False-recent Rate Research Articles

Recent HIV infections and estimated HIV incidence among adolescents from key populations.

To identify recent HIV-1 infection and estimate HIV incidence among adolescent men who have sex with men (AMSM) and transgender women (ATGW) in Brazil. From January to December 2020, a cross-sectional analysis was conducted with baseline data from the PrEP1519 study, an HIV pre-exposure prophylaxis (PrEP) demonstration cohort in Brazil among sexually active AMSM/ATGW aged 15-19. For enrollment, participants were screened with a fourth-generation HIV rapid test. The recent infection testing algorithm (RITA) included a recency assay in blood specimens, viral load, and CD4 cell count prior to antiretroviral treatment use. Among these participants, RITA-based HIV incidence was estimated using a mean duration of recency infection of 214 days and a false-recent rate of 0.02. Out of the 494 participants screened, 21 tested positive for HIV. Following RITA, five adolescents had a recent HIV infection, 14 had long-term infections, and two did not have blood specimens available. We classified these two participants as long-term infection cases due to CD4 cell counts and previous use of antiretroviral treatment. Among those who tested positive, all but one were AMSM (94.7%), 73.6% were aged 18-19, and 76.2% were non-White. The HIV prevalence was 4.2%, and the estimated HIV incidence was 1.7%. The estimated incidence highlights the need for targeted HIV prevention interventions, such as PrEP, for sexual minority adolescents. Integrating RITA into routine HIV testing services for this population provides valuable information on the current HIV epidemic. This strategy can aid in monitoring the effectiveness of prevention efforts and improving early entry to HIV care.

Evaluation of multi-assay algorithms for cross-sectional HIV incidence estimation in settings with universal antiretroviral treatment

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.

Establishment of an anti-hepatitis C virus IgG avidity test for dried serum/plasma spots

Monitoring recency of infection helps to identify current transmission in vulnerable populations for effective disease control. We have established an in-house avidity based hepatitis C virus (HCV) recency assay based on the Monolisa Anti-HCV PLUS Version 3 ELISA kit for use of dried serum/plasma spots (DS/PS) in order to distinguish recent and long-term infections. A first panel of DS/PS (n = 218; genotype 1 n = 170 and non-genotype 1 n = 48) consisting of primary and at least one follow up sample was used to analyze the temporal changes of the Avidity Index (AI) over time. Sub-panels of longitudinal DS/PS (n = 66) and acute cases (<26 weeks; n = 34) were taken to calculate the Mean Duration of Recent Infection (MDRI) and the False Long-term Rate (FLTR), respectively. A second panel of DS/PS >104 weeks (n = 132) and a third panel of DS/PS prepared from resolved infections (≥180 days since last positive; n = 32) were used to calculate the False Recent Rate (FRR). For all genotypes, the optimal AI cut-off was determined to be 40% resulting in an MDRI of 364 days (95% CI: 223–485). FLTR was 5.9% (95% CI: 0.7–19.7), 8.3% (95% CI: 1–27), and 0% (−) and FRR was 13.6% (95% CI: 8.3–20.7), 11.7% (95% CI: 6.6–19), and 30.6% (95% CI: 9.1–61.4) for all genotypes, genotype 1, and non-genotype 1 infections, respectively. For resolved infections, the FRR was 53.1% (95% CI: 35.8–70.4). Thus, this assay performs particularly well for genotype 1 reaching a high rate of correct discriminations between infections acquired less than a year before diagnosis and those acquired earlier by applying an AI cut-off of 40%. Due to a rapid decline in avidity post resolution of an HCV infection this assay is not recommended to be used in HCV RNA negative patients.

Immunological markers for identifying recent HIV infection in North-West India.

