A new general biomarker-based incidence estimator

HIV incidence in US first-time blood donors during 12 and 3 month deferral policy periods between 2015 and 2023 before implementation of individual donor assessment

BACKGROUND

Following FDA guidance, US blood collectors changed donor deferral for men who have sex with men (MSM) from indefinite to a 12 month deferral in 2016 (12 m), and for MSM and several other exposure risks to 3 month deferrals in 2020 (3 m). We evaluated first-time donor (FTD) HIV incidence and demographics during these periods.

STUDY DESIGN AND METHODS

We estimated cross-sectional HIV incidence and incidence rate differences in FTD based on routine donation nucleic acid testing (NAT) and serology with additional limiting antigen (LAg)-Avidity immunoassay and viral load testing. We estimated incidence in the two policy periods (12 and 3 m), incidence trends in two-year intervals between 2015 and 2023, and used multivariable Poisson regression to assess demographic correlates of incident infection.

RESULTS

HIV incidence in FTD during the 12 m deferral period was 2.82 infections/105 person-years (PY) [95% CI: 2.12, 3.67] and during the 3 m deferral period, it was 1.88/105 PY (95% CI: 1.18, 2.67), a statistically significant decline (p < .05). Over the period 2015-2023, incidence was stable. Male sex, younger age, Black or African American race, Hispanic ethnicity, and residence in the South were associated with incident infection in regression analysis, but the time-based deferral policy periods were not.

DISCUSSION

HIV incidence in FTD did not increase between 2015 and 2023. An overall decline in HIV incidence in the 3 m deferral period compared with the 12 m deferral period was evident. These results provide no indication of an increased residual risk of transfusion-transmitted HIV from FTD in the United States with the reduced deferral periods.

Recent infection testing to inform HIV prevention responses and surveillance in a programme context: lessons from implementation within a nationally scaled female sex worker programme in Zimbabwe

INTRODUCTION

In the context of key population HIV testing programmes, identifying new HIV acquisitions, tracking incidence, and responding with prevention and treatment interventions will be critical for achieving HIV epidemic control. Laboratory tests for recently acquired HIV used as part of a "recent infection testing algorithm" (RITA), offer a potential tool to support this work. We implemented a RITA for female sex workers (FSWs) in Zimbabwe to explore opportunities and programmatic benefits.

METHODS

Between October 2021 and January 2023, recency testing was offered to FSWs attending the Centre for Sexual Health and HIV/AIDS Research (CeSHHAR) Zimbabwe's key populations programme. Dried blood spot (DBS) samples were taken at 86 clinic sites across 10 provinces and Laboratory LAg Avidity and viral load testing conducted. RITA results were analysed and linked to programme data to explore geographical differences and calculate HIV incidence. We describe concurrent efforts in HIV testing for social (social network testing [SNT]) and sexual (index case testing [ICT]) contacts of those testing HIV positive.

RESULTS

Among 24,976 FSWs tested at programme sites, 9.5% (2363/24,976) were confirmed HIV positive. We enrolled 55.5% (1311/2363) of eligible HIV-positive FSWs to our study, of whom 11.7% (153/1311) were identified as having recently acquired HIV. It took a median of 37 days (IQR 20-67) for samples to be processed. Enrolment rates varied between provinces but the proportion of recently acquired HIV was similar (range: 18.4% to 4.0%). Overall HIV incidence was 3.4 (95% CI 2.7-4.0) per 100py. Where results could be linked to routinely collected data, we found no evidence of a difference in test-positivity between the ICT and SNT contacts of those with recently acquired compared to those with long-term HIV.

CONCLUSIONS

Implementation of a RITA was possible within a nationally scaled sex worker programme, and while challenging to implement, can provide an understanding of transmission dynamics and HIV incidence in this context. Sub-optimal recruitment and data linkage limited the interpretation of our findings and opportunities for strategic gains though focusing on HIV prevention efforts.

A Human Immunodeficiency Virus Type 1 Risk Assessment Tool for Women Aged 15-49 Years in African Countries: A Pooled Analysis Across 15 Nationally Representative Surveys

BACKGROUND

Women in Africa disproportionately acquire human immunodeficiency virus type 1 (HIV-1). Understanding which women are most likely to acquire HIV-1 can guide focused prevention with preexposure prophylaxis (PrEP). Our objective was to identify women at the highest risk of HIV-1 and estimate PrEP efficiency at different sensitivity levels.

METHODS

Nationally representative data were collected from 2015 through 2019 from 15 population-based household surveys. This analysis included women aged 15-49 who tested HIV-1 seronegative or had recent HIV-1. Least absolute shrinkage and selection operator regression models were fit with 28 variables to predict recent HIV-1. Models were trained on the full population and internally cross-validated. Performance was evaluated using area under the receiver operating characteristic curve (AUC), sensitivity, and number needed to treat (NNT) with PrEP to avert 1 infection.

RESULTS

Among 209 012 participants, 248 had recent HIV-1 infection, representing 118 million women and 402 000 (95% confidence interval [CI], 309 000-495 000) annual infections. Two variables were retained: living in a subnational area with high HIV-1 viremia and having a sexual partner living outside the home. The full-population AUC was 0.80 (95% CI, .76-.84); cross-validated AUC was 0.79 (95% CI, .75-.84). At 33% sensitivity, 130 000 cases could be averted if 7.9 million women were perfectly adherent to PrEP; NNT would be 61. At 67% sensitivity, 260 000 cases could be averted if 25.1 million women were perfectly adherent; NNT would be 96.

CONCLUSIONS

This risk assessment tool was generalizable, predictive, and parsimonious with trade-offs between reach and efficiency.

A likelihood approach to incorporating self-report data in HIV recency classification

Estimating new HIV infections is significant yet challenging due to the difficulty in distinguishing between recent and long-term infections. We demonstrate that HIV recency status (recent versus long-term) could be determined from self-report testing history and biomarkers, which are increasingly available in bio-behavioral surveys. HIV recency status is partially observed, given the self-report testing history. For example, people who tested positive for HIV over 1 year ago should have a long-term infection. Based on the nationally representative samples collected by the Population-based HIV Impact Assessment (PHIA) Project, we propose a likelihood-based probabilistic model for HIV recency classification. The model incorporates individuals with known recency status based on testing histories and individuals whose recency status could not be determined and integrates the mechanism of how HIV recency status depends on biomarkers and the mechanism of how HIV recency status, together with the self-report time of the most recent HIV test, impacts the test results. We compare our method to logistic regression and the binary classification tree (current practice) on Malawi PHIA data, as well as on simulated data. Our model obtains more efficient and less biased parameter estimates and is relatively robust to potential reporting error and model misspecification.

A Statistical Model for Inference of Recent and Incident HIV Infection Using Surveillance Data on Individuals Newly Diagnosed With HIV Infection in Scotland

BACKGROUND

To inform global ambitions to end AIDS, evaluation of progress toward HIV incidence reduction requires robust methods to measure incidence. Although HIV diagnosis date in routine HIV/AIDS surveillance systems are often used as a surrogate marker for incidence, it can be misleading if acquisition of transmission occurred years before testing. Other information present in data such as antibody testing dates, avidity testing result, and CD4 counts can assist, but the degree of missing data is often prohibitive.

METHODS

We constructed a Bayesian statistical model to estimate the annual proportion of first ever HIV diagnoses in Scotland (period 2015-2019) that represent recent HIV infection (ie, occurring within the previous 3-4 months) and incident HIV infection (ie, infection within the previous 12 months), by synthesizing avidity testing results and surveillance data on the interval since last negative HIV test.

RESULTS

Over the 5-year analysis period, the model-estimated proportion of incident infection was 43.9% (95% CI: 40.9 to 47.0), and the proportion of recent HIV infection was 21.6% (95% CI: 19.1 to 24.1). Among the mode of HIV acquisition categories, the highest proportion of recent infection was estimated for people who inject drugs: 27.4% (95% CI: 20.4 to 34.4).

CONCLUSIONS

The Bayesian approach is appropriate for the high prevalence of missing data that can occur in routine surveillance data sets. The proposed model will aid countries in improving their understanding of the number of people who have recently acquired their infection, which is needed to progress toward the goal of HIV transmission elimination.

An enhanced cross-sectional HIV incidence estimator that incorporates prior HIV test results

Incidence estimation of HIV infection can be performed using recent infection testing algorithm (RITA) results from a cross-sectional sample. This allows practitioners to understand population trends in the HIV epidemic without having to perform longitudinal follow-up on a cohort of individuals. The utility of the approach is limited by its precision, driven by the (low) sensitivity of the RITA at identifying recent infection. By utilizing results of previous HIV tests that individuals may have taken, we consider an enhanced RITA with increased sensitivity (and specificity). We use it to propose an enhanced estimator for incidence estimation. We prove the theoretical properties of the enhanced estimator and illustrate its numerical performance in simulation studies. We apply the estimator to data from a cluster-randomized trial to study the effect of community-level HIV interventions on HIV incidence. We demonstrate that the enhanced estimator provides a more precise estimate of HIV incidence compared to the standard estimator.

