Introduction: HIV incidence estimates are critical for monitoring HIV transmission dynamics, and for
design and evaluation of the impact of interventions. Biomarkers and assays for cross-sectional
surveillance of HIV incidence are greatly needed because of the high costs and time needed to
maintain prospective cohorts to determine HIV incidence. New cross-sectional assays for estimation of
HIV incidence are attractive due to their improved performance and cost-effectiveness. In this
dissertation, methods for identification and characterization of recency of HIV infection are described.
An in-depth review of HIV recency determination methods, including novel cross-sectional application
of molecular methods, is given in “From serological assays to genomics.” Multi-assay approaches
were evaluated in order to increase the sensitivity and specificity of the commercial incidence assays in
the context of high treatment coverage and stable but high HIV prevalence in Botswana. A novel
biomarker based on HIV viral diversity was investigated as a complementary or standalone tool to
characterize HIV recency. In this thesis, an innovative use of pairwise diversity and the time to the
most recent common ancestor (tMRCA) in a heterosexual HIV-1 subtype C (HIV-1C) epidemic were
introduced as novel approaches for HIV incidence estimation. We evaluated the properties of the new
potential tools for estimating time since infection, including their specificity and predictive
performance in the context of the HIV-1C epidemic in Botswana.
Methods: Characterization of HIV recency and novel biomarkers for estimation of HIV infection
incidence is based on application of immunologic and molecular methods:
a) Evaluation of the long-term specificity (false recent classification rates) of serological tests for
recent infection, and algorithms for estimating HIV-1C incidence utilizing samples from
patients with known long-standing HIV infection.
b) Application of within-host viral diversity for estimation of HIV-1C recency in Botswana using
samples collected from patients with known time since seroconversion in the primary HIV-1C
infection cohort.
c) Investigation of intra-host viral pairwise diversity and the time to the most common recent
ancestor (tMRCA), as potential markers for HIV infection recency.
Results: We estimated for the first time false recency rates (FRR) of the commercially available BED
and Limiting Antigen (LAg) assays in Botswana. We demonstrated that combined algorithms reduce
FRR to the recommended < 2%. Including viral load in the assay algorithm resulted in an FRR of 0.4%
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for LAg. Analysis of the within-host viral pairwise diversity provided more accurate estimation of HIV
recency, as compared with the recommended LAg and BED using the receiver operator characteristic
analysis (ROC). We demonstrated that intra-host viral pairwise distances reduce misclassification and
increase the accuracy of serologic assays. tMRCA and intra-host viral pairwise distances correlated
with time since HIV infection provide additional novel tools for reliable estimation of HIV recency.
Conclusion: HIV infection recency can be determined cross-sectionally using a combination of
serological and molecular biomarkers. Including viral load and an assessment of prior exposure to
ARVs is critical for accurate estimation of HIV incidence. Intra-host pairwise diversity and tMRCA
are able to predict time since HIV infection and can be used to improve accuracy in estimation of HIV
infection recency