Fostemsavir resistance-associated polymorphisms in HIV-1 subtype C in a large cohort of treatment-naïve and treatment-experienced individuals in Botswana.

IMPORTANCE: Fostemsavir (FTR) is a newly licensed antiretroviral drug that has been shown to have activity against HIV-1. The mechanism of action of FTR is different from all currently available antiretrovirals (ARVs), and as such, it offers hope for HIV-1 suppression in those people with HIV (PWH) who harbor HIV-1 variants with drug resistance mutations to currently used ARVs. Using 6,030 HIV-1 sequences covering the HIV-1 envelope from PWH in Botswana who are antiretroviral therapy (ART) naïve as well as those who are failing ART, we explored the sequences for FTR resistance-associated polymorphisms. We found the prevalence of FTR polymorphisms to be similar in both ART-naïve and ART-experienced individuals with VF in this setting, with no prior FTR exposure. Further studies on the phenotypic impact of these polymorphisms are warranted to guide how to monitor for FTR resistance.

Archived rilpivirine-associated resistance mutations among ART-naive and virologically suppressed people living with HIV-1 subtype C in Botswana: implications for cabotegravir/rilpivirine use.

OBJECTIVES: Pre-existing rilpivirine resistance-associated mutations (RVP-RAMs) have been found to predict HIV-1 virological failure in those switching to long-acting injectable cabotegravir/rilpivirine. We here evaluated the prevalence of archived RPV-RAMs in a cohort of people living with HIV (PWH). METHODS: We analysed near full-length HIV-1 pol sequences from proviral DNA for the presence of RPV-RAMs, which were defined according to the 2022 IAS-USA drug resistance mutation list and Stanford HIV drug resistance database. RESULTS: RPV-RAMs were identified in 757/5805 sequences, giving a prevalence of 13.0% (95% CI 12%-13.9%). Amongst the ART-naive group, 137/1281 (10.7%, 95% CI 9.1%-12.5%) had at least one RPV-RAM. Of the 4524 PWH with viral suppression on ART (VL <400 copies/mL), 620 (13.7%, 95% CI 12.7%-14.7%) had at least one RPV-RAM. E138A was the most prevalent RPV-RAM in the ART-naive group (7.9%) and the ART-suppressed group (9.3%). The rest of the mutations observed (L100I, K101E, E138G, E138K, E138Q, Y181C, H221Y, M230L, A98G, V179D, G190A, G190E and M230I) were below a prevalence of 1%. CONCLUSIONS: RPV-RAMs were present in 10.7% of ART-naive and 13.7% of ART-suppressed PWH in Botswana. The most common RPV-RAM in both groups was E138A. Since individuals with the E138A mutation may be more likely to fail cabotegravir/rilpivirine, monitoring RPV-RAMs will be crucial for effective cabotegravir/rilpivirine implementation in this setting.

Added Value of Next Generation Sequencing in Characterizing the Evolution of HIV-1 Drug Resistance in Kenyan Youth.

Drug resistance remains a global challenge in children and adolescents living with HIV (CALWH). Characterizing resistance evolution, specifically using next generation sequencing (NGS) can potentially inform care, but remains understudied, particularly in antiretroviral therapy (ART)-experienced CALWH in resource-limited settings. We conducted reverse-transcriptase NGS and investigated short-and long-term resistance evolution and its predicted impact in a well-characterized cohort of Kenyan CALWH failing 1st-line ART and followed for up to ~8 years. Drug resistance mutation (DRM) evolution types were determined by NGS frequency changes over time, defined as evolving (up-trending and crossing the 20% NGS threshold), reverting (down-trending and crossing the 20% threshold) or other. Exploratory analyses assessed potential impacts of minority resistance variants on evolution. Evolution was detected in 93% of 42 participants, including 91% of 22 with short-term follow-up, 100% of 7 with long-term follow-up without regimen change, and 95% of 19 with long-term follow-up with regimen change. Evolving DRMs were identified in 60% and minority resistance variants evolved in 17%, with exploratory analysis suggesting greater rate of evolution of minority resistance variants under drug selection pressure and higher predicted drug resistance scores in the presence of minority DRMs. Despite high-level pre-existing resistance, NGS-based longitudinal follow-up of this small but unique cohort of Kenyan CALWH demonstrated continued DRM evolution, at times including low-level DRMs detected only by NGS, with predicted impact on care. NGS can inform better understanding of DRM evolution and dynamics and possibly improve care. The clinical significance of these findings should be further evaluated.

