Analysis of the COVID-19 pandemic impact on the development of human capital in the region using machine learning algorithms

The COVID-19 pandemic has had a major impact on the formation and development of human capital through its negative effect on education and public health. This disease has already claimed hundreds of thousands of lives, caused long-term health problems and deprived many of them of access to quality education. In this regard, during the COVID-19 pandemic, it is of great importance to design modern and accurate methods for analyzing, modeling and predicting the dynamics of the spread of this disease, which enable to identify factors that significantly affect the spread of the infection. The article discusses the stages of constructing machine learning models for conducting a predicative analysis of the COVID-19 incidence, which makes it possible to study the dynamics of the spread of this virus at the regional level, identify the influence of various factors on the severity, the duration of the disease, and subsequently create timely scenarios for managing the human capital of the region in order to reduce the negative impact of the pandemic. To devise the methods, a large array of depersonalized data on the spread of COVID-19 in the Voronezh region, provided by the Voronezh Regional Clinical Consultative and Diagnostic Center, was used. The article presents the results of an exploratory analysis of the available data, highlights additional features that can be employed to build machine learning models and develops methods for interactive visualization and forecasting of COVID-19 dynamics.

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