Mathematical and Statistical Model for Assessing the Impact of COVID-19 Waves on the Regional System (on the Example of the Kirov Region)

Abstract

Since the f rst outbreak in China and the spread of COVID-19 in dif erent countries of the world, the study of mathematical models of the spread of the epidemic has begun and is intensively continuing. Such models are dynamic and of en based on dif erential or dif erence equations. As a rule, these models require an identif cation procedure to determine unknown parameters. But for a number of reasons, unambiguous identif cation of such parameters cannot be performed. For example, the preparation of statistical data for the identif cation procedure may be performed in various ways. T erefore, the preferred method of data preprocessing is to approximate them with the most appropriate functional dependence.T e study shows that epidemic curves may be represented by a superposition of several local waves — an outbreak of an epidemic in a particular region consists of many local waves and some of them may merge into one common wave. In this article, it is proposed to use analogs of the normal distribution density function to predict waves of new COVID-19 cases. T e purpose of the article was to develop a model of the dynamics of the total number of cases and new cases of COVID-19, taking into account the waves of the epidemic and the impact on the regional socioeconomic system.T e study was conducted on the basis of data on the incidence of COVID-19 in the Kirov region4 in 2020—2022. It is shown that the chosen model describes statistical data well and allows making  realistic forecasts for the total number of diseases and new cases of diseases. T e results of the study may be used to develop preventive measures to prevent the spread of the disease and allow assessing the impact of the epidemiological situation on the socio-economic system of the region.