An Automated Bioinformatics Pipeline Informing Near-Real-Time Public Health Responses to New HIV Diagnoses in a Statewide HIV Epidemic.

Molecular HIV cluster data can guide public health responses towards ending the HIV epidemic. Currently, real-time data integration, analysis, and interpretation are challenging, leading to a delayed public health response. We present a comprehensive methodology for addressing these challenges through data integration, analysis, and reporting. We integrated heterogeneous data sources across systems and developed an open-source, automatic bioinformatics pipeline that provides molecular HIV cluster data to inform public health responses to new statewide HIV-1 diagnoses, overcoming data management, computational, and analytical challenges. We demonstrate implementation of this pipeline in a statewide HIV epidemic and use it to compare the impact of specific phylogenetic and distance-only methods and datasets on molecular HIV cluster analyses. The pipeline was applied to 18 monthly datasets generated between January 2020 and June 2022 in Rhode Island, USA, that provide statewide molecular HIV data to support routine public health case management by a multi-disciplinary team. The resulting cluster analyses and near-real-time reporting guided public health actions in 37 phylogenetically clustered cases out of 57 new HIV-1 diagnoses. Of the 37, only 21 (57%) clustered by distance-only methods. Through a unique academic-public health partnership, an automated open-source pipeline was developed and applied to prospective, routine analysis of statewide molecular HIV data in near-real-time. This collaboration informed public health actions to optimize disruption of HIV transmission.

Prediction of Coreceptor Tropism in HIV-1 Subtype C in Botswana.

It remains unknown whether the C-C motif chemokine receptor type 5 (CCR5) coreceptor is still the predominant coreceptor used by Human Immunodeficiency Virus-1 (HIV-1) in Botswana, where the HIV-1 subtype C predominates. We sought to determine HIV-1C tropism in Botswana using genotypic tools, taking into account the effect of antiretroviral treatment (ART) and virologic suppression. HIV-1 gp120 V3 loop sequences from 5602 participants were analyzed for viral tropism using three coreceptor use predicting algorithms/tools: Geno2pheno, HIV-1C Web Position-Specific Score Matrices (WebPSSM) and the 11/25 charge rule. We then compared the demographic and clinical characteristics of people living with HIV (PLWH) harboring R5- versus X4-tropic viruses using χ2 and Wilcoxon rank sum tests for categorical and continuous data analysis, respectively. The three tools congruently predicted 64% of viruses as either R5-tropic or X4-tropic. Geno2pheno and the 11/25 charge rule had the highest concordance at 89%. We observed a significant difference in ART status between participants harboring X4- versus R5-tropic viruses. X4-tropic viruses were more frequent among PLWH receiving ART (χ2 test, p = 0.03). CCR5 is the predominant coreceptor used by HIV-1C strains circulating in Botswana, underlining the strong potential for CCR5 inhibitor use, even in PLWH with drug resistance. We suggest that the tools for coreceptor prediction should be used in combination.

High Prevalence of Hepatitis B Virus Infection Among People With HIV in Rural and Periurban Communities in Botswana.

