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

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.

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.

Improving Biomarker-based HIV Incidence Estimation in the Treatment Era

BACKGROUND

Estimating HIV-1 incidence using biomarker assays in cross-sectional surveys is important for understanding the HIV pandemic. However, the utility of these estimates has been limited by uncertainty about what input parameters to use for false recency rate (FRR) and mean duration of recent infection (MDRI) after applying a recent infection testing algorithm (RITA).

METHODS

This article shows how testing and diagnosis reduce both FRR and mean duration of recent infection compared to a treatment-naive population. A new method is proposed for calculating appropriate context-specific estimates of FRR and mean duration of recent infection. The result of this is a new formula for incidence that depends only on reference FRR and mean duration of recent infection parameters derived in an undiagnosed, treatment-naive, nonelite controller, non-AIDS-progressed population.

RESULTS

Applying the methodology to eleven cross-sectional surveys in Africa results in good agreement with previous incidence estimates, except in 2 countries with very high reported testing rates.

CONCLUSIONS

Incidence estimation equations can be adapted to account for the dynamics of treatment and recent infection testing algorithms. This provides a rigorous mathematical foundation for the application of HIV recency assays in cross-sectional surveys.

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.

Antiretroviral Drug Resistance in HIV Sequences From People Who Inject Drugs and Men Who Have Sex With Men Across 21 Cities in India

Background

Drug resistance testing is limited in public-sector human immunodeficiency virus (HIV) care in India, and there are few systematic samplings for prevalent drug resistance mutations (DRMs), particularly among men who have sex with men (MSM) and people who inject drugs (PWID).

Methods

We conducted genotypic resistance testing on 915 HIV sequences sampled from viremic self-reported antiretroviral therapy (ART) experienced and naive PWID and MSM recruited from 21 cities across India in 2016-2017. We analyzed factors associated with resistance using logistic regression and evaluated evidence for transmitted resistance using phylogenetic analyses.

Results

Of the 915 participants sequenced, median age was 31, 436 were MSM, and 191 were ART experienced. Overall, 62.8% of ART-experienced participants and 14.4% of ART-naive participants were found to have low-level resistance or higher to 1 or more classes of drugs. Prevalence of tenofovir disoproxil fumarate resistance was 25.7% in ART-experienced participants and 1.11% in ART-naive participants. The highest proportion of drug resistance was seen across nucleoside reverse transcriptase inhibitors and nonnucleoside reverse transcriptase inhibitors, and resistance was significantly more common among MSM participants than PWID. Phylogenetic analyses revealed that 54.6% of ART-naive participants with resistance who clustered had shared DRMs, suggesting transmitted resistance may have occurred.

Conclusions

Patients experiencing virologic failure on first-line therapy switched blindly to tenofovir/lamivudine/dolutegravir may effectively be receiving dolutegravir monotherapy due to resistance to tenofovir and lamivudine. While dolutegravir is expected to have full activity in the majority of patients in India, follow-up is needed to understand how resistance may affect long-term outcomes.

A systematic review of limiting antigen avidity enzyme immunoassay for detection of recent HIV-1 infection to expand supported applications

Introduction

The need for detection of new and recent HIV infections is essential for surveillance and assessing interventions in controlling the epidemic. HIV recency assays are one way of providing reliable incidence estimates by determining recent versus non-recent infection. The objective of this study was to review the current body of knowledge of the limiting antigen avidity enzyme immunoassay to expand supported applications through an assessment of what is known and the gaps.

Methods

A search for peer-reviewed literature in PubMed, Embase, and Web of Science Core Collection was conducted using the search term “human immunodeficiency virus and avidity”. Non-peer reviewed published reports from the Population-based HIV Impact Assessment Project were also included. These were limited to literature published in English between January 2010 and August 2021.

