Geographic and Population Distributions of Human Immunodeficiency Virus (HIV)-1 and HIV-2 Circulating Subtypes: A Systematic Literature Review and Meta-analysis (2010-2021).

BACKGROUND: HIV poses significant challenges for vaccine development due to its high genetic mutation and recombination rates. Understanding the distribution of HIV subtypes (clades) across regions and populations is crucial. In this study, a systematic review of the past decade was conducted to characterize HIV-1/HIV-2 subtypes. METHODS: A comprehensive search was performed in PubMed, EMBASE, and CABI Global Health, yielding 454 studies from 91 countries. RESULTS: Globally, circulating recombinant forms (CRFs)/unique recombinant forms (URFs) accounted for 29% of HIV-1 strains, followed by subtype C (23%) and subtype A (17%). Among studies reporting subtype breakdowns in key populations, 62% of HIV infections among men who have sex with men (MSM) and 38% among people who inject drugs (PWIDs) were CRF/URFs. Latin America and the Caribbean exhibited a 25% increase in other CRFs (excluding CRF01_AE or CRF02_AG) prevalence between 2010-2015 and 2016-2021. CONCLUSIONS: This review underscores the global distribution of HIV subtypes, with an increasing prevalence of CRFs and a lower prevalence of subtype C. Data on HIV-2 were limited. Understanding subtype diversity is crucial for vaccine development, which need to elicit immune responses capable of targeting various subtypes. Further research is needed to enhance our knowledge and address the challenges posed by HIV subtype diversity.

Rapid Replacement of SARS-CoV-2 Variants by Delta and Subsequent Arrival of Omicron, Uganda, 2021.

Genomic surveillance in Uganda showed rapid replacement of severe acute respiratory syndrome coronavirus 2 over time by variants, dominated by Delta. However, detection of the more transmissible Omicron variant among travelers and increasing community transmission highlight the need for near-real-time genomic surveillance and adherence to infection control measures to prevent future pandemic waves.

A large population sample of African HIV genomes from the 1980s reveals a reduction in subtype D over time associated with propensity for CXCR4 tropism.

We present 109 near full-length HIV genomes amplified from blood serum samples obtained during early 1986 from across Uganda, which to our knowledge is the earliest and largest population sample from the initial phase of the HIV epidemic in Africa. Consensus sequences were made from paired-end Illumina reads with a target-capture approach to amplify HIV material following poor success with standard approaches. In comparisons with a smaller 'intermediate' genome dataset from 1998 to 1999 and a 'modern' genome dataset from 2007 to 2016, the proportion of subtype D was significantly higher initially, dropping from 67% (73/109), to 57% (26/46) to 17% (82/465) respectively (p < 0.0001). Subtype D has previously been shown to have a faster rate of disease progression than other subtypes in East African population studies, and to have a higher propensity to use the CXCR4 co-receptor ("X4 tropism"); associated with a decrease in time to AIDS. Here we find significant differences in predicted tropism between A1 and D subtypes in all three sample periods considered, which is particularly striking the 1986 sample: 66% (53/80) of subtype D env sequences were predicted to be X4 tropic compared with none of the 24 subtype A1. We also analysed the frequency of subtype in the envelope region of inter-subtype recombinants, and found that subtype A1 is over-represented in env, suggesting recombination and selection have acted to remove subtype D env from circulation. The reduction of subtype D frequency over three decades therefore appears to be a result of selective pressure against X4 tropism and its higher virulence. Lastly, we find a subtype D specific codon deletion at position 24 of the V3 loop, which may explain the higher propensity for subtype D to utilise X4 tropism.

HIV-1 drug resistance genotyping success rates and correlates of Dried-blood spots and plasma specimen genotyping failure in a resource-limited setting.

