External infections contribute minimally to HIV incidence among HIV sero-discordant couples in sub-Saharan Africa

Abstract

Objective: Recent randomised clinical trials among stable HIV sero-discordant couples (SDCs) in sub-Saharan Africa (SSA) have reported that about 20-30% of new HIV infections are acquired from external sexual partners, rather than transmitted from the infected to the uninfected partner within the couple. The aim of this study is to examine whether, and to what extent, these findings are generalisable to SDCs in the wider population in SSA.

Methods: A mathematical model was constructed to calculate the fraction of new HIV-1 infections among SDCs that are due to sources external to the couple. The model was parameterised using empirical and population-based data for 20 countries in SSA. Uncertainty and sensitivity analyses were also conducted.

Results: The contribution of external infections among SDCs was generally modest, but it varied widely across SSA. In low HIV prevalence countries (≤ 3.0%), it ranged from 0.6-2.9%. In intermediate prevalence countries (3.0-18.0%), it ranged from 4.9-11.7%. In Swaziland and Lesotho, the world's most-intense epidemics, sizable levels of 27.9% and 27.3% were found, respectively.

Conclusions: In most countries in SSA, nearly all HIV acquisitions by the uninfected partners in SDCs appear to be due to transmissions from the HIV infected partners in the SDCs. The contribution of externally acquired infections varies with HIV population prevalence, but rarely exceeds 10% in the majority of countries. Only in hyperendemic HIV epidemics the contribution of external infections is substantial and may reach the levels reported in recent randomised clinical trials involving SDCs.

Figure 1

Fraction of new HIV-1 infections among stable HIV-1 sero-discordant couples that are due to sources external to the couple (f_ext) across sub-Saharan Africa (SSA). (A) Country-specific means and 95% CIs for f_ext across 20 countries in SSA. (B) Country-specific ranges for f_ext using a sensitivity analysis on our model assumptions. Countries are shown in order of increasing HIV-1 prevalence. This figure is only reproduced in colour in the online version.