Association Between Early Sexual Debut and New HIV Infections Among Adolescents and Young Adults in 11 African Countries

We investigated the association between early sexual debut and HIV infection among adolescents and young adults. Analyzing data from nationally representative Population-Based HIV Impact Assessment (PHIA) surveys in 11 African countries, the research employed a multivariate logistic regression model to assess the relationship between the early sexual debut and new HIV infections in the age group of 10-24 years. The results revealed a significant and robust association, indicating that young individuals who experienced early sexual debut were approximately 2.65 times more likely to contract HIV than those who did not, even after accounting for other variables. These findings align with prior research suggesting that early initiation of sexual activity may increase vulnerability to HIV infection due to factors such as biological susceptibility and risky behaviors like low condom use and multiple sexual partners. The implications of these findings for HIV prevention strategies are substantial, suggesting that interventions aimed at delaying sexual debut could be an effective component in reducing HIV risk for this population. Targeted sex education programs that address the risks of early sexual debut may play a pivotal role in these prevention efforts. By employing a comprehensive approach, there is a possibility to advance efforts towards ending AIDS by 2030.

The impact of non-disclosure of HIV status and antiretroviral therapy on HIV recency testing and incidence algorithms

BACKGROUND AND OBJECTIVES

Accurate HIV incidence estimates among blood donors are necessary to assess the effectiveness of programs aimed at limiting transfusion-transmitted HIV. We assessed the impact of undisclosed HIV status and antiretroviral (ARV) use on HIV recency and incidence estimates using increasingly comprehensive recent infection testing algorithms.

MATERIALS AND METHODS

Using 2017 donation data from first-time and lapsed donors, we populated four HIV recency algorithms: (1) serology and limiting-antigen avidity testing, (2) with individual donation nucleic amplification testing (ID-NAT) added to Algorithm 1, (3) with viral load added to Algorithm 2 and (4) with ARV testing added to Algorithm 3. Algorithm-specific mean durations of recent infection (MDRI) and false recency rates (FRR) were calculated and used to derive and compare incidence estimates.

RESULTS

Compared with Algorithm 4, progressive algorithms misclassified fewer donors as recent: Algorithm 1: 61 (12.1%); Algorithm 2: 14 (2.8%) and Algorithm 3: 3 (0.6%). Algorithm-specific MDRI and FRR values resulted in marginally lower incidence estimates: Algorithm 1: 0.19% per annum (p.a.) (95% confidence interval [CI]: 0.13%-0.26%); Algorithm 2: 0.18% p.a. (95% CI: 0.13%-0.22%); Algorithm 3: 0.17% p.a. (95% CI: 0.13%-0.22%) and Algorithm 4: 0.17% p.a. (95% CI: 0.13%-0.21%).

CONCLUSION

We confirmed significant misclassification of recent HIV cases when not including viral load and ARV testing. Context-specific MDRI and FRR resulted in progressively lower incidence estimates but did not fully account for the context-specific variability in incidence modelling. The inclusion of ARV testing, in addition to viral load and ID-NAT testing, did not have a significant impact on incidence estimates.

Comparison of HIV prevalence, incidence, and viral load suppression in Zambia population-based HIV impact assessments from 2016 and 2021

BACKGROUND

The Zambian government has implemented a public health response to control the HIV epidemic in the country. Zambia conducted a population-based HIV impact assessment (ZAMPHIA) survey in 2021 to assess the status of the HIV epidemic to guide its public health programs.

METHODS

ZAMPHIA 2021 was a cross-sectional two-stage cluster sample household survey among persons aged ≥15 years conducted in Zambia across all 10 provinces. Consenting participants were administered a standardized questionnaire and whole blood was tested for HIV according to national guidelines. HIV-1 viral load (VL), recent HIV infection, and antiretroviral medications were tested for in HIV-seropositive samples. Viral load suppression (VLS) was defined as <1000 copies/ml. ZAMPHIA 2021 results were compared to ZAMPHIA 2016 for persons aged 15-59 years (i.e., the overlapping age ranges). All estimates were weighted to account for nonresponse and survey design.

RESULTS

During ZAMPHIA 2021, of 25 483 eligible persons aged ≥15 years, 18 804 (73.8%) were interviewed and tested for HIV. HIV prevalence was 11.0% and VLS prevalence was 86.2% overall, but was <80% among people living with HIV aged 15-24 years and in certain provinces. Among persons aged 15-59 years, from 2016 to 2021, HIV incidence declined from 0.6% to 0.3% ( P -value: 0.07) and VLS prevalence increased from 59.2% to 85.7% ( P -value: <0.01).

DISCUSSION

Zambia has made substantial progress toward controlling the HIV epidemic from 2016 to 2021. Continued implementation of a test-and-treat strategy, with attention to groups with lower VLS in the ZAMPHIA 2021, could support reductions in HIV incidence and improve overall VLS in Zambia.

Evidence of HIV incidence reduction in young women, but not in adolescent girls, in KwaZulu-Natal, South Africa

Objectives

We estimated changes in the HIV incidence from 2013-2018 in Eshowe/Mbongolwane, KwaZulu-Natal, South Africa where Médecins Sans Frontières is engaged in providing HIV testing and care since 2011.

Methods

Using data from two cross-sectional household-based surveys conducted in 2013 and 2018, with consenting participants aged 15-59 years, we applied the incidence estimation frameworks of Mahiane et al and Kassanjee et al.

Results

In total, 5599 (62.4% women) and 3276 (65.9% women) individuals were included in 2013 and 2018, respectively. We found a mean incidence in women aged 20-29 years of 2.71 cases per 100 person-years (95% confidence interval [CI]: 1.23;4.19) in 2013 and 0.4 cases per 100 person-years (95% CI: 0.0;1.5) in 2018. The incidence in men aged 20-29 years was 1.91 cases per 100 person-years (95% CI: 0.87; 2.93) in 2013 and 0.53 cases per 100 person-years (95% CI: 0.0; 1.4) in 2018. The incidence decline among women aged 15-19 was -0.34 cases per 100 person-years (95% CI: -1.31;0.64).

Conclusions

The lack of evidence of incidence decline among adolescent girls is noteworthy and disconcerting. Our findings suggest that large-scale surveys should seriously consider focusing their resources on the core group of women aged 15-19 years.

Facilitating Next-Generation Pre-Exposure Prophylaxis Clinical Trials Using HIV Recent Infection Assays: A Consensus Statement from the Forum HIV Prevention Trial Design Project

Standard-of-care HIV pre-exposure prophylaxis (PrEP) is highly efficacious, but uptake of and persistence on a daily oral pill is low in many settings. Evaluation of alternate PrEP products will require innovation to avoid the unpractically large sample sizes in noninferiority trials. We propose estimating HIV incidence in people not on PrEP as an external counterfactual to which on-PrEP incidence in trial subjects can be compared. HIV recent infection testing algorithms (RITAs), such as the limiting antigen avidity assay plus viral load used on specimens from untreated HIV positive people identified during screening, is one possible approach. Its feasibility is partly dependent on the sample size needed to ensure adequate power, which is impacted by RITA performance, the number of recent infections identified, the expected efficacy of the intervention, and other factors. Screening sample sizes to support detection of an 80% reduction in incidence for 3 key populations are more modest, and comparable to the number of participants in recent phase III PrEP trials. Sample sizes would be significantly larger in populations with lower incidence, where the false recency rate is higher or if PrEP efficacy is expected to be lower. Our proposed counterfactual approach appears to be feasible, offers high statistical power, and is nearly contemporaneous with the on-PrEP population. It will be important to monitor the performance of this approach during new product development for HIV prevention. If successful, it could be a model for preventive HIV vaccines and prevention of other infectious diseases.

Improving Biomarker-based HIV Incidence Estimation in the Treatment Era

BACKGROUND

Estimating HIV-1 incidence using biomarker assays in cross-sectional surveys is important for understanding the HIV pandemic. However, the utility of these estimates has been limited by uncertainty about what input parameters to use for false recency rate (FRR) and mean duration of recent infection (MDRI) after applying a recent infection testing algorithm (RITA).

METHODS

This article shows how testing and diagnosis reduce both FRR and mean duration of recent infection compared to a treatment-naive population. A new method is proposed for calculating appropriate context-specific estimates of FRR and mean duration of recent infection. The result of this is a new formula for incidence that depends only on reference FRR and mean duration of recent infection parameters derived in an undiagnosed, treatment-naive, nonelite controller, non-AIDS-progressed population.

RESULTS

Applying the methodology to eleven cross-sectional surveys in Africa results in good agreement with previous incidence estimates, except in 2 countries with very high reported testing rates.

CONCLUSIONS

Incidence estimation equations can be adapted to account for the dynamics of treatment and recent infection testing algorithms. This provides a rigorous mathematical foundation for the application of HIV recency assays in cross-sectional surveys.

Estimation of HIV-1 Incidence Using a Testing History-Based Method; Analysis From the Population-Based HIV Impact Assessment Survey Data in 12 African Countries

BACKGROUND

Estimating HIV incidence is essential to monitoring progress in sub-Saharan African nations toward global epidemic control. One method for incidence estimation is to test nationally representative samples using laboratory-based incidence assays. An alternative method based on reported HIV testing history and the proportion of undiagnosed infections has recently been described.

METHODS

We applied an HIV incidence estimation method which uses history of testing to nationally representative cross-sectional survey data from 12 sub-Saharan African nations with varying country-specific HIV prevalence. We compared these estimates with those derived from laboratory-based incidence assays. Participants were tested for HIV using the national rapid test algorithm and asked about prior HIV testing, date and result of their most recent test, and date of antiretroviral therapy initiation.

RESULTS

The testing history-based method consistently produced results that are comparable and strongly correlated with estimates produced using a laboratory-based HIV incidence assay (ρ = 0.85). The testing history-based method produced incidence estimates that were more precise compared with the biomarker-based method. The testing history-based method identified sex-, age-, and geographic location-specific differences in incidence that were not detected using the biomarker-based method.

