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R-Economy
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Socio-economic factors in the spread of SARS-COV-2 across Russian regions

Authors: Sinitsyn, E. V.; Tolmachev, A. V.; Ovchinnikov, A. S.;

Socio-economic factors in the spread of SARS-COV-2 across Russian regions

Abstract

Relevance. The worldwide spread of a new infection SARS-CoV-2 makes relevant the analysis of the socio-economic factors that make modern civilization vulnerable to previously unknown diseases. In this regard, the development of mathematical models describing the spread of pandemics like COVID-19 and the identification of socio-economic factors affecting the epidemiological situation in regions is an important research task.Research objective. This study seeks to develop a mathematical model describing the spread of COVID-19, thus enabling the analysis of the main characteristics of the spread of the disease and assessment of the impact of various socio-economic factors.Data and methods. The study relies on the official statistical data on the pandemic presented on coronavirus sites in Russia and other countries, Yandex DataLens dataset service, as well as data from the Federal State Statistics Service. The data were analyzed by using a correlation analysis of COVID-19 incidence parameters and socio-economic characteristics of regions; multivariate regression – to determine the parameters of the probabilistic mathematical model of the spread of the pandemic proposed by the authors; clustering – to group the regions with similar incidence characteristics and exclude the regions with abnormal parameters from the analysis.Results. A mathematical model of the spread of the COVID-19 pandemic is proposed. The parameters of this model are determined on the basis of official statistics on morbidity, in particular the frequency (probability) of infections, the reliability of the disease detection, the probability density of the disease duration, and its average value. Based on the specificity of COVID-19, Russia regions are clustered according to disease-related characteristics. For clusters that include regions with typical disease-related characteristics, a correlation analysis of the relationship between the number of cases and the rate of infection ( with the socio-economic characteristics of the region is carried out. The most significant factors associated with the parameters of the pandemic are identified.Conclusions. The proposed mathematical model of the pandemic and the established correlations between the parameters of the epidemiological situation and the socio-economic characteristics of the regions can be used to make informed decisions regarding the key risk factors and their impact on the course of the pandemic.

Keywords

SOCIO-ECONOMIC DETERMINANTS OF THE COVID-19 PANDEMIC, COVID-19, DENSITY OF DISEASE DURATION PROBABILITY, PROBABILITY OF INFECTION AND DISEASE DETECTION, CORRELATION ANALYSIS, MATHEMATICAL MODEL OF THE EPIDEMIC SPREAD, СОЦИАЛЬНО-ЭКОНОМИЧЕСКИЕ ДЕТЕРМИНАНТЫ ПАНДЕМИИ COVID-19, ПЛОТНОСТЬ ВЕРОЯТНОСТИ ПРОДОЛЖИТЕЛЬНОСТИ ЗАБОЛЕВАНИЯ, МАТЕМАТИЧЕСКАЯ МОДЕЛЬ РАСПРОСТРАНЕНИЯ ЭПИДЕМИИ, ВЕРОЯТНОСТЬ ЗАРАЖЕНИЯ И ВЫЯВЛЕНИЯ ЗАБОЛЕВАНИЯ, КОРРЕЛЯЦИОННЫЙ АНАЛИЗ

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Average
gold