Estimation of HIV incidence using multiple biomarkers

Recent and Local HIV Infections among Newly Diagnosed Cases in Two Districts of Chongqing, China (2019-2021)

Newly diagnosed HIV cases often do not clearly indicate whether they are recent or long-standing infections. We collected the history of HIV antibody testing, sexual behavior and initial CD4 + T cell (CD4) count of newly diagnosed HIV/AIDS to determine the time and location of HIV infections. Of the included 612 cases, 17.3% were classified as recent HIV infection. Recent HIV infections were higher in cases aged < 30 (adjusted odds ratio [AOR] = 4.267, 95% Confidence Interval [CI] 1.856-9.813) and 30-49 (AOR = 2.847, 95%CI 1.356-5.977) vs. ≥50, and the transmission mode was men who have sex with men (MSM) (AOR = 4.130, 95%CI 1.815-9.399) was higher than heterosexual contact. Of the 582 cases, 80.8% were classified as local HIV infection (An infection occurred in the two survey districts). Local HIV infections were higher in cases being single and divorced/widowed (AOR = 2.511, 95% CI 1.271-4.962) vs. being married, residing in the survey districts ≥ 5 years (AOR = 168.962, 95%CI 64.942-439.593) vs. < 1 year, transmission mode was MSM (AOR = 8.669, 95%CI 2.668-28.163) vs. heterosexual contact, and acquired infections through spouses or steady partners (AOR = 11.493, 95%CI 3.236-40.819) vs. commercial partners. Both recent and local HIV infections were higher in cases whose transmission mode was MSM, we recommended using internet platforms and MSM dating apps for HIV education and intervention, promoting internet intervention tools to raise awareness about HIV and facilitate early detection.

Study design approaches for future active-controlled HIV prevention trials

Objectives

Vigorous discussions are ongoing about future efficacy trial designs of candidate human immunodeficiency virus (HIV) prevention interventions. The study design challenges of HIV prevention interventions are considerable given rapid evolution of the prevention landscape and evidence of multiple modalities of highly effective products; future trials will likely be 'active-controlled', i.e., not include a placebo arm. Thus, novel design approaches are needed to accurately assess new interventions against these highly effective active controls.

Methods

To discuss active control design challenges and identify solutions, an initial virtual workshop series was hosted and supported by the International AIDS Enterprise (October 2020-March 2021). Subsequent symposia discussions continue to advance these efforts. As the non-inferiority design is an important conceptual reference design for guiding active control trials, we adopt several of its principles in our proposed design approaches.

Results

We discuss six potential study design approaches for formally evaluating absolute prevention efficacy given data from an active-controlled HIV prevention trial including using data from: 1) a registrational cohort, 2) recency assays, 3) an external trial placebo arm, 4) a biomarker of HIV incidence/exposure, 5) an anti-retroviral drug concentration as a mediator of prevention efficacy, and 6) immune biomarkers as a mediator of prevention efficacy.

Conclusions

Our understanding of these proposed novel approaches to future trial designs remains incomplete and there are many future statistical research needs. Yet, each of these approaches, within the context of an active-controlled trial, have the potential to yield reliable evidence of efficacy for future biomedical interventions.

Development of a multiassay algorithm (MAA) to identify recent HIV infection in newly diagnosed individuals in Indonesia

Ongoing HIV transmission is a public health priority in Indonesia. We developed a new multiassay algorithm (MAA) to identify recent HIV infection. The MAA is a sequential decision tree based on multiple biomarkers, starting with CD4+ T cells >200/μL, followed by plasma viral load (pVL) > 1,000 copies/ml, avidity index (AI) < 0 · 7, and pol ambiguity <0 · 47%. Plasma from 140 HIV-infected adults from 19 hospitals across Indonesia (January 2018 - June 2020) was studied, consisting of a training set (N = 60) of longstanding infection (>12-month) and a test set (N = 80) of newly diagnosed (≤1-month) antiretroviral (ARV) drug naive individuals. Ten of eighty (12 · 5%) newly diagnosed individuals were classified as recent infections. Drug resistance mutations (DRMs) against reverse transcriptase inhibitors were identified in two individuals: one infected with HIV subtype C (K219Q, V179T) and the other with CRF01_AE (V179D). Ongoing HIV transmission, including infections with DRMs, is substantial in Indonesia.

Estimation of HIV-1 Incidence Using a Testing History-Based Method; Analysis From the Population-Based HIV Impact Assessment Survey Data in 12 African Countries

BACKGROUND

Estimating HIV incidence is essential to monitoring progress in sub-Saharan African nations toward global epidemic control. One method for incidence estimation is to test nationally representative samples using laboratory-based incidence assays. An alternative method based on reported HIV testing history and the proportion of undiagnosed infections has recently been described.

METHODS

We applied an HIV incidence estimation method which uses history of testing to nationally representative cross-sectional survey data from 12 sub-Saharan African nations with varying country-specific HIV prevalence. We compared these estimates with those derived from laboratory-based incidence assays. Participants were tested for HIV using the national rapid test algorithm and asked about prior HIV testing, date and result of their most recent test, and date of antiretroviral therapy initiation.

RESULTS

The testing history-based method consistently produced results that are comparable and strongly correlated with estimates produced using a laboratory-based HIV incidence assay (ρ = 0.85). The testing history-based method produced incidence estimates that were more precise compared with the biomarker-based method. The testing history-based method identified sex-, age-, and geographic location-specific differences in incidence that were not detected using the biomarker-based method.

CONCLUSIONS

The testing history-based method estimates are more precise and can produce age-specific and sex-specific incidence estimates that are informative for programmatic decisions. The method also allows for comparisons of the HIV transmission rate and other components of HIV incidence among and within countries. The testing history-based method is a useful tool for estimating and validating HIV incidence from cross-sectional survey data.

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

BACKGROUND

Multi-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.

METHODS

Samples 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).

RESULTS

The 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.

CONCLUSIONS

The 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.

Recent HIV Infection: Diagnosis and Public Health Implications

The early period of infection with human immunodeficiency virus (HIV) has been associated with higher infectiousness and, consequently, with more transmission events. Over the last 30 years, assays have been developed that can detect viral and immune biomarkers during the first months of HIV infection. Some of them depend on the functional properties of antibodies including their changing titers or the increasing strength of binding with antigens over time. There have been efforts to estimate HIV incidence using antibody-based assays that detect recent HIV infection along with other laboratory and clinical information. Moreover, some interventions are based on the identification of people who were recently infected by HIV. This review summarizes the evolution of efforts to develop assays for the detection of recent HIV infection and to use these assays for the cross-sectional estimation of HIV incidence or for prevention purposes.

Factors Associated With Newly HIV Infection and Transmitted Drug Resistance Among Men Who Have Sex With Men in Harbin, P.R. China

Background

This study aimed to evaluate HIV incidence, factors associated with HIV incidence and transmitted drug resistance (TDR) among newly infected men who have sex with men (MSM) in Harbin, P.R. China.

Methods

A cohort study was conducted among MSM in Harbin during 2013 and 2018, with a follow-up frequency of every 6 months. Blood samples from MSM were tested for HIV antibodies, RNA was extracted from plasma, and the pol gene was sequenced, and genotypic drug-resistance analyses were performed.

Results

From 2013 to 2018, the overall rate of HIV incidence was 3.55/100 PY. Syphilis infection, unprotected sex with men in the past 6 months, and unawareness of HIV/AIDS knowledge were risk factors for HIV seroconversion. The distribution of HIV genotypes was as follows: CRF01_AE, 57.1%; CRF07_BC, 28.5%; CRF55_01B, 2.0%; B, 8.2%. The prevalence of transmitted drug resistance was 4.08%.

Conclusion

HIV incidence in MSM in Harbin is moderately high, and transmitted drug resistance exists in the population.

Statistical considerations for cross-sectional HIV incidence estimation based on recency test

Longitudinal cohorts to determine the incidence of HIV infection are logistically challenging, so researchers have sought alternative strategies. Recency test methods use biomarker profiles of HIV-infected subjects in a cross-sectional sample to infer whether they are "recently" infected and to estimate incidence in the population. Two main estimators have been used in practice: one that assumes a recency test is perfectly specific, and another that allows for false-recent results. To date, these commonly used estimators have not been rigorously studied with respect to their assumptions and statistical properties. In this article, we present a theoretical framework with which to understand these estimators and interrogate their assumptions, and perform a simulation study and data analysis to assess the performance of these estimators under realistic HIV epidemiological dynamics. We find that the snapshot estimator and the adjusted estimator perform well when their corresponding assumptions hold. When assumptions on constant incidence and recency test characteristics fail to hold, the adjusted estimator is more robust than the snapshot estimator. We conclude with recommendations for the use of these estimators in practice and a discussion of future methodological developments to improve HIV incidence estimation via recency test.