CONCLUSIONS

The testing history-based method estimates are more precise and can produce age-specific and sex-specific incidence estimates that are informative for programmatic decisions. The method also allows for comparisons of the HIV transmission rate and other components of HIV incidence among and within countries. The testing history-based method is a useful tool for estimating and validating HIV incidence from cross-sectional survey data.

Adult HIV-1 incidence across 15 high-burden countries in sub-Saharan Africa from 2015 to 2019: a pooled analysis of nationally representative data

BACKGROUND

Harmonised population-based surveys with recent HIV-1 infection testing algorithms permit pooled cross-sectional estimation of HIV incidence across multiple countries. We aimed to estimate adult HIV-1 incidence rates and number of new infections by sex, age, and subregion in sub-Saharan Africa.

METHODS

We analysed data from 13 Population-Based HIV Impact Assessment (PHIA) surveys and two additional population-based surveys done between 2015 and 2019 in 15 sub-Saharan African countries. HIV-seropositive samples from adults aged 15-59 years were tested for recent HIV-1 infection by use of an algorithm consisting of the HIV-1 limiting antigen avidity enzyme immunoassay, HIV-1 viral load, and qualitative detection of antiretroviral agents. Data were pooled across countries; sampling weights were incorporated to represent all adults in the 15 national populations. Analyses accounted for the complex sample designs. HIV incidence rates, incidence rate differences, and number of new annual infections were estimated.

FINDINGS

Among 445 979 adults sampled, 382 had recent HIV-1 infection. The estimated HIV-1 incidence rate was 3·3 per 1000 person-years (95% CI 2·6-4·0) among women and 2·0 per 1000 person-years (1·2-2·7) among men (incidence rate difference 1·3 per 1000 person-years, 95% CI 0·3-2·3). Among adults aged 15-24 years, the incidence rate was higher for women (3·5 per 1000 person-years) than men (1·2 per 1000 person-years; difference 2·3, 95% CI 0·8-3·8), but infection rates were similar between sexes in all other age groups. The HIV-1 incidence rate was 7·4 per 1000 person-years (95% CI 5·0-9·7) in southern sub-Saharan Africa, 2·3 per 1000 person-years (1·7-2·9) in the eastern subregion, and 0·9 per 1000 person-years (0·6-1·2) in the western and central subregion. 689 000 (95% CI 546 000-833 000) new HIV cases were estimated annually among the 265 million susceptible adults (61·6% in women).

INTERPRETATION

HIV-1 incidence and number of new infections differed by age, sex, and subregion. Approaches for risk stratification are needed to guide comprehensive HIV-1 prevention.

FUNDING

National Institutes of Health.

Probabilistic HIV recency classification-a logistic regression without labeled individual level training data

Accurate HIV incidence estimation based on individual recent infection status (recent vs long-term infection) is important for monitoring the epidemic, targeting interventions to those at greatest risk of new infection, and evaluating existing programs of prevention and treatment. Starting from 2015, the Population-based HIV Impact Assessment (PHIA) individual-level surveys are implemented in the most-affected countries in sub-Saharan Africa. PHIA is a nationally-representative HIV-focused survey that combines household visits with key questions and cutting-edge technologies such as biomarker tests for HIV antibody and HIV viral load which offer the unique opportunity of distinguishing between recent infection and long-term infection, and providing relevant HIV information by age, gender, and location. In this article, we propose a semi-supervised logistic regression model for estimating individual level HIV recency status. It incorporates information from multiple data sources - the PHIA survey where the true HIV recency status is unknown, and the cohort studies provided in the literature where the relationship between HIV recency status and the covariates are presented in the form of a contingency table. It also utilizes the national level HIV incidence estimates from the epidemiology model. Applying the proposed model to Malawi PHIA data, we demonstrate that our approach is more accurate for the individual level estimation and more appropriate for estimating HIV recency rates at aggregated levels than the current practice - the binary classification tree (BCT).

HIV Incidence, Recent HIV Infection, and Associated Factors, Kenya, 2007-2018

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.

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

BACKGROUND

Multi-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.

METHODS

Samples 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).

RESULTS

The 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.

CONCLUSIONS

The 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.

HIV incidence estimation among female sex workers in South Africa: a multiple methods analysis of cross-sectional survey data

BACKGROUND

Although numerous studies have investigated HIV risk factors and shown high HIV prevalence among female sex workers in South Africa, no national HIV incidence estimate exists for this potentially important group for HIV transmission. We aimed to estimate HIV incidence among female sex workers in South Africa who could be accessed through sex worker programmes, and to refine and describe the methods that enabled analysis.

METHODS

This study was embedded in a cross-sectional national survey of female sex workers who were linked to sex worker programmes. We aimed to enrol 3000 female sex workers aged at least 18 years who had sold or transacted in sex in the preceding 6 months in 12 randomly selected districts of the 22 districts with sex worker programmes, ensuring coverage of all provinces of South Africa. Women who self-reported as current victims of human trafficking were excluded from enrolment. We used a multistep process to sample districts and then hotspots, and a chain referral method to recruit participants. We collected cross-sectional data for self-reported HIV status, demographic characteristics, and exposure to violence. Two rapid tests were used to ascertain diagnostic markers, a viral load assay was used to ascertain clinical markers, and the Maxim Limiting Antigen Avidity EIA was used to ascertain infection-staging HIV markers. Given the challenges of estimating HIV incidence, especially cross-sectionally, multiple methods of estimation were adapted to our setting, leveraging the age structure of HIV prevalence, recency-of -infection biomarker results (ie, where recent infection is classified as ≤1·5 normalised optical density [ODn] on the avidity assay and viral load of ≥1000 copies per mL), and reported testing histories.

FINDINGS

Of 3005 female sex workers who were enrolled and interviewed between Feb 4 and June 26, 2019, 2999 who had HIV test results were included in this analysis. The median age of participants was 32 years (IQR 27-38). 1714 (57·2%) of 2999 participants self-reported as being HIV positive, and 1447 (48·3%) of 2993 participants reported client sexual violence in the past year. The measured HIV prevalence was 62·1% (95% CI 60·3-65·7) and peaked at approximately age 40 years. Using recency-of-infection biomarker results, we obtained a base case estimate of HIV incidence of 4·60 cases per 100 person-years (95% CI 1·53-8·45) for the population. Estimates were generally consistent by method, and outlying incidence estimates calculated by self-reported testing histories were considered unreliable. Various sensitivity analyses produced estimates up to 11 cases per 100 person-years, and we did not detect differences by age and region.

INTERPRETATION

We found that female sex workers have extraordinarily high HIV incidence of approximately 5 cases per 100 person-years, emphasising the need to sustain and strengthen efforts to mitigate risk and provide adequate care. The notable role that sex work has in HIV transmission demands substantial investment in ongoing epidemiological monitoring.

FUNDING

South African Medical Research Council, South African National Treasury, Global Fund, South African Department of Science and Innovation, Wellcome Trust.

Recent HIV Infection: Diagnosis and Public Health Implications

The early period of infection with human immunodeficiency virus (HIV) has been associated with higher infectiousness and, consequently, with more transmission events. Over the last 30 years, assays have been developed that can detect viral and immune biomarkers during the first months of HIV infection. Some of them depend on the functional properties of antibodies including their changing titers or the increasing strength of binding with antigens over time. There have been efforts to estimate HIV incidence using antibody-based assays that detect recent HIV infection along with other laboratory and clinical information. Moreover, some interventions are based on the identification of people who were recently infected by HIV. This review summarizes the evolution of efforts to develop assays for the detection of recent HIV infection and to use these assays for the cross-sectional estimation of HIV incidence or for prevention purposes.

Building an integrated serosurveillance platform to inform public health interventions: Insights from an experts' meeting on serum biomarkers

The use of biomarkers to measure immune responses in serum is crucial for understanding population-level exposure and susceptibility to human pathogens. Advances in sample collection, multiplex testing, and computational modeling are transforming serosurveillance into a powerful tool for public health program design and response to infectious threats. In July 2018, 70 scientists from 16 countries met to perform a landscape analysis of approaches that support an integrated serosurveillance platform, including the consideration of issues for successful implementation. Here, we summarize the group's insights and proposed roadmap for implementation, including objectives, technical requirements, ethical issues, logistical considerations, and monitoring and evaluation.

Quantitative interpretation of Sedia LAg Assay test results after HIV diagnosis

Background

Testing for ‘recent HIV infection’ is common in surveillance, where only population-level estimates (of incidence) are reported. Typically, ‘recent infection’ is a category, obtained by applying a threshold on an underlying continuous biomarker from some laboratory assay(s). Interpreting the biomarker values obtained for individual subjects, as estimates of the date of infection, has obvious potential applications in the context of studies of early infection, and has also for some years attracted significant interest as an extra component of post-test counselling and treatment initiation. The applicable analyses have typically run aground on the complexity of the full biomarker growth model, which is in principle a non-linear mixed-effects model of unknown structure, the fitting of which seems infeasible from realistically obtainable data.

Methods

It is known that to estimate Mean Duration of Recent Infection (MDRI) at a given value of the recent/non-recent -infection discrimination threshold, one may compress the full biomarker growth model into a relation capturing the probability of a recent test result as a function of time t since infection, given a value of assay threshold h which defines the recent/non-recent discrimination. We demonstrate that the derivative (gradient), with respect to h. of the probability of recent infection, seen as a function of both t and h, is identical to the formal likelihood relevant to Bayesian inference of the time since seroconversion, for a subject yielding an assay result h, at or close to the date of their first positive HIV test. This observation bypasses the need for fitting a complex detailed biomarker growth model. Using publicly available data from the CEPHIA collaboration, we calibrated this likelihood function for the Sedia Lag assay, and performed Bayesian inference on hypothetical infection data.