Background & objectives:Being more efficient and widely used, limiting antigen (LAg)-avidity enzyme immunoassay (EIA) based on the recent infection testing algorithm (RITA) has been developed for differentiating recent and established HIV-1 infection. So far, LAg-avidity EIA has not been validated among the Indian population. Hence, the present study was planned to identify recent HIV infections in high risk patients in the North-West region of India using modified LAg-avidity RITA.Methods:Four hundred HIV-positive high risk patients registered on pre-antiretroviral therapy (ART) programme in the last one year, from five ART centres in North-Western States of India, were included for identifying the recent HIV infections. One hundred HIV-positive cases registered for pre-ART for greater than two years in ART centres were included for estimating false recent rate (FRR). Single-well LAg-avidity EIA-based modified RITA was used to identify recent HIV infection cases.Results:Of the 400 HIV-1-positive samples, 64 (16%) were found to have been infected within the past 130 days. The proportion of recent HIV infections was 16.8 per cent (18/107) among female sex workers, 10.7 per cent (9/84) among men who have sex with men and 17.7 per cent (37/209) among injecting drug users. The FRR was one per cent (1/100).Interpretation & conclusions:LAg-avidity EIA-based modified RITA provided good discrimination between recent and non-recent HIV infection, hence, it could be considered suitable for estimating HIV incidence in sentinel surveillance system in India.

Evaluation of an HIV recent infection testing algorithm with serological assays among men who have sex with men in Mexico

BackgroundHuman immunodeficiency virus (HIV) incidence should be calculated in cross-sectional studies using recent infection testing algorithms (RITA) that consider clinical variables and serological test results such as enzyme-linked immunosorbent assay (ELISA) and dried blood spot (DBS) analysis. MethodsThe correlation between serum samples and DBS was evaluated using two commercial ELISA kits: SediaTM BED HIV-1 Incidence EIA (BED-Sedia) and Maxim HIV-1 Limiting Antigen Avidity (LAg-Avidity). Eight different RITAs were developed; all of them included serological assays. A combination of the variables viral load, antiretroviral therapy (ART) and CD4 count was used to build the RITAs. The sensitivity, specificity, Youden index, predictive positive value, predictive negative value, false recent rate (FRR) and false long-term rate were evaluated. ResultsThe correlations between serum samples and DBS were 0.990 and 0.867 for BED-Sedia and LAg-avidity, respectively. Using only serological assays, the Youden index was higher for LAg-avidity than BED-Sedia (82.1–83.0% versus 69.2–69.6%). The best RITA was ART-serology, which showed a Youden index of 91.2–93.9% and FRR of 1.8–2.2%. ConclusionsUsing DBS samples to determine HIV incidence is a good tool for epidemiological surveillance. The RITA that included ART and serological tests (BED-Sedia or LAg-avidity) showed the highest sensitivity and specificity and a low FRR.

Evaluation of a BioRad Avidity assay for identification of recent HIV-1 infections using dried serum or plasma spots

Serological methods to differentiate between recently acquired and established HIV-1 infections are a useful tool in the HIV-surveillance to characterize the epidemic, identify groups at risk and assess HIV-preventive interventions. Therefore, an avidity-based, modified BioRad Genscreen™ HIV-1/2 assay (BRAEUR) was evaluated according to the avidity-based, modified BioRad HIV-1/2 Plus O protocol (BRAUSA). Overall, 692 well defined samples (82.5% B and 17.5% non-B subtypes) from recent (<180 days, n = 239), intermediate (181–364 days, n = 35) or long term infections (≥365 days, n = 419) were used to determine a ‘mean duration of recent infection’ (MDRI), a ‘median DRI’ (MdDRI), the false recent rate (FRR), and concordance between the BRAs and the Sedia BED HIV-1 Capture enzyme immunoassay (BED). The optimal avidity index cut-off was determined to be 70% resulting in an MDRI of 233 days (95% IQR: 174–351) and an MdDRI of 171 days (95% IQR: 142–212). Concordance with the BRAUSA was high with 96.4%. The FRR of 6.0% as well as the MdDRI are similar to the BED (8.4%; 170 (139–214) days). Therefore, the BRAEUR is a suitable alternative to replace the BED and trend analysis will be feasible after minimal adjustments for the MdDRI and the MDRI.

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.

Detection of IgG3 antibodies specific to the human immunodeficiency virus type 1 (HIV-1) p24 protein as marker for recently acquired infection.

