Cross-sectional HIV Incidence Research Articles

An enhanced cross-sectional HIV incidence estimator that incorporates prior HIV test results.

Incidence estimation of HIV infection can be performed using recent infection testing algorithm (RITA) results from a cross-sectional sample. This allows practitioners to understand population trends in the HIV epidemic without having to perform longitudinal follow-up on a cohort of individuals. The utility of the approach is limited by its precision, driven by the (low) sensitivity of the RITA at identifying recent infection. By utilizing results of previous HIV tests that individuals may have taken, we consider an enhanced RITA with increased sensitivity (and specificity). We use it to propose an enhanced estimator for incidence estimation. We prove the theoretical properties of the enhanced estimator and illustrate its numerical performance in simulation studies. We apply the estimator to data from a cluster-randomized trial to study the effect of community-level HIV interventions on HIV incidence. We demonstrate that the enhanced estimator provides a more precise estimate of HIV incidence compared to the standard estimator.

Evaluation of multi-assay algorithms for cross-sectional HIV incidence estimation in settings with universal antiretroviral treatment

BackgroundMulti-assay algorithms (MAAs) are used to estimate population-level HIV incidence and identify individuals with recent infection. Many MAAs use low viral load (VL) as a biomarker for long-term infection. This could impact incidence estimates in settings with high rates of early HIV treatment initiation. We evaluated the performance of two MAAs that do not include VL.MethodsSamples were collected from 219 seroconverters (infected < 1 year) and 4376 non-seroconverters (infected > 1 year) in the HPTN 071 (PopART) trial; 28.8% of seroconverter samples and 73.2% of non-seroconverter samples had VLs ≤ 400 copies/mL. Samples were tested with the Limiting Antigen Avidity assay (LAg) and JHU BioRad-Avidity assays. Antibody reactivity to two HIV peptides was measured using the MSD U-PLEX assay. Two MAAs were evaluated that do not include VL: a MAA that includes the LAg-Avidity assay and BioRad-Avidity assay (LAg + BR) and a MAA that includes the LAg-Avidity assay and two peptide biomarkers (LAg + PepPair). Performance of these MAAs was compared to a widely used MAA that includes LAg and VL (LAg + VL).ResultsThe incidence estimate for LAg + VL (1.29%, 95% CI: 0.97–1.62) was close to the observed longitudinal incidence (1.34% 95% CI: 1.17–1.53). The incidence estimates for the other two MAAs were higher (LAg + BR: 2.56%, 95% CI 2.01–3.11; LAg + PepPair: 2.84%, 95% CI: 1.36–4.32). LAg + BR and LAg + PepPair also misclassified more individuals infected > 2 years as recently infected than LAg + VL (1.2% [42/3483 and 1.5% [51/3483], respectively, vs. 0.2% [6/3483]). LAg + BR classified more seroconverters as recently infected than LAg + VL or LAg + PepPair (80 vs. 58 and 50, respectively) and identified ~ 25% of virally suppressed seroconverters as recently infected.ConclusionsThe LAg + VL MAA produced a cross-sectional incidence estimate that was closer to the longitudinal estimate than two MAAs that did not include VL. The LAg + BR MAA classified the greatest number of individual seroconverters as recently infected but had a higher false recent rate.

A top scoring pairs classifier for recent HIV infections.

Accurate incidence estimation of HIV infection from cross-sectional biomarker data is crucial for monitoring the epidemic and determining the impact of HIV prevention interventions. A key feature of cross-sectional incidence testing methods is the mean window period, defined as the average duration that infected individuals are classified as recently infected. Two assays available for cross-sectional incidence estimation, the BED capture immunoassay, and the Limiting Antigen (LAg) Avidity assay, measure a general characteristic of antibody response; performance of these assays can be affected and biased by factors such as viral suppression, resulting in sample misclassification and overestimation of HIV incidence. As availability and use of antiretroviral treatment increase worldwide, algorithms that do not include HIV viral load and are not impacted by viral suppression are needed for cross-sectional HIV incidence estimation. Using a phage display system to quantify antibody binding to over 3300 HIV peptides, we present a classifier based on top scoring peptide pairs that identifies recent infections using HIV antibody responses alone. Based on plasma samples from individuals with known dates of seroconversion, we estimated the mean window period for our classifier to be 217 days (95% confidence interval 183 to 257 days), compared to the estimated mean window period for the LAg-Avidity protocol of 106 days (76 to 146 days). Moreover, each of the four peptide pairs correctly classified more of the recent samples than the LAg-Avidity assay alone at the same classification accuracy for non-recent samples.