Use of HIV Recency Assays for HIV Incidence Estimation and Other Surveillance Use Cases: Systematic Review

BACKGROUND

HIV assays designed to detect recent infection, also known as "recency assays," are often used to estimate HIV incidence in a specific country, region, or subpopulation, alone or as part of recent infection testing algorithms (RITAs). Recently, many countries and organizations have become interested in using recency assays within case surveillance systems and routine HIV testing services to measure other indicators beyond incidence, generally referred to as "non-incidence surveillance use cases."

OBJECTIVE

This review aims to identify published evidence that can be used to validate methodological approaches to recency-based incidence estimation and non-incidence use cases. The evidence identified through this review will be used in the forthcoming technical guidance by the World Health Organization (WHO) and United Nations Programme on HIV/AIDS (UNAIDS) on the use of HIV recency assays for identification of epidemic trends, whether for HIV incidence estimation or non-incidence indicators of recency.

METHODS

To identify the best methodological and field implementation practices for the use of recency assays to estimate HIV incidence and trends in recent infections for specific populations or geographic areas, we conducted a systematic review of the literature to (1) understand the use of recency testing for surveillance in programmatic and laboratory settings, (2) review methodologies for implementing recency testing for both incidence estimation and non-incidence use cases, and (3) assess the field performance characteristics of commercially available recency assays.

RESULTS

Among the 167 documents included in the final review, 91 (54.5%) focused on assay or algorithm performance or methodological descriptions, with high-quality evidence of accurate age- and sex-disaggregated HIV incidence estimation at national or regional levels in general population settings, but not at finer geographic levels for prevention prioritization. The remaining 76 (45.5%) described the field use of incidence assays including field-derived incidence (n=45), non-incidence (n=25), and both incidence and non-incidence use cases (n=6). The field use of incidence assays included integrating RITAs into routine surveillance and assisting with molecular genetic analyses, but evidence was generally weaker or only reported on what was done, without validation data or findings related to effectiveness of using non-incidence indicators calculated through the use of recency assays as a proxy for HIV incidence.

CONCLUSIONS

HIV recency assays have been widely validated for estimating HIV incidence in age- and sex-specific populations at national and subnational regional levels; however, there is a lack of evidence validating the accuracy and effectiveness of using recency assays to identify epidemic trends in non-incidence surveillance use cases. More research is needed to validate the use of recency assays within HIV testing services, to ensure findings can be accurately interpreted to guide prioritization of public health programming.

Evaluation of multi-assay algorithms for identifying individuals with recent HIV infection: HPTN 071 (PopART)

Background

Assays and multi-assay algorithms (MAAs) have been developed for population-level cross-sectional HIV incidence estimation. These algorithms use a combination of serologic and/or non-serologic biomarkers to assess the duration of infection. We evaluated the performance of four MAAs for individual-level recency assessments.

Methods

Samples were obtained from 220 seroconverters (infected <1 year) and 4,396 non-seroconverters (infected >1 year) enrolled in an HIV prevention trial (HPTN 071 [PopART]); 28.6% of the seroconverters and 73.4% of the non-seroconverters had HIV viral loads ≤400 copies/mL. Samples were tested with two laboratory-based assays (LAg-Avidity, JHU BioRad-Avidity) and a point-of-care assay (rapid LAg). The four MAAs included different combinations of these assays and HIV viral load. Seroconverters on antiretroviral treatment (ART) were identified using a qualitative multi-drug assay.

Results

The MAAs identified between 54 and 100 (25% to 46%) of the seroconverters as recently-infected. The false recent rate of the MAAs for infections >2 years duration ranged from 0.2%-1.3%. The MAAs classified different overlapping groups of individuals as recent vs. non-recent. Only 32 (15%) of the 220 seroconverters were classified as recent by all four MAAs. Viral suppression impacted the performance of the two LAg-based assays. LAg-Avidity assay values were also lower for seroconverters who were virally suppressed on ART compared to those with natural viral suppression.

Conclusions

The four MAAs evaluated varied in sensitivity and specificity for identifying persons infected <1 year as recently infected and classified different groups of seroconverters as recently infected. Sensitivity was low for all four MAAs. These performance issues should be considered if these methods are used for individual-level recency assessments.

Regression with interval-censored covariates: Application to cross-sectional incidence estimation

A method for generalized linear regression with interval-censored covariates is described, extending previous approaches. A scenario is considered in which an interval-censored covariate of interest is defined as a function of other variables. Instead of directly modeling the distribution of the interval-censored covariate of interest, the distributions of the variables which determine that covariate are modeled, and the distribution of the covariate of interest is inferred indirectly. This approach leads to an estimation procedure using the Expectation-Maximization (EM) algorithm. The performance of this approach is compared to two alternative approaches, one in which the censoring interval midpoints are used as estimates of the censored covariate values, and another in which the censored values are multiply imputed using uniform distributions over the censoring intervals. A simulation framework is constructed to assess these methods' accuracies across a range of scenarios. The proposed approach is found to have less bias than midpoint analysis and uniform imputation, at the cost of small increases in standard error.

HIV, HCV, and HBV incidence and residual risk in US blood donors before and after implementation of the 12-month deferral policy for men who have sex with men

BACKGROUND

In December 2015, the men who have sex with men (MSM) deferral was reduced to 12 months in the United States. We compared human immunodeficiency virus (HIV), hepatitis C virus (HCV), and hepatitis B virus (HBV) incidence and residual risk before and after this policy change using data from >50% of the US blood supply.

STUDY DESIGN AND METHODS

Three estimation intervals from the Transfusion-Transmissible Infections Monitoring System were compared: 15-months pre- and two consecutive, nonoverlapping 15-month post-MSM deferral implementation. Repeat, first-time, and weighted all-donor incidences were estimated. Residual risk was calculated for all incidence estimates using the incidence/window-period method.

RESULTS

HIV repeat donor incidence was 1.57 per 100 000 person-years (phtpy) in the second 15-month post change and not significantly different from pre-MSM incidence of 2.19 phtpy. Similar values were seen for HCV (1.49 phtpy vs 1.46 phtpy) and HBV (1.14 phtpy vs 0.97 phtpy). In some cases, higher estimated incidence, but without significant change from pre-MSM to the second post change period occurred for males and first-time donors (eg, first-time donors, second post change period: 6.12 phtpy HIV, 6.41 phtpy HCV and 5.34 phtpy HBV). Estimated per donation residual risk was 1:1.6 million for HIV, 1:2.0 million for HCV and 1:1.0 million for HBV based on weighted incidence for all donors.

CONCLUSIONS

Repeat, first-time, and overall donor incidence did not vary significantly comparing pre-MSM to either of the post-MSM estimation intervals. Residual risk estimates vary by study, but all yield residual risks in the United States of ≤1 per million, and thus far have not shown increasing risk with the 12-month MSM policy change.

Antibody avidity-based approach to estimate population-level incidence of hepatitis C

BACKGROUND & AIMS

Accurate HCV incidence estimates are critical for monitoring progress towards HCV elimination goals, including an 80% reduction in HCV incidence by 2030. Moreover, incidence estimates can help guide prevention and treatment programming, particularly in the context of the US opioid epidemic.

METHODS

An inexpensive, Genedia-based HCV IgG antibody avidity assay was evaluated as a platform to estimate cross-sectional, population-level primary HCV incidence using 1,840 HCV antibody and RNA-positive samples from 875 individuals enrolled in 5 cohort studies in the US and India. Using samples collected <2 years following HCV seroconversion, the mean duration of recent infection (MDRI) was calculated by fitting a maximum likelihood binomial regression model to the probability of appearing recent. Among samples collected ≥2 years post-HCV seroconversion, an individual-level false recent ratio (FRR) was calculated by estimating the probability of appearing recent using an exact binomial test. Factors associated with falsely appearing recent among samples collected ≥2 years post seroconversion were determined by Poisson regression with generalized estimating equations and robust variance estimators.