Results

We demonstrate the generation of posteriors for infection date, for patients with various delays between their last negative and first positive HIV test, and a range of LAg assay results (ODn) hypothetically obtained on the date of the first positive result.

Conclusion

Depending on the last-negative / first-positive interval, there is a range of ODn values that yields posteriors significantly different from the uniform prior one would be left with based merely on interval censoring. Hence, a LAg ODn obtained on the date of, or soon after, diagnosis contains potentially significant information about infection dating. It seems worth analysing other assays with meaningful dynamic range, especially tests already routinely used in primary HIV diagnosis (for example chemiluminescent assays and reader/cartridge lateral flow tests which admit objective variable line intensity readings) which have a sufficient dynamic range that corresponds to a clinically meaningful range of times-since-infection that are worth distinguishing from each other.

Statistical considerations for cross-sectional HIV incidence estimation based on recency test

Longitudinal cohorts to determine the incidence of HIV infection are logistically challenging, so researchers have sought alternative strategies. Recency test methods use biomarker profiles of HIV-infected subjects in a cross-sectional sample to infer whether they are "recently" infected and to estimate incidence in the population. Two main estimators have been used in practice: one that assumes a recency test is perfectly specific, and another that allows for false-recent results. To date, these commonly used estimators have not been rigorously studied with respect to their assumptions and statistical properties. In this article, we present a theoretical framework with which to understand these estimators and interrogate their assumptions, and perform a simulation study and data analysis to assess the performance of these estimators under realistic HIV epidemiological dynamics. We find that the snapshot estimator and the adjusted estimator perform well when their corresponding assumptions hold. When assumptions on constant incidence and recency test characteristics fail to hold, the adjusted estimator is more robust than the snapshot estimator. We conclude with recommendations for the use of these estimators in practice and a discussion of future methodological developments to improve HIV incidence estimation via recency test.

Use of HIV Recency Assays for HIV Incidence Estimation and Other Surveillance Use Cases: Systematic Review

BACKGROUND

HIV assays designed to detect recent infection, also known as "recency assays," are often used to estimate HIV incidence in a specific country, region, or subpopulation, alone or as part of recent infection testing algorithms (RITAs). Recently, many countries and organizations have become interested in using recency assays within case surveillance systems and routine HIV testing services to measure other indicators beyond incidence, generally referred to as "non-incidence surveillance use cases."

OBJECTIVE

This review aims to identify published evidence that can be used to validate methodological approaches to recency-based incidence estimation and non-incidence use cases. The evidence identified through this review will be used in the forthcoming technical guidance by the World Health Organization (WHO) and United Nations Programme on HIV/AIDS (UNAIDS) on the use of HIV recency assays for identification of epidemic trends, whether for HIV incidence estimation or non-incidence indicators of recency.

METHODS

To identify the best methodological and field implementation practices for the use of recency assays to estimate HIV incidence and trends in recent infections for specific populations or geographic areas, we conducted a systematic review of the literature to (1) understand the use of recency testing for surveillance in programmatic and laboratory settings, (2) review methodologies for implementing recency testing for both incidence estimation and non-incidence use cases, and (3) assess the field performance characteristics of commercially available recency assays.

RESULTS

Among the 167 documents included in the final review, 91 (54.5%) focused on assay or algorithm performance or methodological descriptions, with high-quality evidence of accurate age- and sex-disaggregated HIV incidence estimation at national or regional levels in general population settings, but not at finer geographic levels for prevention prioritization. The remaining 76 (45.5%) described the field use of incidence assays including field-derived incidence (n=45), non-incidence (n=25), and both incidence and non-incidence use cases (n=6). The field use of incidence assays included integrating RITAs into routine surveillance and assisting with molecular genetic analyses, but evidence was generally weaker or only reported on what was done, without validation data or findings related to effectiveness of using non-incidence indicators calculated through the use of recency assays as a proxy for HIV incidence.

CONCLUSIONS

HIV recency assays have been widely validated for estimating HIV incidence in age- and sex-specific populations at national and subnational regional levels; however, there is a lack of evidence validating the accuracy and effectiveness of using recency assays to identify epidemic trends in non-incidence surveillance use cases. More research is needed to validate the use of recency assays within HIV testing services, to ensure findings can be accurately interpreted to guide prioritization of public health programming.

Naomi: a new modelling tool for estimating HIV epidemic indicators at the district level in sub-Saharan Africa

INTRODUCTION

HIV planning requires granular estimates for the number of people living with HIV (PLHIV), antiretroviral treatment (ART) coverage and unmet need, and new HIV infections by district, or equivalent subnational administrative level. We developed a Bayesian small-area estimation model, called Naomi, to estimate these quantities stratified by subnational administrative units, sex, and five-year age groups.

METHODS

Small-area regressions for HIV prevalence, ART coverage and HIV incidence were jointly calibrated using subnational household survey data on all three indicators, routine antenatal service delivery data on HIV prevalence and ART coverage among pregnant women, and service delivery data on the number of PLHIV receiving ART. Incidence was modelled by district-level HIV prevalence and ART coverage. Model outputs of counts and rates for each indicator were aggregated to multiple geographic and demographic stratifications of interest. The model was estimated in an empirical Bayes framework, furnishing probabilistic uncertainty ranges for all output indicators. Example results were presented using data from Malawi during 2016-2018.

RESULTS

Adult HIV prevalence in September 2018 ranged from 3.2% to 17.1% across Malawi's districts and was higher in southern districts and in metropolitan areas. ART coverage was more homogenous, ranging from 75% to 82%. The largest number of PLHIV was among ages 35 to 39 for both women and men, while the most untreated PLHIV were among ages 25 to 29 for women and 30 to 34 for men. Relative uncertainty was larger for the untreated PLHIV than the number on ART or total PLHIV. Among clients receiving ART at facilities in Lilongwe city, an estimated 71% (95% CI, 61% to 79%) resided in Lilongwe city, 20% (14% to 27%) in Lilongwe district outside the metropolis, and 9% (6% to 12%) in neighbouring Dowa district. Thirty-eight percent (26% to 50%) of Lilongwe rural residents and 39% (27% to 50%) of Dowa residents received treatment at facilities in Lilongwe city.

CONCLUSIONS

The Naomi model synthesizes multiple subnational data sources to furnish estimates of key indicators for HIV programme planning, resource allocation, and target setting. Further model development to meet evolving HIV policy priorities and programme need should be accompanied by continued strengthening and understanding of routine health system data.

HIV Incidence by Male Circumcision Status From the Population-Based HIV Impact Assessment Surveys-Eight Sub-Saharan African Countries, 2015-2017

BACKGROUND

Male circumcision (MC) offers men lifelong partial protection from heterosexually acquired HIV infection. The impact of MC on HIV incidence has not been quantified in nationally representative samples. Data from the population-based HIV impact assessments were used to compare HIV incidence by MC status in countries implementing voluntary medical MC (VMMC) programs.

METHODS

Data were pooled from population-based HIV impact assessments conducted in Eswatini, Lesotho, Malawi, Namibia, Tanzania, Uganda, Zambia, and Zimbabwe from 2015 to 2017. Incidence was measured using a recent infection testing algorithm and analyzed by self-reported MC status distinguishing between medical and nonmedical MC. Country, marital status, urban setting, sexual risk behaviors, and mean population HIV viral load among women as an indicator of treatment scale-up were included in a random-effects logistic regression model using pooled survey weights. Analyses were age stratified (15-34 and 35-59 years). Annualized incidence rates and 95% confidence intervals (CIs) and incidence differences were calculated between medically circumcised and uncircumcised men.

RESULTS

Men 15-34 years reporting medical MC had lower HIV incidence than uncircumcised men [0.04% (95% CI: 0.00% to 0.10%) versus 0.34% (95% CI: 0.10% to 0.57%), respectively; P value = 0.01]; whereas among men 35-59 years, there was no significant incidence difference [1.36% (95% CI: 0.32% to 2.39%) versus 0.55% (95% CI: 0.14% to 0.67%), respectively; P value = 0.14].

DISCUSSION

Medical MC was associated with lower HIV incidence in men aged 15-34 years in nationally representative surveys in Africa. These findings are consistent with the expected ongoing VMMC program impact and highlight the importance of VMMC for the HIV response in Africa.

HIV-1 Recent Infection Testing Algorithm With Antiretroviral Drug Detection to Improve Accuracy of Incidence Estimates

BACKGROUND

HIV-1 incidence calculation currently includes recency classification by HIV-1 incidence assay and unsuppressed viral load (VL ≥ 1000 copies/mL) in a recent infection testing algorithm (RITA). However, persons with recent classification not virally suppressed and taking antiretroviral (ARV) medication may be misclassified.

SETTING

We used data from 13 African household surveys to describe the impact of an ARV-adjusted RITA on HIV-1 incidence estimates.

METHODS

HIV-seropositive samples were tested for recency using the HIV-1 Limiting Antigen (LAg)-Avidity enzyme immunoassay, HIV-1 viral load, ARVs used in each country, and ARV drug resistance. LAg-recent result was defined as normalized optical density values ≤1.5. We compared HIV-1 incidence estimates using 2 RITA: RITA1: LAg-recent + VL ≥ 1000 copies/mL and RITA2: RITA1 + undetectable ARV. We explored RITA2 with self-reported ARV use and with clinical history.