Reducing the risk of human immunodeficiency virus type 1 (HIV-1) transmission is still a public health priority. The development of effective control strategies relies on the quantification of the effects of prophylactic and therapeutic measures in disease incidence. Although several assays can be used to estimate HIV incidence, these estimates are limited by the poor performance of these assays in distinguishing recent from long-standing infections. To address such limitation, we have developed an assay to titrate p24-specific IgG3 antibodies as a marker of recent infection. The assay is based on a recombinant p24 protein capable to detect total IgG antibodies in sera using a liquid micro array and enzyme-linked immunosorbent assay. Subsequently, the assay was optimised to detect and titrate anti-p24 IgG3 responses in a panel of sequential specimens from seroconverters over 24 months. The kinetics of p24-specific IgG3 titres revealed a transient peak in the 4 to 5-month period after seroconversion. It was followed by a sharp decline, allowing infections with less than 6 months to be distinguished from older ones. The developed assay exhibited a mean duration of recent infection of 144 days and a false-recent rate of ca. 14%. Our findings show that HIV-1 p24-specific IgG3 titres can be used as a tool to evaluate HIV incidence in serosurveys and to monitor the efficacy of vaccines and other transmission control strategies.

High avidity anti-integrase antibodies discriminate recent and non-recent HIV infection: Implications for HIV incidence assay

Estimation of HIV incidence provides real-time information of HIV transmission trends for decision makers. Anti-integrase antibodies are the last ones produced during seroconversion and presence of high-avidity anti-integrase antibodies indicates the chronicity of HIV infection. This study aimed to evaluate the performance of these antibodies in discriminating of recent from non-recent HIV infection. For this purpose, different ELISA formats were developed to detect high-avidity anti-integrase antibodies in a commercially available performance panel, and the best assay was selected for further evaluation. The false recent rate of the selected assay was evaluated in a panel of Iranian patients and compared to two commercial assays, BED-EIA and LAg-Avidity. While the false recent rate of the developed assay was 3.8%, it was 14.1% and 1.3% for BED-EIA and LAg-Avidity, respectively. To our knowledge, this is the first report to study the performance of high-avidity anti-integrase antibodies for classification of HIV infection. The preliminary results showed that the specificity of the newly developed assay is markedly higher than BED-EIA and is comparable with LAg-Avidity. The promising results point to the potential use of anti-integrase antibodies as a biomarker in HIV incidence laboratory tests or algorithms. The developed assay needs further evaluation in future.

Performance characteristics of an antibody-based multiplex kit for determining recent HIV-1 infection

The availability of reliable laboratory methods for determining recent HIV infection is vital for accurate estimation of population-based incidence. The mean duration of recent infection (MDRI) and false recent rate (FRR) are critical parameters for HIV incidence assays, as they impact HIV incidence estimates and provide a measure of assay performance. The HIV-1 Multiplex assay is an in-house developed, magnetic bead-based assay that measures virus-specific antibody levels and avidity to multiple analytes. To ensure quality control and to facilitate transfer of the assay to external laboratories or testing facilities, the in-house assay has been adapted and produced in kit form. Here, we describe the performance characteristics of the multiplex kit and demonstrate the stability of the kit components over a one-year period. Two statistical methods were employed to estimate the MDRI of the individual analytes and five different algorithms, combining multiple analyte values. The MDRI estimates for the individual analytes and five algorithms were all between 200 and 300 days post-seroconversion, with no notable difference between the two statistical approaches. All five algorithms exhibited a 0% FRR with specimens from long-term, subtype B HIV-1-infected individuals. The assay parameters described in this study provide the necessary tools to implement the HIV-1 multiplex assay and improves the utility of the assay for field use.

Short Communication: Low False Recent Rate of Limiting Antigen-Avidity Assay Combined with HIV-1 RNA Data in Botswana.

Cross-sectional estimation of HIV incidence could misclassify some established or chronic HIV infections as recent. Usually long-term nonprogressors, elite and viremic controllers, and individuals on ART contribute to misclassification. Local data on the false recent rate (FRR) could minimize misclassification during estimation of HIV incidence. To improve monitoring of HIV incidence, we estimated local FRR in Botswana. A total of 1,036 specimens from individuals infected for at least 1.5-2 years were sampled between 2004 and 2009 and tested using the limiting antigen (LAg)-avidity assay using a cutoff of 1.5 normalized optical density units. The FRR was 0.97% (10/1,036; 95% confidence interval [CI] 0.46-1.77). Four samples had HIV-1 RNA >1,000 cps/ml, giving an adjusted FRR of 0.39% (4/1,036; 95% CI 0.11-0.99). A combination of LAg and HIV-1 RNA load data resulted in FRR below 1% in the Botswana population.

