The impact of an HIV prevention intervention for injecting drug users in Svetlogorsk, Belarus: model predictions

Vickerman, P; Watts, C; (2002) The impact of an HIV prevention intervention for injecting drug users in Svetlogorsk, Belarus: model predictions. International Journal of Drug Policy, 13 (3). pp. 149-164.

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Objectives: To develop a mathematical model to estimate the impact on HIV transmission of a needle exchange project (NEP) in Svetlogorsk, Belarus. Background: From the mid -- 1990’s, there has been a rapid spread of HIV infection amongst intravenous drug users (IDUs) in Svetlogorsk. In 1997, when the IDU HIV prevalence had reached 74%, two NEPs were established in the town. These interventions have been operating, with some interruptions due to a lack of funding in 1998, up to present. Methods: This paper presents a deterministic epidemiological model ‘IDU 2.4’ that simulates the transmission of HIV among IDUs sharing injecting equipment, and between IDUs and their sexual partners. The model incorporates the impact of the interrupted distribution of clean syringes and condoms, is validated against data from Svetlogorsk, and is used to estimate the impact of the intervention on HIV transmission. Results: The model predicts that, between 1997 and 2000 the intervention averted 414 HIV infections in Svetlogorsk (CI, 180---690) and caused a 6.5% decrease in IDU HIV prevalence compared to if there had been no intervention. The gap in funding in 1998 and 1999 resulted in a 35% reduction in the HIV infections averted among the IDUs during that period and the IDU HIV prevalence being 3.2% higher in 2000 (CI, 1.9%---4.6%) than if there had been no gap in funding. Conclusions: The model predicts that the intervention had an important impact on HIV transmission in Svetlogorsk even though the HIV prevalence amongst the IDUs is high. The findings reinforce the importance of replicating similar projects in the region and highlight the detrimental impact of gaps in funding.

Item Type: Article
Faculty and Department: Faculty of Public Health and Policy > Dept of Global Health and Development
Research Centre: Social and Mathematical Epidemiology (SaME)
SaME Modelling & Economics


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