RESULTS

Overall, 357 adult HIV-positive participants were classified as having recent infection with RITA1. RITA2 reclassified 55 (15.4%) persons with detectable ARV as having long-term infection. Those with detectable ARV were significantly more likely to be aware of their HIV-positive status (84% vs. 10%) and had higher levels of drug resistance (74% vs. 26%) than those without detectable ARV. RITA2 incidence was lower than RITA1 incidence (range, 0%-30% decrease), resulting in decreased estimated new infections from 390,000 to 341,000 across the 13 countries. Incidence estimates were similar using detectable or self-reported ARV (R2 > 0.995).

CONCLUSIONS

Including ARV in RITA2 improved the accuracy of HIV-1 incidence estimates by removing participants with likely long-term HIV infection.

Temporal change in population-level prevalence of detectable HIV viraemia and its association with HIV incidence in key populations in India: a serial cross-sectional study

BACKGROUND

Population-level prevalence of detectable HIV viraemia (PDV) has been proposed as a metric for monitoring the population-level effectiveness of HIV treatment as prevention. We aimed to characterise temporal changes in PDV in people who inject drugs (PWID) and men who have sex with men (MSM) in India and evaluate community-level and individual-level associations with cross-sectional HIV incidence.

METHODS

We did a serial cross-sectional study in which baseline (from Oct 1, 2012, to Dec 19, 2013) and follow-up (from Aug 1, 2016, to May 28, 2017) respondent-driven sampling (RDS) surveys were done in MSM (ten community sites) and PWID (12 community sites) across 21 cities in India. Eligible participants were those aged 18 years or older who provided informed consent and possessed a valid RDS referral coupon. Annualised HIV incidence was estimated with validated multiple-assay algorithms. PDV was calculated as the percentage of people with detectable HIV RNA (>150 copies per mL) in a community site. Community-level associations were determined by linear regression. Multivariable, multilevel Poisson regression was used to assess associations with recent HIV infection.

FINDINGS

We recruited 21 990 individuals in the baseline survey and 21 726 individuals in the follow-up survey. The median community-level HIV incidence estimate increased from 0·9% (range 0·0-2·2) at baseline to 1·5% (0·5-3·0) at follow-up in MSM and from 1·6% (0·5-12·4) to 3·6% (0·0-18·4) in PWID. At the community-level, every 1 percentage point increase in baseline PDV and temporal change in PDV between surveys was associated with higher annualised HIV incidence at follow-up: for baseline PDV β=0·41 (95% CI 0·18-0·63) and for change in PDV β=0·52 (0·38-0·66). After accounting for individual-level risk factors, every 10 percentage point increase in baseline PDV and temporal change in PDV was associated with higher individual-level risk of recent HIV infection at follow-up: adjusted risk ratio 1·85 (95% CI 1·44-2·37) for baseline PDV and 1·81 (1·43-2·29) for change in PDV.

INTERPRETATION

PDV was temporally associated with community-level and individual-level HIV incidence. These data support scale-up of treatment as prevention programmes to reduce HIV incidence and the programmatic use of PDV to monitor community HIV risk potential.

FUNDING

US National Institutes of Health, Elton John AIDS Foundation.

Recent HIV infection among pregnant women in the 2017 antenatal sentinel cross-sectional survey, South Africa: Assay-based incidence measurement

Introduction

New 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.

Methods

Between 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.

Results

Of 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.

Conclusions

Compared 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.

Brief Report: HIV Incidence Among Older Adults in a Rural South African Setting: 2010-2015

In South Africa, evidence shows high HIV prevalence in older populations, with sexual behavior consistent with high HIV acquisition and transmission risk. However, there is a dearth of evidence on older people's HIV incidence.

Sample size calculation for active-arm trial with counterfactual incidence based on recency assay

Objectives

The past decade has seen tremendous progress in the development of biomedical agents that are effective as pre-exposure prophylaxis (PrEP) for HIV prevention. To expand the choice of products and delivery methods, new medications and delivery methods are under development. Future trials of non-inferiority, given the high efficacy of ARV-based PrEP products as they become current or future standard of care, would require a large number of participants and long follow-up time that may not be feasible. This motivates the construction of a counterfactual estimate that approximates incidence for a randomized concurrent control group receiving no PrEP.

Methods

We propose an approach that is to enroll a cohort of prospective PrEP users and aug-ment screening for HIV with laboratory markers of duration of HIV infection to indicate recent infections. We discuss the assumptions under which these data would yield an estimate of the counterfactual HIV incidence and develop sample size and power calculations for comparisons to incidence observed on an investigational PrEP agent.

Results

We consider two hypothetical trials for men who have sex with men (MSM) and transgender women (TGW) from different regions and young women in sub-Saharan Africa. The calculated sample sizes are reasonable and yield desirable power in simulation studies.

Conclusions

Future one-arm trials with counterfactual placebo incidence based on a recency assay can be conducted with reasonable total screening sample sizes and adequate power to determine treatment efficacy.

Recently acquired infection among HIV-seropositive donors in the US from 2010-2018

BACKGROUND

Monitoring of transfusion-transmissible infections in the blood supply is essential for blood safety, as the donor population is not static, and changes in policy, donor behavior, or other factors could increase the risk of recipient infection. We assessed patterns of recently acquired HIV infection in US blood donors, including before and after the implementation of the 12-month deferral for men who have sex with men (MSM).

STUDY DESIGN AND METHODS

A large convenience sample of donations from donors testing HIV-1 nucleic acid testing (NAT) and serology-reactive were further tested with the Sedia HIV-1 Limiting Antigen enzyme immunoassay. Samples were analyzed across available demographic and donation data to provide an assessment of recently acquired HIV infection in US blood donors from 2010 to 2018.

RESULTS

Overall, 317 of 1154 (27.5%; 95% confidence interval, 24.9%-30.1%) donations from HIV NAT and serology-reactive donors had recently acquired HIV infection. There was no evidence of change in the percentages of recent HIV infection by year over the study period, either in all donors or in male donors, including after the MSM policy change. In multivariable logistic regression analysis, donors aged 24 years or younger were over 2.7 times more likely and repeat donors 2.2 times more likely to have recently acquired HIV infection compared to donors aged 55 years or older and first-time donors, respectively.

CONCLUSION

Patterns of recently acquired HIV infection varied by demographics but not over time. These findings suggest no impact of the MSM policy change on recently acquired HIV infection in US blood donors.

HIV incidence in US first-time blood donors and transfusion risk with a 12-month deferral for men who have sex with men

In 2015, the US Food and Drug Administration published revised guidance that recommended a change in blood donor deferral of men who have sex with men (MSM) from an indefinite to a 12-month deferral since the donor last had sex with a man. We assessed whether HIV incidence in first-time blood donors or associated transfusion risk increased. Donations in 4 major blood collection organizations were monitored for 15 months before and 2 years after implementation of the 12-month MSM deferral policy. HIV-positive donations were classified as recently acquired or long-term using a recent infection testing algorithm and incidence in both periods estimated. Residual transfusion transmission risk was estimated by multiplying incidence by the length of the infectious window period. The latter was estimated using a model based on infectious dose and the sensitivity of nucleic acid testing. Factors associated with incident infection in each period were assessed using Poisson regression. Overall HIV incidence in first-time donors before implementation of the 12-month MSM deferral was estimated at 2.62 cases per 100 000 person-years (105 PY) (95% credible interval [CI], 1.53-3.93 cases/105 PY), and after implementation at 2.85 cases/105 PY (95% CI, 1.96-3.93 cases/105 PY), with no statistically significant change. In male first-time donors, the incidence difference was 0.93 cases/105 PY (95% CI, -1.74-3.58 cases/105 PY). The residual risk of HIV transfusion transmission through components sourced from first-time donors was estimated at 0.32 transmissions per million (106) packed red blood cell transfusions (95% CI, 0.29-0.65 transmissions/106 transfusions) before and 0.35 transmissions/106 transfusions (95% CI, 0.31-0.65 transmissions/106 transfusions) after implementation. The difference was not statistically significant. Factors associated with incident infection were the same in each period. We observed no increase in HIV incidence or HIV transfusion transmission risk after implementation of a 12-month MSM deferral policy.

Successes and gaps in the HIV cascade of care of a high HIV prevalence setting in Zimbabwe: a population-based survey

INTRODUCTION

Gutu, a rural district in Zimbabwe, has been implementing comprehensive HIV care with the support of Médecins Sans Frontières (MSF) since 2011, decentralizing testing and treatment services to all rural healthcare facilities. We evaluated HIV prevalence, incidence and the cascade of care, in Gutu District five years after MSF began its activities.

METHODS

A cross-sectional study was implemented between September and December 2016. Using multistage cluster sampling, individuals aged ≥15 years living in the selected households were eligible. Individuals who agreed to participate were interviewed and tested for HIV at home. All participants who tested HIV-positive had their HIV-RNA viral load (VL) measured, regardless of their antiretroviral therapy (ART) status, and those not on ART with HIV-RNA VL ≥ 1000 copies/mL had Limiting-Antigen-Avidity EIA Assay for cross-sectional estimation of population-level HIV incidence.

RESULTS

Among 5439 eligible adults ≥15 years old, 89.0% of adults were included in the study and accepted an HIV test. The overall prevalence was 13.6% (95%: Confidence Interval (CI): 12.6 to 14.5). Overall HIV-positive status awareness was 87.4% (95% CI: 84.7 to 89.8), linkage to care 85.5% (95% CI: 82.5 to 88.0) and participants in care 83.8% (95% CI: 80.7 to 86.4). ART coverage among HIV-positive participants was 83.0% (95% CI: 80.0 to 85.7). Overall, 71.6% (95% CI 68.0 to 75.0) of HIV-infected participants had a HIV-RNA VL < 1000 copies/mL. Women achieved higher outcomes than men in the five stages of the cascade of care. Viral Load Suppression (VLS) among participants on ART was 83.2% (95% CI: 79.7 to 86.2) and was not statistically different between women and men (p = 0.98). The overall HIV incidence was estimated at 0.35% (95% CI 0.00 to 0.70) equivalent to 35 new cases/10,000 person-years.