BACKGROUND: HIV-1 drug resistance genotyping is critical to the monitoring of antiretroviral treatment. Data on HIV-1 genotyping success rates of different laboratory specimen types from multiple sources is still scarce. METHODS: In this cross-sectional study, we determined the laboratory genotyping success rates (GSR) and assessed the correlates of genotyping failure of 6837 unpaired dried blood spot (DBS) and plasma specimens. Specimens from multiple studies in a resource-constrained setting were analysed in our laboratory between 2016 and 2019. RESULTS: We noted an overall GSR of 65.7% and specific overall GSR for DBS and plasma of 49.8% and 85.9% respectively. The correlates of genotyping failure were viral load (VL) < 10,000 copies/mL (aOR 0.3 95% CI: 0.24-0.38; p < 0.0001), lack of viral load testing prior to genotyping (OR 0.85 95% CI: 0.77-0.94; p = 0.002), use of DBS specimens (aOR 0.10 95% CI: 0.08-0.14; p < 0.0001) and specimens from routine clinical diagnosis (aOR 1.4 95% CI: 1.10-1.75; p = 0.005). CONCLUSIONS: We report rapidly decreasing HIV-1 genotyping success rates between 2016 and 2019 with increased use of DBS specimens for genotyping and note decreasing median viral loads over the years. We recommend improvement in DBS handling, pre-genotyping viral load testing to screen samples to enhance genotyping success and the development of more sensitive assays with well-designed primers to genotype specimens with low or undetectable viral load, especially in this era where virological suppression rates are rising due to increased antiretroviral therapy roll-out.

Employing phylogenetic tree shape statistics to resolve the underlying host population structure.

BACKGROUND: Host population structure is a key determinant of pathogen and infectious disease transmission patterns. Pathogen phylogenetic trees are useful tools to reveal the population structure underlying an epidemic. Determining whether a population is structured or not is useful in informing the type of phylogenetic methods to be used in a given study. We employ tree statistics derived from phylogenetic trees and machine learning classification techniques to reveal an underlying population structure. RESULTS: In this paper, we simulate phylogenetic trees from both structured and non-structured host populations. We compute eight statistics for the simulated trees, which are: the number of cherries; Sackin, Colless and total cophenetic indices; ladder length; maximum depth; maximum width, and width-to-depth ratio. Based on the estimated tree statistics, we classify the simulated trees as from either a non-structured or a structured population using the decision tree (DT), K-nearest neighbor (KNN) and support vector machine (SVM). We incorporate the basic reproductive number ([Formula: see text]) in our tree simulation procedure. Sensitivity analysis is done to investigate whether the classifiers are robust to different choice of model parameters and to size of trees. Cross-validated results for area under the curve (AUC) for receiver operating characteristic (ROC) curves yield mean values of over 0.9 for most of the classification models. CONCLUSIONS: Our classification procedure distinguishes well between trees from structured and non-structured populations using the classifiers, the two-sample Kolmogorov-Smirnov, Cucconi and Podgor-Gastwirth tests and the box plots. SVM models were more robust to changes in model parameters and tree size compared to KNN and DT classifiers. Our classification procedure was applied to real -world data and the structured population was revealed with high accuracy of [Formula: see text] using SVM-polynomial classifier.

HIV drug resistance among adults initiating antiretroviral therapy in Uganda.

BACKGROUND: WHO revised their HIV drug resistance (HIVDR) monitoring strategy in 2014, enabling countries to generate nationally representative HIVDR prevalence estimates from surveys conducted using this methodology. In 2016, we adopted this strategy in Uganda and conducted an HIVDR survey among adults initiating or reinitiating ART. METHODS: A cross-sectional survey of adults aged ≥18 years initiating or reinitiating ART was conducted at 23 sites using a two-stage cluster design sampling method. Participants provided written informed consent prior to enrolment. Whole blood collected in EDTA vacutainer tubes was used for preparation of dried blood spot (DBS) specimens or plasma. Samples were shipped from the sites to the Central Public Health Laboratory (CPHL) for temporary storage before transfer to the Uganda Virus Research Institute (UVRI) for genotyping. Prevalence of HIVDR among adults initiating or reinitiating ART was determined. RESULTS: Specimens from 491 participants (median age 32 years and 61.5% female) were collected between August and December 2016. Specimens from 351 participants were successfully genotyped. Forty-nine had drug resistance mutations, yielding an overall weighted HIVDR prevalence of 18.2% with the highest noted for NNRTIs at 14.1%. CONCLUSIONS: We observed a high HIVDR prevalence for NNRTIs among adults prior to initiating or reinitiating ART in Uganda. This is above WHO's recommended threshold of 10% when countries should consider changing from NNRTI- to dolutegravir-based first-line regimens. This recommendation was adopted in the revised Ugandan ART guidelines. Dolutegravir-containing ART regimens are preferred for first- and second-line ART regimens.