RESULTS

An avidity index cut-off of <40% resulted in an MDRI of 113 days (95% CI 84-146), and FRRs of 0.4% (95% CI 0.0-1.2), 4.6% (95% CI 2.2-8.3), and 9.5% (95% CI 3.6-19.6) among individuals who were HIV-uninfected, HIV-infected, and HIV-infected with a CD4 count <200/μl, respectively. No variation was seen between HCV genotypes 1 and 3. In hypothetical scenarios of high-risk settings, a sample size of <1,000 individuals could reliably estimate primary HCV incidence.

CONCLUSIONS

This cross-sectional approach can estimate primary HCV incidence for the most common genotypes. This tool can serve as a valuable resource for program and policy planners seeking to monitor and reduce HCV burden.

LAY SUMMARY

Determining the rate of new hepatitis C virus (HCV) infections in a population is critical to monitoring progress toward HCV elimination and to appropriately guide control efforts. However, since HCV infections are most often initially asymptomatic, it is difficult to estimate the rate of new HCV infections without following HCV-uninfected people over time and repeatedly testing them for HCV infection. Here, we present a novel, resource-efficient method to estimate the rate of new HCV infections in a population using data from a single timepoint.

Design of a Multiplexed Analyte Biosensor using Digital Barcoded Particles and Impedance Spectroscopy

Multiplexing allows quantifying multiple analytes in a single step, providing advantages over individual testing through shorter processing time, lower sample volume, and reduced cost per test. Currently, flow cytometry is the gold standard for biomedical multiplexing, but requires technical training, extensive data processing, and expensive operational and capital costs. To solve this challenge, we designed digital barcoded particles and a microfluidic architecture for multiplexed analyte quantification. In this work, we simulate and model non-fluorescence-based microfluidic impedance detection with a single excitation and detection scheme using barcoded polymer microparticles. Our barcoded particles can be designed with specific coding regions and generate numerous distinct patterns enabling digital barcoding. We found that signals based on adhered microsphere position and relative orientation were evaluated and separated based on their associated electrical signatures and had a 7 µm microsphere limit of detection. Our proposed microfluidic system can enumerate micron-sized spheres in a single assay using barcoded particles of various configurations. As representation of blood cells, the microsphere concentrations may provide useful information on disease onset and progression. Such sensors may be used for diagnostic and management of common critical care diseases like sepsis, acute kidney injury, urinary tract infections, and HIV/AIDS.

Viral Diversity Based on Next-Generation Sequencing of HIV-1 Provides Precise Estimates of Infection Recency and Time Since Infection

BACKGROUND

Human immunodeficiency virus type 1 (HIV-1) genetic diversity increases over the course of infection and can be used to infer the time since infection and, consequently, infection recency, which are crucial for HIV-1 surveillance and the understanding of viral pathogenesis.

METHODS

We considered 313 HIV-infected individuals for whom reliable estimates of infection dates and next-generation sequencing (NGS)-derived nucleotide frequency data were available. Fractions of ambiguous nucleotides, obtained by population sequencing, were available for 207 samples. We assessed whether the average pairwise diversity calculated using NGS sequences provided a more exact prediction of the time since infection and classification of infection recency (<1 year after infection), compared with the fraction of ambiguous nucleotides.

RESULTS

NGS-derived average pairwise diversity classified an infection as recent with a sensitivity of 88% and a specificity of 85%. When considering only the 207 samples for which fractions of ambiguous nucleotides were available, the NGS-derived average pairwise diversity exhibited a higher sensitivity (90% vs 78%) and specificity (95% vs 67%) than the fraction of ambiguous nucleotides. Additionally, the average pairwise diversity could be used to estimate the time since infection with a mean absolute error of 0.84 years, compared with 1.03 years for the fraction of ambiguous nucleotides.

CONCLUSIONS

Viral diversity based on NGS data is more precise than that based on population sequencing in its ability to predict infection recency and provides an estimated time since infection that has a mean absolute error of <1 year.

Cross-sectional human immunodeficiency virus incidence estimation accounting for heterogeneity across communities

Accurate estimation of human immunodeficiency virus (HIV) incidence rates is crucial for the monitoring of HIV epidemics, the evaluation of prevention programs, and the design of prevention studies. Traditional cohort approaches to measure HIV incidence require repeatedly testing large cohorts of HIV-uninfected individuals with an HIV diagnostic test (eg, enzyme-linked immunosorbent assay) for long periods of time to identify new infections, which can be prohibitively costly, time-consuming, and subject to loss to follow-up. Cross-sectional approaches based on the usual HIV diagnostic test and biomarkers of recent infection offer important advantages over standard cohort approaches, in terms of time, cost, and attrition. Cross-sectional samples usually consist of individuals from different communities. However, small sample sizes limit the ability to estimate community-specific incidence and existing methods typically ignore heterogeneity in incidence across communities. We propose a permutation test for the null hypothesis of no heterogeneity in incidence rates across communities, develop a random-effects model to account for this heterogeneity and to estimate community-specific incidence, and provide one way to estimate the coefficient of variation. We evaluate the performance of the proposed methods through simulation studies and apply them to the data from the National Institute of Mental Health Project ACCEPT, a phase 3 randomized controlled HIV prevention trial in Sub-Saharan Africa, to estimate the overall and community-specific HIV incidence rates.

Modeling methods for estimating HIV incidence: a mathematical review

Estimating HIV incidence is crucial for monitoring the epidemiology of this infection, planning screening and intervention campaigns, and evaluating the effectiveness of control measures. However, owing to the long and variable period from HIV infection to the development of AIDS and the introduction of highly active antiretroviral therapy, accurate incidence estimation remains a major challenge. Numerous estimation methods have been proposed in epidemiological modeling studies, and here we review commonly-used methods for estimation of HIV incidence. We review the essential data required for estimation along with the advantages and disadvantages, mathematical structures and likelihood derivations of these methods. The methods include the classical back-calculation method, the method based on CD4+ T-cell depletion, the use of HIV case reporting data, the use of cohort study data, the use of serial or cross-sectional prevalence data, and biomarker approach. By outlining the mechanistic features of each method, we provide guidance for planning incidence estimation efforts, which may depend on national or regional factors as well as the availability of epidemiological or laboratory datasets.

Establishment of an anti-hepatitis C virus IgG avidity test for dried serum/plasma spots

Monitoring recency of infection helps to identify current transmission in vulnerable populations for effective disease control. We have established an in-house avidity based hepatitis C virus (HCV) recency assay based on the Monolisa Anti-HCV PLUS Version 3 ELISA kit for use of dried serum/plasma spots (DS/PS) in order to distinguish recent and long-term infections. A first panel of DS/PS (n = 218; genotype 1 n = 170 and non-genotype 1 n = 48) consisting of primary and at least one follow up sample was used to analyze the temporal changes of the Avidity Index (AI) over time. Sub-panels of longitudinal DS/PS (n = 66) and acute cases (<26 weeks; n = 34) were taken to calculate the Mean Duration of Recent Infection (MDRI) and the False Long-term Rate (FLTR), respectively. A second panel of DS/PS >104 weeks (n = 132) and a third panel of DS/PS prepared from resolved infections (≥180 days since last positive; n = 32) were used to calculate the False Recent Rate (FRR). For all genotypes, the optimal AI cut-off was determined to be 40% resulting in an MDRI of 364 days (95% CI: 223-485). FLTR was 5.9% (95% CI: 0.7-19.7), 8.3% (95% CI: 1-27), and 0% (-) and FRR was 13.6% (95% CI: 8.3-20.7), 11.7% (95% CI: 6.6-19), and 30.6% (95% CI: 9.1-61.4) for all genotypes, genotype 1, and non-genotype 1 infections, respectively. For resolved infections, the FRR was 53.1% (95% CI: 35.8-70.4). Thus, this assay performs particularly well for genotype 1 reaching a high rate of correct discriminations between infections acquired less than a year before diagnosis and those acquired earlier by applying an AI cut-off of 40%. Due to a rapid decline in avidity post resolution of an HCV infection this assay is not recommended to be used in HCV RNA negative patients.