Development and Evaluation of a Modified Fourth-Generation Human Immunodeficiency Virus Enzyme Immunoassay for Cross-Sectional Incidence Estimation in Clade B Populations.

Accurate methods for cross-sectional incidence estimation are needed for HIV surveillance and prevention research. We developed an avidity assay based on the fourth-generation Genetic Systems HIV Combo Ag/Ab EIA (Bio-Rad Combo assay) and evaluated its performance. The Bio-Rad Combo assay was modified incubating samples with and without 0.025 M diethylamine (DEA). The avidity index (AI) was calculated as the ratio of the DEA-treated to untreated result for a specific sample. We analyzed 2,140 samples from 808 individuals from the United States with known duration of HIV infection. The mean duration of recent infection (MDRI) and the false-recent rate (FRR, fraction of samples from individuals known to be infected >2 years misclassified as recent) were calculated for AI cutoffs of 20%-90% for the avidity assay alone and in combination with a viral load assay (VL, limit of detection 400 copies/ml). Factors associated with misclassification of samples collected ≥2 years after infections were also evaluated. The MDRI for the Bio-Rad Combo Avidity assay ranged from 50 days using an AI cutoff of 20% to 276 days using an AI cutoff of 90%; the FRR ranged from 0% to 9%. When samples with a VL <400 copies/ml were classified as nonrecent, the FRRs were reduced approximately twofold and the MDRI estimates were reduced by ∼20%. An AI cutoff of 50% provided an MDRI of 135 days with an FRR of 2.1%. All samples from elite suppressors had an AI >80%. In adjusted analysis, viral suppression and low CD4 cell count were significantly associated with misclassification among individuals infected >2 years. This modified Bio-Rad Combo Avidity assay may be a useful tool for cross-sectional HIV incidence estimation. Further research is needed to evaluate use of this assay in combination with other assays to accurately estimate population-level HIV incidence.

Short Communication: Low False Recent Rate of Limiting-Antigen Avidity Assay Among Long-Term Infected Subjects from Guangxi, China.

Assays used for HIV cross-sectional incidence testing can misclassify some individuals with nonrecent HIV infection as recently infected, overestimating HIV incidence. We analyzed the frequency and factors associated with false-recent misclassification on subjects from Quangxi, China known to have long-term infection using the limited antigen-avidity assay (LAg-Avidity). Stored samples from treatment-naive individuals from Guangxi, China were tested using the LAg-Avidity. A total of 362 samples from individuals known to be infected 2 to 13.5 years were tested and the false-recent rate (FRR), the frequency of samples with a positive result, was determined at different cutoff values of the assay. Additionally, factors associated with misclassification were determined. The FRR of the LAg-Avidity was 1.1% (4/362) using a cutoff of 1.5 normalized optical density units (OD-n). All four samples had viral loads >1,000 copies/ml. Using a cutoff of 3.0 OD-n the FRR was 5.5% (20/362), with four samples having viral loads <1,000 copies/ml. Factors associated with a higher odds of misclassification were female gender (OR 7.7, 95% CI 1.0-56.4) and being a female sex worker (OR 31.3, 95% CI 4.0-242). At the higher cutoff, being of Zhuang decent, relative to Han, had higher odds of misclassification (OR 6.2, 95% CI 1.99-19.0). The LAg-Avidity assay had a low FRR in this Chinese population. Further investigations of the higher frequency of low LAg-Avidity results seen in female sex workers and individuals of Zhuang descent should be explored in a larger study.

Incorporating incidence information within the UNAIDS Estimation and Projection Package framework: a study based on simulated incidence assay data.