Main Routes of Entry and Genomic Diversity of SARS-CoV-2, Uganda.

We established rapid local viral sequencing to document the genomic diversity of severe acute respiratory syndrome coronavirus 2 entering Uganda. Virus lineages closely followed the travel origins of infected persons. Our sequence data provide an important baseline for tracking any further transmission of the virus throughout the country and region.

Prevalence of viral load suppression, predictors of virological failure and patterns of HIV drug resistance after 12 and 48 months on first-line antiretroviral therapy: a national cross-sectional survey in Uganda.

OBJECTIVES: We implemented the WHO cross-sectional survey protocol to determine rates of HIV viral load (VL) suppression (VLS), and weighted prevalence, predictors and patterns of acquired drug resistance (ADR) in individuals with virological failure (VF) defined as VL ≥1000 copies/mL. METHODS: We enrolled 547 and 1064 adult participants on first-line ART for 12 (±3) months (ADR12) and ≥48 months (ADR48), respectively. Dried blood spots and plasma specimens were collected for VL testing and genotyping among the VFs. RESULTS: VLS was 95.0% (95% CI 93.4%-96.5%) in the ADR12 group and 87.9% (95% CI 85.0%-90.9%) in the ADR48 group. The weighted prevalence of ADR was 96.1% (95% CI 72.9%-99.6%) in the ADR12 and 90.4% (95% CI 73.6-96.8%) in the ADR48 group, out of the 30 and 95 successful genotypes in the respective groups. Initiation on a zidovudine-based regimen compared with a tenofovir-based regimen was significantly associated with VF in the ADR48 group; adjusted OR (AOR) 1.96 (95% CI 1.13-3.39). Independent predictors of ADR in the ADR48 group were initiation on a zidovudine-based regimen compared with tenofovir-based regimens, AOR 3.16 (95% CI 1.34-7.46) and ART duration of ≥82 months compared with <82 months, AOR 1.92 (95% CI 1.03-3.59). CONCLUSIONS: While good VLS was observed, the high prevalence of ADR among the VFs before they underwent the recommended three intensive adherence counselling (IAC) sessions followed by repeat VL testing implies that IAC prior to treatment switching may be of limited benefit in improving VLS.

Rates of HIV-1 virological suppression and patterns of acquired drug resistance among fisherfolk on first-line antiretroviral therapy in Uganda.

OBJECTIVES: We examined virological outcomes, patterns of acquired HIV drug resistance (ADR), correlates of virological failure (VF) and acquired drug resistance among fisherfolk on first-line ART. METHODS: We enrolled 1169 adults on ART for a median duration of 6, 12, 24, 36 and ≥48 months and used a pooled VL testing approach to identify VF (VL ≥1000 copies/mL). We performed genotyping among VF cases and determined correlates of VF and ADR by logistic regression. RESULTS: The overall virological suppression rate was 91.7% and ADR was detected in 71/97 (73.2%) VF cases. The most prevalent mutations were M184V/I (53.6%) for NRTIs and K103N (39.2%) for NNRTIs. Thymidine analogue mutations were detected in 21.6% of VF cases while PI mutations were absent. A zidovudine-based ART regimen, duration on ART (≥24 months) and secondary/higher education level were significantly associated with VF. A nevirapine-based regimen [adjusted OR (aOR): 1.87; 95% CI: 0.03-0.54)] and VL ≥10000 copies/mL (aOR: 3.48; 95% CI: 1.37-8.85) were ADR correlates. The pooling strategies for VL testing with a negative predictive value (NPV) of ≥95.2% saved US $20320 (43.5%) in VL testing costs. CONCLUSIONS: We observed high virological suppression rates among these highly mobile fisherfolk; however, there was widespread ADR among those with VF at the first VL testing prior to intensive adherence counselling. Timely treatment switching and adherence support is recommended for better treatment outcomes. Adoption of pooled VL testing could be cost effective, particularly in resource-limited settings.

