L.R. Borisova1, I.S. Sedykh2, M.B. Khripunova3

1 Financial University under the Government of the Russian Federation (Moscow, Russia)
1 lrborisova@fa.ru, 2 isedih@fa.ru, 3 mbkhripunova@fa.ru

When developing programs for the socio-economic development of regions, the problem associated with non-standard, nonlinear processes of the spread of socially significant diseases and timely response to provide high-quality sanitary, medical care and a set of measures aimed at improving the environmental situation is relevant.

Goal – To analyze the dynamics of the spread of socially significant diseases using a nonlinear infection model in the regions of the Russian Federation, as well as to investigate the influence of morbidity factors of major socially significant diseases, social development and the impact of economic activity on the environment on the well-being of life in the regions.

The data of Rosstat on the main indicators of socio-economic development and the ecological state of the regions of the Russian Federation have been studied. The influence of these indicators on the number of abortions per 100 births has been studied. A nonlinear infection model was used, and real data on the incidence of major socially significant diseases were approximated using it.

Regression analysis, machine learning methods collected in the Data Master Azforus (DMA) program, as well as cluster analysis were applied. The conducted research has demonstrated the effectiveness of using machine learning methods to identify patterns linking the frequency of socially significant phenomena and indicators of socio-economic development and the state of ecology in the region. An analysis of the results obtained using a nonlinear infection model showed that the incidence of major socially significant diseases is associated with a limited population.

Borisova L.R., Sedykh I.Yu., Khripunova M.B. Efficiency Study of the dynamics of socially significant diseases and their connection with the socio-economic development of the regions of the Russian Federation. Nonlinear World. 2024. V. 22. № 4. P. 36–45. DOI: https://doi.org/10.18127/ j20700970-202404-05 (In Russian)

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