Mathematical modeling of the spread of the coronavirus epidemic in the world and countries with the highest number of infected in the first half of 2020
( Pp. 61-68)

Based on nonlinear dynamics methods, mathematical modeling of the spread of the COVID-19 coronavirus epidemic in the world and in the countries with the largest number of infected in the first half of 2020 was carried out: USA, Brazil, Russia, India. It was shown that for countries where strict restrictive measures were observed, the spread of the coronavirus epidemic COVID-19 fit on one wave with a small capacity, for a number of countries with violation of restrictive measures the spread of the epidemic fit on a wave superposition. For countries with large population mixing (Brazil, India), the spread of the coronavirus epidemic today also fits into a single wave, but with a huge capacity value (for Brazil, 80 million people, for India - 40 million people). It is estimated that the spread of the epidemic in the world today fits into 5 waves. The first two waves are caused by the spread of the epidemic in China (the first - in Wuhan), the third by the spread of the epidemic in European countries, the fourth mainly by the spread of the epidemic in Russia, the USA, the fifth wave is caused mainly by the spread of the epidemic in Latin America and South Asia. It was the fifth wave that led to the spread of the epidemic of the coronavirus COVID-19 entering a new phase, with an increase in the number of infected more than 100 thousand inhabitants. For all the studied countries and the world, for each of the superposition waves, the wave capacities and growth indicators were calculated. The local peaks of the waves and their ending times are determined.

Kurkina E.S., Vasetsky A.M., Koltsova E.M., (2020), MATHEMATICAL MODELING OF THE SPREAD OF THE CORONAVIRUS EPIDEMIC IN THE WORLD AND COUNTRIES WITH THE HIGHEST NUMBER OF INFECTED IN THE FIRST HALF OF 2020. Economic Problems and Legal Practice, 3 => 61-68.

Keeling M. J., Rohani P. Modeling infectious diseases in humans and animals. Princeton University Press. 2008.
Murray J. D. Mathematical Biology: An introduction Springer. 2002.
Tam K. M., Walker N., Moreno J. Projected Development of COVID-19 in Louisiana. arXiv preprint arXiv: 2004.02859. 2020.
Blasius B. Power-law distribution in the number of confirmed COVID-19 cases. arXiv preprint arXiv: 2004.00940. 2020.
Roques L. et al. Using early data to estimate the actual infection fatality ratio from COVID-19 in France. Biology. 2020. V. 9. №. 5. P. 97.
Bj rnstad O. SEIR model. McMaster University. 2005. P. 1-8.
COVID-19 Scenarios. Elektronnyy resurs URL: https://neherlab.org/covid19 (Data obrashcheniya: 27.03.2020)
Kol tsova E. M., Kurkina E. S., Vasetskiy A. M. Matematicheskoe modelirovanie rasprostraneniya epidemii koronavirusa COVID-19 v Moskve. Computational nanotechnology. 2020. Tom. 7. №. 1. s. 99-105.
Kol tsova E. M., Kurkina E. S., Vasetskiy A. M. Matematicheskoe modelirovanie rasprostraneniya epidemii koronavirusa COVID-19 v ryade evropeyskikh, aziatskikh stran, Izraile i Rossii. Problemy ekonomiki i yuridicheskoy praktiki. 2020. №. 2. s.154-165.
Kol tsova E.M., Gordeev L.S. Metody sinergetiki v khimii i khimicheskoy tekhnologii. M.: KHimiya, 1999. 256 c.
URL: https://www.worldometers.info/coronavirus/
URL: https://coronavirus-monitor.ru/coronavirus-v-rossii/
Andrianov M.S., Bogolyubov S. A., Booth N.D., Dobretsov D.G., Ermakova K.P. Legitimacy: theory and practice: monography: edited by Tikhomirov Y.A., Subanova N.V. Institute of legislation and comparative law at the government of Russian Federation, Academy of the Prosecutor Generals office of Russian Federation. Moscow: Contract, 2017. 244 p.

pandemic, coronavirus COVID-19, epidemic spread in the world, mathematical modeling coronavirus COVID-19, mathematical modeling.