Cross-sectional HIV incidence estimation in an evolving epidemic

The cross-sectional approach to HIV incidence estimation overcomes some of the challenges with longitudinal cohort studies and has been successfully applied in many settings around the world. However, the cross-sectional approach does rely on an initial training data set to develop and calibrate the statistical methods to be used in cross-sectional surveys. The problem addressed in this paper is that the initial training data set may, over time, not reflect the current target population of interest because of evolution of the epidemic. For example, the mismatch between the target population and the initial data set could occur because of increasing use of anti-retroviral therapy among HIV-infected persons throughout the world. We developed methods to adjust the initial training data set with the goal that the adjusted data sets better reflect the target population. These adjustment procedures could help avoid the time and expense of collecting a completely new training data set from the current target population. We report the results of a simulation study to evaluate the procedures. We applied the methods to a dataset of HIV subtype B infection. The adjustment procedures could be applicable in situations other than cross-sectional incidence estimation where complex statistical analyses are to be conducted using an initial data set but those results may not be directly transportable to a new target population of interest. The approach we have proposed could offer a practical and cost-effective way to apply cross-sectional incidence methods to new target populations as the epidemic evolves.

Identification and validation of a multi-assay algorithm for cross-sectional HIV incidence estimation in populations with subtype C infection

Introduction

Cross‐sectional methods can be used to estimate HIV incidence for surveillance and prevention studies. We evaluated assays and multi‐assay algorithms (MAAs) for incidence estimation in subtype C settings.

Methods

We analysed samples from individuals with subtype C infection with known duration of infection (2442 samples from 278 adults; 0.1 to 9.9 years after seroconversion). MAAs included 1‐4 of the following assays: Limiting Antigen Avidity assay (LAg‐Avidity), BioRad‐Avidity assay, CD4 cell count and viral load (VL). We evaluated 23,400 MAAs with different assays and assay cutoffs. We identified the MAA with the largest mean window period, where the upper 95% confidence interval (CI) of the shadow was <1 year. This MAA was compared to the LAg‐Avidity and BioRad‐Avidity assays alone, a widely used LAg algorithm (LAg‐Avidity <1.5 OD‐n + VL >1000 copies/mL), and two MAAs previously optimized for subtype B settings. We compared these cross‐sectional incidence estimates to observed incidence in an independent longitudinal cohort.

Results

The optimal MAA was LAg‐Avidity <2.8 OD‐n  +  BioRad‐Avidity <95% + VL >400 copies/mL. This MAA had a mean window period of 248 days (95% CI: 218, 284), a shadow of 306 days (95% CI: 255, 359), and provided the most accurate and precise incidence estimate for the independent cohort. The widely used LAg algorithm had a shorter mean window period (142 days, 95% CI: 118, 167), a longer shadow (410 days, 95% CI; 318, 491), and a less accurate and precise incidence estimate for the independent cohort.

Conclusions

An optimal MAA was identified for cross‐sectional HIV incidence in subtype C settings. The performance of this MAA is superior to a testing algorithm currently used for global HIV surveillance.

Short Communication: Viral Genetic Linkage Analysis Among Black Men Who Have Sex With Men (HIV Prevention Trials Network 061)

Analysis of viral genetic linkage can reveal generalized transmission patterns within a population. The HIV Prevention Trials Network 061 study evaluated HIV incidence among black men who have sex with men. HIV genotypes from 169 men who were HIV infected at enrollment and 23 men who seroconverted during the study were analyzed for genetic linkage. This analysis showed some associations of viral linkage with income, study site, and timing of infection.

Evaluation of a BioRad Avidity assay for identification of recent HIV-1 infections using dried serum or plasma spots

Serological methods to differentiate between recently acquired and established HIV-1 infections are a useful tool in the HIV-surveillance to characterize the epidemic, identify groups at risk and assess HIV-preventive interventions. Therefore, an avidity-based, modified BioRad Genscreen™ HIV-1/2 assay (BRA_EUR) was evaluated according to the avidity-based, modified BioRad HIV-1/2 Plus O protocol (BRA_USA). Overall, 692 well defined samples (82.5% B and 17.5% non-B subtypes) from recent (<180 days, n = 239), intermediate (181-364 days, n = 35) or long term infections (≥365 days, n = 419) were used to determine a 'mean duration of recent infection' (MDRI), a 'median DRI' (MdDRI), the false recent rate (FRR), and concordance between the BRAs and the Sedia BED HIV-1 Capture enzyme immunoassay (BED). The optimal avidity index cut-off was determined to be 70% resulting in an MDRI of 233 days (95% IQR: 174-351) and an MdDRI of 171 days (95% IQR: 142-212). Concordance with the BRA_USA was high with 96.4%. The FRR of 6.0% as well as the MdDRI are similar to the BED (8.4%; 170 (139-214) days). Therefore, the BRA_EUR is a suitable alternative to replace the BED and trend analysis will be feasible after minimal adjustments for the MdDRI and the MDRI.

A Window Into the HIV Epidemic from a South African Emergency Department

The aim of the study was to describe the HIV care continuum in emergency department (ED) patients in the Eastern Cape region of South Africa. This is a cross-sectional, identity-unlinked serosurvey, whereby discarded/excess samples from all patients who had blood drawn during the study period for routine care and sufficient serum remaining were tested for HIV, hepatitis B virus, and hepatitis C virus infection; HIV viral load (VL); and presence of antiretroviral (ARV) drugs. We also estimated cross-sectional incidence using the Limiting-Antigen Avidity assay and HIV VL. The study was conducted between September and November 2016 at the Frere Hospital Emergency Department in East London, South Africa. The overall HIV prevalence in our study population was 26.9% [95% confidence interval (CI): 25.0-28.8; n = 2,100]. The highest prevalence was observed among females in the 30-39 years age group [60.3% (95% CI: 53.2-67.1)]. HIV prevalence was significantly higher among females compared with males in both the 20-29 years age group and 30-39 years age group (p < .05), but nearly identical to older age groups. ARV drugs were detected in 53.5% (95% CI: 48.1-58.9) of HIV-infected subjects. The frequency of HIV viral suppression (< 1,000 copies/mL) was 48.5% (95% CI: 44.3-52.7), and was not statistically different between males and females (age-adjusted prevalence ratio = 1.15, 95% CI: 0.95-1.39). The HIV incidence rate was estimated to be 2.6% (95% CI: 1.2-3.9). The Frere Hospital ED has an extremely high burden of HIV infection. The detection of ARV drugs and prevalence of viral suppression fall short of the World Health Organization 90-90-90 goals in this population. Furthermore, there were a large number of patients with recent infection in the ED. The ED is a critical venue for testing and linkage to care of high-yield population who are likely missed by current testing and linkage-to-care programs.

Development of a Multiplex Assay for Concurrent Diagnoses and Detection of HIV-1, HIV-2, and Recent HIV-1 Infection in a Single Test

Laboratory assays that can accurately distinguish recent (occurring within the past year) from long-standing (>1 year) HIV infection are crucial for understanding HIV transmission dynamics in a population. However, often these efforts are confounded by inaccurate HIV diagnosis and the presence of HIV-2 in the population being surveyed. This study describes development of a multiplex assay that can simultaneously perform HIV diagnosis, HIV serotyping, and detection of recent HIV-1 infection in a single well. HIV diagnosis and HIV-2 serotyping were accomplished by coupling beads with an HIV-1 p24-gp41 fusion protein and HIV-2 peptide from gp36 immunodominant region, respectively. HIV-1 recent infection detection was accomplished by coupling beads with limiting amounts of multi-subtype gp41 immunodominant protein, recombinant immunodominant region, group M (rIDR-M). Assay conditions, including concentration of coupled antigens, were systematically optimized using well-characterized specimens with known HIV-status (positive or negative), HIV-2 specimens, and recent or long-term HIV-1 classification based on LAg-Avidity enzyme immunoassay (EIA) in a stepwise manner. Beads were then combined in a multiplex assay to evaluate its performance using large panel of specimens (n = 1,500) that included HIV-1 positive (n = 570, recent = 78, long-term = 492), HIV-2 positive (n = 31), and seronegative individuals (n = 899). The diagnostic component of the assay performed with high sensitivity (99.8%) and specificity (99.7%), while the HIV-2 serotyping sensitivity and specificity were 96.7% and 100%, respectively. There was a high correlation (R = 0.84) between the LAg-Avidity EIA and the multiplex assay for recent infection detection. The assay showed high inter- and intra-assay reproducibility with %coefficient of variation of <10% in the dynamic range. The multiplex assay has the ability to diagnose HIV infection, perform serotyping, and detect and distinguish recent from long-term HIV infections, all in a single well. This novel assay has the potential to simplify HIV surveillance by reducing the multiple steps that are otherwise required.

