Viral and Host Characteristics of Recent and Established HIV-1 Infections in Kisumu based on a Multiassay Approach

Development of a multiassay algorithm (MAA) to identify recent HIV infection in newly diagnosed individuals in Indonesia

Ongoing HIV transmission is a public health priority in Indonesia. We developed a new multiassay algorithm (MAA) to identify recent HIV infection. The MAA is a sequential decision tree based on multiple biomarkers, starting with CD4+ T cells >200/μL, followed by plasma viral load (pVL) > 1,000 copies/ml, avidity index (AI) < 0 · 7, and pol ambiguity <0 · 47%. Plasma from 140 HIV-infected adults from 19 hospitals across Indonesia (January 2018 - June 2020) was studied, consisting of a training set (N = 60) of longstanding infection (>12-month) and a test set (N = 80) of newly diagnosed (≤1-month) antiretroviral (ARV) drug naive individuals. Ten of eighty (12 · 5%) newly diagnosed individuals were classified as recent infections. Drug resistance mutations (DRMs) against reverse transcriptase inhibitors were identified in two individuals: one infected with HIV subtype C (K219Q, V179T) and the other with CRF01_AE (V179D). Ongoing HIV transmission, including infections with DRMs, is substantial in Indonesia.

High Genetic Diversity of HIV-1 and Active Transmission Clusters among Male-to-Male Sexual Contacts (MMSCs) in Zhuhai, China

Monitoring genetic diversity and recent HIV infections (RHIs) is critical for understanding HIV epidemiology. Here, we report HIV-1 genetic diversity and RHIs in blood samples from 190 HIV-positive MMSCs in Zhuhai, China. MMSCs with newly reported HIV were enrolled from January 2020 to June 2022. A nested PCR was performed to amplify the HIV polymerase gene fragments at HXB2 positions 2604-3606. We constructed genetic transmission network at both 0.5% and 1.5% distance thresholds using the Tamura-Nei93 model. RHIs were identified using a recent infection testing algorithm (RITA) combining limiting antigen avidity enzyme immunoassay (LAg-EIA) assay with clinical data. The results revealed that 19.5% (37/190) were RHIs and 48.4% (92/190) were CRF07_BC. Two clusters were identified at a 0.5% distance threshold. Among them, one was infected with CRF07_BC for the long term, and the other was infected with CRF55_01B recently. We identified a total of 15 clusters at a 1.5% distance threshold. Among them, nine were infected with CRF07_BC subtype, and RHIs were found in 38.8% (19/49) distributed in eight genetic clusters. We identified a large active transmission cluster (n = 10) infected with a genetic variant, CRF79_0107. The multivariable logistic regression model showed that clusters were more likely to be RHIs (adjusted OR: 3.64, 95% CI: 1.51~9.01). The RHI algorithm can help to identify recent or ongoing transmission clusters where the prevention tools are mostly needed. Prompt public health measures are needed to contain the further spread of active transmission clusters.

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.

A systematic review of limiting antigen avidity enzyme immunoassay for detection of recent HIV-1 infection to expand supported applications

Introduction

The need for detection of new and recent HIV infections is essential for surveillance and assessing interventions in controlling the epidemic. HIV recency assays are one way of providing reliable incidence estimates by determining recent versus non-recent infection. The objective of this study was to review the current body of knowledge of the limiting antigen avidity enzyme immunoassay to expand supported applications through an assessment of what is known and the gaps.

Methods

A search for peer-reviewed literature in PubMed, Embase, and Web of Science Core Collection was conducted using the search term “human immunodeficiency virus and avidity”. Non-peer reviewed published reports from the Population-based HIV Impact Assessment Project were also included. These were limited to literature published in English between January 2010 and August 2021.

Results

This search resulted in 2080 publications and 14 reports, with 137 peer-reviewed studies and 14 non-peer reviewed reports that met the inclusion criteria, yielding a total of 151 studies for the final review. There were similar findings among studies that compared the performances of assay manufacturers and sample types. Studies that evaluated various assay algorithms and thresholds were heterogeneous, illustrating the need for context-specific test characteristics for classifying recent infections. Most studies estimated subtype-specific test characteristics for HIV subtypes A, B, C, and D. This was further illustrated when looking only at studies that compared HIV incidence estimates from recency assay algorithms and longitudinal cohorts.

Conclusions

These findings suggest that the current body of knowledge provides important information that contributes towards distinguishing recent and non-recent infection and incidence estimation. However, there are knowledge gaps with respect to factors that influence the test characteristics (e.g., HIV-1 subtype, population characteristics, assay algorithms and thresholds). Further studies are needed to estimate and establish context-specific test characteristics that consider these influencing factors to improve and expand the use of this assay for detection of recent HIV infection.

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.