Background: We aimed to determine the prevalence of hepatitis B virus (HBV) infection among people with human immunodeficiency virus (PWH) in rural and periurban communities in Botswana. Methods: PWH from a previous population-based study, the Botswana Prevention Combination Project, which enrolled adults in 30 communities across Botswana (2013-2018), were screened for HBV surface antigen (HBsAg) and HBV core antibody (anti-HBc). HBsAg-positive (HBsAg+) samples were further screened for HBV core immunoglobulin M antibodies (anti-HBc immunoglobulin M [IgM]) and HBV e antigen (HBeAg). We quantified HBV viral load on participants who tested positive (n = 148) and negative for HBsAg (n = 381). Results: Of 3304 participants tested, 271 (8% [95% confidence interval {CI}, 7%-9%]) were HBsAg+ while 1788 (56% [95% CI, 54%-57%]) of 3218 PWH whom we tested had positive anti-HBc. Approximately 88% of HBsAg+ participants were on antiretroviral therapy (ART), 40% and 56% of whom were receiving lamivudine- and tenofovir-containing ART, respectively. Male sex (relative risk ratio [RRR], 1.8 [95% CI, 1.2-2.7]) and the northern geographic region (RRR, 2.5 [95% CI, 1.4-4.7]) were independent predictors of HBV infection (HBsAg+). Of 381 persons with negative HBsAg who were tested for occult HBV, 126 (33% [95% CI, 29%-38%]) had positive HBV DNA. Eleven participants were highly viremic with high HBV viral load while on a lamivudine- or tenofovir-containing regimen. Ten (91%) of these participants also had positive HBeAg serology, while 4 (36%) had positive anti-HBc IgM serology. Conclusions: The prevalence of HBV was high among PWH in Botswana while on ART regimens with activity against HBV.

Not all clusters are equal: dynamics of molecular HIV-1 clusters in a statewide Rhode Island epidemic.

OBJECTIVES: Molecular epidemiology is a powerful tool to characterize HIV epidemics and prioritize public health interventions. Typically, HIV clusters are assumed to have uniform patterns over time. We hypothesized that assessment of cluster evolution would reveal distinct cluster behavior, possibly improving molecular epidemic characterization, towards disrupting HIV transmission. DESIGN: Retrospective cohort. METHODS: Annual phylogenies were inferred by cumulative aggregation of all available HIV-1 pol sequences of individuals with HIV-1 in Rhode Island (RI) between 1990 and 2020, representing a statewide epidemic. Molecular clusters were detected in annual phylogenies by strict and relaxed cluster definition criteria, and the impact of annual newly-diagnosed HIV-1 cases to the structure of individual clusters was examined over time. RESULTS: Of 2153 individuals, 31% (strict criteria) - 47% (relaxed criteria) clustered. Longitudinal tracking of individual clusters identified three cluster types: normal, semi-normal and abnormal. Normal clusters (83-87% of all identified clusters) showed predicted growing/plateauing dynamics, with approximately three-fold higher growth rates in large (15-18%) vs. small (∼5%) clusters. Semi-normal clusters (1-2% of all clusters) temporarily fluctuated in size and composition. Abnormal clusters (11-16% of all clusters) demonstrated collapses and re-arrangements over time. Borderline values of cluster-defining parameters explained dynamics of non-normal clusters. CONCLUSIONS: Comprehensive tracing of molecular HIV clusters over time in a statewide epidemic identified distinct cluster types, likely missed in cross-sectional analyses, demonstrating that not all clusters are equal. This knowledge challenges current perceptions of consistent cluster behavior over time and could improve molecular surveillance of local HIV epidemics to better inform public health strategies.

HIV-1C in-House RNA-Based Genotyping Assay for Detection of Drug Resistance Mutations in Samples with Low-Level Viral Loads.