Cross-sectional estimates revealed high HIV incidence in Botswana rural communities in the era of successful ART scale-up in 2013-2015

BACKGROUND

Botswana is close to reaching the UNAIDS "90-90-90" HIV testing, antiretroviral treatment (ART), and viral suppression goals. We sought to determine HIV incidence in this setting with both high HIV prevalence and high ART coverage.

METHODS

We used a cross-sectional approach to assessing HIV incidence. A random, population-based sample of adults age 16-64 years was enrolled in 30 rural and peri-urban communities as part of the Botswana Combination Prevention Project (BCPP), from October 2013 -November 2015. Data and samples from the baseline household survey were used to estimate cross-sectional HIV incidence, following an algorithm that combined Limiting-Antigen Avidity Assay (LAg-Avidity EIA), ART status (documented or by testing ARV drugs in plasma) and HIV-1 RNA load. The LAg-Avidity EIA cut-off normalized optical density (ODn) was set at 1.5. The HIV-1 RNA cut-off was set at 400 copies/mL. For estimation purposes, the Mean Duration of Recent Infection was 130 days and the False Recent Rate (FRR) was evaluated at values of either 0 or 0.39%.

RESULTS

Among 12,610 individuals participating in the baseline household survey, HIV status was available for 12,570 participants and 3,596 of them were HIV positive. LAg-Avidity EIA data was generated for 3,581 (99.6%) of HIV-positive participants. Of 326 participants with ODn ≤1.5, 278 individuals were receiving ART verified through documentation and were considered to represent longstanding HIV infections. Among the remaining 48 participants who reported no use of ART, 14 had an HIV-1 RNA load ≤400 copies/mL (including 3 participants with ARVs in plasma) and were excluded, as potential elite/viremic controllers or undisclosed ART. Thus, 34 LAg-Avidity-EIA-recent, ARV-naïve individuals with detectable HIV-1 RNA (>400 copies/mL) were classified as individuals with recent HIV infections. The annualized HIV incidence among 16-64 year old adults was estimated at 1.06% (95% CI 0.68-1.45%) with zero FRR, and at 0.64% (95% CI 0.24-1.04%) using a previously defined FRR of 0.39%. Within a subset of younger individuals 16-49 years old, the annualized HIV incidence was estimated at 1.29% (95% CI 0.82-1.77%) with zero FRR, and at 0.90% (95% CI 0.42-1.38%) with FRR set to 0.39%.

CONCLUSIONS

Using a cross-sectional estimate of HIV incidence from 2013-2015, we found that at the time of near achievement of the UNAIDS 90-90-90 targets, ~1% of adults (age 16-64 years) in Botswana's rural and peri-urban communities became HIV infected annually.

Population-level HIV incidence estimates using a combination of synthetic cohort and recency biomarker approaches in KwaZulu-Natal, South Africa

Introduction

There is a notable absence of consensus on how to generate estimates of population-level incidence. Incidence is a considerably more sensitive indicator of epidemiological trends than prevalence, but is harder to estimate. We used a novel hybrid method to estimate HIV incidence by age and sex in a rural district of KwaZulu-Natal, South Africa.

Methods

Our novel method uses an ‘optimal weighting’ of estimates based on an implementation of a particular ‘synthetic cohort’ approach (interpreting the age/time structure of prevalence, in conjunction with estimates of excess mortality) and biomarkers of ‘recent infection’ (combining Lag-Avidity, Bio-Rad Avidity and viral load results to define recent infection, and adapting the method for age-specific incidence estimation). Data were obtained from a population-based cross-sectional HIV survey conducted in Mbongolwane and Eshowe health service areas in 2013.

Results

Using the combined method, we find that age-specific HIV incidence in females rose rapidly during adolescence, from 1.33 cases/100 person-years (95% CI: 0.98,1.67) at age 15 to a peak of 5.01/100PY (4.14,5.87) at age 23. In males, incidence was lower, 0.34/100PY (0.00-0.74) at age 15, and rose later, peaking at 3.86/100PY (2.52-5.20) at age 30. Susceptible population-weighted average incidence in females aged 15-29 was estimated at 3.84/100PY (3.36-4.40), in males aged 15-29 at 1.28/100PY (0.68-1.50) and in all individuals aged 15-29 at 2.55/100PY (2.09-2.76). Using the conventional recency biomarker approach, we estimated HIV incidence among females aged 15-29 at 2.99/100PY (1.79-4.36), among males aged 15-29 at 0.87/100PY (0.22-1.60) and among all individuals aged 15-59 at 1.66/100PY (1.13-2.27).

Discussion

HIV incidence was very high in women aged 15-30, peaking in the early 20s. Men had lower incidence, which peaked at age 30. The estimates obtained from the hybrid method are more informative than those produced by conventional analysis of biomarker data, and represents a more optimal use of available data than either the age-continuous biomarker or synthetic cohort methods alone. The method is mainly useful at younger ages, where excess mortality is low and uncertainty in the synthetic cohort estimates is reasonably small.

Conclusion

Application of this method to large-scale population-based HIV prevalence surveys is likely to result in improved incidence surveillance over methods currently in wide use. Reasonably accurate and precise age-specific estimates of incidence are important to target better prevention, diagnosis and care strategies.

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.

Western Blot-Based Logistic Regression Model for the Identification of Recent HIV-1 Infection: A Promising HIV-1 Surveillance Approach for Resource-Limited Regions

Objectives

Identifying recent infections is necessary to monitor HIV/AIDS epidemic; however, it needs to be further developed.

Methods and Results

Participants were defined as having recent infection or older infection according to the estimated duration of HIV-1 infection and further assigned into training set and validation set according to their entering time points. Western blot (WB) confirmatory test and BED-CEIA were performed. The performance of the two methods on recent HIV-1 diagnosis was evaluated and compared. 81 subjects were enrolled in the training set and 72 in the validation set. Relative grey ratios of p24, p39, p31, p66, gp41, and gp160 were significantly higher in older infected patients of the training set. The present status of p55 was more frequently missing in recently infected patients in both sets. The logistic stepwise regression analysis of WB method shows sensitivity, specificity, and accuracy of 93.02%, 92.11%, and 92.59%. For BED-CEIA, they were 76.74%, 86.84%, and 81.48%. In the validation set, overall agreement rate, sensitivity, and specificity were 88.46%, 84.78%, and 86.11% in the WB-based method and 50.00%, 84.78%, and 72.22% in the BED-CEIA method.

Conclusions

WB-based method is a promising approach to predict recent HIV-1 infection, especially in resource-limited regions.

Performance characteristics of an antibody-based multiplex kit for determining recent HIV-1 infection

The availability of reliable laboratory methods for determining recent HIV infection is vital for accurate estimation of population-based incidence. The mean duration of recent infection (MDRI) and false recent rate (FRR) are critical parameters for HIV incidence assays, as they impact HIV incidence estimates and provide a measure of assay performance. The HIV-1 Multiplex assay is an in-house developed, magnetic bead-based assay that measures virus-specific antibody levels and avidity to multiple analytes. To ensure quality control and to facilitate transfer of the assay to external laboratories or testing facilities, the in-house assay has been adapted and produced in kit form. Here, we describe the performance characteristics of the multiplex kit and demonstrate the stability of the kit components over a one-year period. Two statistical methods were employed to estimate the MDRI of the individual analytes and five different algorithms, combining multiple analyte values. The MDRI estimates for the individual analytes and five algorithms were all between 200 and 300 days post-seroconversion, with no notable difference between the two statistical approaches. All five algorithms exhibited a 0% FRR with specimens from long-term, subtype B HIV-1-infected individuals. The assay parameters described in this study provide the necessary tools to implement the HIV-1 multiplex assay and improves the utility of the assay for field use.

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.

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.

Analysis of HIV Diversity in HIV-Infected Black Men Who Have Sex with Men (HPTN 061)

Background

HIV populations often diversify in response to selective pressures, such as the immune response and antiretroviral drug use. We analyzed HIV diversity in Black men who have sex with men who were enrolled in the HIV Prevention Trials Network 061 study.

