Identification of the Mathematical Model of Tuberculosis and HIV Co-Infection Dynamics

This paper proposes and analyzes a mathematical model of tuberculosis and HIV co-infection that specifies for Russian Federation regions, based on mass balance law and described by eight ordinary differential equations. A sensitivity-based identifiability analysis of this mathematical model was performed, which revealed the sensitivity of the averaged parameters of the models to statistical real data of infectious individuals based on the Sobol method. The problem of identifying the sensitive epidemiological parameters (contagiousness, the rate of tuberculosis activation, additional mortality rate, etc.) for the model was reduced to the problem of minimization of the quadratic misfit function. The numerical results of the modeling of the number of people expected to be infected with tuberculosis and HIV were shown and discussed for the Sverdlovsk and Moscow regions of the Russian Federation. It has been shown that increasing the capacity of the medical system by 10% will make it possible to reduce the number of diagnosed cases of active tuberculosis by 2 times over the next 3 years in some regions of Russian Federation.

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Publication Details

Journal
Mathematics
Published
2024-11-21
DOI
https://doi.org/10.3390/math12233636
Citations
6
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
Type
article
Field-Weighted Citation Impact
3.26
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article

Identification of the Mathematical Model of Tuberculosis and HIV Co-Infection Dynamics

Grigory Kaminskiy, Olga Krivorotko, Andrei Neverov, Sergey Igorevich Kabanikhin et al.
6 citations
Mathematics
Mathematical and Theoretical Epidemiology and Ecology Models
3.26
article

Identification of the Mathematical Model of Tuberculosis and HIV Co-Infection Dynamics

Grigory Kaminskiy, Olga Krivorotko, Andrei Neverov, Sergey Igorevich Kabanikhin, О. В. Семенова
article en
6 citations

Abstract

This paper proposes and analyzes a mathematical model of tuberculosis and HIV co-infection that specifies for Russian Federation regions, based on mass balance law and described by eight ordinary differential equations. A sensitivity-based identifiability analysis of this mathematical model was performed, which revealed the sensitivity of the averaged parameters of the models to statistical real data of infectious individuals based on the Sobol method. The problem of identifying the sensitive epidemiological parameters (contagiousness, the rate of tuberculosis activation, additional mortality rate, etc.) for the model was reduced to the problem of minimization of the quadratic misfit function. The numerical results of the modeling of the number of people expected to be infected with tuberculosis and HIV were shown and discussed for the Sverdlovsk and Moscow regions of the Russian Federation. It has been shown that increasing the capacity of the medical system by 10% will make it possible to reduce the number of diagnosed cases of active tuberculosis by 2 times over the next 3 years in some regions of Russian Federation.

MathematicsVol. 12(23)
Novosibirsk Tuberculosis Research Institute (RU), Sobolev Institute of Mathematics (RU), Ministry of Health of the Russian Federation (RU), Siberian Branch of the Russian Academy of Sciences (RU)
Good health and well-being
Openalex Percentile: Top 7%
Mathematical and Theoretical Epidemiology and Ecology Models
3.26
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