Sustained virological response and drug resistance among female sex workers living with HIV on antiretroviral therapy in Kampala, Uganda: a cross-sectional study.

OBJECTIVES: We assessed the prevalence and risk factors associated with virological failure among female sex workers living with HIV on antiretroviral therapy (ART) in Kampala, Uganda. METHODS: We conducted a cross-sectional study between January 2015 and December 2016 using routinely collected data at a research clinic providing services to women at high risk of STIs including HIV. Plasma samples were tested for viral load from HIV-seropositive women aged ≥18 years who had been on ART for at least 6 months and had received adherence counselling. Samples from women with virological failure (≥1000 copies/mL) were tested for HIV drug resistance by population-based sequencing. We used logistic regression to identify factors associated with virological failure. RESULTS: Of 584 women, 432 (74%) with a mean age of 32 (SD 6.5) were assessed, and 38 (9%) were found to have virological failure. HIV resistance testing was available for 78% (28/38), of whom 82.1% (23/28) had at least one major drug resistance mutation (DRM), most frequently M184V (70%, 16/23) and K103N (65%, 15/23). In multivariable analysis, virological failure was associated with participant age 18-24 (adjusted OR (aOR)=5.3, 95% CI 1.6 to 17.9), self-reported ART non-adherence (aOR=2.6, 95% CI 1.2 to 5.8) and baseline CD4+ T-cell count ≤350 cells/mm3 (aOR=3.1, 95% CI 1.4 to 7.0). CONCLUSIONS: A relatively low prevalence of virological failure but high rate of DRM was found in this population at high risk of transmission. Younger age, self-reported ART non-adherence and low CD4+ T-cell count on ART initiation were associated with increased risk of virological failure.

Characterization of the Neutralizing Antibody Response in a Case of Genetically Linked HIV Superinfection.

This report describes the identification of a genetically confirmed linked heterosexual human immunodeficiency virus (HIV) superinfection (HIV-SI) in a woman with chronic HIV infection who acquired a second strain of the virus from her husband. Serum neutralizing antibody (NAb) responses against their homologous and heterologous viruses, including the superinfecting strain, in the woman and her husband were examined before and after onset of HIV-SI. The woman displayed a moderately potent and broad anti-HIV NAb response prior to superinfection but did not possess NAb activity against the superinfecting strain. This case highlights the unique potential of linked HIV-SI studies to examine natural protection from HIV infection.

Designing a course model for distance-based online bioinformatics training in Africa: The H3ABioNet experience.

Africa is not unique in its need for basic bioinformatics training for individuals from a diverse range of academic backgrounds. However, particular logistical challenges in Africa, most notably access to bioinformatics expertise and internet stability, must be addressed in order to meet this need on the continent. H3ABioNet (www.h3abionet.org), the Pan African Bioinformatics Network for H3Africa, has therefore developed an innovative, free-of-charge "Introduction to Bioinformatics" course, taking these challenges into account as part of its educational efforts to provide on-site training and develop local expertise inside its network. A multiple-delivery-mode learning model was selected for this 3-month course in order to increase access to (mostly) African, expert bioinformatics trainers. The content of the course was developed to include a range of fundamental bioinformatics topics at the introductory level. For the first iteration of the course (2016), classrooms with a total of 364 enrolled participants were hosted at 20 institutions across 10 African countries. To ensure that classroom success did not depend on stable internet, trainers pre-recorded their lectures, and classrooms downloaded and watched these locally during biweekly contact sessions. The trainers were available via video conferencing to take questions during contact sessions, as well as via online "question and discussion" forums outside of contact session time. This learning model, developed for a resource-limited setting, could easily be adapted to other settings.

