A Multiplex HIV Incidence Assay for Inferring Recent HIV-1 Transmission and Time of Infection.
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ABSTRACT: Background
Laboratory assays for determining recent HIV-1 infection are an important public health tool for aiding in the estimation of HIV incidence. Some incidence assay analytes are remarkably predictive of time since seroconversion and may be useful for additional applications, such as predicting recent transmission events during HIV outbreaks and informing prevention strategies.Methods
Plasma samples (n = 154) from a recent HIV-1 outbreak in a rural community in Indiana were tested with the customized HIV-1 Multiplex assay, based on the Bio-Rad Bio-Plex platform, which measures antibody response to HIV envelope antigens, gp120, gp160, and gp41. Assay cutoffs for each analyte were established to determine whether an individual seroconverted within 30, 60, or 90 days of the sample collection date. In addition, a novel bioinformatics method was implemented to infer infection dates of persons newly diagnosed with HIV during the outbreak.Results
Sensitivity/specificity of the HIV-1 Multiplex assay for predicting seroconversion within 30, 60, and 90 days, based on a training data set, was 90.5%/95.4%, 94.1%/90%, and 89.4%/82.9%, respectively. Of 154 new diagnoses in Indiana between December 2014 and August 2016, the majority (71%) of recent infections (≤3 months since seroconversion) were identified between February and May 2016. The epidemiologic curve derived from the bioinformatics analysis indicated HIV transmission began as early as 2010, grew exponentially in 2014, and leveled off in April 2015.Conclusions
The HIV-1 Multiplex assay has the potential to identify and monitor trends in recent infection during an epidemic to assess the efficacy of programmatic or treatment interventions.
SUBMITTER: Curtis KA
PROVIDER: S-EPMC11342239 | biostudies-literature | 2019 Apr
REPOSITORIES: biostudies-literature
Publications
A Multiplex HIV Incidence Assay for Inferring Recent HIV-1 Transmission and Time of Infection.
Curtis Kelly A KA Campbell Ellsworth M EM Hanson Debra L DL Rudolph Donna L DL Duwve Joan J J Blosser Sara S Gentry Jessica J Lovchik Judith J Peters Philip J PJ Owen Sherry Michele SM Switzer William M WM
Journal of acquired immune deficiency syndromes (1999) 20190401 4
<h4>Background</h4>Laboratory assays for determining recent HIV-1 infection are an important public health tool for aiding in the estimation of HIV incidence. Some incidence assay analytes are remarkably predictive of time since seroconversion and may be useful for additional applications, such as predicting recent transmission events during HIV outbreaks and informing prevention strategies.<h4>Methods</h4>Plasma samples (n = 154) from a recent HIV-1 outbreak in a rural community in Indiana were ...[more]
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Project description:BackgroundMeasuring recent HIV infections from routine surveillance systems could allow timely and granular monitoring of HIV incidence patterns. We evaluated the relationship of two recent infection indicators with alternative denominators to true incidence patterns.MethodsWe used a mathematical model of HIV testing behaviours, calibrated to population-based surveys and HIV testing services programme data, to estimate the number of recent infections diagnosed annually from 2010 to 2019 in Côte d'Ivoire, Malawi, and Mozambique. We compared two different denominators to interpret recency data: those at risk of HIV acquisition (HIV-negative tests and recent infections) and all people testing HIV positive. Sex and age-specific longitudinal trends in both interpretations were then compared with modelled trends in HIV incidence, testing efforts and HIV positivity among HIV testing services clients.ResultsOver 2010-2019, the annual proportion of the eligible population tested increased in all countries, while positivity decreased. The proportion of recent infections among those at risk of HIV acquisition decreased, similar to declines in HIV incidence among adults (≥15 years old). Conversely, the proportion of recent infections among HIV-positive tests increased. The female-to-male ratio of the proportion testing recent among those at risk was closer to 1 than the true incidence sex ratio.ConclusionThe proportion of recent infections among those at risk of HIV acquisition is more indicative of HIV incidence than the proportion among HIV-positive tests. However, interpreting the observed patterns as surrogate measures for incidence patterns may still be confounded by different HIV testing rates between population groups or over time.
