The HIV Genomic Incidence Assay Meets False Recency Rate and Mean Duration of Recency Infection Performance Standards

Use of Next-Generation Sequencing in a State-Wide Strategy of HIV-1 Surveillance: Impact of the SARS-COV-2 Pandemic on HIV-1 Diagnosis and Transmission

BACKGROUND

The ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic posed an unpreceded threat to the management of other pandemics such as human immunodeficiency virus-1 (HIV-1) in the United States. The full impact of the SARS-CoV-2 pandemic on the HIV-1 pandemic needs to be evaluated.

METHODS

All individuals with newly reported HIV-1 diagnoses from NC State Laboratory of Public Health were enrolled in this prospective observational study, 2018-2021. We used a sequencing-based recency assay to identify recent HIV-1 infections and to determine the days postinfection (DPI) for each person at the time of diagnosis.

RESULTS

Sequencing used diagnostic serum samples from 814 individuals with new HIV-1 diagnoses spanning this 4-year period. Characteristics of individuals diagnosed in 2020 differed from those in other years. People of color diagnosed in 2021 were on average 6 months delayed in their diagnosis compared to those diagnosed in 2020. There was a trend that genetic networks were more known for individuals diagnosed in 2021. We observed no major integrase resistance mutations over the course of the study.

CONCLUSIONS

SARS-CoV-2 pandemic may contribute to the spread of HIV-1. Public health resources need to focus on restoring HIV-1 testing and interrupting active, ongoing, transmission.

Precision detection of recent HIV infections using high-throughput genomic incidence assay

HIV incidence is a key measure for tracking disease spread and identifying populations and geographic regions where new infections are most concentrated. The HIV sequence population provides a robust signal for the stage of infection. Large-scale and high-precision HIV sequencing is crucial for effective genomic incidence surveillance. We produced 1,034 full-length envelope gene sequences from a seroconversion cohort by conducting HIV microdrop sequencing and measuring the genomic incidence assay's genome similarity index (GSI) dynamics. The measured dynamics of 9 of 12 individuals aligned with the GSI distribution estimated independently using 417 publicly available incident samples. We enhanced the capacity to identify individuals with recent infections, achieving predicted detection accuracies of 92% (89%-94%) for cases within 6 months and 81% (74%-87%) for cases within 9 months. These accuracy levels agreed with the observed detection accuracy intervals of an independent validation data set. Additionally, we produced 131 full-length envelope gene sequences from eight individuals with chronic HIV infection. This analysis confirmed a false recency rate (FRR) of 0%, which was consistent with 162 publicly available chronic samples. The mean duration of recent infection (MDRI) was 238 (209-267) days, indicating an 83% improvement in performance compared to current recent infection testing algorithms. The shifted Poisson mixture model was then used to estimate the time since infection, and the model estimates showed an 88% consistency with the days post infection derived from HIV RNA test dates and/or seroconversion dates. HIV microdrop sequencing provides unique prospects for large-scale incidence surveillance using high-throughput sequencing. IMPORTANCE Accurate identification of recently infected individuals is vital for prioritizing specific populations for interventions, reducing onward transmission risks, and optimizing public health services. However, current HIV-specific antibody-based methods have not been satisfactory in accurately identifying incident cases, hindering the use of HIV recency testing for prevention efforts and partner protection. Genomic incidence assays offer a promising alternative for identifying recent infections. In our study, we used microdroplet technologies to produce a large number of complete HIV envelope gene sequences, enabling the accurate detection of early infection signs. We assessed the dynamics of the incidence assay's metrics and compared them with statistical models. Our approach demonstrated high accuracy in identifying individuals with recent infections, achieving predicted detection rates exceeding 90% within 6 months and over 80% within 9 months of infection. This high-resolution method holds significant potential for enhancing the effectiveness of HIV incidence screening for case-based surveillance in public health initiatives.

Microdrop Human Immunodeficiency Virus Sequencing for Incidence and Drug Resistance Surveillance

BACKGROUND

Precise and cost-efficient human immunodeficiency virus (HIV) incidence and drug resistance surveillances are in high demand for the advancement of the 90-90-90 "treatment for all" target.

METHODS

We developed microdrop HIV sequencing for the HIV incidence and drug resistance assay (HIDA), a single-blood-draw surveillance tool for incidence and drug resistance mutation (DRM) detection. We amplified full-length HIV envelope and pol gene sequences within microdroplets, and this compartmental amplification with long-read high-throughput sequencing enabled us to recover multiple unique sequences.

RESULTS

We achieved greater precision in determining the stage of infection than current incidence assays, with a 1.2% false recency rate (proportion of misclassified chronic infections) and a 262-day mean duration of recent infection (average time span of recent infection classification) from 83 recently infected and 81 chronically infected individuals. Microdrop HIV sequencing demonstrated an increased capacity to detect minority variants and linked DRMs. By screening all 93 World Health Organization surveillance DRMs, we detected 6 pretreatment drug resistance mutations with 2.6%-13.2% prevalence and cross-linked mutations.