Impact of Early Antiretroviral Treatment Initiation on Performance of Cross-Sectional Incidence Assays.

Antiretroviral therapy (ART) can impact assays used for cross-sectional HIV incidence testing, causing inaccurate HIV incidence estimates. We evaluated the relationship between the timing of ART initiation and the performance of two serologic HIV incidence assays. We analyzed 302 samples from 55 individuals from the RV217 cohort (Early Capture HIV Cohort Study). Participants were grouped by ART start time: ART started <1 year after infection (N = 9); ART started 1-3 years after infection (N = 12); and never received ART (N = 34). Samples were tested using the Sedia LAg-Avidity and Johns Hopkins modified Bio-Rad-Avidity assays. Results were compared with those from the Johns Hopkins HIV Cohort in which participants initiated ART an average of 10 years after infection (N = 17). Participants on ART were virally suppressed at the time of sample collection. The increase in normalized optical density (ODn) values was an average of 2.15 U/year lower in participants who started ART <1 year after infection than in those who did not start ART. Participants who started ART 1-3 years after infection had a decline in ODn values 0.90 U/year faster compared with those who started ART an average of 10 years after infection. Timing of ART initiation did not significantly impact results obtained with the Bio-Rad-Avidity assay. ART initiation <1 year after HIV infection was associated with persistently low limiting antigen (Lag)-Avidity values; this could lead to overestimation of HIV incidence. LAg-Avidity values declined more rapidly the earlier ART was initiated. Bio-Rad-Avidity values were not impacted by the timing of ART initiation.

Comprehensive Profiling of HIV Antibody Evolution

SUMMARYThis study evaluates HIV antibody responses and their evolution during the course of HIV infection. A phage display system is used to characterize antibody binding to >3,300 HIV peptides in 57 adults with early- to late-stage infection. We find that the number of unique epitopes targeted (“antibody breadth”) increases early in infection and then stabilizes or declines. A decline in antibody breadth 9 months to 2 years after infection is associated with subsequent antiretroviral treatment (ART) initiation, and a faster decline in antibody breadth is associated with a shorter time to ART initiation. We identify 266 peptides with increasing antibody reactivity over time and 43 peptides with decreasing reactivity over time. These data are used to design a prototype four-peptide “serosignature” to predict duration of HIV infection. We also demonstrate that epitope engineering can be used to optimize peptide binding properties for applications such as cross-sectional HIV incidence estimation.

Impact of Home-Based HIV Testing Services on Progress Toward the UNAIDS 90-90-90 Targets in a Hyperendemic Area of South Africa.

In several subgroups of South Africa, the percentage of HIV-positive individuals aware of their status falls well below the UNAIDS 90% target. This study examined the impact that home-based HIV testing services (HBHTS) had on knowledge of status in a hyperendemic area of South Africa. We analysed data from the second cross-sectional HIV Incidence Provincial Surveillance System survey (2015/2016), a representative sample (n = 10,236) of individuals aged 15-49 years. Participants completed a questionnaire, provided blood samples for laboratory testing (used to estimate HIV prevalence), and were offered HBHTS. The proportion of people living with HIV (n = 3870) made aware of their status through HBHTS was measured, and factors associated with HBHTS uptake were identified. Knowledge of HIV-positive status at the time of the survey was 62.9% among men and 73.4% among women. Through HBHTS, the percentage of HIV-positive men and women who knew their status rose to 74.2% and 80.5%, respectively. The largest impact was observed among youth (15-24 years). Knowledge of status increased from 36.6% to 59.3% and from 50.8% to 64.8% among young men and women, respectively. In addition, 51.4% of those who had previously never tested received their first test. Key reasons for declining HBHTS among undiagnosed HIV-positive individuals included fear and self-report of an HIV-negative status. HBHTS was effective in increasing awareness of HIV-positive status, particularly among youth, men, and those who had never tested. HBHTS could have a marked impact on progress toward the UNAIDS 90-90-90 targets within these subgroups.