| S-EPMC8631145 | biostudies-literature
Project description:ObjectivesAccurate methods of estimating HIV-1 incidence are critical for monitoring the status of the epidemic and the impact of prevention strategies. Although several laboratory-based tests have been developed strictly for this purpose, several limitations exist and improved methods or technologies are needed. We sought to further optimize a previously described bead-based, HIV-1-specific multiplex assay with the capability of measuring multiple immune responses for determining recent infection.MethodsWe refined the customized HIV-1 Bio-Plex assay by determining cutoffs and mean durations of recency (MDR), based on the reactivity to longitudinal seroconversion specimens (n = 1347) from 311 ART-naïve, HIV-1-infected subjects. False-recent rates (FRRs) were calculated for various long-term cohorts, including AIDS patients, individuals on ART, and subtype C specimens. Incidence was estimated for each individual assay analyte from a simulated population with a known incidence of 1%. For improved incidence estimates, multi-analyte algorithms based on combinations of 3 to 6 analytes were evaluated and compared to the performance of each individual analyte.ResultsThe MDR for the six analytes varied from 164.2 to 279.4 days, while the multi-analyte algorithm MDRs were less variable with a minimum and maximum value of 228.4 and 277.9 days, respectively. The FRRs for the 7 multi-analyte algorithms evaluated in this study varied from 0.3% to 3.1%, in a population of ART-naïve, long-term individuals. All algorithms yielded improved incidence estimates as compared to the individual analytes, predicting an incidence of 0.95% to 1.02%.ConclusionsThe HIV-specific multiplex assay described here measures several distinct immune responses in a single assay, allowing for the consideration of multi-analyte algorithms for improved HIV incidence estimates.
| S-EPMC3661489 | biostudies-literature
Project description:BackgroundWe developed the HIV Triplex multiplex bead assay to identify and serotype HIV infection with high sensitivity and specificity; and distinguish recent from long-term HIV-1 infections. It can facilitate accurate incidence estimation, while reducing the number of tests and blood collected, which is highly desirable for use in future studies and surveys. Using previously collected, treatment-naive longitudinal seroconversion HIV-1 positive panels and specimens from individuals infected for >12 months, we determined the assay's mean duration of recent infection (MDRI) and false-recency rate (FRR) respectively, at various mean fluorescent intensity (MFI) cutoffs.MethodsWe tested seroconversion specimens (N = 814) from 142 individuals infected with HIV-1 subtypes B, C, or AE, and 1341 cross-sectional specimens from individuals infected >12 months. The MFI cutoffs of 1000 to 2000 were evaluated for recency classification, including an MFI of 1250 corresponding to the limiting antigen avidity enzyme immunoassay (LAg-EIA) cutoff of 1.5 normalized optical density for MDRI and FRR. We used four statistical methods: Methods 1 and 2 used the empirically balanced observation time approach. Method 2 MFI values were raised to power = 1.33, based on a repeated measures model to linearize the relationship between MFI and time points, whereas Method 1 was not linearized. Methods 3 and 4 employed quadratic and linear interpolations for each seroconversion panel. FRR was calculated by dividing the number of specimens misclassified as recent by the total number of specimens tested.ResultsMDRI values ranged from 135-146 days at MFI = 1000 to 229-279 days at MFI = 2000 by the 4 methods. FRR varied from 0.15%-1.27% with increasing MFI cutoff. At MFI = 1250, the average MDRI of 4 methods was 169 days and ranged from 159-183 with overlapping 95% CIs and FRR = 0.52%.ConclusionThe HIV Triplex assay demonstrates a longer dynamic range compared to current HIV recency assays with a low FRR for cutoffs examined. With a longer dynamic range and low FRR, the MDRI for recent infection can be extended as appropriate to detect more recent infections, increasing the value of incidence assays benefiting public health surveillance and future surveys.
| S-EPMC11508083 | biostudies-literature
Project description:Nationally representative surveys provide an opportunity to assess trends in recent human immunodeficiency virus (HIV) infection based on assays for recent HIV infection. We assessed HIV incidence in Kenya in 2018 and trends in recent HIV infection among adolescents and adults in Kenya using nationally representative household surveys conducted in 2007, 2012, and 2018. To assess trends, we defined a recent HIV infection testing algorithm (RITA) that classified as recently infected (<12 months) those HIV-positive participants that were recent on the HIV-1 limiting antigen (LAg)-avidity assay without evidence of antiretroviral use. We assessed factors associated with recent and long-term (≥12 months) HIV infection versus no infection using a multinomial logit model while accounting for complex survey design. Of 1,523 HIV-positive participants in 2018, 11 were classified as recent. Annual HIV incidence was 0.14% in 2018 [95% confidence interval (CI) 0.057-0.23], representing 35,900 (95% CI 16,300-55,600) new infections per year in Kenya among persons aged 15-64 years. The percentage of HIV infections that were determined to be recent was similar in 2007 and 2012 but fell significantly from 2012 to 2018 [adjusted odds ratio (aOR) = 0.31, p < .001]. Compared to no HIV infection, being aged 25-34 versus 35-64 years (aOR = 4.2, 95% CI 1.4-13), having more lifetime sex partners (aOR = 5.2, 95% CI 1.6-17 for 2-3 partners and aOR = 8.6, 95% CI 2.8-26 for ≥4 partners vs. 0-1 partners), and never having tested for HIV (aOR = 4.1, 95% CI 1.5-11) were independently associated with recent HIV infection. Although HIV remains a public health priority in Kenya, HIV incidence estimates and trends in recent HIV infection support a significant decrease in new HIV infections from 2012 to 2018, a period of rapid expansion in HIV diagnosis, prevention, and treatment.
