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Have the explosive HIV epidemics in sub-Saharan Africa been driven by higher community viral load?

Abu-Raddad, Laith J.a,b,c; Barnabas, Ruanne V.c,e,f; Janes, Hollyc,g; Weiss, Helen A.i; Kublin, James G.c; Longini, Ira M. Jrj,k; Wasserheit, Judith N.d,e,f,h

doi: 10.1097/01.aids.0000432463.23508.a2

aInfectious Disease Epidemiology Group, Weill Cornell Medical College - Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar

bDepartment of Public Health, Weill Cornell Medical College, Cornell University, New York, New York

cVaccine and Infectious Disease Division

dClinical Research Division, Fred Hutchinson Cancer Research Centre

eDepartment of Global Health

fDepartment of Medicine

gDepartment of Biostatistics

hDepartment of Epidemiology, Schools of Medicine and Public Health, University of Washington, Seattle, Washington, USA

iMRC Tropical Epidemiology Group, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK

jDepartment of Biostatistics

kEmerging Pathogens Institute, Colleges of Public Health and Medicine, University of Florida, Gainesville, Florida, USA.

Correspondence to Dr Laith J. Abu-Raddad, PhD, Infectious Disease Epidemiology Group, Weill Cornell Medical College - Qatar, Qatar Foundation - Education City, P.O. Box 24144, Doha, Qatar. Tel: +974 4492 8321; fax: +974 4492 8333; e-mail:

Kenyon and Boulle [1] provide a critique of our study that centres around one of the sources of data from South Africa. These are valid concerns and, indeed, most of the points raised were addressed in our article or its Supplemental Digital Content [2]. Kenyon and Boulle [1] argue that our results are ‘misleading’ because we treated the results of one source of data from South Africa as an outlier. We believe that it is misleading to report an effect estimate for South Africa that is highly influenced by one outlier for which there is direct evidence indicating a gross underestimation of HIV-1 plasma RNA viral load. Therefore, in this ecological analysis, we presented the data from the different cohorts all across sub-Saharan Africa with and without the outlier, so that readers may draw their own conclusions.

Kenyon and Boulle [1] imply that we arbitrarily excluded South Africa from the region of Southern Africa to strengthen our argument. In fact, South Africa was treated separately as a subregion from the onset of the study before we identified the source of data that turned out to be an outlier. This study was motivated by our previous analysis of the role of malaria in enhancing HIV epidemics [3], and South Africa has limited malaria burden [4]. Indeed, South Africa was considered separately because of its lower burden of tropical infectious diseases relative to other countries in the region, as our underlying hypothesis was that high burden of tropical coinfections drives elevated viral load in resource-limited settings. The fact that we obtained more data from South Africa than from other countries in sub-Saharan Africa added more rationale for treating South Africa separately from Southern Africa. Including South Africa within the region of Southern Africa would have biased the results of the entire region to those of one country, as opposed to being more representative of this region as a whole.

Kenyon and Boulle [1] argue that our underlying hypothesis is in question because it cannot explain the epidemic in South Africa. This is an oversimplification of the drivers of HIV epidemics in sub-Saharan Africa, and a misinterpretation of our findings. Our study identified elevated viral load as a central driver of generalized HIV epidemics, but we did not claim that it is the only driver of these epidemics. Our modelling projections estimated that about 15% of HIV infections could be explained by augmented infectiousness due to increased viral load. Clearly, other factors contributed to the remaining 85% of HIV infections in South Africa and other parts of Africa, and we highlighted several of these, such as sexual networks [5] and subtype-specific viral dynamics [6]. It is also noteworthy that South Africa may have elevated community viral load. When we excluded the results of the outlier in question from South Africa, as explained in our article, viral load bordered on being significantly higher in South Africa than in North America.

Different assays may provide different levels of accuracy in different populations and for different HIV subtypes. Commercially available RNA tests tend to be optimized to detect subtype B infection, the predominant HIV subtype in North America and Europe, and are frequently suboptimal in detecting HIV subtypes found in other parts of the world [7]. As explained in our article, we treated the South African bDNA data from the central laboratory as an outlier based on a separate study that indicated that these viral load data were likely to underestimate the viral load levels by 0.58 log10 compared with the Roche 1.5 PCR assay [8]. Other studies have also consistently shown that bDNA assays had the highest rates of underquantification by at least 1.0 log10 mainly for HIV non-B subtypes [9,10]. Even if we exclude all bDNA data from our study, including those from North America for subtype B infection as Kenyon and Boulle [1] suggest, our results are very similar, but with slightly wider confidence intervals because of the reduced sample size. The estimated mean log10 viral load would be then 0.70 higher [95% confidence interval (CI) 0.36–1.05] in Southern Africa, 0.26 higher (95% CI -0.05 to 0.57) in West Africa, 0.68 higher (95% CI 0.31–1.05) in East Africa and 0.13 higher (95% CI -0.22 to 0.47) in South Africa than that in North America.

In conclusion, we would like to stress here that our study was conducted over several years using cautious, rigorous and conservative methodology, and that the issues raised by Kenyon and Boulle [1] are discussed in the published article. We agree with Kenyon and Boulle [1] that prospective studies are needed to further explore the findings of our ecological analysis. With increasing availability of viral load testing, and the expected WHO recommendation that viral load testing be used for clinical monitoring, prospective studies may examine this question in a more controlled fashion.

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Conflicts of interest

There are no conflicts of interest.

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