Results

This search resulted in 2080 publications and 14 reports, with 137 peer-reviewed studies and 14 non-peer reviewed reports that met the inclusion criteria, yielding a total of 151 studies for the final review. There were similar findings among studies that compared the performances of assay manufacturers and sample types. Studies that evaluated various assay algorithms and thresholds were heterogeneous, illustrating the need for context-specific test characteristics for classifying recent infections. Most studies estimated subtype-specific test characteristics for HIV subtypes A, B, C, and D. This was further illustrated when looking only at studies that compared HIV incidence estimates from recency assay algorithms and longitudinal cohorts.

Conclusions

These findings suggest that the current body of knowledge provides important information that contributes towards distinguishing recent and non-recent infection and incidence estimation. However, there are knowledge gaps with respect to factors that influence the test characteristics (e.g., HIV-1 subtype, population characteristics, assay algorithms and thresholds). Further studies are needed to estimate and establish context-specific test characteristics that consider these influencing factors to improve and expand the use of this assay for detection of recent HIV infection.

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.

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.

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.

Validation of population-level HIV-1 incidence estimation by cross-sectional incidence assays in the HPTN 071 (PopART) trial

Introduction

Cross‐sectional incidence testing is used to estimate population‐level HIV incidence and measure the impact of prevention interventions. There are limited data evaluating the accuracy of estimates in settings where antiretroviral therapy coverage and levels of viral suppression are high. Understanding cross‐sectional incidence estimates in these settings is important as viral suppression can lead to false recent test results. We compared the accuracy of multi‐assay algorithms (MAA) for incidence estimation to that observed in the community‐randomized HPTN 071 (PopART) trial, where the majority of participants with HIV infection were virally suppressed.

Methods

HIV incidence was assessed during the second year of the study, and included only individuals who were tested for HIV at visits 1 and 2 years after the start of the study (2016–2017). Incidence estimates from three MAAs were compared to the observed incidence between years 1 and 2 (MAA‐C: LAg‐Avidity <2.8 ODn + BioRad Avidity Index <95% + VL >400 copies/ml; LAg+VL MAA: LAg‐Avidity <1.5 ODn + VL >1000 copies/ml; Rapid+VL MAA: Asanté recent rapid result + VL >1000 copies/ml). The mean duration of recent infection (MDRI) used for the three MAAs was 248, 130 and 180 days, respectively.

Results and discussion

The study consisted of: 15,845 HIV‐negative individuals; 4406 HIV positive at both visits; and 221 who seroconverted between visits. Viral load (VL) data were available for all HIV‐positive participants at the 2‐year visit. Sixty four (29%) of the seroconverters and 3227 (72%) prevelant positive participants were virally supressed (<400 copies/ml). Observed HIV incidence was 1.34% (95% CI: 1.17–1.53). Estimates of incidence were similar to observed incidence for MAA‐C, 1.26% (95% CI: 1.02–1.51) and the LAg+VL MAA, 1.29 (95% CI: 0.97–1.62). Incidence estimated by the Rapid+VL MAA was significantly lower than observed incidence (0.92%, 95% CI: 0.69–1.15, p<0.01).

Conclusions

MAA‐C and the LAg+VL MAA provided accurate point estimates of incidence in this cohort with high levels of viral suppression. The Rapid+VL significantly underestimated incidence, suggesting that the MDRI recommended by the manufacturer is too long or the assay is not accurately detecting enough recent infections.

Estimating HIV, HCV and HSV2 incidence from emergency department serosurvey

Background: Our understanding of pathogens and disease transmission has improved dramatically over the past 100 years, but coinfection, how different pathogens interact with each other, remains a challenge. Cross-sectional serological studies including multiple pathogens offer a crucial insight into this problem.  Methods: We use data from three cross-sectional serological surveys (in 2003, 2007 and 2013) in a Baltimore emergency department to predict the prevalence for HIV, hepatitis C virus (HCV) and herpes simplex virus, type 2 (HSV2), in a fourth survey (in 2016). We develop a mathematical model to make this prediction and to estimate the incidence of infection and coinfection in each age and ethnic group in each year. Results: Overall we find a much stronger age cohort effect than a time effect, so that, while incidence at a given age may decrease over time, individuals born at similar times experience a more constant force of infection over time. Conclusions: These results emphasise the importance of age-cohort counselling and early intervention while people are young. Our approach adds value to data such as these by providing age- and time-specific incidence estimates which could not be obtained any other way, and allows forecasting to enable future public health planning.

