Review 1: "Age and Gender Profiles of HIV Infection Burden and Viraemia: Novel Metrics for HIV Epidemic Control in African Populations with High Antiretroviral Therapy Coverage"

Wolfgang Hladik

doi:doi:10.1162/2e3983f5.ce3f5bde

Age and gender profiles of HIV infection burden and viraemia: novel metrics for HIV epidemic control in African populations with high antiretroviral therapy coverage

by Andrea Brizzi, Joseph Kagaayi, Robert Ssekubugu, Lucie Abeler-Dörner, Alexandra Blenkinsop, David Bonsall, Larry W. Chang, Christophe Fraser, Ronald M. Galiwango, Godfrey Kigozi, Imogen Kyle, Mélodie Monod, Gertrude Nakigozi, Fred Nalugoda, Joseph G. Rosen, Oliver Laeyendecker, Thomas C. Quinn, M. Kate Grabowski, Steven J. Reynolds, Oliver Ratmann, and the Rakai Health Sciences Program

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Published on Apr 22, 2024
www.medrxiv.org

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Abstract Introduction To prioritize and tailor interventions for ending AIDS by 2030 in Africa, it is important to characterize the population groups in which HIV viraemia is concentrating.Methods We analysed HIV testing and viral load data collected between 2013-2019 from the open, population-based Rakai Community Cohort Study (RCCS) in Uganda, to estimate HIV seroprevalence and population viral suppression over time by gender, one-year age bands and residence in inland and fishing communities. All estimates were standardized to the underlying source population using census data. We then assessed 95-95-95 targets in their ability to identify the populations in which viraemia concentrates.Results Following the implementation of Universal Test and Treat, the proportion of individuals with viraemia decreased from 4.9% (4.6%-5.3%) in 2013 to 1.9% (1.7%-2.2%) in 2019 in inland communities and from 19.1% (18.0%-20.4%) in 2013 to 4.7% (4.0%-5.5%) in 2019 in fishing communities. Viraemia did not concentrate in the age and gender groups furthest from achieving 95-95-95 targets. Instead, in both inland and fishing communities, women aged 25-29 and men aged 30-34 were the 5-year age groups that contributed most to population-level viraemia in 2019, despite these groups being close to or had already achieved 95-95-95 targets.Conclusions The 95-95-95 targets provide a useful benchmark for monitoring progress towards HIV epidemic control, but do not contextualize underlying population structures and so may direct interventions towards groups that represent a marginal fraction of the population with viraemia.

RR:C19 Evidence Scale rating by reviewer:

Strong. The main study claims are very well-justified by the data and analytic methods used. There is little room for doubt that the study produced has very similar results and conclusions as compared with the hypothetical ideal study. The study’s main claims should be considered conclusive and actionable without reservation.

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Review: This is a well written and important paper on a relatively basic topic deserving more widespread attention. Using prospective (serial) general population data from two communities (inland community and fishing community) in the Rakai Community Cohort Study in SW Uganda, the authors first establish, by gender and sex, the background HIV prevalence (from 2013-19), as well as assess progress towards the UNAIDS 95 targets which are directly related to the cascading treatment program elements (testing, linking to treatment, retaining in treatment). These 95 targets are generally deemed of pivotal importance for HIV control as they are directly related to the concept of Treatment as Prevention (TasP). The authors’ key achievement in this analysis that viral load suppression (VLS, the 3^rd UNAIDS 95 target) is not necessarily correlated of population viremia, i.e., the population prevalence of viremic (1,000+ copies/ml) HIV. Importantly, population viremia is a function of both VLS (i.e., 1-VLS) and HIV prevalence, whereas VLS itself is agnostic to a population’s HIV prevalence. Hence one rightly concludes that population viremia is more predictive of HIV transmission than VLS. While several other (cited) papers come to analogous observations and findings in other setting, this paper is a welcome and necessary addition to the literature on this topic. That said, this reviewer would have liked to see a clearer inclusion/description of HIV incidence estimates in these two communities over time and their possible correlation with population viremia (and VLS), i.e., whether higher population viremia indeed was accompanied by higher HIV incidence (understanding the caveat that HIV transmission may well originate from someone not residing in the same community).

Some specific (minor) observations:

Results:

Table 1: Proportion of PLHIV, in each age group - a bit unclear; please rephrase. Do you mean HIV prevalence?
Line 38++: “Thus, while suppression levels among PLHIV were higher in fishing communities compared to inland communities in both men and women, suppression levels in the population, i.e. among census eligible individuals, were lower in fishing communities rather than inland communities due to the overall higher HIV prevalence.”
Consider rephrasing as “suppression levels in the population” is an unusual perspective; it seems more intuitive to interpret the data through viremia levels.
Discussion: “Second, our study only considered data from Uganda, and our results may not directly generalize to other settings.” While the RCCS is an invaluable population cohort study, its findings are not (automatically) generalizable even to all of Uganda. I suggest rephrasing.

Review 1: "Age and Gender Profiles of HIV Infection Burden and Viraemia: Novel Metrics for HIV Epidemic Control in African Populations with High Antiretroviral Therapy Coverage"

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