Antiretroviral (ARV) Drug Resistance and HIV-1 Subtypes among Injecting Drug Users in the Coastal Region of Kenya

HIV-1 genetic diversity results into the development of widespread drug-resistant mutations (DRMs) for the first-line retroviral therapy. Nevertheless, few studies have investigated the relationship between DRMs and HIV-1 subtypes among HIV-positive injecting drug users (IDUs). This study therefore determined the association between HIV-1 genotypes and DRMs among the 200 IDUs. Stanford HIV Drug Resistance Database was used to interpret DRMs. The five HIV-1 genotypes circulating among the IDUs were A₁ (25 (53.2%)), A₂ (2 (4.3%)), B (2 (4.3%)), C (9 (19.1%)), and D (9 (19.1%)). The proportions of DRMs were A₁ (12 (52.2%)), A₂ (1 (4.3%)), B (0 (0.0%)), C (5 (21.7%)), and D (5 (21.7%)). Due to the large proportion of drug resistance across all HIV-1 subtypes, surveillance and behavioral studies need to be explored as IDUs may be spreading the drug resistance to the general population. In addition, further characterization of DRMs including all the relevant clinical parameters among the larger population of IDUs is critical for effective drug resistance surveillance.

Evaluation of multi-assay algorithms for identifying individuals with recent HIV infection: HPTN 071 (PopART)

Background

Assays and multi-assay algorithms (MAAs) have been developed for population-level cross-sectional HIV incidence estimation. These algorithms use a combination of serologic and/or non-serologic biomarkers to assess the duration of infection. We evaluated the performance of four MAAs for individual-level recency assessments.

Methods

Samples were obtained from 220 seroconverters (infected <1 year) and 4,396 non-seroconverters (infected >1 year) enrolled in an HIV prevention trial (HPTN 071 [PopART]); 28.6% of the seroconverters and 73.4% of the non-seroconverters had HIV viral loads ≤400 copies/mL. Samples were tested with two laboratory-based assays (LAg-Avidity, JHU BioRad-Avidity) and a point-of-care assay (rapid LAg). The four MAAs included different combinations of these assays and HIV viral load. Seroconverters on antiretroviral treatment (ART) were identified using a qualitative multi-drug assay.

Results

The MAAs identified between 54 and 100 (25% to 46%) of the seroconverters as recently-infected. The false recent rate of the MAAs for infections >2 years duration ranged from 0.2%-1.3%. The MAAs classified different overlapping groups of individuals as recent vs. non-recent. Only 32 (15%) of the 220 seroconverters were classified as recent by all four MAAs. Viral suppression impacted the performance of the two LAg-based assays. LAg-Avidity assay values were also lower for seroconverters who were virally suppressed on ART compared to those with natural viral suppression.

Conclusions

The four MAAs evaluated varied in sensitivity and specificity for identifying persons infected <1 year as recently infected and classified different groups of seroconverters as recently infected. Sensitivity was low for all four MAAs. These performance issues should be considered if these methods are used for individual-level recency assessments.

Validation of population-level HIV-1 incidence estimation by cross-sectional incidence assays in the HPTN 071 (PopART) trial

Introduction

Cross‐sectional incidence testing is used to estimate population‐level HIV incidence and measure the impact of prevention interventions. There are limited data evaluating the accuracy of estimates in settings where antiretroviral therapy coverage and levels of viral suppression are high. Understanding cross‐sectional incidence estimates in these settings is important as viral suppression can lead to false recent test results. We compared the accuracy of multi‐assay algorithms (MAA) for incidence estimation to that observed in the community‐randomized HPTN 071 (PopART) trial, where the majority of participants with HIV infection were virally suppressed.

Methods

HIV incidence was assessed during the second year of the study, and included only individuals who were tested for HIV at visits 1 and 2 years after the start of the study (2016–2017). Incidence estimates from three MAAs were compared to the observed incidence between years 1 and 2 (MAA‐C: LAg‐Avidity <2.8 ODn + BioRad Avidity Index <95% + VL >400 copies/ml; LAg+VL MAA: LAg‐Avidity <1.5 ODn + VL >1000 copies/ml; Rapid+VL MAA: Asanté recent rapid result + VL >1000 copies/ml). The mean duration of recent infection (MDRI) used for the three MAAs was 248, 130 and 180 days, respectively.

Results and discussion

The study consisted of: 15,845 HIV‐negative individuals; 4406 HIV positive at both visits; and 221 who seroconverted between visits. Viral load (VL) data were available for all HIV‐positive participants at the 2‐year visit. Sixty four (29%) of the seroconverters and 3227 (72%) prevelant positive participants were virally supressed (<400 copies/ml). Observed HIV incidence was 1.34% (95% CI: 1.17–1.53). Estimates of incidence were similar to observed incidence for MAA‐C, 1.26% (95% CI: 1.02–1.51) and the LAg+VL MAA, 1.29 (95% CI: 0.97–1.62). Incidence estimated by the Rapid+VL MAA was significantly lower than observed incidence (0.92%, 95% CI: 0.69–1.15, p<0.01).

