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Modeling combination interventions to prevent human immunodeficiency virus in adolescent girls and young women in South Africa (HIV Prevention Trials Network 068)
Stoner, M. C. D., Westreich, D., Ahern, J., Edwards, J., Gómez-Olivé, F. X., Tollman, S. M., Lippman, S., Kahn, K., & Pettifor, A. (2021). Modeling combination interventions to prevent human immunodeficiency virus in adolescent girls and young women in South Africa (HIV Prevention Trials Network 068). Clinical Infectious Diseases, 73(7), e1911-e1918. https://doi.org/10.1093/cid/ciaa1598
BACKGROUND: Combination interventions may be an effective way to prevent human immunodeficiency virus (HIV) in adolescent girls and young women. However, current studies are not designed to understand which specific interventions and combinations will be most effective. We estimate the possible impacts of interventions on a combination of factors associated with HIV.
METHODS: We used the g-formula to model interventions on combinations of HIV risk factors to identify those that would prevent the most incident HIV infections, including low school attendance, intimate partner violence, depression, transactional sex, and age-disparate partnerships. We used data from the HIV Prevention Trials Network (HPTN) 068 study in rural South Africa from 2011 to 2017. We estimated HIV incidence under a potential intervention that reduced each risk factor and compared this to HIV incidence under the current distribution of these risk factors.
RESULTS: Although many factors had strong associations with HIV, potential intervention estimates did not always suggest large reductions in HIV incidence because the prevalence of risk factors was low. When modeling combination effects, an intervention to increase schooling, decrease depression, and decease transactional sex showed the largest reduction in incident infection (risk difference, -1.4%; 95% confidence interval [CI], -2.7% to -.2%), but an intervention on only transactional sex and depression still reduced HIV incidence by -1.3% (95% CI, -2.6% to -.2%).
CONCLUSIONS: To achieve the largest reductions in HIV, both prevalence of the risk factor and strength of association with HIV must be considered. Additionally, intervening on more risk factors may not necessarily result in larger reductions in HIV incidence.