Objectives:The objective of this study is to extend the UNAIDS incidence estimation model, the UNAIDS Estimation and Projection Package (EPP), so that it can incorporate data from incidence assays.Methods:We propose combining the likelihood of the incidence assay data with the likelihood of other data, in a manner that is consistent with the biomarker-based incidence estimator using incidence assay data. Two calibrating parameters specify the performance of the incidence assays: the false recent rate and the mean duration of recent infection. We then use synthetic data, based on prevalence data obtained from antenatal clinic surveillances, and in some cases household surveys, from 24 countries, to examine the impact of including incidence assay data, under circumstances wherein the incidence assay data imply the same or a different incidence rate as that inferred from the prevalence data alone, and wherein incorrect calibrating parameters for the incidence assay data are used.Results:Using incidence assay data, in addition to prevalence data, can improve estimate by narrowing uncertainty intervals in derived HIV incidence estimates, and by providing information on levels or trends in incidence that were not apparent in the prevalence data alone. However, the effect is relatively modest if the sample size of the incidence assay survey is small and results can be biased if the calibrating parameters for the incidence assay data are not known accurately.Conclusion:Incorporating information from incidence assays in the manner proposed has the potential to improve estimates. Further work will examine in more detail the circumstances under which the contribution of incidence assay data would be most valuable.

Short Communication: Defining Optimality of a Test for Recent Infection for HIV Incidence Surveillance

The estimation of HIV incidence from cross-sectional surveys using tests for recent infection has attracted much interest. It is increasingly recognized that the lack of high performance recent infection tests is hindering the implementation of this surveillance approach. With growing funding opportunities, test developers are currently trying to fill this gap. However, there is a lack of consensus and clear guidance for developers on the evaluation and optimization of candidate tests. A fundamental shift from conventional thinking about test performance is needed: away from metrics relevant in typical public health settings where the detection of a condition in individuals is of primary interest (sensitivity, specificity, and predictive values) and toward metrics that are appropriate when estimating a population-level parameter such as incidence (accuracy and precision). The inappropriate use of individual-level diagnostics performance measures could lead to spurious assessments and suboptimal designs of tests for incidence estimation. In some contexts, such as population-level application to HIV incidence, bias of estimates is essentially negligible, and all that remains is the maximization of precision. The maximization of the precision of incidence estimates provides a completely general criterion for test developers to assess and optimize test designs. Summarizing the test dynamics into the properties relevant for incidence estimation, high precision estimates are obtained when (1) the mean duration of recent infection is large, and (2) the false-recent rate is small. The optimal trade-off between these two test properties will produce the highest precision, and therefore the most epidemiologically useful incidence estimates.

Evaluation of the False Recent Classification Rates of Multiassay Algorithms in Estimating HIV Type 1 Subtype C Incidence

Laboratory cross-sectional assays are useful for the estimation of HIV incidence, but are known to misclassify individuals with long-standing infection as recently infected. The false recent rate (FRR) varies widely across geographic areas; therefore, accurate estimates of HIV incidence require a locally defined FRR. We determined FRR for Botswana, where HIV-1 subtype C infection is predominant, using the BED capture enzyme immunoassay (BED), a Bio-Rad Avidity Index (BAI) assay (a modification of the Bio-Rad HIV1/2+O EIA), and two multiassay algorithms (MAA) that included clinical data. To estimate FRR, stored blood samples from 512 antiretroviral (ARV)-naive HIV-1 subtype C-infected individuals from a prospective cohort in Botswana were tested at 18-24 months postenrollment. The following FRR mean (95% CI) values were obtained: BED 6.05% (4.15-8.48), BAI 5.57% (3.70-8.0), BED-BAI 2.25% (1.13-4.0), and a combination of BED-BAI with CD4 (>200) and viral load (>400) threshold 1.43% (0.58-2.93). The interassay agreement between BED and BAI was 92.8% (95% CI, 90.1-94.5) for recent/long-term classification. Misclassification was associated with viral suppression for BED [adjusted OR (aOR) 10.31; p=0.008], BAI [aOR 9.72; p=0.019], and MAA1 [aOR 16.6; p=0.006]. Employing MAA can reduce FRR to <2%. A local FRR can improve cross-sectional HIV incidence estimates.