| S-EPMC9942172 | biostudies-literature
Project description:We previously developed a multiassay algorithm (MAA) to identify recent HIV infection that includes the BED-capture enzyme immunoassay, an avidity assay based on the Genetic Systems HIV-1/HIV-2 + O enzyme immunoassay, CD4 cell count, and HIV viral load. We used this MAA to evaluate the association between recent maternal HIV infection and in-utero transmission of HIV.Plasma samples were collected at delivery from 2561 HIV-infected women in the postexposure prophylaxis of infants-Malawi trial. The MAA described above was used to identify women with recent HIV infection. Logistic regression models assessed association between recent HIV infection and in-utero HIV transmission (defined as a positive infant HIV DNA test at birth).Seventy-three women were identified as recently infected using the MAA. Those women were younger and had lower parity than women who were identified as not recently infected using the MAA (P < 0.0001 for age and parity). The frequency of in-utero HIV transmission was 17.8% among women identified as recently infected, compared with 6.7% among women identified as not recently infected (13/73 vs. 166/2488, P = 0.001). In a multivariate model, three factors were independently associated with in-utero HIV transmission: recent infection [adjusted odds ratio (AOR): 2.49, 95% confidence interval (CI): 1.30-4.78, P = 0.006], log(10) HIV viral load at delivery (AOR: 2.01, 95% CI: 1.60-2.51, P < 0.0001), and younger age (per 10 year increase, AOR: 0.66, 95% CI: 0.43-0.93, P = 0.02).Results obtained using a MAA suggest that recent maternal HIV acquisition is strongly associated with in-utero HIV transmission, independent of HIV viral load at delivery.
| S-EPMC3263827 | biostudies-literature
Project description: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.
| S-EPMC10580985 | biostudies-literature
Project description:MotivationAround 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.ResultsWe 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 implementationWeb-based HIITE and source code of HIITE are available at http://www.hayounlee.org/software.html.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC6390194 | biostudies-literature
Project description:IntroductionNew HIV infection during pre-conception and pregnancy is a significant contributor of mother-to-child transmission of HIV in South Africa. This study estimated HIV incidence (defined as new infection within the last one year from the time of the survey which included both new infections occurred during pregnancy or just before pregnancy) among pregnant women and described the characteristics of recently infected pregnant women at national level.MethodsBetween 1 October and 15 November 2017, we conducted a national cross-sectional survey among pregnant women aged 15-49 years old attending antenatal care at 1,595 public facilities. Blood specimens were collected from pregnant women and tested for HIV in a centralised laboratory. Plasma viral load and Limiting Antigen Avidity Enzyme Immunosorbent Assay (LAg) tests were further performed on HIV positive specimens to differentiate between recent and long-term infections. Recent infection was defined as infection that occurred within one year from the date of collection of blood specimen for the survey. Data on age, age of partner, and marital status were collected through interviews. Women whose specimens were classified as recent by LAg assay and with viral loads >1,000 copies/mL were considered as recently infected. The calculated proportion of HIV positive women with recent infection was adjusted for assay-specific parameters to estimate annual incidence. Survey multinomial logistic regression was used to examine factors associated with being recently infected using HIV negative women as a reference group. Age-disparate relationship was defined as having a partner 5 or more years older.ResultsOf 10,049 HIV positive participants with LAg and viral load data, 1.4% (136) were identified as recently infected. The annual HIV incidence was 1.5% (95% confidence interval (CI): 1.2-1.7). In multivariable analyses, being single (adjusted odds ratio, aOR: 3.4, 95% CI: 1.8-6.2) or cohabiting (aOR: 3.8, 95% CI: 1.8-7.7), compared to being married as well as being in an age-disparate relationship among young women (aOR: 3.1, 95% CI: 2.0-4.7; reference group: young women (15-24years) whose partners were not 5 years or more older) were associated with higher odds of recent infection.ConclusionsCompared to previous studies among pregnant women, the incidence estimated in this study was substantially lower. However, the UNAIDS target to reduce incidence by 75% by 2020 (which is equivalent to reducing incidence to <1%) has not been met. The implementation of HIV prevention and treatment interventions should be intensified, targeting young women engaged in age-disparate relationship and unmarried women to fast track progress towards the UNAIDS target.
| S-EPMC8046194 | biostudies-literature
Project description:When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously-described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source's infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time-calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model-which make use of different information within a tree-suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.
| S-EPMC10515827 | biostudies-literature
Project description:When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source's infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model-which make use of different information within a tree-suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.
| S-EPMC10776241 | biostudies-literature