Methods

A high resolution melting (HRM) diversity assay was used to measure diversity in six regions of the HIV genome: two in gag, one in pol, and three in env. HIV diversity was analyzed for 146 men who were HIV infected at study enrollment, including three with acute infection and 13 with recent infection (identified using a multi-assay algorithm), and for 21 men who seroconverted during the study. HIV diversification was analyzed in a paired analysis for 62 HIV-infected men using plasma samples from the enrollment and 12-month (end of study) visits.

Results

Men with acute or recent infection at enrollment and seroconverters had lower median HRM scores (lower HIV diversity) than men with non-recent infection in all six regions analyzed. In univariate analyses, younger age, higher CD4 cell count, and HIV drug resistance were associated with lower median HRM scores in multiple regions; ARV drug detection was marginally associated with lower diversity in the pol region. In multivariate analysis, acute or recent infection (all six regions) and HIV drug resistance (both gag regions) were associated with lower median HRM scores. Diversification in the pol region over 12 months was greater for men with acute or recent infection, higher CD4 cell count, and lower HIV viral load at study enrollment.

Conclusions

HIV diversity was significantly associated with duration of HIV infection, and lower gag diversity was observed in men who had HIV drug resistance. HIV pol diversification was more pronounced in men with acute or recent infection, higher CD4 cell count, and lower HIV viral load.

Viral and Host Characteristics of Recent and Established HIV-1 Infections in Kisumu based on a Multiassay Approach

Integrated approaches provide better understanding of HIV/AIDS epidemics. We optimised a multiassay algorithm (MAA) and assessed HIV incidence, correlates of recent infections, viral diversity, plus transmission clusters among participants screened for Kisumu Incidence Cohort Study (KICoS1) (2007–2009). We performed BED-CEIA, Limiting antigen (LAg) avidity, Biorad avidity, and viral load (VL) tests on HIV-positive samples. Genotypic analyses focused on HIV-1 pol gene. Correlates of testing recent by MAA were assessed using logistic regression model. Overall, 133 (12%, 95% CI: 10.2–14.1) participants were HIV-positive, of whom 11 tested recent by MAA (BED-CEIA OD-n < 0.8 + LAg avidity OD-n < 1.5 + VL > 1000 copies/mL), giving an incidence of 1.46% (95% CI: 0.58–2.35) per year. This MAA-based incidence was similar to longitudinal KICoS1 incidence. Correlates of testing recent included sexually transmitted infection (STI) treatment history (OR = 3.94, 95% CI: 1.03–15.07) and syphilis seropositivity (OR = 10.15, 95% CI: 1.51–68.22). Overall, HIV-1 subtype A (63%), D (15%), C (3%), G (1%) and recombinants (18%), two monophyletic dyads and intrinsic viral mutations (V81I, V81I/V, V108I/V and K101Q) were observed. Viral diversity mirrored known patterns in this region, while resistance mutations reflected likely non-exposure to antiretroviral drugs. Management of STIs may help address ongoing HIV transmission in this region.

Characterization of Humoral Immune Responses against Capsid Protein p24 and Transmembrane Glycoprotein gp41 of Human Immunodeficiency Virus Type 1 in China

The objective of this study was to extend our previous research and to further characterize the humoral immune responses against HIV-1 p24, gp41 and the specific peptides carrying the immunodominant epitopes (IDEs) that react with human serum samples from HIV-1-infected individuals in China. We found that the majority (90.45%, 180/199) of the samples did not react with any of the three HIV-1 p24 peptides carrying IDEs, but did react with the recombinant full-length p24, suggesting that these samples tested in China were primarily directed against the conformational epitopes of HIV-1 p24. In contrast, 84.54% (164/194) of the samples reacted with at least one HIV-1 linear gp41 peptide, in particular the gp41-p1 peptide (amino acids 560-616). Both recently and long-term HIV-1-infected individuals displayed similar humoral immune responses against the recombinant gp41. However, samples from long-term HIV-1-infected subjects but not from recently infected subjects, showed a very strong reaction against the gp41-p1 peptide. The different response patterns observed for the two groups against the gp41 and the peptide gp41-p1 were statistically significant (P<0.01, Chi-square test). These results have direct relevance and importance for design of improved HIV-1 p24 detection assays and the gp41- based immunoassay that can be used to reliably distinguish recent and long-term HIV-1 infection.

Evaluation of the limiting antigen avidity EIA (LAg) in people who inject drugs in Greece

This analysis assessed the utility of the limiting antigen avidity assay (LAg). Samples of people who inject drugs (PWID) in Greece with documented duration of HIV-1 infection were tested by LAg. A LAg-normalized optical density (ODn) ⩽1·5 corresponds to a recency window period of 130 days. The proportion true recent (PTR) and proportion false recent (PFR) were estimated in 28 seroconverters and in 366 samples collected >6 months after HIV diagnosis, respectively. The association between LAg ODn and HIV RNA level was evaluated in 232 persons. The PTR was 85·7%. The PFR was 20·8% but fell to 5·9% in samples from treatment-naive individuals with long-standing infection (>1 year), and to 0 in samples with the circulating recombinant form CRF35 AD. A LAg-based algorithm with a PFR of 3·3% estimated a similar incidence trend to that calculated by analyses based on HIV-1 seroconversions. In recently infected persons indicated by LAg, the median log10 HIV RNA level was high (5·30, interquartile range 4·56-5·90). LAg can help identify highly infectious HIV(+) individuals as it accurately identifies recent infections and is correlated with the HIV RNA level. It can also produce reliable estimates of HIV-1 incidence.

Viral load criteria and threshold optimization to improve HIV incidence assay characteristics

OBJECTIVE

Assays for classifying HIV infections as 'recent' or 'nonrecent' for incidence surveillance fail to simultaneously achieve large mean durations of 'recent' infection (MDRIs) and low 'false-recent' rates (FRRs), particularly in virally suppressed persons. The potential for optimizing recent infection testing algorithms (RITAs), by introducing viral load criteria and tuning thresholds used to dichotomize quantitative measures, is explored.

DESIGN

The Consortium for the Evaluation and Performance of HIV Incidence Assays characterized over 2000 possible RITAs constructed from seven assays (Limiting Antigen, BED, Less-sensitive Vitros, Vitros Avidity, BioRad Avidity, Architect Avidity, and Geenius) applied to 2500 diverse specimens.

METHODS

MDRIs were estimated using regression, and FRRs as observed 'recent' proportions, in various specimen sets. Context-specific FRRs were estimated for hypothetical scenarios. FRRs were made directly comparable by constructing RITAs with the same MDRI through the tuning of thresholds. RITA utility was summarized by the precision of incidence estimation.

RESULTS

All assays produce high FRRs among treated patients and elite controllers (10-80%). Viral load testing reduces FRRs, but diminishes MDRIs. Context-specific FRRs vary substantially by scenario - BioRad Avidity and Limiting Antigen provided the lowest FRRs and highest incidence precision in scenarios considered.

CONCLUSION

The introduction of a low viral load threshold provides crucial improvements in RITAs. However, it does not eliminate nonzero FRRs, and MDRIs must be consistently estimated. The tuning of thresholds is essential for comparing and optimizing the use of assays. The translation of directly measured FRRs into context-specific FRRs critically affects their magnitudes and our understanding of the utility of assays.

Analysis of Viral Diversity in Relation to the Recency of HIV-1C Infection in Botswana

BACKGROUND

Cross-sectional, biomarker methods to determine HIV infection recency present a promising and cost-effective alternative to the repeated testing of uninfected individuals. We evaluate a viral-based assay that uses a measure of pairwise distances (PwD) to identify HIV infection recency, and compare its performance with two serologic incidence assays, BED and LAg. In addition, we assess whether combination BED plus PwD or LAg plus PwD screening can improve predictive accuracy by reducing the likelihood of a false-recent result.

METHODS

The data comes from 854 time-points and 42 participants enrolled in a primary HIV-1C infection study in Botswana. Time points after treatment initiation or with evidence of multiplicity of infection were excluded from the final analysis. PwD was calculated from quasispecies generated using single genome amplification and sequencing. We evaluated the ability of PwD to correctly classify HIV infection recency within <130, <180 and <360 days post-seroconversion using Receiver Operator Characteristics (ROC) methods. Following a secondary PwD screening, we quantified the reduction in the relative false-recency rate (rFRR) of the BED and LAg assays while maintaining a sensitivity of either 75, 80, 85 or 90%.

