COVID-19 dynamic model: balanced identification of general biological and country specific features

Typical tasks of scientific research include breaking down a complex phenomenon into its components, considering the processes that determine its dynamics, formalizing the accepted hypotheses in mathematical equations, selecting appropriate experimental and statistical material, and ultimately, constructing a mathematical model. This paper explores a complex bio-social phenomenon (COVID-19 epidemic) using a specific data processing method (balanced identification) as part of data driven modeling approach. Combined with appropriate information technology, the method made it possible to consider a number of models, describe the general biological laws of the virus vs. human interaction (common to all populations), and the country specific social epidemic management in the populations under consideration. As statistical data, only new cases were used. Data from different countries was taken from official sources and processed in a uniform way.