Purpose: Monitoring HIV-1 drug resistance mutations (DRM) in treated patients on combination antiretroviral therapy (cART) with a detectable HIV-1 viral load (VL) is important for the selection of appropriate cART. Currently, there is limited data on HIV DRM at low-level viremia (LLV) (VL 401-999 copies/mL) due to the use of a threshold of VL ≥1000 copies/mL for HIV DRM testing. We here assess the performance of an in-house HIV drug resistance genotyping assay using plasma for the detection of DRM at LLV. Methods: We used a total of 96 HIV plasma samples from the population-based Botswana Combination Prevention Project (BCPP). The samples were stratified by VL groups: 50 samples had LLV, defined as 401-999 copies/mL, and 46 had ≥1000 copies/mL. HIV pol (PR and RT) region was amplified and sequenced using an in-house genotyping assay with BigDye sequencing chemistry. Known HIV DRMs were identified using the Stanford HIV Drug Resistance Database. Genotyping success rate between the two groups was estimated and compared using the comparison of proportions test. Results: The overall genotyping success rate was 79% (76/96). For VL groups, the genotyping success was 72% (36/50) at LLV and 87% (40/46) at VL ≥1000 copies/mL. Among generated sequences, the overall prevalence of individuals with at least 1 major or intermediate-associated DRM was 24% (18/76). The proportions of NNRTI-, NRTI- and PI-associated resistance mutations were 28%, 24%, and 0%, respectively. The most predominant mutations detected were K103N (18%) and M184V (12%) in NNRTI- and NRTI-associated mutations, respectively. The prevalence of DRM was 17% (6/36) at LLV and 30% (12/40) at VL ≥1000 copies/mL. Conclusion: The in-house HIV genotyping assay successfully genotyped 72% of LLV samples and was able to detect 17% of DRM amongst them. Our results highlight the possibility and clinical significance of genotyping HIV among individuals with LLV.

Doravirine-associated resistance mutations in antiretroviral therapy naïve and experienced adults with HIV-1 subtype C infection in Botswana.

OBJECTIVES: There are limited data on the prevalence of doravirine (DOR)-associated drug resistance mutations in people with HIV (PWH) in Botswana. This cross-sectional, retrospective study aimed to explore the prevalence of DOR-associated resistance mutations among ART-naïve and -experienced PWH in Botswana enrolled in the population-based Botswana Combination Prevention Project (BCPP). METHODS: A total of 6078 HIV-1C pol sequences were analysed for DOR-associated resistance mutations using the Stanford HIV drug resistance database, and their levels were predicted according to the Stanford DRM penalty scores and resistance interpretation. Virologic failure was defined as HIV-1 RNA load (VL) >400 copies/mL. RESULTS: Among 6078 PWH, 5999 (99%) had known ART status, and 4529/5999 (79%) were on ART at time of sampling. The suppression rate among ART-experienced was 4517/4729 (96%). The overall prevalence of any DOR-associated resistance mutations was 181/1473 (12.3% [95% confidence interval {CI}: 10.7-14.1]); by ART status: 42/212 (19.8% [95% CI: 14.7-25.4]) among ART-failing individuals (VL ≥400 copies/mL) and 139/1261 (11.0% [95% CI: 9.3-12.9]) among ART-naïve individuals (P < 0.01). Intermediate DOR-associated resistance mutations were observed in 106/1261 (7.8% [95% CI: 6.9-10.1]) in ART-naïve individuals and 29/212 (13.7% [95% CI: 9.4-8.5]) among ART-experienced participants (P < 0.01). High-level DOR-associated resistance mutations were observed in 33/1261 (2.6% [95% CI: 1.8-3.7]) among ART-naïve and 13/212 (6.1% [95% CI: 3.6-10.8]) among ART-failing PWH (P < 0.01). PWH failing ART with at least one EFV/NVP-associated resistance mutation had high prevalence 13/67 (19.4%) of high-level DOR-associated resistance mutations. CONCLUSION: DOR-associated mutations were rare (11.0%) among ART-naive PWH but present in 62.7% of Botswana individuals who failed NNRTI-based ART with at least one EFV/NVP-associated resistance mutation. Testing for HIV drug resistance should underpin the use of DOR in PWH who have taken first-generation NNRTIs.

Epidemiological and viral characteristics of undiagnosed HIV infections in Botswana.