Undisclosed HIV status and antiretroviral therapy use among South African blood donors

BACKGROUND

Undisclosed antiretroviral drug (ARV) use among blood donors who tested HIV antibody positive, but RNA negative, was previously described by our group. Undisclosed ARV use represents a risk to blood transfusion safety. We assessed the prevalence of and associations with undisclosed ARV use among HIV-positive donors who donated during 2017.

STUDY DESIGN AND METHODS

South African National Blood Service (SANBS) blood donors are screened by self-administered questionnaire, semi-structured interview, and individual donation nucleic acid amplification testing for HIV. Stored samples from HIV-positive donations were tested for ARV and characterized as recent/longstanding using lag avidity testing.

RESULTS

Of the 1462 HIV-positive donations in 2017, 1250 had plasma availability for testing of which 122 (9.8%) tested positive for ARV. Undisclosed ARV use did not differ by gender (p = .205) or ethnicity (p = .505) but did differ by age category (p < .0001), donor (p < .0001), clinic type (p = .012), home province (p = .01), and recency (p < .0001). Multivariable logistic regression found older age (adjusted odds ratio [aOR] 3.73, 95% confidence interval [CI] 1.98-7.04 for donors >40 compared with those <21), first-time donation (aOR 5.24; 95% CI 2.48-11.11), and donation in a high HIV-prevalence province (aOR 9.10; 95% CI 2.70-30.72) compared with Northern Rural provinces to be independently associated with undisclosed ARV use.

DISCUSSION

Almost 1 in 10 HIV-positive blood donors neglected to disclose their HIV status and ARV use. Demographic characteristics of donors with undisclosed ARV use differed from those noted in other study. Underlying motivations for nondisclosure among blood donors remain unclear and may differ from those in other populations with significant undisclosed ARV use.

Temporal change in population-level prevalence of detectable HIV viraemia and its association with HIV incidence in key populations in India: a serial cross-sectional study

BACKGROUND

Population-level prevalence of detectable HIV viraemia (PDV) has been proposed as a metric for monitoring the population-level effectiveness of HIV treatment as prevention. We aimed to characterise temporal changes in PDV in people who inject drugs (PWID) and men who have sex with men (MSM) in India and evaluate community-level and individual-level associations with cross-sectional HIV incidence.

METHODS

We did a serial cross-sectional study in which baseline (from Oct 1, 2012, to Dec 19, 2013) and follow-up (from Aug 1, 2016, to May 28, 2017) respondent-driven sampling (RDS) surveys were done in MSM (ten community sites) and PWID (12 community sites) across 21 cities in India. Eligible participants were those aged 18 years or older who provided informed consent and possessed a valid RDS referral coupon. Annualised HIV incidence was estimated with validated multiple-assay algorithms. PDV was calculated as the percentage of people with detectable HIV RNA (>150 copies per mL) in a community site. Community-level associations were determined by linear regression. Multivariable, multilevel Poisson regression was used to assess associations with recent HIV infection.

FINDINGS

We recruited 21 990 individuals in the baseline survey and 21 726 individuals in the follow-up survey. The median community-level HIV incidence estimate increased from 0·9% (range 0·0-2·2) at baseline to 1·5% (0·5-3·0) at follow-up in MSM and from 1·6% (0·5-12·4) to 3·6% (0·0-18·4) in PWID. At the community-level, every 1 percentage point increase in baseline PDV and temporal change in PDV between surveys was associated with higher annualised HIV incidence at follow-up: for baseline PDV β=0·41 (95% CI 0·18-0·63) and for change in PDV β=0·52 (0·38-0·66). After accounting for individual-level risk factors, every 10 percentage point increase in baseline PDV and temporal change in PDV was associated with higher individual-level risk of recent HIV infection at follow-up: adjusted risk ratio 1·85 (95% CI 1·44-2·37) for baseline PDV and 1·81 (1·43-2·29) for change in PDV.