CONCLUSIONS

Our study provides population-level evidence that achievement of HIV cascade of care coverage overall and among women is feasible in a context with broad access to services and implementation of a decentralized model of care. However, the VLS was relatively low even among participants on ART. Quality care remains the most critical gap in the cascade of care to further reduce mortality and HIV transmission.

A new method for estimating HIV incidence from a single cross-sectional survey

Estimating incidence from cross-sectional data sources is both important to the understanding of the HIV epidemic and challenging from a methodological standpoint. We develop a new incidence estimator that measures the size of the undiagnosed population and the amount of time spent undiagnosed in order to infer incidence and transmission rates. The estimator is calculated using commonly collected information on testing history and HIV status and, thus, can be deployed in many HIV surveys without additional cost. If ART biomarker status and/or viral load information is available, the estimator can be adjusted for biases in self-reported testing history. The performance of the estimator is explored in two large surveys in Kenya, where we find our point estimates to be consistent with assay-derived estimates, with much smaller standard errors.

Antibody avidity-based approach to estimate population-level incidence of hepatitis C

BACKGROUND & AIMS

Accurate HCV incidence estimates are critical for monitoring progress towards HCV elimination goals, including an 80% reduction in HCV incidence by 2030. Moreover, incidence estimates can help guide prevention and treatment programming, particularly in the context of the US opioid epidemic.

METHODS

An inexpensive, Genedia-based HCV IgG antibody avidity assay was evaluated as a platform to estimate cross-sectional, population-level primary HCV incidence using 1,840 HCV antibody and RNA-positive samples from 875 individuals enrolled in 5 cohort studies in the US and India. Using samples collected <2 years following HCV seroconversion, the mean duration of recent infection (MDRI) was calculated by fitting a maximum likelihood binomial regression model to the probability of appearing recent. Among samples collected ≥2 years post-HCV seroconversion, an individual-level false recent ratio (FRR) was calculated by estimating the probability of appearing recent using an exact binomial test. Factors associated with falsely appearing recent among samples collected ≥2 years post seroconversion were determined by Poisson regression with generalized estimating equations and robust variance estimators.

RESULTS

An avidity index cut-off of <40% resulted in an MDRI of 113 days (95% CI 84-146), and FRRs of 0.4% (95% CI 0.0-1.2), 4.6% (95% CI 2.2-8.3), and 9.5% (95% CI 3.6-19.6) among individuals who were HIV-uninfected, HIV-infected, and HIV-infected with a CD4 count <200/μl, respectively. No variation was seen between HCV genotypes 1 and 3. In hypothetical scenarios of high-risk settings, a sample size of <1,000 individuals could reliably estimate primary HCV incidence.

CONCLUSIONS

This cross-sectional approach can estimate primary HCV incidence for the most common genotypes. This tool can serve as a valuable resource for program and policy planners seeking to monitor and reduce HCV burden.

LAY SUMMARY

Determining the rate of new hepatitis C virus (HCV) infections in a population is critical to monitoring progress toward HCV elimination and to appropriately guide control efforts. However, since HCV infections are most often initially asymptomatic, it is difficult to estimate the rate of new HCV infections without following HCV-uninfected people over time and repeatedly testing them for HCV infection. Here, we present a novel, resource-efficient method to estimate the rate of new HCV infections in a population using data from a single timepoint.

Viral Diversity Based on Next-Generation Sequencing of HIV-1 Provides Precise Estimates of Infection Recency and Time Since Infection

BACKGROUND

Human immunodeficiency virus type 1 (HIV-1) genetic diversity increases over the course of infection and can be used to infer the time since infection and, consequently, infection recency, which are crucial for HIV-1 surveillance and the understanding of viral pathogenesis.

METHODS

We considered 313 HIV-infected individuals for whom reliable estimates of infection dates and next-generation sequencing (NGS)-derived nucleotide frequency data were available. Fractions of ambiguous nucleotides, obtained by population sequencing, were available for 207 samples. We assessed whether the average pairwise diversity calculated using NGS sequences provided a more exact prediction of the time since infection and classification of infection recency (<1 year after infection), compared with the fraction of ambiguous nucleotides.

RESULTS

NGS-derived average pairwise diversity classified an infection as recent with a sensitivity of 88% and a specificity of 85%. When considering only the 207 samples for which fractions of ambiguous nucleotides were available, the NGS-derived average pairwise diversity exhibited a higher sensitivity (90% vs 78%) and specificity (95% vs 67%) than the fraction of ambiguous nucleotides. Additionally, the average pairwise diversity could be used to estimate the time since infection with a mean absolute error of 0.84 years, compared with 1.03 years for the fraction of ambiguous nucleotides.

CONCLUSIONS

Viral diversity based on NGS data is more precise than that based on population sequencing in its ability to predict infection recency and provides an estimated time since infection that has a mean absolute error of <1 year.

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

BACKGROUND

Human 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.

METHODS

The 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.

RESULTS

The 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%.

CONCLUSIONS

Using 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.

Correlates of HIV infection in adolescent girls and young women in Lesotho: results from a population-based survey

BACKGROUND

HIV acquisition remains high among adolescent girls and young women (AGYW, aged 15-24 years) in sub-Saharan Africa. We aimed to estimate prevalence and incidence of HIV in AGYW and to identify correlates of HIV infection by using data from the Lesotho Population-based HIV Impact Assessment (LePHIA).

METHODS

LePHIA was a nationally representative survey of adults and children based on a multistage cluster sampling method with random selection of enumeration areas and households. All adults aged 15 years and older who had slept in the household the night before were eligible for participation; participants completed an interview and HIV testing. We estimated incidence with the HIV-1 limiting antigen avidity enzyme immunoassay combined with viral load and examined the association between demographic and behavioural variables (including characteristics of cohabitating mothers and sexual partners, when available) and prevalence and incidence among AGYW using logistic regression, incorporating survey weights.

FINDINGS

We interviewed 8824 households, including 2358 AGYW who were tested for HIV infection. Weighted HIV prevalence was 11·1% (95% CI 9·7-12·5) in the overall population (273 of 2358 AGYW), 5·7% (4·1-7·2) in adolescent girls aged 15-19 years (64 of 1156), and 16·7% (14·4-19·0) in women aged 20-24 years (209 of 1212). Annualised HIV incidence was 1·8% (0·8-2·8). Correlates of prevalent infection include reporting a history of anal sex (adjusted odds ratio [aOR] 3·08, 1·11-8·57), having lived outside Lesotho in the past year (1·86, 1·01-3·42), having a partner suspected or known to be HIV positive (11·7, 6·0-22·5), and having two or more lifetime sexual partners (1·84, 1·21-2·78, for 2-3 lifetime sexual partners; 2·44, 1·45-4·08, for ≥4 lifetime sexual partners). For the 570 AGYW living with their mothers, maternal education was negatively associated with HIV prevalence in their daughters (aOR 0·36, 0·15-0·82, per increase in level attended). For AGYW with a cohabitating partner, the factors associated with AGYW infection were partner age (OR 4·54, 1·30-15·80, for partners aged 35-49 years, although the OR was no longer significant when adjusted for HIV status of partner), HIV status (aOR 11·22, 4·05-31·05), lack of viral load suppression (OR 0·16, 0·04-0·66), and partner employment in the past year (aOR 3·41, 1·12-10·42).

INTERPRETATION

The findings confirm the importance of improving the treatment cascade in male partners and targeting preventive interventions to AGYW who are at increased risk. A regional approach to prevention could mitigate the effect of migration on transnational spread of HIV.

FUNDING

President's Emergency Plan for AIDS Relief through the Centers for Disease Control and Prevention.

Performance comparison of the Maxim and Sedia Limiting Antigen Avidity assays for HIV incidence surveillance

BACKGROUND

Two manufacturers, Maxim Biomedical and Sedia Biosciences Corporation, supply CDC-approved versions of the HIV-1 Limiting Antigen Avidity EIA (LAg) for detecting 'recent' HIV infection in cross-sectional incidence estimation. This study assesses and compares the performance of the two assays for incidence surveillance.

METHODS

We ran both assays on a panel of 2,500 well-characterized HIV-1-infected specimens. We analysed concordance of assay results, assessed reproducibility using repeat testing and estimated mean durations of recent infection (MDRIs) and false-recent rates (FRRs) for a range of normalized optical density (ODn) thresholds, alone and in combination with viral load thresholds. We defined three hypothetical surveillance scenarios, similar to the Kenyan and South African epidemics, and a concentrated epidemic. These scenarios allowed us to evaluate the precision of incidence estimates obtained by means of various recent infection testing algorithms (RITAs) based on each of the two assays.

RESULTS

The Maxim assay produced lower ODn values than the Sedia assay on average, largely as a result of higher calibrator readings (mean OD of 0.749 vs. 0.643), with correlation of normalized readings lower (R2 = 0.908 vs. R2 = 0.938). Reproducibility on blinded control specimens was slightly better for Maxim. The MDRI of a Maxim-based algorithm at the 'standard' threshold (ODn ≤1.5 & VL >1,000) was 201 days (95% CI: 180,223) and for Sedia 171 (152,191). The difference Differences in MDRI were estimated at 32.7 (22.9,42.8) and 30.9 days (21.7,40.7) for the two algorithms, respectively. Commensurately, the Maxim algorithm had a higher FRR in treatment-naive subjects (1.7% vs. 1.1%). The two assays produced similar precision of incidence estimates in the three surveillance scenarios.