Short Communication: Dried Blood Spots Stored at Room Temperature Should Not Be Used for HIV Incidence Testing.

The limiting antigen (LAg)-avidity assay is a serologic assay used for cross-sectional HIV incidence testing. We compared the results obtained with the LAg-avidity assay using dried blood spot (DBS) samples stored at room temperature (18°C-25°C) or stored frozen at -80°C with results obtained from matched plasma samples. Matched DBS and plasma samples (306 paired samples) were collected in the HIV Prevention Trials Network (HPTN) 068 trial in South Africa (2012-2014). The DBS were stored at room temperature before testing. Matched DBS and plasma samples (100 paired samples) from the Consortium for the Evaluation and Performance of HIV Incidence Assays (CEPHIA) were collected in 2016 and were stored at -80°C. All DBS testing was performed in 2017. Differences in normalized optical density (ODn) were compared between matched DBS and plasma samples. For DBS samples stored at room temperature (HPTN 068), the average difference in ODn values for plasma versus DBS was 1.49 (95% confidence intervals [CI]: 1.36-1.62). In contrast, when DBS samples were stored at -80°C (CEPHIA), the average difference in ODn values for plasma versus DBS was -0.22 (95% CI: -0.32 to -0.13). DBS samples stored at room temperature should not be used for cross-sectional HIV incidence testing with the LAg-avidity assay.

Cross-Sectional HIV Incidence Estimation with Missing Biomarkers.

Considerable progress has been made in the development of approaches for HIV incidence estimation based on a cross-sectional survey for biomarkers of recent infection. Multiple biomarkers when used in combination can increase the precision of cross-sectional HIV incidence estimates. Multi-assay algorithms (MAAs) for cross-sectional HIV incidence estimation are hierarchical stepwise algorithms for testing the biological samples with multiple biomarkers. The objective of this paper is to consider some of the statistical challenges for addressing the problem of missing biomarkers in such testing algorithms. We consider several methods for handling missing biomarkers for (1) estimating the mean window period, and (2) estimating HIV incidence from a cross sectional survey once the mean window period has been determined. We develop a conditional estimation approach for addressing the missing data challenges and compare that method with two naïve approaches. Using MAAs developed for HIV subtype B, we evaluate the methods by simulation. We show that the two naïve estimation methods lead to biased results in most of the missing data scenarios considered. The proposed conditional approach protects against bias in all of the scenarios.

Infection Staging and Incidence Surveillance Applications of High Dynamic Range Diagnostic Immuno-Assay Platforms

Custom HIV staging assays, including the Sedia HIV-1 Limiting Antigen (LAg) Avidity EIA and avidity modifications of the Ortho VITROS anti-HIV-1+2 and Abbott ARCHITECT HIV Ag/Ab Combo assays, are used to identify "recent" infections in clinical settings and for cross-sectional HIV incidence estimation. However, the high dynamic range of chemiluminescent platforms allows differentiating recent and long-standing infection on signal intensity, and this raises the prospect of using unmodified diagnostic assays for infection timing and surveillance applications. We tested a panel of 2500 well-characterized specimens with estimable duration of HIV infection with the 3 assays and the unmodified ARCHITECT. Regression models were used to estimate mean durations of recent infection (MDRIs), context-specific false-recent rates (FRRs) and correlation between diagnostic signal intensity and LAg measurements. Hypothetical epidemiological scenarios were constructed to evaluate utility in surveillance applications. Over a range of MDRIs (reflecting recency discrimination thresholds), a diluted ARCHITECT-based RITA produced lower FRRs than the VITROS platform (FRR ≈ 0.5% and 1.5%, respectively at MDRI ≈ 200 days), and the unmodified diagnostic ARCHITECT produces incidence estimates with comparable precision to LAg (relative SE ≈ 17.5% and 15%, respectively at MDRI ≈ 200 days). ARCHITECT S/CO measurements were highly correlated with LAg optical density measurements (r = 0.80), and values below 200 are strongly predictive of LAg recency and duration of infection less than 1 year. Low quantitative measurements from the unmodified ARCHITECT obviate the need for additional recency testing, and its use is feasible in clinical staging and incidence surveillance applications.

Short Communication: False Recent Ratio of the Limiting-Antigen Avidity Assay and Viral Load Testing Algorithm Among Cameroonians with Long-Term HIV Infection.

