Cross-sectional HIV incidence surveillance, using assays that distinguish 'recent' from 'nonrecent' infections, has been hampered by inadequate performance and characterization of incidence assays. In this study, the Consortium for the Evaluation and Performance of HIV Incidence Assays presents results of the first independent evaluation of five incidence assays (BED, Limiting Antigen Avidity, Less-sensitive Vitros, Vitros Avidity and BioRad Avidity). A large repository of diverse specimens from HIV-positive patients was established, multiple assays were run on 2500 selected specimens, and data were analyzed to estimate assay characteristics relevant for incidence surveillance. The mean duration of recent infection (MDRI, average time 'recent' while infected for less than some time cut-off T) was estimated from longitudinal data on seroconverters by regression. The false-recent rate (FRR, probability of testing 'recent' when infected for longer than T) was explored by measuring the proportions of 'recent' results in various subsets of patients. Assays continue to fail to attain the simultaneously large MDRI and small FRR demanded by existing performance guidelines. All assays produce high FRRs amongst virally suppressed patients (>40%), including elite controllers and treated patients. Results from this first independent evaluation provide valuable information about the current performance of assays, and suggest the need for further optimization. Variation of 'recent'/'nonrecent' thresholds and the use of multiple antibody-maturation assays, as well as other biomarkers, can now be explored, using the rich data generated by the Consortium for the Evaluation and Performance of HIV Incidence Assays. Consistently high FRRs amongst those virally suppressed suggest that viral load will be a particularly valuable supplementary marker.

Background: Estimating disease incidence from cross-sectional surveys, using biomarkers for “recent” infection, has attracted much interest. Despite widespread applications to HIV, there is currently no consensus on the correct handling of biomarker results classifying persons as “recently” infected long after the infections occurred. Methods: We derive a general expression for a weighted average of recent incidence that—unlike previous estimators—requires no particular assumption about recent infection biomarker dynamics or about the demographic and epidemiologic context. This is possible through the introduction of an explicit timescale T that truncates the period of averaging implied by the estimator. Results: The recent infection test dynamics can be summarized into 2 parameters, similar to those appearing in previous estimators: a mean duration of recent infection and a false-recent rate. We identify a number of dimensionless parameters that capture the bias that arises from working with tractable forms of the resulting estimator and elucidate the utility of the incidence estimator in terms of the performance of the recency test and the population state. Estimation of test characteristics and incidence is demonstrated using simulated data. The observed confidence interval coverage of the test characteristics and incidence is within 1% of intended coverage. Conclusions: Biomarker-based incidence estimation can be consistently adapted to a general context without the strong assumptions of previous work about biomarker dynamics and epidemiologic and demographic history.

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. 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. 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). 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.

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.

Introduction: The Spectrum/AIM model is used by national HIV programs and UNAIDS to prepare annual estimates of key HIV indicators. This article describes key updates to paediatric and adult models for the 2021 round of HIV estimates.Methods: Potential updates to Spectrum arise due to newly available data, new analyses of existing data, and the need for new issues to be addressed. Updates are guided by experts through the UNAIDS Reference Group on Estimates, Modelling and Projections. Changes are tested and assessed for impact before being accepted into the final model.Results: Spectrum tracks children living with HIV by CD4% for ages 0–4 and CD4 count for ages 5–14. Data from IeDEA treatment sites have been used to map the transition from CD4% to CD4 count at age 5. Breastfeeding patterns in sub‐Saharan Africa have been updated with the latest survey data and estimates of continuation on antiretroviral therapy (ART) with breastfeeding have been revised based on recent studies. Model assumptions about the CD4 counts of people who drop out of ART have been revised to account for CD4 count increases while on treatment. If available, monthly data on numbers on ART can now be used to estimate the effects of COVID‐19‐related disruptions during 2020.Conclusions: These changes are intended to provide more accurate estimates of HIV burden. The effects of these changes on paediatric indicators are small except in countries with new surveys that might have updated patterns of breastfeeding. Changes to the adult model have little effect on total new infections. AIDS‐related deaths will be somewhat lower in countries that have data on ART drop out but might be increased by HIV care disruptions due to COVID‐19. The updated model uses newly available data to improve the estimation of paediatric and adult HIV indicators.

Background: While people with human immunodeficiency virus (PWH) start antiretroviral treatment (ART) regardless of CD4 count, CD4 measurement remains crucial for detecting advanced human immunodeficiency virus (HIV) disease and evaluating ART programs. We explored CD4 measurement (proportion of PWH with a CD4 result available) and prevalence of CD4 <200 cells/µL (hereafter “CD4 <200”) at ART initiation within the International epidemiology Databases to Evaluate AIDS (IeDEA) global collaboration. Methods: We included PWH at participating ART programs who first initiated ART at age 15–80 years during 2005–2019. We described proportions of PWH with a CD4 result (measured within 6 months before to 2 weeks after ART initiation) and, among those with a CD4 result, with CD4 <200, by year of ART initiation and region. Results: We included 1 355 104 PWH from 42 countries in 7 regions; 63% were female. The median (interquartile range) age at ART initiation was 37 (3144) years in males and 32 (26–39) years in females. CD4 measurement initially increased, or remained stable over time until around 2013, but then declined to low levels in some regions (Southern Africa, except South Africa: from 54% to 13%; East Africa: 85% to 31%; Central Africa: 72% to 20%; West Africa: 91% to 53%; and Latin America: 87% to 56%). Prevalence of CD4 <200 declined over time in all regions, but plateaued after 2015 at ≥30%. Conclusions: CD4 measurement has declined sharply in recent years, especially in sub-Saharan Africa. Among those with a CD4 measurement, the prevalence of CD4 <200 remains concerningly high. Scaling up CD4 testing and securing adequate funding are urgent priorities.