CONCLUSIONS

HIDA with microdrop HIV sequencing may promote global HIV real-time surveillance by serving as a precise and high-throughput cross-sectional survey tool that can be generalized for surveillance of other pathogens.

Recent levels and trends in HIV incidence rates among adolescent girls and young women in ten high-prevalence African countries: a systematic review and meta-analysis

BACKGROUND

The roll-out of antiretroviral therapy (ART) has changed contexts of HIV risk, but the influence on HIV incidence among young women is not clear. We aimed to summarise direct estimates of HIV incidence among adolescent girls and young women since ART and before large investments in targeted prevention for those in sub-Saharan Africa.

METHODS

We did a systematic review and meta-analysis. We searched MEDLINE, Embase, Web of Science, Global Health, and CINAHL for studies reporting HIV incidence data from serological samples collected among females aged 15-24 years in ten countries (Kenya, Lesotho, Malawi, Mozambique, South Africa, Swaziland, Tanzania, Uganda, Zambia, and Zimbabwe) that were selected for DREAMS investment in 2015. We only included articles published in English. Our main outcome was to summarise recent levels and trends in HIV incidence estimates collected between 2005 and 2015, published or received from study authors, by age and sex, and pooled by region.

FINDINGS

51 studies were identified from nine of the ten DREAMS countries; no eligible studies from Lesotho were identified. Directly observed HIV incidence rates were lowest among females aged 13-19 years in Kumi, Uganda (0·38 cases per 100 person-years); and directly observed HIV incidence rates were highest in KwaZulu-Natal, South Africa (7·79 per 100 person-years among females aged 15-19 years, and 8·63 in those aged 20-24 years), among fishing communities in Uganda (12·40 per 100 person-years in females aged 15-19 years and 4·70 in those aged 20-24 years), and among female sex workers aged 18-24 years in South Africa (13·20 per 100 person-years) and Zimbabwe (10·80). In pooled rates from the general population studies, the greatest sex differentials were in the youngest age groups-ie, females aged 15-19 years compared with male peers in both southern African (pooled relative risk 5·94, 95% CI 3·39-10·44) and eastern African countries (3·22, 1·51-6·87), and not significantly different among those aged 25-29 years in either region. Incidence often peaked earlier (during teenage years) among high-risk groups compared with general populations. Since 2005, HIV incidence among adolescent girls and young women declined in Rakai (Uganda) and Manicaland (Zimbabwe), and also declined among female sex workers in Kenya, but not in the highest-risk communities in South Africa and Uganda.

INTERPRETATION

Few sources of direct estimates of HIV incidence exist in high-burden countries and trend analyses with disaggregated data for age and sex are rare but indicate recent declines among adolescent girls and young women. In some of the highest-risk settings, however, little evidence exists to suggest ART availability and other efforts slowed transmission by 2016. Despite wide geographical diversity in absolute levels of incidence in adolescent girls and young women, risk relative to males persisted in all settings, with the greatest sex differentials in the youngest age groups. To end new infections among the growing population of adolescents in sub-Saharan Africa, prevention programmes must address gender inequalities driving excessive risk among adolescent girls.

FUNDING

This work was conducted as part of a planning grant funded by the Bill & Melinda Gates Foundation.

HIITE: HIV-1 incidence and infection time estimator

Motivation

Around 2.1 million new HIV-1 infections were reported in 2015, alerting that the HIV-1 epidemic remains a significant global health challenge. Precise incidence assessment strengthens epidemic monitoring efforts and guides strategy optimization for prevention programs. Estimating the onset time of HIV-1 infection can facilitate optimal clinical management and identify key populations largely responsible for epidemic spread and thereby infer HIV-1 transmission chains. Our goal is to develop a genomic assay estimating the incidence and infection time in a single cross-sectional survey setting.

Results

We created a web-based platform, HIV-1 incidence and infection time estimator (HIITE), which processes envelope gene sequences using hierarchical clustering algorithms and informs the stage of infection, along with time since infection for incident cases. HIITE's performance was evaluated using 585 incident and 305 chronic specimens' envelope gene sequences collected from global cohorts including HIV-1 vaccine trial participants. HIITE precisely identified chronically infected individuals as being chronic with an error less than 1% and correctly classified 94% of recently infected individuals as being incident. Using a mixed-effect model, an incident specimen's time since infection was estimated from its single lineage diversity, showing 14% prediction error for time since infection. HIITE is the first algorithm to inform two key metrics from a single time point sequence sample. HIITE has the capacity for assessing not only population-level epidemic spread but also individual-level transmission events from a single survey, advancing HIV prevention and intervention programs.

Availability and implementation

Web-based HIITE and source code of HIITE are available at http://www.hayounlee.org/software.html.

Supplementary information

Supplementary data are available at Bioinformatics online.