Conclusions

MAA‐C and the LAg+VL MAA provided accurate point estimates of incidence in this cohort with high levels of viral suppression. The Rapid+VL significantly underestimated incidence, suggesting that the MDRI recommended by the manufacturer is too long or the assay is not accurately detecting enough recent infections.

Human immunodeficiency virus (HIV) type 1 genetic diversity in HIV positive individuals on antiretroviral therapy in a cross-sectional study conducted in Teso, Western Kenya

Introduction

high HIV-1 infection rates and genetic diversity especially in African population pose significant challenges in HIV-1 clinical management and drug design and development. HIV-1 is a major health challenge in Kenya and causes mortality and morbidity in the country as well as straining the healthcare system and the economy. This study sought to identify HIV-1 genetic subtypes circulating in Teso, Western Kenya which borders the Republic of Uganda.

Methods

a cross-sectional study was conducted in January 2019 to December 2019. Sequencing of the partial pol gene was carried out on 80 HIV positive individuals on antiretroviral therapy. Subtypes and recombinant forms were generated using the jumping profile hidden Markov model. Alignment of the sequences was done using ClustalW program and phylogenetic tree constructed using MEGA7 neighbor-joining method.

Results

sixty three samples were successful sequenced. In the analysis of these sequences, it was observed that HIV-1 subtype A1 was predominant 43 (68.3%) followed by D 8 (12.7%) and 1 (1.6%) each of C, G and B and inter-subtype recombinants A1-D 3 (4.8%), A1-B 2 (3.2%) and 1 (1.6%) each of A1-A2, A1-C, BC and BD. Phylogenetic analysis of these sequences showed close clustering of closely related and unrelated sequences with reference sequences.

Conclusion

there was observed increased genetic diversity of HIV-1 subtypes which not only pose a challenge in disease control and management but also drug design and development. Therefore, there is need for continued surveillance to enhance future understanding of the geographical distribution and transmission patterns of the HIV epidemic.

Identifying major drivers of incident HIV infection using recent infection testing algorithms (RITAs) to precisely inform targeted prevention

BACKGROUND

Recent infection testing algorithms (RITAs) incorporating clinical information with the HIV recency assay have been proven to accurately classify recent infection. However, little evidence exists on whether RITAs would help in precisely identifying major drivers of the ongoing HIV epidemic.

METHODS

HIV recency test results and clinical information were collected from 1152 newly diagnosed HIV cases between 2015 and 2017 in Dehong prefecture of Yunnan province, and the efficacy of four different RITAs in identifying risk factors for new HIV infection was compared.

RESULTS

RITA 1 uses the recency test only. RITA 2 and RITA 3 combine the recency test with CD4+ T cell count and viral load (VL), respectively. RITA 4 combines both CD4+ T cell count and VL. All RITAs identified the MSM group and young people between 15 and 24 years as risk factors for incident HIV infection. RITA 3 and RITA 4 further identified the Dai ethnic minority as a risk factor, which had not been identified before when only the HIV recency test was used.

CONCLUSIONS

By comparing different RITAs, we determined that greater accuracy in classifying recent HIV infection could help elucidate major drivers impacting the ongoing epidemic and thus inform targeted interventions.

HIV-1 subtype diversity, transmission networks and transmitted drug resistance amongst acute and early infected MSM populations from Coastal Kenya

Background

HIV-1 molecular epidemiology amongst men who have sex with men (MSM) in sub-Saharan Africa remains not well characterized. We aimed to determine HIV-1 subtype distribution, transmission clusters and transmitted drug resistance (TDR) in acute and early infected MSM from Coastal Kenya.

Methods

Analysis of HIV-1 partial pol sequences from MSM recruited 2005–2017 and sampled within six months of the estimated date of infection. Volunteers were classified as men who have sex with men exclusively (MSME) or with both men and women (MSMW). HIV-1 subtype and transmission clusters were determined by maximum-likelihood phylogenetics. TDR mutations were determined using the Stanford HIV drug resistance database.

Results

Of the 97 volunteers, majority (69%) were MSMW; 74%, 16%, 9% and 1% had HIV-1 subtypes A1, D, C or G, respectively. Overall, 65% formed transmission clusters, with substantial mixing between MSME and MSMW. Majority of volunteer sequences were either not linked to any reference sequence (56%) or clustered exclusively with sequences of Kenyan origin (19%). Eight (8% [95% CI: 4–16]) had at least one TDR mutation against nucleoside (n = 2 [2%]) and/or non-nucleoside (n = 7 [7%]) reverse transcriptase inhibitors. The most prevalent TDR mutation was K103N (n = 5), with sequences forming transmission clusters of two and three taxa each. There were no significant differences in HIV-1 subtype distribution and TDR between MSME and MSMW.

Conclusions

This HIV-1 MSM epidemic was predominantly sub-subtype A1, of Kenyan origin, with many transmission clusters and having intermediate level of TDR. Targeted HIV-1 prevention, early identification and care interventions are warranted to break the transmission cycle amongst MSM from Coastal Kenya.