Current serological assays that are used for cross-sectional HIV incidence estimation have been shown to misclassify individuals with chronic infection. Limited information exists on the performance of cross-sectional incidence assays in Central Africa. HIV-positive individuals from Cameroon who were infected for at least 1 or 2 years were evaluated to determine the false recent ratio (FRR) of a two-assay algorithm, which includes the Limiting Antigen Avidity (LAg-Avidity) assay (normalized optical density units, ODn <1.5) and HIV viral load (>1000 copies/ml). The subject-level FRR was 5.3% (95% confidence interval [CI], 2.1-10.5) for individuals infected for ≥1 year and 3.9% (95% CI, 0.8-11.0) for individuals infected for ≥2 years. These data suggest that the LAg-Avidity plus viral load incidence algorithm may overestimate HIV incidence rates in Central Africa.

Cross-Sectional HIV Incidence Surveillance: A Benchmarking of Approaches for Estimating the ‘Mean Duration of Recent Infection’

Abstract The application of biomarkers for ‘recent’ infection in cross-sectional HIV incidence surveillance requires the estimation of critical biomarker characteristics. Various approaches have been employed for using longitudinal data to estimate the Mean Duration of Recent Infection (MDRI) – the average time in the ‘recent’ state. In this systematic benchmarking of MDRI estimation approaches, a simulation platform was used to measure accuracy and precision of over twenty approaches, in thirty scenarios capturing various study designs, subject behaviors and test dynamics that may be encountered in practice. Results highlight that assuming a single continuous sojourn in the ‘recent’ state can produce substantial bias. Simple interpolation provides useful MDRI estimates provided subjects are tested at regular intervals. Regression performs the best – while ‘random effects’ describe the subject-clustering in the data, regression models without random effects proved easy to implement, stable, and of similar accuracy in scenarios considered; robustness to parametric assumptions was improved by regressing ‘recent’/‘non-recent’ classifications rather than continuous biomarker readings. All approaches were vulnerable to incorrect assumptions about subjects’ (unobserved) infection times. Results provided show the relationships between MDRI estimation performance and the number of subjects, inter-visit intervals, missed visits, loss to follow-up, and aspects of biomarker signal and noise.

Cross-Sectional HIV Incidence Surveillance: A Benchmarking of Approaches for Estimating the 'Mean Duration of Recent Infection'.

The application of biomarkers for 'recent' infection in cross-sectional HIV incidence surveillance requires the estimation of critical biomarker characteristics. Various approaches have been employed for using longitudinal data to estimate the Mean Duration of Recent Infection (MDRI) - the average time in the 'recent' state. In this systematic benchmarking of MDRI estimation approaches, a simulation platform was used to measure accuracy and precision of over twenty approaches, in thirty scenarios capturing various study designs, subject behaviors and test dynamics that may be encountered in practice. Results highlight that assuming a single continuous sojourn in the 'recent' state can produce substantial bias. Simple interpolation provides useful MDRI estimates provided subjects are tested at regular intervals. Regression performs the best - while 'random effects' describe the subject-clustering in the data, regression models without random effects proved easy to implement, stable, and of similar accuracy in scenarios considered; robustness to parametric assumptions was improved by regressing 'recent'/'non-recent' classifications rather than continuous biomarker readings. All approaches were vulnerable to incorrect assumptions about subjects' (unobserved) infection times. Results provided show the relationships between MDRI estimation performance and the number of subjects, inter-visit intervals, missed visits, loss to follow-up, and aspects of biomarker signal and noise.

Development and Evaluation of a Modified Fourth-Generation Human Immunodeficiency Virus Enzyme Immunoassay for Cross-Sectional Incidence Estimation in Clade B Populations.

