Modeling of forecasting the development of the HIV epidemic process in a region with a high level of HIV infection as a determinant of the direction of anti-epidemic measure

Aim. Identification of opportunities to influence the development of the epidemic process of HIV infection.

Materials and methods. Mathematical modeling and statistical analysis methods were used to assess the epidemiological situation forecast. In addition, the work uses methods of epidemiological research: analytical, descriptive and evaluative, statistical observation method with the calculation of intensive and extensive indicators, a continuous observational retrospective epidemiological study in the volume of the General population over a long period.

Results. A retrospective analysis of the development of the epidemic process of HIV infection in a region with a high level of HIV infection over a 26-year period since the first case was registered in 1993 showed that a concentrated stage of the epidemic has formed in the region at the present stage with an average annual rate of HIV growth of +259,9% against the national rate of +31,4%. By the end of 2018 a characteristic trend in the age structure of HIV is to reduce the proportion of persons aged up to 24 years, the prevalence of persons 35–44 years of age, a notable increase of the age group 55–64 years with a predominance of women infected by heterosexual sex (55,8 per cent). Predicting the epidemiological situation in relation to the age structure of HIV-infected people until 2023 showed a steady trend towards an increase in the HIV-positive age group up to 14 years, 40– 49 years, 50 years and older. There is a fairly high rate of HIV transmission among women.

Conclusions. At the present stage of development of the epidemic process of HIV infection, the main share of HIV-infected people is 35–44 years old (72,4%). The results obtained during the study of predicting the development of the epidemic situation with regard to HIV infection until 2023 allow us to focus the anti-epidemic work of epidemiologically significant age groups.

1. Rozental V.V., Belyakov N.A., Vinogradova T.N. et al. A dynamic model for describing and predicting the course of the HIV epidemic. Medicinskij akademicheskij zhurnal, 2012, Vol. 12, No. 1, pp. 95–102 (In Russ).

2. Belozerov E.S., Bulankov Yu.I. HIV-infection. Elista: APP «Dzhankar», 2006, 224 р. (In Russ.).

3. Pokrovsky V.I. Actual issues of therapy and prevention in the evolution of infectious diseases. Infectious diseases, 2003, Vol. 1, No. 1, pp. 5–8 (In Russ.).

4. Pokrovskij V.V. HIV infection and AIDS. Clinical guidelines. Moscow: Publishing house GEOTAR-Media, 2016, pp. 23–35 (In Russ.).

5. Pinkham S., Malinowska-Sempruch K. Women, harm reduction and HIV // Reprod. Health Matters. 2008. Vol. 16, No. 31. Р. 168–181. PMID: 18513618. doi: 10.1016/S0968-8080(08)31345-7.

6. Pokrovsky V.V. HIV-infection and demography. Materials of the VI International Conference on HIV/AIDS in Eastern Europe and Central Asia EECAAC. Moscow, 2018. P. 6 (In Russ.).

7. Pokrovsky V.V. HIV and AIDS: Clinical Recommendations. 4th ed. Revised. and add. Moscow: Publishing house GEOTAR-Media, 2019, 160 р. (In Russ.).

8. National Institute on Aging. HIV, AIDS, and older people. Bethesda, MD: National Institutes of Health, 2016.

9. Analysis of the structure of HIV-infected persons according to sex, transmission routes of infection, age in the Region with high level of prevalence of HIV on the example of Tyumen Region. Public Health and Environment, 2019, No. 7 (316), pp. 44–49 (In Russ.). doi: 10.35627/2219-5238/2019-316-7-44-49.

10. The control system of HIV-infection. Part 1. Principles of operation and optimal parameters. HIV Infection and Immunosuppressive Disorders, 2017, Vol. 9, No. 4, pp. 93–101 (In Russ.). doi: 10.22328/2077-9828-2017-9-4-93-101.