INTERPRETATION

PDV was temporally associated with community-level and individual-level HIV incidence. These data support scale-up of treatment as prevention programmes to reduce HIV incidence and the programmatic use of PDV to monitor community HIV risk potential.

FUNDING

US National Institutes of Health, Elton John AIDS Foundation.

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.

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.

Identifying major drivers of incident HIV infection using recent infection testing algorithms (RITAs) to precisely inform targeted prevention

BACKGROUND

Recent infection testing algorithms (RITAs) incorporating clinical information with the HIV recency assay have been proven to accurately classify recent infection. However, little evidence exists on whether RITAs would help in precisely identifying major drivers of the ongoing HIV epidemic.

METHODS

HIV recency test results and clinical information were collected from 1152 newly diagnosed HIV cases between 2015 and 2017 in Dehong prefecture of Yunnan province, and the efficacy of four different RITAs in identifying risk factors for new HIV infection was compared.

RESULTS

RITA 1 uses the recency test only. RITA 2 and RITA 3 combine the recency test with CD4+ T cell count and viral load (VL), respectively. RITA 4 combines both CD4+ T cell count and VL. All RITAs identified the MSM group and young people between 15 and 24 years as risk factors for incident HIV infection. RITA 3 and RITA 4 further identified the Dai ethnic minority as a risk factor, which had not been identified before when only the HIV recency test was used.

CONCLUSIONS

By comparing different RITAs, we determined that greater accuracy in classifying recent HIV infection could help elucidate major drivers impacting the ongoing epidemic and thus inform targeted interventions.

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.

Performance of a Modified In-House HIV-1 Avidity Assay among a Cohort of Newly Diagnosed HIV-1 Infected Individuals and the Effect of ART on the Maturation of HIV-1 Specific Antibodies

BACKGROUND

Viral kinetics impact humoral immune response to HIV; antibody avidity testing helps distinguish recent (<6 months) and long-term HIV infection. This study aims to determine the frequency of recent HIV-1 infection among clients attending ICTC (Integrated Counselling and Testing Centre) using a commercial EIA, to correlate it with a modified in-house avidity assay and to study the impact of ART on anti-HIV-1 antibody maturation.

METHODS

Commercial LAg Avidity EIA was used to detect antibody avidity among 117 treatment naïve HIV-1 infected individuals. A second-generation HIV ELISA was modified for in-house antibody avidity testing and cutoff was set based on Receiver Operating Characteristic (ROC) analysis. Archived paired samples from 25 HIV-1 infected individuals before ART and after successful ART; samples from 7 individuals responding to ART and during virological failure were also tested by LAg Avidity EIA.

RESULTS

Six individuals (5.1%) were identified as recently infected by a combination of LAg avidity assay and HIV-1 viral load testing. The modified in-house avidity assay demonstrated sensitivity and specificity of 100% and 98.2%, respectively, at AI=0.69 by ROC analysis. Median ODn values of individuals when responding to ART were significantly lower than pre-ART [4.136 (IQR 3.437- 4.827) vs 4.455 (IQR 3.748-5.120), p=0.006] whereas ODn values were higher during virological failure [4.260 (IQR 3.665 - 4.515) vs 2.868 (IQR 2.247 - 3.921), p=0.16].

CONCLUSION

This modified in-house antibody avidity assay is an inexpensive method to detect recent HIV-1 infection. ART demonstrated significant effect on HIV-1 antibody avidity owing to changes in viral kinetics.

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.

Targeting the HIV Epidemic in South Africa: The Need for Testing and Linkage to Care in Emergency Departments

BACKGROUND

The Eastern Cape province of South Africa has one of the highest burdens of HIV in the world. Emergency Departments (EDs) can serve as optimal clinical sites for the identification of new HIV infections and entry into care. We sought to determine the current burden of HIV disease among ED patients in the Eastern Cape.