Accurate methods for cross-sectional incidence estimation are needed for HIV surveillance and prevention research. We developed an avidity assay based on the fourth-generation Genetic Systems HIV Combo Ag/Ab EIA (Bio-Rad Combo assay) and evaluated its performance. The Bio-Rad Combo assay was modified incubating samples with and without 0.025 M diethylamine (DEA). The avidity index (AI) was calculated as the ratio of the DEA-treated to untreated result for a specific sample. We analyzed 2,140 samples from 808 individuals from the United States with known duration of HIV infection. The mean duration of recent infection (MDRI) and the false-recent rate (FRR, fraction of samples from individuals known to be infected >2 years misclassified as recent) were calculated for AI cutoffs of 20%-90% for the avidity assay alone and in combination with a viral load assay (VL, limit of detection 400 copies/ml). Factors associated with misclassification of samples collected ≥2 years after infections were also evaluated. The MDRI for the Bio-Rad Combo Avidity assay ranged from 50 days using an AI cutoff of 20% to 276 days using an AI cutoff of 90%; the FRR ranged from 0% to 9%. When samples with a VL <400 copies/ml were classified as nonrecent, the FRRs were reduced approximately twofold and the MDRI estimates were reduced by ∼20%. An AI cutoff of 50% provided an MDRI of 135 days with an FRR of 2.1%. All samples from elite suppressors had an AI >80%. In adjusted analysis, viral suppression and low CD4 cell count were significantly associated with misclassification among individuals infected >2 years. This modified Bio-Rad Combo Avidity assay may be a useful tool for cross-sectional HIV incidence estimation. Further research is needed to evaluate use of this assay in combination with other assays to accurately estimate population-level HIV incidence.

Improvements in the continuum of HIV care in an inner-city emergency department.

The Johns Hopkins Hospital Emergency Department has served as a window on the HIV epidemic for 25 years, and as a pioneer in emergency department-based screening/linkage-to-care (LTC) programs. We document changes in the burden of HIV and HIV care metrics to the evolving HIV epidemic in inner-city Baltimore. We analyzed seven serosurveys conducted on 18 ,144 adult Johns Hopkins Hospital Emergency Department patients between 1987 and 2013 as well as our HIV-screening/LTC program (2007, 2013) for trends in HIV prevalence, cross-sectional annual incidence estimates, undiagnosed HIV, LTC, antiretrovirals treatment, and viral suppression. HIV prevalence in 1987 was 5.2%, peaked at more than 11% from 1992 to 2003 and declined to 5.6% in 2013. Seroprevalence was highest for black men (initial 8.0%, peak 20.0%, last 9.9%) and lowest for white women. Among HIV-positive individuals, proportion of undiagnosed infection was 77% in 1987, 28% in 1992, and 12% by 2013 (P < 0.001). Cross-sectional annual HIV incidence estimates declined from 2.28% in 2001 to 0.16% in 2013. Thirty-day LTC improved from 32% (2007) to 72% (2013). In 2013, 80% of HIV-positive individuals had antiretrovirals ARVs detected in sera, markedly increased from 2007 (27%) (P < 0.001). Proportion of HIV-positive individuals with viral suppression (<400 copies/ml) increased from 23% (2001) to 59% (2013) (P < 0.001). Emergency department-based HIV testing has evolved from describing the local epidemic to a strategic interventional role, serving as a model for early HIV detection and LTC. Our contribution to community-based HIV-screening and LTC program parallels declines in undiagnosed HIV infection and incidence, and increases in antiretroviral use with associated viral suppression in the community.

High HIV prevalence and incidence among MSM across 12 cities in India.

To characterize prevalence, incidence, and associated correlates of HIV infection among MSM in 12 cities across India. Cross-sectional sample using respondent-driven sampling from September 2012 to June 2013. A total 12022 MSM (~1000/city) were recruited. Participants had to be at least 18 years, self-identify as male, and report oral/anal intercourse with a man in the prior year. HIV infection was diagnosed using three rapid tests. Cross-sectional HIV incidence was estimated using a multiassay algorithm. All estimates incorporate respondent-driven sampling-II weights. Median age was 25 years, 45% self-identified as 'panthi' (predominantly penetrative anal intercourse) and 30.6% reported being married to a woman. Weighted HIV prevalence was 7.0% (range: 1.7-13.1%). In multivariate analysis, significantly higher odds of HIV infection was observed among those who were older, had lower educational attainment, were practicing purely receptive anal sex or both receptive and penetrative sex, and those who were herpes simplex virus-2 positive. Of 1147 MSM who tested HIV positive, 53 were identified as recent HIV infections (annualized incidence = 0.87%; range = 0-2.2%). In multivariate analysis, injecting drugs in the prior 6 months, syphilis, and higher number of male partners and fewer female partners were significantly associated with recent HIV infection. We observed a high burden of HIV among MSM in India with tremendous diversity in prevalence, incidence, and risk behaviors. In particular, we observed high incidence in areas with relatively low prevalence suggesting emerging epidemics in areas not previously recognized to have high HIV burden.

