Mean field game for modeling of COVID-19 spread

Viktoriya Petrakova; Olga Krivorotko

doi:10.1016/j.jmaa.2022.126271

Mean field game for modeling of COVID-19 spread

J Math Anal Appl. 2022 Oct 1;514(1):126271. doi: 10.1016/j.jmaa.2022.126271. Epub 2022 Apr 19.

Authors

Viktoriya Petrakova¹, Olga Krivorotko^{2

3}

Affiliations

¹ Institute of Computational Modeling of SB RAS, 50/44 Akademgorodok str., 660036, Krasnoyarsk, Russia.
² Institute of Computational Mathematics and Mathematical Geophysics of SB RAS, 6 Ac. Lavrentieva ave., 630090, Novosibirsk, Russia.
³ Novosibirsk State University, 2 Pirogova str., 630090, Novosibirsk, Russia.

Abstract

The paper presents one of the possible approaches to pandemic spread modeling. The proposed model is based on the mean-field control inside separate groups of population, namely, suspectable (S), infected (I), removed (R) and cross-immune (C) ones. The numerical algorithm to solve this problem ensures conservation of the total population mass during timeline. The numerical experiments demonstrate modeling results for COVID-19 spread in Novosibirsk (Russia) for two 100-day periods.

Keywords: COVID-19; Epidemic propagation; Mean field games; SIRC model.