METHODS

We conducted a prospective cross-sectional observational study in the EDs of three Hospitals in the Eastern Cape province of South Africa from June 2017 to July 2018. All adult, non-critical patients presenting to the ED were systematically approached and offered a Point-Of-Care (POC) HIV test in accordance with South African guidelines. All HIV-positive individuals had their blood tested for the presence of antiretroviral therapy (ART) and the presence of viral suppression (≤ 1000 copies/ml). HIV incidence was estimated using a multi-assay algorithm, validated for a subtype C epidemic.

FINDINGS

Of the 2901 patients for whom HIV status was determined (either known HIV-positive or underwent POC HIV testing), 811 (28.0%) were HIV positive, of which 234 (28.9%) were newly diagnosed. HIV prevalence was higher in Mthatha [34% (388/1134) at Mthatha Regional Hospital and 28% (142/512) at Nelson Mandela Academic Hospital], compared to Port Elizabeth [22% (281/1255) at Livingstone Hospital]. HIV incidence was estimated at 4.5/100 person-years (95% CI: 2.4, 6.50) for women and 1.5 (CI 0.5, 2.5) for men. Of all HIV positive individuals tested for ART (585), 54% (316/585) tested positive for the presence of ARTs, and for all HIV positive participants with viral load data (609), 49% (299/609) were found to be virally suppressed.

INTERPRETATION

Our study not only observed a high prevalence and incidence of HIV among ED patients but also highlights significant attrition along the HIV care cascade for HIV positive individuals. Furthermore, despite developing an optimal testing environment, we were only able to enrol a small sub-set of the ED population. Given the high HIV prevalence and high attrition in the ED population, HIV services in the ED should also develop strategies that can accommodate large testing volumes and ART initiation.

Evaluation of the Performance of Three Biomarker Assays for Recent HIV Infection Using a Well-Characterized HIV-1 Subtype C Incidence Cohort

Biomarkers for detecting early HIV infection and estimating HIV incidence should minimize false-recent rates (FRRs) while maximizing mean duration of recent infection (MDRI). We compared HIV subtypes B, E and D (BED) capture enzyme immunoassay (BED), Sedia limiting antigen (LAg) avidity enzyme immunoassay, and Bio-Rad avidity incidence (BRAI) assays using samples from Zimbabwean postpartum women infected with clade C HIV. We calculated MDRIs using 590 samples from 351 seroconverting postpartum women, and FRRs using samples from 2,825 women known to be HIV positive for >12 months. Antibody kinetics were more predictable with LAg and had higher precision compared with BED or BRAI. BRAI also exhibited more variability, and avidity reversal in some cases. For BED, LAg, and BRAI, used alone or with viral load, MDRI values in days were: BED-188 and 170 at normalized optical density (ODn) 0.8; LAg-104 and 100 at ODn cutoff 1.5; BRAI-135 and 134 at avidity index cutoff 30%. Corresponding FRRs were: BRAI 1.1% and 1.0% and LAg 0.57% and 0.35%: these were 3.8-10.9 times lower than BED values of 4.8% and 3.8%. BRAI and LAg have significantly lower FRRs and MDRIs than in published studies, and much lower than BED and could be used to estimate incidence in perinatal women and to measure population-level HIV incidence in HIV control operations in Africa.

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.

Comprehensive Profiling of HIV Antibody Evolution

This 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.

Integrated HIV testing, prevention, and treatment intervention for key populations in India: a cluster-randomised trial

BACKGROUND

To achieve reductions in HIV incidence, we need strategies to engage key population at risk for HIV in low-income and middle-income countries. We evaluated the effectiveness of integrated care centres in India that provided single-venue HIV testing, prevention, and treatment services for people who inject drugs (PWID) and men who have sex with men (MSM).