CONCLUSIONS

Differences between the assays can be primarily attributed to the calibrators supplied by the manufacturers. Performance for surveillance was extremely similar, although different thresholds were optimal (i.e. produced the lowest variance of incidence estimates) and at any given ODn threshold, different estimates of MDRI and FRR were obtained. The two assays cannot be treated as interchangeable: assay and algorithm-specific performance characteristic estimates must be used for survey planning and incidence estimation.

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.

A Window Into the HIV Epidemic from a South African Emergency Department

The aim of the study was to describe the HIV care continuum in emergency department (ED) patients in the Eastern Cape region of South Africa. This is a cross-sectional, identity-unlinked serosurvey, whereby discarded/excess samples from all patients who had blood drawn during the study period for routine care and sufficient serum remaining were tested for HIV, hepatitis B virus, and hepatitis C virus infection; HIV viral load (VL); and presence of antiretroviral (ARV) drugs. We also estimated cross-sectional incidence using the Limiting-Antigen Avidity assay and HIV VL. The study was conducted between September and November 2016 at the Frere Hospital Emergency Department in East London, South Africa. The overall HIV prevalence in our study population was 26.9% [95% confidence interval (CI): 25.0-28.8; n = 2,100]. The highest prevalence was observed among females in the 30-39 years age group [60.3% (95% CI: 53.2-67.1)]. HIV prevalence was significantly higher among females compared with males in both the 20-29 years age group and 30-39 years age group (p < .05), but nearly identical to older age groups. ARV drugs were detected in 53.5% (95% CI: 48.1-58.9) of HIV-infected subjects. The frequency of HIV viral suppression (< 1,000 copies/mL) was 48.5% (95% CI: 44.3-52.7), and was not statistically different between males and females (age-adjusted prevalence ratio = 1.15, 95% CI: 0.95-1.39). The HIV incidence rate was estimated to be 2.6% (95% CI: 1.2-3.9). The Frere Hospital ED has an extremely high burden of HIV infection. The detection of ARV drugs and prevalence of viral suppression fall short of the World Health Organization 90-90-90 goals in this population. Furthermore, there were a large number of patients with recent infection in the ED. The ED is a critical venue for testing and linkage to care of high-yield population who are likely missed by current testing and linkage-to-care programs.

Cross-sectional estimates revealed high HIV incidence in Botswana rural communities in the era of successful ART scale-up in 2013-2015

BACKGROUND

Botswana is close to reaching the UNAIDS "90-90-90" HIV testing, antiretroviral treatment (ART), and viral suppression goals. We sought to determine HIV incidence in this setting with both high HIV prevalence and high ART coverage.

METHODS

We used a cross-sectional approach to assessing HIV incidence. A random, population-based sample of adults age 16-64 years was enrolled in 30 rural and peri-urban communities as part of the Botswana Combination Prevention Project (BCPP), from October 2013 -November 2015. Data and samples from the baseline household survey were used to estimate cross-sectional HIV incidence, following an algorithm that combined Limiting-Antigen Avidity Assay (LAg-Avidity EIA), ART status (documented or by testing ARV drugs in plasma) and HIV-1 RNA load. The LAg-Avidity EIA cut-off normalized optical density (ODn) was set at 1.5. The HIV-1 RNA cut-off was set at 400 copies/mL. For estimation purposes, the Mean Duration of Recent Infection was 130 days and the False Recent Rate (FRR) was evaluated at values of either 0 or 0.39%.

RESULTS

Among 12,610 individuals participating in the baseline household survey, HIV status was available for 12,570 participants and 3,596 of them were HIV positive. LAg-Avidity EIA data was generated for 3,581 (99.6%) of HIV-positive participants. Of 326 participants with ODn ≤1.5, 278 individuals were receiving ART verified through documentation and were considered to represent longstanding HIV infections. Among the remaining 48 participants who reported no use of ART, 14 had an HIV-1 RNA load ≤400 copies/mL (including 3 participants with ARVs in plasma) and were excluded, as potential elite/viremic controllers or undisclosed ART. Thus, 34 LAg-Avidity-EIA-recent, ARV-naïve individuals with detectable HIV-1 RNA (>400 copies/mL) were classified as individuals with recent HIV infections. The annualized HIV incidence among 16-64 year old adults was estimated at 1.06% (95% CI 0.68-1.45%) with zero FRR, and at 0.64% (95% CI 0.24-1.04%) using a previously defined FRR of 0.39%. Within a subset of younger individuals 16-49 years old, the annualized HIV incidence was estimated at 1.29% (95% CI 0.82-1.77%) with zero FRR, and at 0.90% (95% CI 0.42-1.38%) with FRR set to 0.39%.

CONCLUSIONS

Using a cross-sectional estimate of HIV incidence from 2013-2015, we found that at the time of near achievement of the UNAIDS 90-90-90 targets, ~1% of adults (age 16-64 years) in Botswana's rural and peri-urban communities became HIV infected annually.

Population-level HIV incidence estimates using a combination of synthetic cohort and recency biomarker approaches in KwaZulu-Natal, South Africa

Introduction

There is a notable absence of consensus on how to generate estimates of population-level incidence. Incidence is a considerably more sensitive indicator of epidemiological trends than prevalence, but is harder to estimate. We used a novel hybrid method to estimate HIV incidence by age and sex in a rural district of KwaZulu-Natal, South Africa.

Methods

Our novel method uses an ‘optimal weighting’ of estimates based on an implementation of a particular ‘synthetic cohort’ approach (interpreting the age/time structure of prevalence, in conjunction with estimates of excess mortality) and biomarkers of ‘recent infection’ (combining Lag-Avidity, Bio-Rad Avidity and viral load results to define recent infection, and adapting the method for age-specific incidence estimation). Data were obtained from a population-based cross-sectional HIV survey conducted in Mbongolwane and Eshowe health service areas in 2013.

Results

Using the combined method, we find that age-specific HIV incidence in females rose rapidly during adolescence, from 1.33 cases/100 person-years (95% CI: 0.98,1.67) at age 15 to a peak of 5.01/100PY (4.14,5.87) at age 23. In males, incidence was lower, 0.34/100PY (0.00-0.74) at age 15, and rose later, peaking at 3.86/100PY (2.52-5.20) at age 30. Susceptible population-weighted average incidence in females aged 15-29 was estimated at 3.84/100PY (3.36-4.40), in males aged 15-29 at 1.28/100PY (0.68-1.50) and in all individuals aged 15-29 at 2.55/100PY (2.09-2.76). Using the conventional recency biomarker approach, we estimated HIV incidence among females aged 15-29 at 2.99/100PY (1.79-4.36), among males aged 15-29 at 0.87/100PY (0.22-1.60) and among all individuals aged 15-59 at 1.66/100PY (1.13-2.27).

Discussion

HIV incidence was very high in women aged 15-30, peaking in the early 20s. Men had lower incidence, which peaked at age 30. The estimates obtained from the hybrid method are more informative than those produced by conventional analysis of biomarker data, and represents a more optimal use of available data than either the age-continuous biomarker or synthetic cohort methods alone. The method is mainly useful at younger ages, where excess mortality is low and uncertainty in the synthetic cohort estimates is reasonably small.

Conclusion

Application of this method to large-scale population-based HIV prevalence surveys is likely to result in improved incidence surveillance over methods currently in wide use. Reasonably accurate and precise age-specific estimates of incidence are important to target better prevention, diagnosis and care strategies.

Cross-Sectional HIV Incidence Estimation with Missing Biomarkers

Considerable progress has been made in the development of approaches for HIV incidence estimation based on a cross-sectional survey for biomarkers of recent infection. Multiple biomarkers when used in combination can increase the precision of cross-sectional HIV incidence estimates. Multi-assay algorithms (MAAs) for cross-sectional HIV incidence estimation are hierarchical stepwise algorithms for testing the biological samples with multiple biomarkers. The objective of this paper is to consider some of the statistical challenges for addressing the problem of missing biomarkers in such testing algorithms. We consider several methods for handling missing biomarkers for (1) estimating the mean window period, and (2) estimating HIV incidence from a cross sectional survey once the mean window period has been determined. We develop a conditional estimation approach for addressing the missing data challenges and compare that method with two naïve approaches. Using MAAs developed for HIV subtype B, we evaluate the methods by simulation. We show that the two naïve estimation methods lead to biased results in most of the missing data scenarios considered. The proposed conditional approach protects against bias in all of the scenarios.

Development of antibody biomarkers of long term and recent dengue virus infections

Dengue virus (DENV) infections elicit antibody responses to the non-structural protein 1 (NS1) that are associated with protection against disease. However, the antibody isotypes and subclasses involved, and their kinetics have not been extensively studied. We characterized the antibody responses to DENV NS1 by enzyme-linked immunosorbent assay (ELISA) in a longitudinal cohort of 266 confirmed dengue cases in Recife, Northeast Brazil. Samples were collected during the febrile phase and up to over 3 years after onset of symptoms. The antibodies investigated [IgA, IgM, total IgG (all subclasses measured together) and each subclass (IgG2, IgG3 and IgG4) measured separately] had distinct kinetic profiles following primary or secondary DENV infections. Of interest, most of these antibodies were consistently detected greater than 6 months after onset of symptoms, except for IgG3. Anti-dengue NS1-specific IgG was consistently detected from the acute phase to beyond 3 years after symptom onset. In contrast, anti-dengue NS1-specific IgG3 was detected within the first week, peaked at week 2-3, and disappeared within 4-6 months after onset of symptoms. The mean duration of the IgG3 positive signal was 149 days (ranging from 126 to 172 days). In conclusion, anti-dengue NS1-specific IgG and IgG3 are potential biomarkers of long-term and recent (less than 6 months) DENV infections, respectively.

