Of the studies in the review, eight either presented a relative risk for incident HSV-2 as a risk factor for HIV seroconversion, or presented data allowing for its calculation. These RR values are presented in Table 3. However, with few exceptions, the majority of HSV-2 and HIV seroconversions were recorded during the same follow-up intervals, so it was impossible to determine which infection occurred first, or whether both infections occurred simultaneously. Also, in contrast to our meta-analyses, very few studies adjusted for confounders such as markers of sexual behaviour. In most [19,24,25,27,32], but not all [30,33] studies, recent HSV-2 seroconverters had a higher risk of HIV acquisition than those who had seroconverted to HSV-2 before the study began (comparing Table 3 with Table 1), but these estimates should be interpreted with caution.
This systematic literature review and meta-analysis shows for the first time that prevalent HSV-2 infection is a statistically significant risk factor for HIV acquisition in both men and women in the general population, after adjusting for confounding by age and sexual behaviour. In general populations, men and women infected with HSV-2 had approximately three times the risk of acquiring HIV. Although there was evidence of heterogeneity in the effect among men in the general population, all nine studies contributing to this male summary estimate found a positive association (RR values ranging from 1.3 to 7.5). In MSM, the effect appeared slightly lower than in general population males. This may be due to chance or it could reflect true differences owing to the different transmission route.
The relationship between prevalent HSV-2 and HIV acquisition was not consistent in studies among high-risk women, with RR values ranging from 0.5 to 6.3. This variation between studies could be due to different prevalences of other STI, which act as cofactors for HIV transmission, since these would increase the rate of HIV acquisition in HSV-2-negative individuals. Alternatively, the difference may be a result of residual confounding, if adjustment for sexual exposure to HIV was more complete in some studies than others.
By limiting our meta-analysis to studies with known time sequence of HSV-2 infection and HIV infection, we tried to minimize any bias owing to HIV effects on subsequent acquisition of HSV-2. However, a time lag exists between acquisition of infection and a positive test for both infections. For HSV-2, median time to a positive test from culture-documented primary HSV-2 episodes is 21–120 days, dependent upon the type of test used . The time sequence could, therefore, be misclassified in either direction. This is a particular problem for the examination of incident HSV-2 as a risk factor for HIV, where exact timings are even more difficult to establish.
Although our analysis concentrated on the effect of prevalent HSV-2, there would have been variation between studies in the proportion of individuals with recent and with more remote HSV-2 infections. Since recent HSV-2 may have a stronger effect on HIV acquisition than does more long-standing HSV-2 infection, owing to greater frequency and severity [7,52] of clinical HSV-2 episodes, studies including more recent HSV-2 infections might be expected to have higher RR values.
It was not possible to assess the effect of very recent (incident) HSV-2 infections directly. Few studies examined incident HSV-2, and most of these recorded HSV-2 and HIV seroconversions during the same follow-up interval; consequently, the sequence of infections could not be established. While these studies are consistent with the hypothesis that recent HSV-2 infection is a stronger risk factor for HIV acquisition than is prevalent HSV-2 infection, problems with the time lag, small study size, long intervals between testing dates and lack of adjustment for confounding make the evidence inconclusive.
We attempted to minimize confounding by requesting that authors adjust their estimates of relative risk by a-priori confounders of age and sexual behaviour. Only studies adjusting for at least these confounders were included in the meta-analysis of the effect of prevalent HSV-2. However, residual confounding, especially by sexual behaviour, which was controlled for in a wide variety of ways by included studies, is a major concern in a meta-analysis of observational studies. Obtaining accurate information on sexual behaviour is extremely difficult. However, in most studies the RR changed little upon adjustment for a wide range of confounders.
Studies also used a wide range of HIV and HSV-2 tests. The sensitivity and specificity vary between different tests, and between the same test used on different populations . Misclassification of HSV-2 status is likely to be non-differential with respect to HIV status, leading to underestimation of the association between HSV-2 and HIV.
Publication bias is unlikely to have played an important role in our study since only 5 of the 23 RR values used were published in the form in which they appear in this analysis. Many RR values were extracted from papers or requested from authors whose papers had been published with a different purpose. In these cases, publication was probably not determined by the strength of the RR of interest to this meta-analysis. The funnel plots of ‘inclusion’ bias showed little evidence of any bias.
Controlling HSV-2 could potentially have a large impact on HIV incidence in areas of high HSV-2 prevalence. In a recent review, HSV-2 prevalence in Africa in random and population-based samples of individuals of reproductive age was found to be 29–71% in women and 5–53% in men . Despite the limitations of calculating population-attributable fractions for infectious diseases based on observational studies, from this range of prevalence values and the summary RR values calculated in this meta-analysis, our results suggest that, in these general populations, potentially 38–60% of new HIV infections may be attributable to prevalent HSV-2 infection in women and 8–49% in men.
HSV-2 antiviral treatment is available and has been shown to significantly reduce HSV-2 transmission between discordant heterosexual couples . The impact of this treatment on HIV incidence is not yet known . Ultimately, the best way to establish causality and to understand the impact of HSV-2 interventions on HIV is to undertake HSV-2 intervention studies; several are currently underway.
We would like to thank the authors of studies included in the review, and especially researchers contributing information and further data analyses to this review (listed alphabetically by study group/institution): Scott Holmberg (Centers for Disease Control); Nicolas Nagot (Centre Muraz, Burkina Faso); Eduard Sanders, Nicole Dukers (Ethio-Netherlands AIDS Research Project); Ron Gray (Johns Hopkins University Bloomberg School of Public Health); Steven Reynolds, Mary Shepherd, Sanjay Mehendale (Johns Hopkins University–National AIDS Research Institute India Collaboration); Jim Todd (London School of Hygiene and Tropical Medicine); Gabriele Riedner, Michael Hoelscher (Mbeya Medical Research Programme); Gita Ramjee, Eleanor Gouws, Brian Williams (Medical Research Council, South Africa/UNAIDS/WHO); Willi McFarland, Tim Kellogg (San Francisco Department of Public Health); Peter Kilmarx, Sara Whitehead, Philip Mock, Khanchit Limpakarniarnarat (Thailand MOPH–US CDC Collaboration); Lawrence Kingsley (University of Pittsburgh); Rupert Kaul (University of Toronto); Ludo Lavreys, Jared Baeten, Joel Rakwar (University of Washington/University of Nairobi).
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