Comparing different methods to measure HIV incidence in a sub-Saharan African population

Estimating HIV incidence using a cross-sectional survey: comparison of three approaches in a hyperendemic setting, Ndhiwa sub-county, Kenya, 2012.

Blaizot S, Kim AA, Zeh C, Riche B, Maman D, DeCock K, Etard JF, Ecochard R. AIDS Res Hum Retroviruses. 2016 Dec 13. [Epub ahead of print]

Objectives: Estimating HIV incidence is critical for identifying groups at risk for HIV infection, planning and targeting interventions, and evaluating these interventions over time. The use of reliable estimation methods for HIV incidence is thus of high importance. The aim of this study was to compare methods for estimating HIV incidence in a population-based cross-sectional survey.

Design/methods: The incidence estimation methods evaluated included assay-derived methods, a testing history-derived method, and a probability-based method applied to data from the Ndhiwa HIV Impact in Population Survey (NHIPS). Incidence rates by sex and age and cumulative incidence as a function of age were presented.

Results: HIV incidence ranged from 1.38 [95% confidence interval (CI) 0.67-2.09] to 3.30 [95% CI 2.78-3.82] per 100 persons-years overall; 0.59 [95% CI 0.00-1.34] to 2.89 [95% CI 0.11-5.68] in men; and 1.62 [95% CI 0.16-6.04] to 4.03 [95% CI 3.30-4.77] per 100 persons-years in women. Women had higher incidence rates than men for all methods. Incidence rates were highest among women aged 15-24 and 25-34 years and highest among men aged 25-34 years.

Conclusion: Comparison of different methods showed variations in incidence estimates, but they were in agreement to identify most-at-risk groups. The use and comparison of several distinct approaches for estimating incidence are important to provide the best-supported estimate of HIV incidence in the population.

Abstract access

Editor’s notes: The estimation of HIV incidence is important both for planning effective HIV prevention strategies, and also to provide a proximal measure of changes in HIV epidemics both in general populations and in higher risk sub-groups. Further development of methods for accurately measuring HIV incidence that can be applied in routine monitoring settings is necessary.

This study compares three assay-based incidence estimation methods with approaches using self-reported testing history and a probabilistic technique on age and sex stratified sero-prevalence data. Two of the assays, BioRad and Lag, use antibody markers and a recent infection testing algorithm (RITA). The BioRad assay allowed for a longer time window for detection post-infection than the Lag. Recent infections were reclassified using results from HIV viral load tests and self-reported ART use, as appropriate. The other assay detected trace levels of HIV RNA in HIV seronegative individuals. The results for the two RITA assays were very similar at 1.38 [95% CI 0.67 – 2.09] infections per 100 person years (PY) for the BioRad and 1.46 [95% CI 0.71 – 2.22] per 100 PY for Lag. Combining these with HIV-RNA results led to small increases in each incidence estimate. The results for the probability-based incidence assays were very close to those derived from the combination of the RITA and HIV-RNA assays. However, the testing history-derived approach estimated incidence as almost double that from the other methods and this is likely to be in large part due to reporting/recall bias.

Despite the limitations of the methods, it was possible to identify population sub-groups defined by age and sex at higher risk of HIV infection. 

Africa
Kenya
  • share