BACKGROUND: HIV-1 is endemic in Botswana. The country's primary challenge is identifying people living with HIV who are unaware of their status. We evaluated factors associated with undiagnosed HIV infection using HIV-1 phylogenetic, behavioural, and demographic data. METHODS: As part of the Botswana Combination Prevention Project, 20% of households in 30 villages were tested for HIV and followed from 2013 to 2018. A total of 12,610 participants were enrolled, 3596 tested HIV-positive at enrolment, and 147 participants acquired HIV during the trial. Extensive socio-demographic and behavioural data were collected from participants and next-generation sequences were generated for HIV-positive cases. We compared three groups of participants: (1) those previously known to be HIV-positive at enrolment (n = 2995); (2) those newly diagnosed at enrolment (n = 601) and (3) those who tested HIV-negative at enrolment but tested HIV-positive during follow-up (n = 147). We searched for differences in demographic and behavioural factors between known and newly diagnosed group using logistic regression. We also compared the topology of each group in HIV-1 phylogenies and used a genetic diversity-based algorithm to classify infections as recent (< 1 year) or chronic (≥ 1 year). RESULTS: Being male (aOR = 2.23) and younger than 35 years old (aOR = 8.08) was associated with undiagnosed HIV infection (p < 0.001), as was inconsistent condom use (aOR = 1.76). Women were more likely to have undiagnosed infections if they were married, educated, and tested frequently. For men, being divorced increased their risk. The genetic diversity-based algorithm classified most incident infections as recent (75.0%), but almost none of known infections (2.0%). The estimated proportion of recent infections among new diagnoses was 37.0% (p < 0.001). CONCLUSION: Our results indicate that those with undiagnosed infections are likely to be young men and women who do not use condoms consistently. Among women, several factors were predictive: being married, educated, and testing frequently increased risk. Men at risk were more difficult to delineate. A sizeable proportion of undiagnosed infections were recent based on a genetic diversity-based classifier. In the era of "test and treat all", pre-exposure prophylaxis may be prioritized towards individuals who self-identify or who can be identified using these predictors in order to halt onward transmission in time.

A Challenging Knowledge Gap: Estimating Modes of HIV Acquisition Among Adolescents Entering HIV Care During Adolescence.

Characterizing HIV acquisition modes among adolescents with HIV (AHIV) enrolling in care during adolescence is a challenging gap that impacts differential interventions. We explored whether primary data collection with targeted questionnaires may address this gap and improve understanding of risk factors and perceptions about adolescents' HIV acquisition, in Kenyan AHIV entering care at ≥10 years, and their mothers with HIV (MHIV). Clinical data were derived through chart review. Among 1073 AHIV in care, only 26 (2%) met eligibility criteria of being ≥10 years at care enrollment, disclosed to, and with living MHIV. Among 18/26 AHIV-MHIV dyads enrolled (median age of AHIV 14 years), none had documented HIV acquisition modes. Data suggested perinatal infection in 17/18 AHIV, with 1 reported non-perinatal acquisition risk factor, and some discordance between adolescent-mother perceptions of HIV acquisition. In this difficult-to-enroll, vulnerable population of AHIV-MHIV dyads, primary data collection can enhance understanding of AHIV acquisition modes.

Beyond HIV outbreaks: protocol, rationale and implementation of a prospective study quantifying the benefit of incorporating viral sequence clustering analysis into routine public health interventions.

INTRODUCTION: HIV continues to have great impact on millions of lives. Novel methods are needed to disrupt HIV transmission networks. In the USA, public health departments routinely conduct contact tracing and partner services and interview newly HIV-diagnosed index cases to obtain information on social networks and guide prevention interventions. Sequence clustering methods able to infer HIV networks have been used to investigate and halt outbreaks. Incorporation of such methods into routine, not only outbreak-driven, contact tracing and partner services holds promise for further disruption of HIV transmissions. METHODS AND ANALYSIS: Building on a strong academic-public health collaboration in Rhode Island, we designed and have implemented a state-wide prospective study to evaluate an intervention that incorporates real-time HIV molecular clustering information with routine contact tracing and partner services. We present the rationale and study design of our approach to integrate sequence clustering methods into routine public health interventions as well as related important ethical considerations. This prospective study addresses key questions about the benefit of incorporating a clustering analysis triggered intervention into the routine workflow of public health departments, going beyond outbreak-only circumstances. By developing an intervention triggered by, and incorporating information from, viral sequence clustering analysis, and evaluating it with a novel design that avoids randomisation while allowing for methods comparison, we are confident that this study will inform how viral sequence clustering analysis can be routinely integrated into public health to support the ending of the HIV pandemic in the USA and beyond. ETHICS AND DISSEMINATION: The study was approved by both the Lifespan and Rhode Island Department of Health Human Subjects Research Institutional Review Boards and study results will be published in peer-reviewed journals.

