Sexual behaviour does not reflect HIV-1 prevalence differences: a comparison study of Zimbabwe and Tanzania

Background Substantial heterogeneity in HIV prevalence has been observed within sub-Saharan Africa. It is not clear which factors can explain these differences. Our aim was to identify risk factors that could explain the large differences in HIV-1 prevalence among pregnant women in Harare, Zimbabwe, and Moshi, Tanzania. Methods Cross-sectional data from a two-centre study that enrolled pregnant women in Harare (N = 691) and Moshi (N = 2654) was used. Consenting women were interviewed about their socio-demographic background and sexual behaviour, and tested for presence of sexually transmitted infections and reproductive tract infections. Prevalence distribution of risk factors for HIV acquisition and spread were compared between the two areas. Results The prevalence of HIV-1 among pregnant women was 26% in Zimbabwe and 7% in Tanzania. The HIV prevalence in both countries rises constantly with age up to the 25-30 year age group. After that, it continues to rise among Zimbabwean women, while it drops for Tanzanian women. Risky sexual behaviour was more prominent among Tanzanians than Zimbabweans. Mobility and such infections as HSV-2, trichomoniasis and bacterial vaginosis were more prevalent among Zimbabweans than Tanzanians. Reported male partner circumcision rates between the two countries were widely different, but the effect of male circumcision on HIV prevalence was not apparent within the populations. Conclusions The higher HIV-1 prevalence among pregnant women in Zimbabwe compared with Tanzania cannot be explained by differences in risky sexual behaviour: all risk factors tested for in our study were higher for Tanzania than Zimbabwe. Non-sexual transmission of HIV might have played an important role in variation of HIV prevalence. Male circumcision rates and mobility could contribute to the rate and extent of spread of HIV in the two countries

The Contribution of Viral Genotype to Plasma Viral Set-Point in HIV Infection

Disease progression in HIV-infected individuals varies greatly, and while the environmental and host factors influencing this variation have been widely investigated, the viral contribution to variation in set-point viral load, a predictor of disease progression, is less clear. Previous studies, using transmission-pairs and analysis of phylogenetic signal in small numbers of individuals, have produced a wide range of viral genetic effect estimates. Here we present a novel application of a population-scale method based in quantitative genetics to estimate the viral genetic effect on set-point viral load in the UK subtype B HIV-1 epidemic, based on a very large data set. Analyzing the initial viral load and associated pol sequence, both taken before anti-retroviral therapy, of 8,483 patients, we estimate the proportion of variance in viral load explained by viral genetic effects to be 5.7% (CI 2.8-8.6%). We also estimated the change in viral load over time due to selection on the virus and environmental effects to be a decline of 0.05 log10 copies/mL/year, in contrast to recent studies which suggested a reported small increase in viral load over the last 20 years might be due to evolutionary changes in the virus. Our results suggest that in the UK epidemic, subtype B has a small but significant viral genetic effect on viral load. By allowing the analysis of large sample sizes, we expect our approach to be applicable to the estimation of the genetic contribution to traits in many organisms

Markers, Cofactors and Staging Systems in the Study of HIV Disease Progression: A Review

This paper is aimed at providing a comprehensive review of markers, cofactors and staging systems used for HIV disease, focusing on some aspects that nowadays could even be considered historical, and advancing in current issues such as the prognostic value of viral load measurements, viral genotypic and phenotypic characterization, and new HIV disease treatment protocols. CD4+ cell values, combined with the new viral markers mentioned are promising as a parsimonious predictor set for defining both severity and progression. An adequate predictor of patient resource use for planning purposes still needs to be define