Детальная информация

This study examines the application of mathematical modeling methods to explain the emergence of new SARS-CoV-2 strains. Population genetic models were adapted to simulate SARS-CoV-2 evolution. Previously developed methods for measuring selection coefficients and epistasis were improved, tested, and utilized to find the parameters. Ultimately, evidence was obtained in favor of the hypothesis that the virus crosses a fitness valley through a deleterious primary mutation linked to beneficial mutations and followed by secondary mutations, which compensate the fitness effect of primary mutation. Based on the data obtained, further research into the nature of variants of concern can be conducted to clarify the mechanism of their emergence and develop new vaccination strategies in the event of a recurrence of a situation similar to the COVID-19 pandemic. The following information technologies were used in this study: PyCharm, Unipro UGENE, MEGA11, MATLABR2023a, Circos, GitHub, GISAID, NCBI Virus, MAFFT.