Comparative transmissibility of SARS-CoV-2 variants Delta and Alpha in New England, USA.

The SARS-CoV-2 Delta variant rose to dominance in mid-2021, likely propelled by an estimated 40%-80% increased transmissibility over Alpha. To investigate if this ostensible difference in transmissibility is uniform across populations, we partner with public health programs from all six states in New England in the United States. We compare logistic growth rates during each variant's respective emergence period, finding that Delta emerged 1.37-2.63 times faster than Alpha (range across states). We compute variant-specific effective reproductive numbers, estimating that Delta is 63%-167% more transmissible than Alpha (range across states). Finally, we estimate that Delta infections generate on average 6.2 (95% CI 3.1-10.9) times more viral RNA copies per milliliter than Alpha infections during their respective emergence. Overall, our evidence suggests that Delta's enhanced transmissibility can be attributed to its innate ability to increase infectiousness, but its epidemiological dynamics may vary depending on underlying population attributes and sequencing data availability.

HIV-1 drug resistance mutations among individuals with low-level viraemia while taking combination ART in Botswana.

OBJECTIVES: To assess whether a single instance of low-level viraemia (LLV) is associated with the presence of drug resistance mutations (DRMs) and predicts subsequent virological failure (VF) in adults receiving ART in 30 communities participating in the Botswana Combination Prevention Project. METHODS: A total of 6078 HIV-1 C pol sequences were generated and analysed using the Stanford HIV drug resistance database. LLV was defined as plasma VL = 51-999 copies/mL and VF was defined as plasma VL ≥ 1000 copies/mL. RESULTS: Among 6078 people with HIV (PWH), 4443 (73%) were on ART for at least 6 months. Of the 332 persons on ART with VL > 50 copies/mL, 175 (4%) had VL ≥ 1000 copies/mL and 157 (4%) had LLV at baseline. The prevalence of any DRM was 57 (36%) and 78 (45%) in persons with LLV and VL ≥ 1000 copies/mL, respectively. Major DRMs were found in 31 (20%) with LLV and 53 (30%) with VL ≥ 1000 copies/mL (P = 0.04). Among the 135 PWH with at least one DRM, 17% had NRTI-, 35% NNRTI-, 6% PI- and 3% INSTI-associated mutations. Among the 3596 participants who were followed up, 1709 (48%) were on ART for ≥6 months at entry and had at least one subsequent VL measurement (median 29 months), 43 (3%) of whom had LLV. The OR of experiencing VF in persons with LLV at entry was 36-fold higher than in the virally suppressed group. CONCLUSIONS: A single LLV measurement while on ART strongly predicted the risk of future VF, suggesting the use of VL > 50 copies/mL as an indication for more intensive adherence support with more frequent VL monitoring.

DirectDetect SARS-CoV-2 Direct Real-Time RT-PCR Study Using Patient Samples.

COVID-19 is an infectious disease that caused a global pandemic affecting people worldwide. As disease detection and vaccine rollout continue to progress, there is still a need for efficient diagnostic tools to satisfy continued testing needs. This preliminary study evaluated a novel SARS-CoV-2 diagnostic test called DirectDetect SARS-CoV-2 Direct Real-time reverse transcriptase polymerase chain reaction (RT-PCR) based on a limited sample size of 24 respiratory samples from 14 SARS-CoV-2-positive patients. The test is advantageous compared to others on the market since it does not require viral transport medium or viral RNA extraction prior to nucleic acid amplification and detection. This capability transforms the hours-long sample preparation time into a minutes-long procedure while also eliminating the need for many costly reagents which may be difficult to obtain during the surge in nucleic acid-based testing during the pandemic. The results show a positive agreement of 94.7, 100, and 94.7% between dry sample swabs, treated samples, and untreated samples tested using the DirectDetect SARS-CoV-2 Direct Real-time RT-PCR compared to tests used in a clinical laboratory, respectively. The findings indicate that DirectDetect can be used for multiple different sample types while reducing the number of reagents and time needed for diagnosis. Although this study shows promising results using the DirectDetect results, further validation of this test using a larger sample set is required to assess the true performance of this test.