Comparison of antibody responses to HIV infection in Ugandan women infected with HIV subtypes A and D.

We compared the serologic response to HIV infection in Ugandan women with HIV subtype A (N=82) and D (N=32) infection using a limiting antigen avidity assay (LAg-Avidity assay); 2,614 samples were analyzed. Study participants were followed a median of 6.6 years after HIV seroconversion. Samples were classified as assay positive if they had a LAg-Avidity assay result <1.5 normalized optical density units (OD-n). Women with subtype D infection were more likely to have delayed antibody maturation. During the first 2 years after seroconversion, the mean time that women had an assay-positive result (mean duration of recent infection, MDRI) was longer for women with subtype D infection than women with subtype A infection (267.9 days, 95% CI: 231.2-308.2 vs. 167.3 days, 95% CI: 151.8-185.9 days, p<0.01). The MDRI was also longer for women with subtype D infection after excluding low viral load samples and samples from women on antiretroviral therapy (ART). Women infected for >2 years were also more likely to be misclassified as recently infected in they had subtype D infection. Women with subtype D infection were also more likely to have antibody waning compared to women with subtype A infection. These findings may be related to the higher pathogenicity of subtype D HIV infection and are relevant to use of the LAg-Avidity assay for cross-sectional HIV incidence estimation in populations where subtype D infection is prevalent.

A comparison of two measures of HIV diversity in multi-assay algorithms for HIV incidence estimation.

BackgroundMulti-assay algorithms (MAAs) can be used to estimate HIV incidence in cross-sectional surveys. We compared the performance of two MAAs that use HIV diversity as one of four biomarkers for analysis of HIV incidence.MethodsBoth MAAs included two serologic assays (LAg-Avidity assay and BioRad-Avidity assay), HIV viral load, and an HIV diversity assay. HIV diversity was quantified using either a high resolution melting (HRM) diversity assay that does not require HIV sequencing (HRM score for a 239 base pair env region) or sequence ambiguity (the percentage of ambiguous bases in a 1,302 base pair pol region). Samples were classified as MAA positive (likely from individuals with recent HIV infection) if they met the criteria for all of the assays in the MAA. The following performance characteristics were assessed: (1) the proportion of samples classified as MAA positive as a function of duration of infection, (2) the mean window period, (3) the shadow (the time period before sample collection that is being assessed by the MAA), and (4) the accuracy of cross-sectional incidence estimates for three cohort studies.ResultsThe proportion of samples classified as MAA positive as a function of duration of infection was nearly identical for the two MAAs. The mean window period was 141 days for the HRM-based MAA and 131 days for the sequence ambiguity-based MAA. The shadows for both MAAs were <1 year. Both MAAs provided cross-sectional HIV incidence estimates that were very similar to longitudinal incidence estimates based on HIV seroconversion.ConclusionsMAAs that include the LAg-Avidity assay, the BioRad-Avidity assay, HIV viral load, and HIV diversity can provide accurate HIV incidence estimates. Sequence ambiguity measures obtained using a commercially-available HIV genotyping system can be used as an alternative to HRM scores in MAAs for cross-sectional HIV incidence estimation.

Performance of a Limiting-Antigen Avidity Enzyme Immunoassay for Cross-Sectional Estimation of HIV Incidence in the United States