Assays for estimating HIV incidence: updated global market assessment and estimated economic value

Introduction

Accurate incidence estimates are needed to characterize the HIV epidemic and guide prevention efforts. HIV Incidence assays are cost‐effective laboratory assays that provide incidence estimates from cross‐sectional surveys. We conducted a global market assessment of HIV incidence assays under three market scenarios and estimated the economic value of improved incidence assays.

Methods

We interviewed 27 stakeholders, and reviewed journal articles, working group proceedings, and manufacturers’ sales figures. We determined HIV incidence assay use in 2014, and estimated use in 2015 to 2017 and in 5 to 10‐years under three market scenarios, as well as the cost of conducting national and key population surveys using an HIV incidence assay with improved performance.

Results

Global 2014 HIV incidence assay use was 308,900 tests, highest in Asia and mostly for case‐ and population‐based surveillance. Estimated 2015 to 2017 use was 94,475 annually, with declines due to China and the United States discontinuing incidence assay use for domestic surveillance. Annual projected 5 to 10 year use under scenario 1 – no change in technology – was 94,475. For scenario 2 – a moderately improved incidence assay – projected annual use was 286,031. Projected annual use for scenario 3 – game‐changing technologies with an HIV incidence assay part of (a) standard confirmatory testing, and (b) standard rapid testing, were 500,000 and 180 million, respectively. As HIV incidence assay precision increases, decreased sample sizes required for incidence estimation resulted in $5 to 23 million annual reductions in survey costs and easily offset the approximately $3 million required to develop a new assay.

Conclusions

Improved HIV incidence assays could substantially reduce HIV incidence estimation costs. Continued development of HIV incidence assays with improved performance is required to realize these cost benefits.

Infection Staging and Incidence Surveillance Applications of High Dynamic Range Diagnostic Immuno-Assay Platforms

BACKGROUND

Custom HIV staging assays, including the Sedia HIV-1 Limiting Antigen (LAg) Avidity EIA and avidity modifications of the Ortho VITROS anti-HIV-1+2 and Abbott ARCHITECT HIV Ag/Ab Combo assays, are used to identify "recent" infections in clinical settings and for cross-sectional HIV incidence estimation. However, the high dynamic range of chemiluminescent platforms allows differentiating recent and long-standing infection on signal intensity, and this raises the prospect of using unmodified diagnostic assays for infection timing and surveillance applications.

METHODS

We tested a panel of 2500 well-characterized specimens with estimable duration of HIV infection with the 3 assays and the unmodified ARCHITECT. Regression models were used to estimate mean durations of recent infection (MDRIs), context-specific false-recent rates (FRRs) and correlation between diagnostic signal intensity and LAg measurements. Hypothetical epidemiological scenarios were constructed to evaluate utility in surveillance applications.

RESULTS

Over a range of MDRIs (reflecting recency discrimination thresholds), a diluted ARCHITECT-based RITA produced lower FRRs than the VITROS platform (FRR ≈ 0.5% and 1.5%, respectively at MDRI ≈ 200 days), and the unmodified diagnostic ARCHITECT produces incidence estimates with comparable precision to LAg (relative SE ≈ 17.5% and 15%, respectively at MDRI ≈ 200 days). ARCHITECT S/CO measurements were highly correlated with LAg optical density measurements (r = 0.80), and values below 200 are strongly predictive of LAg recency and duration of infection less than 1 year.

CONCLUSIONS

Low quantitative measurements from the unmodified ARCHITECT obviate the need for additional recency testing, and its use is feasible in clinical staging and incidence surveillance applications.

Short Communication: False Recent Ratio of the Limiting-Antigen Avidity Assay and Viral Load Testing Algorithm Among Cameroonians with Long-Term HIV Infection

Current serological assays that are used for cross-sectional HIV incidence estimation have been shown to misclassify individuals with chronic infection. Limited information exists on the performance of cross-sectional incidence assays in Central Africa. HIV-positive individuals from Cameroon who were infected for at least 1 or 2 years were evaluated to determine the false recent ratio (FRR) of a two-assay algorithm, which includes the Limiting Antigen Avidity (LAg-Avidity) assay (normalized optical density units, ODn <1.5) and HIV viral load (>1000 copies/ml). The subject-level FRR was 5.3% (95% confidence interval [CI], 2.1-10.5) for individuals infected for ≥1 year and 3.9% (95% CI, 0.8-11.0) for individuals infected for ≥2 years. These data suggest that the LAg-Avidity plus viral load incidence algorithm may overestimate HIV incidence rates in Central Africa.

A comparison of self-report and antiretroviral detection to inform estimates of antiretroviral therapy coverage, viral load suppression and HIV incidence in Kwazulu-Natal, South Africa

Background

Accurately identifying individuals who are on antiretroviral therapy (ART) is important to determine ART coverage and proportion on ART who are virally suppressed. ART is also included in recent infection testing algorithms used to estimate incidence. We compared estimates of ART coverage, viral load suppression rates and HIV incidence using ART self-report and detection of antiretroviral (ARV) drugs and we identified factors associated with discordance between the methods.

Methods

Cross-sectional population-based survey in KwaZulu-Natal, South Africa. Individuals 15–59 years were eligible. Interviews included questions about ARV use. Rapid HIV testing was performed at the participants’ home. Blood specimens were collected for ARV detection, LAg-Avidity HIV incidence testing and viral load quantification in HIV-positive individuals. Multivariate logistic regression models were used to identify socio-demographic covariates associated with discordance between self-reported ART and ARV detection.

Results

Of the 5649 individuals surveyed, 1423 were HIV-positive. Median age was 34 years and 76.3% were women. ART coverage was estimated at 51.4% (95%CI:48.5–54.3), 53.1% (95%CI:50.2–55.9) and 56.1% (95%CI:53.5–58.8) using self-reported ART, ARV detection and both methods combined (classified as ART exposed if ARV detected and/or ART reported) respectively. ART coverage estimates using the 3 methods were fairly similar within sex and age categories except in individuals aged 15–19 years: 33.3% (95%CI:23.3–45.2), 33.8% (95%CI:23.9–45.4%) and 44.3% (95%CI:39.3–46.7) using self-reported ART, ARV detection and both methods combined. Viral suppression below 1000cp/mL in individuals on ART was estimated at 89.8% (95%CI:87.3–91.9), 93.1% (95%CI:91.0–94.8) and 88.7% (95%CI:86.2–90.7) using self-reported ART, ARV detection and both methods combined respectively. HIV incidence was estimated at 1.4 (95%CI:0.8–2.0) new cases/100 person-years when employing no measure of ARV use, 1.1/100PY (95%CI:0.6–1.7) using self-reported ART, and 1.2/100PY (95%CI:0.7–1.7) using ARV detection. In multivariate analyses, individuals aged 15–19 years had a higher risk of discordance on measures of ARV exposure (aOR:9.4; 95%CI:3.9–22.8), while migrants had a lower risk (aOR:0.3; 95%CI:0.1–0.6).

Conclusions

In KwaZulu-Natal, the method of identifying ARV use had little impact on estimates of ART coverage, viral suppression rate and HIV incidence. However, discordant results were more common in younger individuals. This may skew estimates of ART coverage and viral suppression, particularly in adolescent surveys.

Electronic supplementary material

The online version of this article (10.1186/s12879-017-2740-y) contains supplementary material, which is available to authorized users.

HCV avidity as a tool for detection of recent HCV infection: Sensitivity depends on HCV genotype

Accurate detection of incident hepatitis C virus (HCV) infection is required to target and evaluate public health interventions, but acute infection is largely asymptomatic and difficult to detect using traditional methods. Our aim was to evaluate a previously developed HCV avidity assay to distinguish acute from chronic HCV infection. Plasma samples collected from recent seroconversion subjects in two large Australian cohorts were tested using the avidity assay, and the avidity index (AI) was calculated. Demographic and clinical characteristics of patients with low/high AI were compared via logistic regression. Sensitivity and specificity of the assay for recent infection and the mean duration of recent infection (MDRI) were estimated stratified by HCV genotype. Avidity was assessed in 567 samples (from 215 participants), including 304 with viraemia (defined as ≥250 IU/mL). An inverse relationship between AI and infection duration was found in viraemic samples only. The adjusted odds of a low AI (<30%) decreased with infection duration (odds ratio [OR] per week of 0.93; 95% CI:0.89-0.97), and were lower for G1 compared with G3 samples (OR = 0.14; 95% CI:0.05-0.39). Defining recent infection as <26 weeks, sensitivity (at AI cut-off of 20%) was estimated at 48% (95% CI:39-56%), 36% (95% CI:20-52%), and 65% (95% CI:54-75%) and MDRI was 116, 83, and 152 days for all genotypes, G1, and G3, respectively. Specificity (≥52 weeks infection duration, all genotypes) was 96% (95% CI:90-98%). HCV avidity testing has utility for detecting recent HCV infection in patients, and for assessing progress in reaching incidence targets for eliminating transmission, but variation in assay performance across genotype should be recognized.