Statewide Longitudinal Trends in Transmitted HIV-1 Drug Resistance in Rhode Island, USA.

BACKGROUND: HIV-1 transmitted drug resistance (TDR) remains a global challenge that can impact care, yet its comprehensive assessment is limited and heterogenous. We longitudinally characterized statewide TDR in Rhode Island. METHODS: Demographic and clinical data from treatment-naïve individuals were linked to protease, reverse transcriptase, and integrase sequences routinely obtained over 2004-2020. TDR extent, trends, impact on first-line regimens, and association with transmission networks were assessed using the Stanford Database, Mann-Kendall statistic, and phylogenetic tools. RESULTS: In 1123 individuals, TDR to any antiretroviral increased from 8% (2004) to 26% (2020), driven by non-nucleotide reverse transcriptase inhibitor (NNRTI; 5%-18%) and, to a lesser extent, nucleotide reverse transcriptase inhibitor (NRTI; 2%-8%) TDR. Dual- and triple-class TDR rates were low, and major integrase strand transfer inhibitor resistance was absent. Predicted intermediate to high resistance was in 77% of those with TDR, with differential suppression patterns. Among all individuals, 34% were in molecular clusters, some only with members with TDR who shared mutations. Among clustered individuals, people with TDR were more likely in small clusters. CONCLUSIONS: In a unique (statewide) assessment over 2004-2020, TDR increased; this was primarily, but not solely, driven by NNRTIs, impacting antiretroviral regimens. Limited TDR to multiclass regimens and pre-exposure prophylaxis are encouraging; however, surveillance and its integration with molecular epidemiology should continue in order to potentially improve care and prevention interventions.

Human Immunodeficiency Virus (HIV) Genetic Diversity Informs Stage of HIV-1 Infection Among Patients Receiving Antiretroviral Therapy in Botswana.

BACKGROUND: Human immunodeficiency virus (HIV)-1 genetic diversity increases during infection and can help infer the time elapsed since infection. However, the effect of antiretroviral treatment (ART) on the inference remains unknown. METHODS: Participants with estimated duration of HIV-1 infection based on repeated testing were sourced from cohorts in Botswana (n = 1944). Full-length HIV genome sequencing was performed from proviral deoxyribonucleic acid. We optimized a machine learning model to classify infections as < or >1 year based on viral genetic diversity, demographic, and clinical data. RESULTS: The best predictive model included variables for genetic diversity of HIV-1 gag, pol, and env, viral load, age, sex, and ART status. Most participants were on ART. Balanced accuracy was 90.6% (95% confidence interval, 86.7%-94.1%). We tested the algorithm among newly diagnosed participants with or without documented negative HIV tests. Among those without records, those who self-reported a negative HIV test within <1 year were more frequently classified as recent than those who reported a test >1 year previously. There was no difference in classification between those self-reporting a negative HIV test <1 year, whether or not they had a record. CONCLUSIONS: These results indicate that recency of HIV-1 infection can be inferred from viral sequence diversity even among patients on suppressive ART.

Longitudinal typing of molecular HIV clusters in a statewide epidemic.