RESULTS

The final analytic sample consisted of 758 time-points from 40 participants. The PwD assay was more accurate in classifying infection recency for the 130 and 180-day cut-offs when compared with the recommended LAg and BED thresholds. A higher AUC statistic confirmed the superior predictive performance of the PwD assay for the three cut-offs. When used for combination screening, the PwD assay reduced the rFRR of the LAg assay by 52% and the BED assay by 57.8% while maintaining a 90% sensitivity for the 130 and 180-day cut-offs respectively.

CONCLUSION

PwD can accurately determine HIV infection recency. A secondary PwD screening reduces misclassification and increases the accuracy of serologic-based assays.

Mean Recency Period for Estimation of HIV-1 Incidence with the BED-Capture EIA and Bio-Rad Avidity in Persons Diagnosed in the United States with Subtype B

HIV incidence estimates are used to monitor HIV-1 infection in the United States. Use of laboratory biomarkers that distinguish recent from longstanding infection to quantify HIV incidence rely on having accurate knowledge of the average time that individuals spend in a transient state of recent infection between seroconversion and reaching a specified biomarker cutoff value. This paper describes five estimation procedures from two general statistical approaches, a survival time approach and an approach that fits binomial models of the probability of being classified as recently infected, as a function of time since seroconversion. We compare these procedures for estimating the mean duration of recent infection (MDRI) for two biomarkers used by the U.S. National HIV Surveillance System for determination of HIV incidence, the Aware BED EIA HIV-1 incidence test (BED) and the avidity-based, modified Bio-Rad HIV-1/HIV-2 plus O ELISA (BRAI) assay. Collectively, 953 specimens from 220 HIV-1 subtype B seroconverters, taken from 5 cohorts, were tested with a biomarker assay. Estimates of MDRI using the non-parametric survival approach were 198.4 days (SD 13.0) for BED and 239.6 days (SD 13.9) for BRAI using cutoff values of 0.8 normalized optical density and 30%, respectively. The probability of remaining in the recent state as a function of time since seroconversion, based upon this revised statistical approach, can be applied in the calculation of annual incidence in the United States.

Estimating HIV incidence among key affected populations in China from serial cross-sectional surveys in 2010-2014

Introduction

HIV incidence is an important measure for monitoring the development of the epidemic, but it is difficult to ascertain. We combined serial HIV prevalence and mortality data to estimate HIV incidence among key affected populations (KAPs) in China.

Methods

Serial cross-sectional surveys were conducted among KAPs from 2010 to 2014. Trends in HIV prevalence were assessed by the Cochran-Armitage test, adjusted by risk group. HIV incidence was estimated from a mathematical model that describes the relationship between changes in HIV incidence with HIV prevalence and mortality.

Results

The crude HIV prevalence for the survey samples remained stable at 1.1 to 1.2% from 2010 to 2014. Among drug users (DUs), HIV prevalence declined from 4.48 to 3.29% (p<0.0001), and among men who have sex with men (MSM), HIV prevalence increased from 5.73 to 7.75% (p<0.0001). Changes in HIV prevalence among female sex workers (FSWs) and male patients of sexually transmitted disease clinics were more modest but remained statistically significant (all p<0.0001). The MSM population had the highest incidence estimates at 0.74% in 2011, 0.59% in 2012, 0.57% in 2013 and 0.53% in 2014. Estimates of the annual incidence for DUs and FSWs were very low and may not be reliable.

Conclusions

Serial cross-sectional prevalence data from representative samples may be another approach to construct approximate estimates of national HIV incidence among key populations. We observed that the MSM population had the highest incidence for HIV among high-risk groups in China, and we suggest that interventions targeting MSM are urgently needed to curb the growing HIV epidemic.

Use of Hepatitis C Virus (HCV) Immunoglobulin G Antibody Avidity as a Biomarker to Estimate the Population-Level Incidence of HCV Infection

BACKGROUND

Sensitive methods are needed to estimate the population-level incidence of hepatitis C virus (HCV) infection.

METHODS

We developed an HCV immunoglobulin G (IgG) antibody avidity assay by modifying the Ortho 3.0 HCV enzyme-linked immunoassay and tested 997 serum or plasma samples from 568 people who inject drugs enrolled in prospective cohort studies. Avidity-based testing algorithms were evaluated by their (1) mean duration of recent infection (MDRI), defined as the average time an individual is identified as having been recently infected, according to a given algorithm; (2) false-recent rate, defined as the proportion of samples collected >2 years after HCV seroconversion that were misclassified as recent; (3) sample sizes needed to estimate incidence; and (4) power to detect a reduction in incidence between serial cross-sectional surveys.

RESULTS

A multiassay algorithm (defined as an avidity index of <30%, followed by HCV viremia detection) had an MDRI of 147 days (95% confidence interval [CI], 125-195 days), and the false-recent rates were 0.7% (95% CI, .2%-1.8%) and 7.6% (95% CI, 4.2%-12.3%) among human immunodeficiency virus (HIV)-negative and HIV-positive persons, respectively. In various simulated high-risk populations, this algorithm required <1000 individuals to estimate incidence (relative standard error, 30%) and had >80% power to detect a 50% reduction in incidence.

CONCLUSIONS

Avidity-based algorithms have the capacity to accurately estimate HCV infection incidence and rapidly assess the impact of public health efforts among high-risk populations. Efforts to optimize this method should be prioritized.

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

OBJECTIVE

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.

DESIGN/METHODS

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.

RESULTS

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).

CONCLUSION

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.

Sample size methods for estimating HIV incidence from cross-sectional surveys

Understanding HIV incidence, the rate at which new infections occur in populations, is critical for tracking and surveillance of the epidemic. In this article, we derive methods for determining sample sizes for cross-sectional surveys to estimate incidence with sufficient precision. We further show how to specify sample sizes for two successive cross-sectional surveys to detect changes in incidence with adequate power. In these surveys biomarkers such as CD4 cell count, viral load, and recently developed serological assays are used to determine which individuals are in an early disease stage of infection. The total number of individuals in this stage, divided by the number of people who are uninfected, is used to approximate the incidence rate. Our methods account for uncertainty in the durations of time spent in the biomarker defined early disease stage. We find that failure to account for this uncertainty when designing surveys can lead to imprecise estimates of incidence and underpowered studies. We evaluated our sample size methods in simulations and found that they performed well in a variety of underlying epidemics. Code for implementing our methods in R is available with this article at the Biometrics website on Wiley Online Library.

Identifying Recent HIV Infections: From Serological Assays to Genomics

In this paper, we review serological and molecular based methods to identify HIV infection recency. The accurate identification of recent HIV infection continues to be an important research area and has implications for HIV prevention and treatment interventions. Longitudinal cohorts that follow HIV negative individuals over time are the current gold standard approach, but they are logistically challenging, time consuming and an expensive enterprise. Methods that utilize cross-sectional testing and biomarker information have become an affordable alternative to the longitudinal approach. These methods use well-characterized biological makers to differentiate between recent and established HIV infections. However, recent results have identified a number of limitations in serological based assays that are sensitive to the variability in immune responses modulated by HIV subtypes, viral load and antiretroviral therapy. Molecular methods that explore the dynamics between the timing of infection and viral evolution are now emerging as a promising approach. The combination of serological and molecular methods may provide a good solution to identify recent HIV infection in cross-sectional data. As part of this review, we present the advantages and limitations of serological and molecular based methods and their potential complementary role for the identification of HIV infection recency.

How can we better identify early HIV infections?

PURPOSE OF REVIEW

Detection of early HIV infections (EHIs), including acute HIV infection (AHI), is important for individual health, prevention of HIV transmission, and measurement of HIV incidence. We describe markers of EHI, diagnostic strategies for detecting these markers, and ways to incorporate these strategies into diagnostic and HIV incidence algorithms.

