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

ABSTRACT: 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.

SUBMITTER: Laeyendecker O

PROVIDER: S-EPMC5829581 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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

Laeyendecker Oliver O Konikoff Jacob J Morrison Douglas E DE Brookmeyer Ronald R Wang Jing J Celum Connie C Morrison Charles S CS Abdool Karim Quarraisha Q Pettifor Audrey E AE Eshleman Susan H SH

Journal of the International AIDS Society 20180201 2

<h4>Introduction</h4>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.<h4>Methods</h4>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), BioR ...[more]

PMID: 29489059

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

Project description:IntroductionCross-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.MethodsHIV 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 discussionThe 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).ConclusionsMAA-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.

Project description:HIV incidence has been declining in Africa with scale-up of HIV interventions. However, there is limited data on HIV evolutionary trends in African populations with waning epidemics. We evaluated changes in HIV viral diversity and genetic divergence in southern Uganda over a twenty-five-year period spanning the introduction and scale-up of HIV prevention and treatment programs using HIV sequence and survey data from the Rakai Community Cohort Study, an open longitudinal population-based HIV surveillance cohort. Gag (p24) and env (gp41) HIV data were generated from persons living with HIV (PLHIV) in 31 inland semi-urban trading and agrarian communities (1994 to 2018) and four hyperendemic Lake Victoria fishing communities (2011 to 2018) under continuous surveillance. HIV subtype was assigned using the Recombination Identification Program with phylogenetic confirmation. Inter-subtype diversity was estimated using the Shannon diversity index and intra-subtype diversity with the nucleotide diversity and pairwise TN93 genetic distance. Genetic divergence was measured using root-to-tip distance and pairwise TN93 genetic distance analyses. Evolutionary dynamics were assessed among demographic and behavioral sub-groups, including by migration status. 9,931 HIV sequences were available from 4,999 PLHIV, including 3,060 and 1,939 persons residing in inland and fishing communities, respectively. In inland communities, subtype A1 viruses proportionately increased from 14.3% in 1995 to 25.9% in 2017 (p<0.001), while those of subtype D declined from 73.2% in 1995 to 28.2% in 2017 (p<0.001). The proportion of viruses classified as recombinants significantly increased by more than four-fold. Inter-subtype HIV diversity has generally increased. While p24 intra-subtype genetic diversity and divergence leveled off after 2014, diversity and divergence of gp41 increased through 2017. Inter- and intra-subtype viral diversity increased across all population sub-groups, including among individuals with no recent migration history or extra-community sexual partners. This study provides insights into population-level HIV evolutionary dynamics in declining African HIV epidemics following the scale-up of HIV prevention and treatment programs. Continued molecular surveillance may provide a better understanding of the dynamics driving population HIV evolution and yield important insights for epidemic control and vaccine development.

Dataset Information

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

Publications

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

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