BACKGROUND: HIV molecular epidemiology is increasingly integrated into public health prevention. We conducted cluster typing to enhance characterization of a densely sampled statewide epidemic towards informing public health. METHODS: We identified HIV clusters, categorized them into types, and evaluated their dynamics between 2004 and 2019 in Rhode Island. We grouped sequences by diagnosis year, assessed cluster changes between paired phylogenies, t0 and t1, representing adjacent years and categorized clusters as stable (cluster in t0 phylogeny = cluster in t1 phylogeny) or unstable (cluster in t0 ≠ cluster in t1). Unstable clusters were further categorized as emerging (t1 phylogeny only) or growing (larger in t1 phylogeny). We determined proportions of each cluster type, of individuals in each cluster type, and of newly diagnosed individuals in each cluster type, and assessed trends over time. RESULTS: A total of 1727 individuals with available HIV-1 subtype B pol sequences were diagnosed in Rhode Island by 2019. Over time, stable clusters and individuals in them dominated the epidemic, increasing over time, with reciprocally decreasing unstable clusters and individuals in them. Conversely, proportions of newly diagnosed individuals in unstable clusters significantly increased. Within unstable clusters, proportions of emerging clusters and of individuals in them declined; whereas proportions of newly diagnosed individuals in growing clusters significantly increased over time. CONCLUSION: Distinct molecular cluster types were identified in the Rhode Island epidemic. Cluster dynamics demonstrated increasing stable and decreasing unstable clusters driven by growing, rather than emerging clusters, suggesting consistent in-state transmission networks. Cluster typing could inform public health beyond conventional approaches and direct interventions.

Empirical comparison of analytical approaches for identifying molecular HIV-1 clusters.

Public health interventions guided by clustering of HIV-1 molecular sequences may be impacted by choices of analytical approaches. We identified commonly-used clustering analytical approaches, applied them to 1886 HIV-1 Rhode Island sequences from 2004-2018, and compared concordance in identifying molecular HIV-1 clusters within and between approaches. We used strict (topological support ≥ 0.95; distance 0.015 substitutions/site) and relaxed (topological support 0.80-0.95; distance 0.030-0.045 substitutions/site) thresholds to reflect different epidemiological scenarios. We found that clustering differed by method and threshold and depended more on distance than topological support thresholds. Clustering concordance analyses demonstrated some differences across analytical approaches, with RAxML having the highest (91%) mean summary percent concordance when strict thresholds were applied, and three (RAxML-, FastTree regular bootstrap- and IQ-Tree regular bootstrap-based) analytical approaches having the highest (86%) mean summary percent concordance when relaxed thresholds were applied. We conclude that different analytical approaches can yield diverse HIV-1 clustering outcomes and may need to be differentially used in diverse public health scenarios. Recognizing the variability and limitations of commonly-used methods in cluster identification is important for guiding clustering-triggered interventions to disrupt new transmissions and end the HIV epidemic.

Mapping of HIV-1C Transmission Networks Reveals Extensive Spread of Viral Lineages Across Villages in Botswana Treatment-as-Prevention Trial.

BACKGROUND: Phylogenetic mapping of HIV-1 lineages circulating across defined geographical locations is promising for better understanding HIV transmission networks to design optimal prevention interventions. METHODS: We obtained near full-length HIV-1 genome sequences from people living with HIV (PLWH), including participants on antiretroviral treatment in the Botswana Combination Prevention Project, conducted in 30 Botswana communities in 2013-2018. Phylogenetic relationships among viral sequences were estimated by maximum likelihood. RESULTS: We obtained 6078 near full-length HIV-1C genome sequences from 6075 PLWH. We identified 984 phylogenetically distinct HIV-1 lineages (molecular HIV clusters) circulating in Botswana by mid-2018, with 2-27 members per cluster. Of these, dyads accounted for 62%, approximately 32% (n = 316) were found in single communities, and 68% (n = 668) were spread across multiple communities. Men in clusters were approximately 3 years older than women (median age 42 years, vs 39 years; P < .0001). In 65% of clusters, men were older than women, while in 35% of clusters women were older than men. The majority of identified viral lineages were spread across multiple communities. CONCLUSIONS: A large number of circulating phylogenetically distinct HIV-1C lineages (molecular HIV clusters) suggests highly diversified HIV transmission networks across Botswana communities by 2018.