.

Keywords: Mathematical model; Multifractal dynamics; COVID-19 pandemic; Finite-difference parametric nonlinear equations; Reduced SIR model (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:161:y:2022:i:c:s0960077922005112

DOI: 10.1016/j.chaos.2022.112301

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