HIV Prevalence and Incidence Among Women at Higher Risk of Infection in Addis Ababa, Ethiopia

This study aimed to estimate HIV incidence among women at higher HIV risk in Addis Ababa, Ethiopia using cross-sectional data. To refine the estimate, we sought to determine a local correction factor by estimating a false recent rate for the BED assay. The overall study had two parallel phases: cross-sectional incidence and BED false recent (BED FR). A total of 1856 women at higher HIV risk were enrolled into the cross-sectional phase. For the BED FR, 500 women and 70 men with known HIV infection of greater than 12 months were enrolled. Rapid HIV tests were used to assess participant HIV status. Samples from women with positive results on HIV rapid testing were then analyzed using the BED assay to determine incident HIV infections. The overall HIV prevalence was 11.3%, with women greater than 25 years old having a higher prevalence (26.5% vs. 7.9% for younger women). The overall unadjusted HIV incidence was 3.3%. The estimated HIV incidence was 2.6% when adjusted using the locally derived false recent rate of 3.5%. Similar incidence rates were found between the younger and older age groups. This is one of the first field-based studies of HIV incidence in Ethiopia; it demonstrates that there is sufficient incidence to warrant further HIV prevention efforts among women at higher risk of HIV infection.

HIV Incidence Determination in the United States: A Multiassay Approach

Accurate testing algorithms are needed for estimating human immunodeficiency virus (HIV) incidence from cross-sectional surveys. We developed a multiassay algorithm (MAA) for HIV incidence that includes the BED capture enzyme immunoassay (BED-CEIA), an antibody avidity assay, HIV load, and CD4(+) T-cell count. We analyzed 1782 samples from 709 individuals in the United States who had a known duration of HIV infection (range, 0 to >8 years). Logistic regression with cubic splines was used to compare the performance of the MAA to the BED-CEIA and to determine the window period of the MAA. We compared the annual incidence estimated with the MAA to the annual incidence based on HIV seroconversion in a longitudinal cohort. The MAA had a window period of 141 days (95% confidence interval [CI], 94-150) and a very low false-recent misclassification rate (only 0.4% of 1474 samples from subjects infected for >1 year were misclassified as indicative of recent infection). In a cohort study, annual incidence based on HIV seroconversion was 1.04% (95% CI, .70%-1.55%). The incidence estimate obtained using the MAA was essentially identical: 0.97% (95% CI, .51%-1.71%). The MAA is as sensitive for detecting recent HIV infection as the BED-CEIA and has a very low rate of false-recent misclassification. It provides a powerful tool for cross-sectional HIV incidence determination.

Lower-Sensitivity and Avidity Modifications of the Vitros Anti-HIV 1+2 Assay for Detection of Recent HIV Infections and Incidence Estimation

Recent-infection testing assays/algorithms (RITAs) have been developed to exploit the titer and avidity of HIV antibody evolution following seroconversion for incidence estimation. The Vitros Anti-HIV 1+2 assay (Ortho-Clinical Diagnostics) was approved by the FDA to detect HIV-1 and HIV-2 infections. We developed a less-sensitive (LS) and an avidity-modified version of this assay to detect recent HIV infection. Seroconversion panels (80 subjects, 416 samples) were tested to calculate the mean duration of recent infection (MDR) for these assays. A panel from known long-term (2+ years) HIV-infected subjects on highly active antiretroviral therapy (HAART) (n = 134) and subjects with low CD4 counts (AIDS patients [n = 140]) was used to measure the false-recent rate (FRR) of the assays. Using a signal-to-cutoff ratio of 20 and the LS-Vitros assay gave a RITA MDR of 215 days (95% confidence interval [95% CI], ± 65 days) and using an avidity index (AI) of 0.6 gave an MDR of 170 days (± 44 days), while a combination of the two assays yielded a MDR of 146 days (± 38.6) and an FRR of 8%. Misclassifying subjects with known long-term infection as recently infected occurred in 14% of AIDS patients and 29% (95% CI, 22, 38) of HAART subjects and 3% (95% CI, 0.8, 7.2) and 42% (95% CI, 33, 51), respectively, for the LS- and avidity-modified Vitros assays, with a misclassification rate of 15% (95% CI, 11, 20) overall using a dual-assay algorithm. Both modified Vitros assays can be used to estimate the length of time since seroconversion and in calculations for HIV incidence. Like other RITAs, they are subject to high FRR in subjects on HAART or with AIDS.

A New General Biomarker-based Incidence Estimator

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. 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. 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. 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.