BackgroundA limiting antigen avidity enzyme immunoassay (HIV-1 LAg-Avidity assay) was recently developed for cross-sectional HIV incidence estimation. We evaluated the performance of the LAg-Avidity assay alone and in multi-assay algorithms (MAAs) that included other biomarkers.Methods and FindingsPerformance of testing algorithms was evaluated using 2,282 samples from individuals in the United States collected 1 month to >8 years after HIV seroconversion. The capacity of selected testing algorithms to accurately estimate incidence was evaluated in three longitudinal cohorts. When used in a single-assay format, the LAg-Avidity assay classified some individuals infected >5 years as assay positive and failed to provide reliable incidence estimates in cohorts that included individuals with long-term infections. We evaluated >500,000 testing algorithms, that included the LAg-Avidity assay alone and MAAs with other biomarkers (BED capture immunoassay [BED-CEIA], BioRad-Avidity assay, HIV viral load, CD4 cell count), varying the assays and assay cutoffs. We identified an optimized 2-assay MAA that included the LAg-Avidity and BioRad-Avidity assays, and an optimized 4-assay MAA that included those assays, as well as HIV viral load and CD4 cell count. The two optimized MAAs classified all 845 samples from individuals infected >5 years as MAA negative and estimated incidence within a year of sample collection. These two MAAs produced incidence estimates that were consistent with those from longitudinal follow-up of cohorts. A comparison of the laboratory assay costs of the MAAs was also performed, and we found that the costs associated with the optimal two assay MAA were substantially less than with the four assay MAA.ConclusionsThe LAg-Avidity assay did not perform well in a single-assay format, regardless of the assay cutoff. MAAs that include the LAg-Avidity and BioRad-Avidity assays, with or without viral load and CD4 cell count, provide accurate incidence estimates.

Development of Methods for Cross-Sectional HIV Incidence Estimation in a Large, Community Randomized Trial

BackgroundAccurate methods of HIV incidence determination are critically needed to monitor the epidemic and determine the population level impact of prevention trials. One such trial, Project Accept, a Phase III, community-randomized trial, evaluated the impact of enhanced, community-based voluntary counseling and testing on population-level HIV incidence. The primary endpoint of the trial was based on a single, cross-sectional, post-intervention HIV incidence assessment.Methods and FindingsTest performance of HIV incidence determination was evaluated for 403 multi-assay algorithms [MAAs] that included the BED capture immunoassay [BED-CEIA] alone, an avidity assay alone, and combinations of these assays at different cutoff values with and without CD4 and viral load testing on samples from seven African cohorts (5,325 samples from 3,436 individuals with known duration of HIV infection [1 month to >10 years]). The mean window period (average time individuals appear positive for a given algorithm) and performance in estimating an incidence estimate (in terms of bias and variance) of these MAAs were evaluated in three simulated epidemic scenarios (stable, emerging and waning). The power of different test methods to detect a 35% reduction in incidence in the matched communities of Project Accept was also assessed. A MAA was identified that included BED-CEIA, the avidity assay, CD4 cell count, and viral load that had a window period of 259 days, accurately estimated HIV incidence in all three epidemic settings and provided sufficient power to detect an intervention effect in Project Accept.ConclusionsIn a Southern African setting, HIV incidence estimates and intervention effects can be accurately estimated from cross-sectional surveys using a MAA. The improved accuracy in cross-sectional incidence testing that a MAA provides is a powerful tool for HIV surveillance and program evaluation.

HIV Diversity as a Biomarker for HIV Incidence Estimation: Including a High-Resolution Melting Diversity Assay in a Multiassay Algorithm

Multiassay algorithms (MAAs) can be used to estimate cross-sectional HIV incidence. We previously identified a robust MAA that includes the BED capture enzyme immunoassay (BED-CEIA), the Bio-Rad Avidity assay, viral load, and CD4 cell count. In this report, we evaluated MAAs that include a high-resolution melting (HRM) diversity assay that does not require sequencing. HRM scores were determined for eight regions of the HIV genome (2 in gag, 1 in pol, and 5 in env). The MAAs that were evaluated included the BED-CEIA, the Bio-Rad Avidity assay, viral load, and the HRM diversity assay, using HRM scores from different regions and a range of region-specific HRM diversity assay cutoffs. The performance characteristics based on the proportion of samples that were classified as MAA positive by duration of infection were determined for each MAA, including the mean window period. The cross-sectional incidence estimates obtained using optimized MAAs were compared to longitudinal incidence estimates for three cohorts in the United States. The performance of the HRM-based MAA was nearly identical to that of the MAA that included CD4 cell count. The HRM-based MAA had a mean window period of 154 days and provided cross-sectional incidence estimates that were similar to those based on cohort follow-up. HIV diversity is a useful biomarker for estimating HIV incidence. MAAs that include the HRM diversity assay can provide accurate HIV incidence estimates using stored blood plasma or serum samples without a requirement for CD4 cell count data.