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Lancet Infect Dis. 2008 Sep;8(9):553-63. doi: 10.1016/S1473-3099(08)70156-7. Epub 2008 Aug 4.

Rethinking the heterosexual infectivity of HIV-1: a systematic review and meta-analysis.

Author information

  • 1Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599-7435, USA. powersk@email.unc.edu

Abstract

Studies of cumulative HIV incidence suggest that cofactors such as genital ulcer disease, HIV disease stage, and male circumcision influence HIV transmission; however, the heterosexual infectivity of HIV-1 is commonly cited as a fixed value (approximately 0.001, or one transmission per 1000 contacts). We sought to estimate transmission cofactor effects on the heterosexual infectivity of HIV-1 and to quantify the extent to which study methods have affected infectivity estimates. We undertook a systematic search (up to April 27, 2008) of PubMed, Web of Science, and relevant bibliographies to identify articles estimating the heterosexual infectivity of HIV-1. We used meta-regression and stratified random-effects meta-analysis to assess differences in infectivity associated with cofactors and study methods. Infectivity estimates were very heterogeneous, ranging from zero transmissions after more than 100 penile-vaginal contacts in some serodiscordant couples to one transmission for every 3.1 episodes of heterosexual anal intercourse. Estimates were only weakly associated with study methods. Infectivity differences, expressed as number of transmissions per 1000 contacts, were 8.1 (95 % CI 0.4-15.8) when comparing uncircumcised to circumcised susceptible men, 6.0 (3.3-8.8) comparing susceptible individuals with and without genital ulcer disease, 1.9 (0.9-2.8) comparing late-stage to mid-stage index cases, and 2.5 (0.2-4.9) comparing early-stage to mid-stage index cases. A single value for the heterosexual infectivity of HIV-1 fails to reflect the variation associated with important cofactors. The commonly cited value of 0.001 was estimated among stable couples with low prevalences of high-risk cofactors, and represents a lower bound. Cofactor effects are important to include in epidemic models, policy considerations, and prevention messages.

PMID:
18684670
[PubMed - indexed for MEDLINE]
PMCID:
PMC2744983
Free PMC Article

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