Building a Model and Assessing the Level of Morbidity During the Epidemic

Aigul Kubegenova, Айнура Гумарова, Gaukhar A. Kamalova, Jan Rabčan

2023

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DOI 10.1109/idt59031.2023.10194453
Data confidence 70 medium
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Abstract

The article discusses the effectiveness, methods, and mathematical models of measures to control the spread of the human immunodeficiency virus (HIV) in Kazakhstan. Data were obtained for a 10-year period of the incidence of HIV infection, and a distribution schedule for the morbidity of the population was created and analyzed using the Statistica application software package. A model of HIV spread is considered taking into account the social adaptation of the population, a scheme of a probabilistic model is constructed, and a system of probabilistic differential equations is used. The current direction of the strategy for combating HIV infection is largely determined by a scientifically based system for assessing the epidemiological state of HIV infection using mathematical models that can determine the patterns of the epidemiological process with great confidence and predict the expected level of morbidity. Currently, according to scientists, there are about 150 different forecasting methods, but in practice, 15–20 types of methods are most often used. One of the methods used in the majority is expert assessment, extrapolation, mathematical modeling, and mixed forecasts. To date, the problem of HIV infection is one of the most important Kazakhstan consistently implements steps to curb the spread of HIV infection. The issues of combating HIV infection are included in the state program of healthcare development of the Republic of Kazakhstan for 2020-2025.