Analytical features of the SIR model and their applications to COVID-19.

Nikolay A Kudryashov, Mikhail A Chmykhov, Michael Vigdorowitsch
Author Information
  1. Nikolay A Kudryashov: Department of Applied Mathematics, National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), 31 Kashirskoe Shosse, Moscow 115409, Russian Federation.
  2. Mikhail A Chmykhov: Department of Applied Mathematics, National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), 31 Kashirskoe Shosse, Moscow 115409, Russian Federation.
  3. Michael Vigdorowitsch: Angara GmbH, In der Steele 2, Düsseldorf 40599, Germany.

Abstract

A classic two-parameter epidemiological SIR-model of the coronavirus propagation is considered. The first integrals of the system of non-linear equations are obtained. The Painlevé test shows that the system of equations is not integrable in the general case. However, the general solution is obtained in quadrature as an inverse time-function. Using the first integrals of the system of equations, analytical dependencies for the number of infected patients () and that of recovered patients () on the number of susceptible to infection () are obtained. A particular attention is paid to interrelation of () and () both depending on /, where is the contact rate in the community and is the intensity of recovery/decease of patients. It is demonstrated that the data on particular morbidity waves in Hubei (China), Italy, Austria, South Korea, Moscow (Russia) as well some Australian territories are satisfactorily described by the expressions obtained for (). The variability of parameter having been traditionally considered as a static population size is discussed.

Keywords

References

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