RECENT FINDINGS

For individual diagnosis in the USA and Europe, laboratory-based diagnostic algorithms increasingly incorporate fourth-generation HIV antigen tests, allowing for earlier detection. In some sub-Saharan African settings, symptom-based screening is being explored to identify subsets of persons at high risk for AHI. Point-of-care diagnostics designed for AHI detection are in the pipeline and, if validated, represent an opportunity for real-time AHI diagnosis. At the population level, multiassay algorithms are promising new strategies for estimating HIV incidence on the basis of several assays applied to cross-sectional samples. These algorithms can be developed to optimize performance, in addition to cost and logistical considerations.

SUMMARY

There are important recent advances in detection of EHIs at the individual and population levels. Applying optimal combinations of tests in diagnostic and HIV incidence algorithms is urgently needed to support the multiple goals derived from enhanced detection and discrimination of EHIs.

Antiretroviral Drug Use and HIV Drug Resistance Among HIV-Infected Black Men Who Have Sex With Men: HIV Prevention Trials Network 061

BACKGROUND

HIV Prevention Trials Network (HPTN) 061 enrolled black men who have sex with men in the United States. Some men with low/undetectable HIV RNA had unusual patterns of antiretroviral (ARV) drug use or had drugs detected in the absence of viral suppression. This report includes a comprehensive analysis of ARV drug use and drug resistance among men in HPTN 061 who were not virally suppressed.

METHODS

The analysis included 169 men who had viral loads >400 copies per milliliter at enrollment, including 3 with acute infection and 13 with recent infection. By self-report, 88 were previously diagnosed, including 31 in care; 137 men reported no ARV drug use. Samples from these 169 men and 23 seroconverters were analyzed with HIV genotyping and ARV drug assays.

RESULTS

Forty-eight (28%) of the 169 men had ≥ 1 drug resistance mutation (DRM); 19 (11%) had multiclass resistance. Sixty men (36%) had ≥ 1 ARV drug detected, 42 (70%) of whom reported no ARV drug use. Nine (23%) of 39 newly infected men had ≥ 1 DRM; 10 had ≥ 1 ARV drug detected. Unusual patterns of ARV drugs were detected more frequently in newly diagnosed men than previously diagnosed men. The rate of transmitted drug resistance was 23% based on HIV genotyping and self-reported ARV drug use but was 12% after adjusting for ARV drug detection.

CONCLUSIONS

Many men in HPTN 061 had drug-resistant HIV, and many were at risk of acquiring additional DRMs. ARV drug testing revealed unusual patterns of ARV drug use and provided a more accurate estimate of transmitted drug resistance.

Longitudinal trends of recent HIV-1 infections in Slovenia (1986-2012) determined using an incidence algorithm

Resolving dilemma whether the rise in the number of HIV diagnoses represents an actual increase in HIV transmissions or is a result of improved HIV surveillance is crucial before implementing national HIV prevention strategies. Annual proportions of recent infections (RI) among newly diagnosed persons infected with HIV-1 in Slovenia during 27 years (1986-2012) were determined using an algorithm consisting of routine baseline CD4 and HIV viral load measurements and the Aware BED EIA HIV-1 Incidence Test (BED test). The study included the highest coverage of persons diagnosed with HIV during the entire duration of an HIV epidemic in a given country/region (71%). Out of 416 patients, 170 (40.9%) had a baseline CD4 cell count less than 200 cells/mm(3) and/or HIV-1 viral load less than 400 copies/ml and were characterized as having a long-standing infection (LSI). The remaining 246 patients were additionally tested using the BED test. Overall, 23% (97/416) of the patients were labeled RI. The characteristics significantly associated with RI were as follows: younger age, acute retroviral syndrome, CDC class A and other than C, no AIDS defining illnesses, HIV test performed in the past, a higher viral load, and a higher CD4 cell count. An interesting trend in the proportion of RI was observed, with a peak in 2005 (47% of RI) and the lowest point in 2008 (12%) in parallel with a rise in the numbers of new HIV diagnoses. This study could help promote the idea of introducing periodic HIV incidence monitoring using a simple and affordable algorithm.

Recalibration of the limiting antigen avidity EIA to determine mean duration of recent infection in divergent HIV-1 subtypes

Background

Mean duration of recent infection (MDRI) and misclassification of long-term HIV-1 infections, as proportion false recent (PFR), are critical parameters for laboratory-based assays for estimating HIV-1 incidence. Recent review of the data by us and others indicated that MDRI of LAg-Avidity EIA estimated previously required recalibration. We present here results of recalibration efforts using >250 seroconversion panels and multiple statistical methods to ensure accuracy and consensus.

Methods

A total of 2737 longitudinal specimens collected from 259 seroconverting individuals infected with diverse HIV-1 subtypes were tested with the LAg-Avidity EIA as previously described. Data were analyzed for determination of MDRI at ODn cutoffs of 1.0 to 2.0 using 7 statistical approaches and sub-analyzed by HIV-1 subtypes. In addition, 3740 specimens from individuals with infection >1 year, including 488 from patients with AIDS, were tested for PFR at varying cutoffs.

Results

Using different statistical methods, MDRI values ranged from 88–94 days at cutoff ODn = 1.0 to 177–183 days at ODn = 2.0. The MDRI values were similar by different methods suggesting coherence of different approaches. Testing for misclassification among long-term infections indicated that overall PFRs were 0.6% to 2.5% at increasing cutoffs of 1.0 to 2.0, respectively. Balancing the need for a longer MDRI and smaller PFR (<2.0%) suggests that a cutoff ODn = 1.5, corresponding to an MDRI of 130 days should be used for cross-sectional application. The MDRI varied among subtypes from 109 days (subtype A&D) to 152 days (subtype C).

Conclusions

Based on the new data and revised analysis, we recommend an ODn cutoff = 1.5 to classify recent and long-term infections, corresponding to an MDRI of 130 days (118–142). Determination of revised parameters for estimation of HIV-1 incidence should facilitate application of the LAg-Avidity EIA for worldwide use.

Mixture models for calibrating the BED for HIV incidence testing

A number of antibody biomarkers have been developed to distinguish between recent and established Human Immunodeficiency Virus (HIV) infection and used for HIV incidence estimation from cross-sectional specimens. In general, a cut-off value is specified, and estimates of the following parameters are needed: (i) the mean time interval .w/ between seroconversion and reaching that cut-off; (ii) the probability of correctly identifying individuals who became infected in the last w years (sensitivity); and (iii) the probability of correctly identifying individuals who have been infected for more than w years (specificity). We develop two statistical methods to study the distribution of a biomarker and derive a formula for estimating HIV incidence from a cross-sectional survey. Both methods allow handling interval censored data and basically consist of using a generalized mixture model to model the growth of the biomarker as a function of time since infection. The first uses data from all followed-up individuals and allows incidence estimation in the cohort, whereas the second only uses data from seroconverters. We illustrate our methods using repeated measures of the IgG capture BED enzyme immunoassay. Estimates of calibration parameters, that is, mean window period, mean recency period, sensitivity, and specificities obtained from both models are comparable. The formula derived for incidence estimation gives the maximum likelihood estimate of incidence which, for a given window period, depends only on sensitivity and specificity. The optimal choice of the window period is discussed. Numerical simulations suggest that data from seroconverters can provide reasonable estimates of the calibration parameters.

Longitudinal analysis of HIV-1-specific antibody responses

Laboratory assays for determining recent HIV-1 infection are of great public health importance for aiding in the estimation of HIV incidence. Concerns have been raised about the potential for misclassification with serology-based assays due to fluctuations in the antibody response, particularly following progression to AIDS. We characterized longitudinal antibody responses to HIV using a cohort of men who have sex with men (MSM) sampled for up to 17 years, in which 57% of the 65 study subjects included in the current analyses progressed to AIDS during the study period. Envelope-specific total IgG antibody levels, avidity, and p24-specific IgG3 levels were evaluated using a multiplexed Bio-Plex assay. For the majority of the analytes, no significant difference in IgG reactivity was observed between AIDS and non-AIDS specimens. Although a slight decline in gp120 reactivity was noted with decreasing CD4(+) T cell count, the drop in assay values was relatively minimal and would likely not lead to an increase in the misclassification rate of the assay. A peak in HIV-1 p24 IgG3 levels was observed during early infection, as confirmed by testing 1,216 specimens from 342 recent seroconverters with the Bio-Plex assay. As expected, IgG3 reactivity declined with disease progression and decreasing CD4(+) T cell count in the MSM cohort; however, 37% of the study subjects exhibited relatively high IgG3 levels late in the course of infection.