Sources of HIV incidence among stable couples in sub‐Saharan Africa

Abstract

Introduction The recent availability of efficacious prevention interventions among stable couples offers new opportunities for reducing HIV incidence in sub‐Saharan Africa. Understanding the dynamics of HIV incidence among stable couples is critical to inform HIV prevention strategy across sub‐Saharan Africa. Methods We quantified the sources of HIV incidence arising among stable couples in sub‐Saharan Africa using a cohort‐type mathematical model parameterized by nationally representative data. Uncertainty and sensitivity analyses were incorporated. Results HIV incidence arising among stable concordant HIV‐negative couples contribute each year, on average, 29.4% of total HIV incidence; of those, 22.5% (range: 11.1%–39.8%) are infections acquired by one of the partners from sources external to the couple, less than 1% are infections acquired by both partners from external sources within a year and 6.8% (range: 3.6%–11.6%) are transmissions to the uninfected partner in the couple in less than a year after the other partner acquired the infection from an external source. The mean contribution of stable HIV sero‐discordant couples to total HIV incidence is 30.4%, with most of those, 29.7% (range: 9.1%–47.9%), being due to HIV transmissions from the infected to the uninfected partner within the couple. The remaining incidence, 40.2% (range: 23.7%–64.6%), occurs among persons not in stable couples. Conclusions Close to two‐thirds of total HIV incidence in sub‐Saharan Africa occur among stable couples; however, only half of this incidence is attributed to HIV transmissions from the infected to the uninfected partner in the couple. The remaining incidence is acquired through extra‐partner sex. Substantial reductions in HIV incidence can be achieved only through a prevention approach that targets all modes of HIV exposure among stable couples and among individuals not in stable couples.

Keywords

• stable couples
• sources of infection
• HIV incidence
• Sub‐Saharan Africa
• demographic and health surveys
• mathematical model