METHODS

We did baseline respondent-driven sampling surveys in 27 sites across India, and selected 22 of these (12 PWID and ten MSM) for a cluster randomised trial on the basis of high HIV prevalence and logistical considerations. We used stratified (by PWID and MSM), restricted randomisation to allocate sites to either the integrated care intervention or usual care (11 sites per group). We implemented integrated care centres in 11 cities (six PWID integrated care centres embedded within opioid agonist treatment centres and five MSM centres within government-sponsored health services), with a single integrated care centre per city in all but one city. After a 2-year intervention phase, we did respondent-driven sampling evaluation surveys of target population members who were aged 18 years or older at all sites. The primary outcome was self-reported HIV testing in the previous 12 months (recent testing), determined via the evaluation survey. We used a biometric identification system to estimate integrated care centre exposure (visited an integrated care centre at least once) among evaluation survey participants at intervention sites. This trial is registered with ClinicalTrials.gov, number NCT01686750.

FINDINGS

Between Oct 1, 2012, and Dec 19, 2013, we recruited 11 993 PWID and 9997 MSM in the baseline survey and, between Aug, 1 2016, and May 27, 2017, surveyed 11 721 PWID and 10 005 MSM in the evaluation survey using respondent-driven sampling, across the 22 trial sites. During the intervention phase, integrated care centres provided HIV testing for 14 698 unique clients (7630 PWID and 7068 MSM. In the primary population-level analysis, recent HIV testing was 31% higher at integrated care centres than at usual care sites (adjusted prevalence ratio [PR] 1·31, 95% CI 0·95-1·81, p=0·09). Among survey participants at intervention sites, integrated care centre exposure was lower than expected (median exposure 40% at PWID sites and 24% at MSM sites). In intervention sites, survey participants who visited an integrated care centre were more likely to report recent HIV testing than were participants who had not (adjusted PR 3·46, 2·94-4·06).

INTERPRETATION

Although integrated care centres increased HIV testing among visitors, our low exposure findings suggest that the scale-up of a single integrated care centre in most cities was insufficient to serve the large PWID and MSM populations. Future work should address the use of population size estimates to guide the dose of combination HIV interventions targeting key populations.

FUNDING

US National Institutes of Health and the Elton John AIDS Foundation.

Validation of the Limiting Antigen Avidity Assay to Estimate Level and Trends in HIV Incidence in an A/D Epidemic in Rakai, Uganda

The limiting-antigen avidity (LAg-Avidity) assay with viral load (VL) >1,000 copies/mL is being used to estimate population-level HIV incidence in Africa. However, this has not been validated in East Africa where HIV-1 subtypes A and D circulate. Sera from persons seen in two surveys (2008-2009 and 2012-2013) limited to those who attended the previous round of the Rakai Community Cohort in Uganda were analyzed. The performance of the current LAg-Avidity protocol, with a mean duration of recent infection (MDRI) of 130 days and false recent rate (FRR) of 0%, was compared with subtype-specific MDRI and FRR, adjusted to subtype distributions. The observed incidence was 1.05/100 person years (py) [95% confidence interval (CI) 0.90-1.23] in 2008-2009 and 0.66/100 py (95% CI 0.52-0.83) in 2012-2013. In contrast, the per-protocol LAg-Avidity incidence estimates were 1.63/100 py (95% CI 0.97-2.30) in 2008-2009 and 2.55/100 py (95% CI 1.51-3.59) in 2012-2013 (a significant increase, p < .05.) However, using a subtype-specific MDRI and FRR, the subtype adjusted incidence was 0.88% (95% CI 0.44-1.33) in 2008-2009 and 0.67% (95% CI 0.00-1.68) in 2012-2013, approximating to the observed incidence trends. In this subtype A/D epidemic, the per protocol LAg-Avidity + VL assay overestimated HIV incidence and failed to detect declines in incidence. Adjustment for FRR, MDRI, and subtype distribution provided incidence estimates similar to empirically observed incidence level and trends. Thus, use of the LAg-Avidity assay in an A/D epidemic requires adjustment for subtype.