Analysis of the history and spread of HIV-1 in Uganda using phylodynamics.

HIV prevalence has decreased in Uganda since the 1990s, but remains substantial within high-risk groups. Here, we reconstruct the history and spread of HIV subtypes A1 and D in Uganda and explore the transmission dynamics in high-risk populations. We analysed HIV pol sequences from female sex workers in Kampala (n = 42), Lake Victoria fisher-folk (n = 46) and a rural clinical cohort (n = 74), together with publicly available sequences from adjacent regions in Uganda (n = 412) and newly generated sequences from samples taken in Kampala in 1986 (n = 12). Of the sequences from the three Ugandan populations, 60 (37.1 %) were classified as subtype D, 54 (33.3 %) as subtype A1, 31 (19.1 %) as A1/D recombinants, six (3.7 %) as subtype C, one (0.6 %) as subtype G and 10 (6.2 %) as other recombinants. Among the A1/D recombinants we identified a new candidate circulating recombinant form. Phylodynamic and phylogeographic analyses using BEAST indicated that the Ugandan epidemics originated in 1960 (1950-1968) for subtype A1 and 1973 (1970-1977) for D, in rural south-western Uganda with subsequent spread to Kampala. They also showed extensive interconnection with adjacent countries. The sequence analysis shows both epidemics grew exponentially during the 1970s-1980s and decreased from 1992, which agrees with HIV prevalence reports in Uganda. Inclusion of sequences from the 1980s indicated the origin of both epidemics was more recent than expected and substantially narrowed the confidence intervals in comparison to previous estimates. We identified three transmission clusters and ten pairs, none of them including patients from different populations, suggesting active transmission within a structured transmission network.

Near full-length genome analysis of the first-reported HIV-1 Circulating Recombinant Form (CRF)_10CD in Uganda.

HIV-1 is characterized by remarkable genetic diversity resulting from its high replication rate, error-prone reverse transcriptase enzyme and recombination events. In Uganda, HIV-1 subtype diversity is mostly dominated by subtypes A, D, and A1/D Unique Recombinant Forms (URFs). In this study, deep sequences of HIV from patients with known antiretroviral therapy (ART) status were analyzed to determine the subtypes and to identify drug-resistance mutations circulating in the study population. Of the 187 participant samples processed for next-generation sequencing (NGS), 137 (73%) were successfully classified. The majority of HIV-1 strains were classified as subtype A (75, 55%), D (43, 31%), with other subtypes including C (3, 2%), A1/D (9, 7%) and CRF10_CD (1, <1%). Recombinant analysis of 9 complete A1/D HIV genomes identified novel recombination patterns described herein. Furthermore, we report for the first time in Uganda, an HIV-1 CRF10_CD strain from a fisherfolk in a Lake Victoria Island fishing community.

HIVseqDB: a portable resource for NGS and sample metadata integration for HIV-1 drug resistance analysis.

Summary: Human immunodeficiency virus (HIV) remains a public health threat, with drug resistance being a major concern in HIV treatment. Next-generation sequencing (NGS) is a powerful tool for identifying low-abundance drug resistance mutations (LA-DRMs) that conventional Sanger sequencing cannot reliably detect. To fully understand the significance of LA-DRMs, it is necessary to integrate NGS data with clinical and demographic data. However, freely available tools for NGS-based HIV-1 drug resistance analysis do not integrate these data. This poses a challenge in interpretation of the impact of LA-DRMs, mainly for resource-limited settings due to the shortage of bioinformatics expertise. To address this challenge, we present HIVseqDB, a portable, secure, and user-friendly resource for integrating NGS data with associated clinical and demographic data for analysis of HIV drug resistance. HIVseqDB currently supports uploading of NGS data and associated sample data, HIV-1 drug resistance data analysis, browsing of uploaded data, and browsing and visualizing of analysis results. Each function of HIVseqDB corresponds to an individual Django application. This ensures efficient incorporation of additional features with minimal effort. HIVseqDB can be deployed on various computing environments, such as on-premises high-performance computing facilities and cloud-based platforms. Availability and implementation: HIVseqDB is available at https://github.com/AlfredUg/HIVseqDB. A deployed instance of HIVseqDB is available at https://hivseqdb.org.

Increasing intra- and inter-subtype HIV diversity despite declining HIV incidence in Uganda.

HIV incidence has been declining in Africa with scale-up of HIV interventions. However, there is limited data on HIV evolutionary trends in African populations with waning epidemics. We evaluated changes in HIV viral diversity and genetic divergence in southern Uganda over a twenty-five-year period spanning the introduction and scale-up of HIV prevention and treatment programs using HIV sequence and survey data from the Rakai Community Cohort Study, an open longitudinal population-based HIV surveillance cohort. Gag (p24) and env (gp41) HIV data were generated from persons living with HIV (PLHIV) in 31 inland semi-urban trading and agrarian communities (1994 to 2018) and four hyperendemic Lake Victoria fishing communities (2011 to 2018) under continuous surveillance. HIV subtype was assigned using the Recombination Identification Program with phylogenetic confirmation. Inter-subtype diversity was estimated using the Shannon diversity index and intra-subtype diversity with the nucleotide diversity and pairwise TN93 genetic distance. Genetic divergence was measured using root-to-tip distance and pairwise TN93 genetic distance analyses. Evolutionary dynamics were assessed among demographic and behavioral sub-groups, including by migration status. 9,931 HIV sequences were available from 4,999 PLHIV, including 3,060 and 1,939 persons residing in inland and fishing communities, respectively. In inland communities, subtype A1 viruses proportionately increased from 14.3% in 1995 to 25.9% in 2017 (p<0.001), while those of subtype D declined from 73.2% in 1995 to 28.2% in 2017 (p<0.001). The proportion of viruses classified as recombinants significantly increased by more than four-fold. Inter-subtype HIV diversity has generally increased. While p24 intra-subtype genetic diversity and divergence leveled off after 2014, diversity and divergence of gp41 increased through 2017. Inter- and intra-subtype viral diversity increased across all population sub-groups, including among individuals with no recent migration history or extra-community sexual partners. This study provides insights into population-level HIV evolutionary dynamics in declining African HIV epidemics following the scale-up of HIV prevention and treatment programs. Continued molecular surveillance may provide a better understanding of the dynamics driving population HIV evolution and yield important insights for epidemic control and vaccine development.

Transmitted antiretroviral drug resistance among drug-naive female sex workers with recent infection in Kampala, Uganda.

During 2006-2007, transmitted human immunodeficiency virus (HIV) drug resistance (TDR) among drug-naive women with newly diagnosed HIV infection and likely to be recently infected when attending antenatal clinics in Entebbe was found to be <5% with use of the World Health Organization (WHO) survey method. Using the same method, we attempted to classify TDR among women who seroconverted during 2008-2010 and who were identified from a cohort of recently infected sex workers in Kampala, Uganda. TDR mutations were identified using the 2009 WHO TDR mutations list. The WHO survey method could not be used to classify TDR because the necessary sample size was not reached during the survey period. However, a point prevalence estimate of 2.6% (95% confidence interval, 0.07%-13.8%) nonnucleoside reverse-transcriptase inhibitor TDR was determined.

QuasiFlow: a Nextflow pipeline for analysis of NGS-based HIV-1 drug resistance data.

Summary: Next-generation sequencing (NGS) enables reliable detection of resistance mutations in minority variants of human immunodeficiency virus type 1 (HIV-1). There is paucity of evidence for the association of minority resistance to treatment failure, and this requires evaluation. However, the tools for analyzing HIV-1 drug resistance (HIVDR) testing data are mostly web-based which requires uploading data to webservers. This is a challenge for laboratories with internet connectivity issues and instances with restricted data transfer across networks. We present QuasiFlow, a pipeline for reproducible analysis of NGS-based HIVDR testing data across different computing environments. Since QuasiFlow entirely depends on command-line tools and a local copy of the reference database, it eliminates challenges associated with uploading HIV-1 NGS data onto webservers. The pipeline takes raw sequence reads in FASTQ format as input and generates a user-friendly report in PDF/HTML format. The drug resistance scores obtained using QuasiFlow were 100% and 99.12% identical to those obtained using web-based HIVdb program and HyDRA web respectively at a mutation detection threshold of 20%. Availability and implementation: QuasiFlow and corresponding documentation are publicly available at https://github.com/AlfredUg/QuasiFlow. The pipeline is implemented in Nextflow and requires regular updating of the Stanford HIV drug resistance interpretation algorithm. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Detection of HIV-1 Transmission Clusters from Dried Blood Spots within a Universal Test-and-Treat Trial in East Africa.

The Sustainable East Africa Research in Community Health (SEARCH) trial was a universal test-and-treat (UTT) trial in rural Uganda and Kenya, aiming to lower regional HIV-1 incidence. Here, we quantify breakthrough HIV-1 transmissions occurring during the trial from population-based, dried blood spot samples. Between 2013 and 2017, we obtained 549 gag and 488 pol HIV-1 consensus sequences from 745 participants: 469 participants infected prior to trial commencement and 276 SEARCH-incident infections. Putative transmission clusters, with a 1.5% pairwise genetic distance threshold, were inferred from maximum likelihood phylogenies; clusters arising after the start of SEARCH were identified with Bayesian time-calibrated phylogenies. Our phylodynamic approach identified nine clusters arising after the SEARCH start date: eight pairs and one triplet, representing mostly opposite-gender linked (6/9), within-community transmissions (7/9). Two clusters contained individuals with non-nucleoside reverse transcriptase inhibitor (NNRTI) resistance, both linked to intervention communities. The identification of SEARCH-incident, within-community transmissions reveals the role of unsuppressed individuals in sustaining the epidemic in both arms of a UTT trial setting. The presence of transmitted NNRTI resistance, implying treatment failure to the efavirenz-based antiretroviral therapy (ART) used during SEARCH, highlights the need to improve delivery and adherence to up-to-date ART recommendations, to halt HIV-1 transmission.

Phylogenetic Networks and Parameters Inferred from HIV Nucleotide Sequences of High-Risk and General Population Groups in Uganda: Implications for Epidemic Control.

Phylogenetic inference is useful in characterising HIV transmission networks and assessing where prevention is likely to have the greatest impact. However, estimating parameters that influence the network structure is still scarce, but important in evaluating determinants of HIV spread. We analyzed 2017 HIV pol sequences (728 Lake Victoria fisherfolk communities (FFCs), 592 female sex workers (FSWs) and 697 general population (GP)) to identify transmission networks on Maximum Likelihood (ML) phylogenetic trees and refined them using time-resolved phylogenies. Network generative models were fitted to the observed degree distributions and network parameters, and corrected Akaike Information Criteria and Bayesian Information Criteria values were estimated. 347 (17.2%) HIV sequences were linked on ML trees (maximum genetic distance ≤4.5%, ≥95% bootstrap support) and, of these, 303 (86.7%) that consisted of pure A1 (n = 168) and D (n = 135) subtypes were analyzed in BEAST v1.8.4. The majority of networks (at least 40%) were found at a time depth of ≤5 years. The waring and yule models fitted best networks of FFCs and FSWs respectively while the negative binomial model fitted best networks in the GP. The network structure in the HIV-hyperendemic FFCs is likely to be scale-free and shaped by preferential attachment, in contrast to the GP. The findings support the targeting of interventions for FFCs in a timely manner for effective epidemic control. Interventions ought to be tailored according to the dynamics of the HIV epidemic in the target population and understanding the network structure is critical in ensuring the success of HIV prevention programs.