The 2023 South Sudanese outbreak of Hepatitis E emphasizes ongoing circulation of genotype 1 in North, Central, and East Africa.

In April 2023, an outbreak of acute hepatitis was reported amongst internally displaced persons in the Nazareth community of South Sudan. IgM serology-based screening suggested the likely etiologic agent to be Hepatitis E virus (HEV). In this study, plasma specimens collected from anti-HEV IgM-positive cases were subjected to additional RT-qPCR testing and sequencing of extracted nucleic acids, resulting in the recovery of five full and eight partial HEV genomes. Maximum likelihood phylogenetic reconstruction confirmed the genomes belong to HEV genotype 1. Using distance-based methods, we show that genotype 1 is best split into three sub-genotypes instead of the previously proposed seven, and that these sub-genotypes are geographically restricted. The South Sudanese sequences confidently cluster within sub-genotype 1e, endemic to northeast, central, and east Africa. Bayesian Inference of phylogeny incorporating sampling dates shows that this new outbreak is not directly descended from other recent local outbreaks for which sequence data is available. However, the analysis suggests that sub-genotype 1e has been consistently and cryptically circulating locally for at least the past half century and that the known outbreaks are often not directly descended from one another. The ongoing presence of HEV, combined with poor sanitation and hygiene in the conflict-affected areas in the region, place vulnerable populations at risk for infection and its more serious effects, including progression to fulminant hepatitis.

Next-Generation Sequencing Reveals a High Frequency of HIV-1 Minority Variants and an Expanded Drug Resistance Profile among Individuals on First-Line ART.

We assessed the performance and clinical relevance of Illumina MiSeq next-generation sequencing (NGS) for HIV-1 genotyping compared with Sanger sequencing (SS). We analyzed 167 participants, 45 with virologic failure (VL ≥ 1000 copies/mL), i.e., cases, and 122 time-matched participants with virologic suppression (VL < 1000 copies/mL), i.e., controls, 12 months post-ART initiation. Major surveillance drug resistance mutations (SDRMs) detected by SS were all detectable by NGS. Among cases at 12 months, SS identified SDRMs in 32/45 (71.1%) while NGS identified SDRMs among 35/45 (77.8%), increasing the number of cases with SDRMs by 3/45 (6.7%). Participants identified with, and proportions of major SDRMs increased when NGS was used. NGS vs. SS at endpoint revealed for NNRTIs: 36/45 vs. 33/45; Y181C: 26/45 vs. 24/45; K103N: 9/45 vs. 6/45 participants with SDRMs, respectively. At baseline, NGS revealed major SDRMs in 9/45 (20%) cases without SDRMs by SS. Participant MBL/043, among the nine, the following major SDRMs existed: L90M to PIs, K65R and M184V to NRTIs, and Y181C and K103N to NNRTIs. The SDRMs among the nine increased SDRMs to NRTIs, NNRTIs, and PIs. Only 43/122 (25.7%) of participants had pre-treatment minority SDRMs. Also, 24.4% of the cases vs. 26.2 of controls had minority SDRMs (p = 0.802); minority SDRMs were not associated with virologic failure. NGS agreed with SS in HIV-1 genotyping but detected additional major SDRMs and identified more participants harboring major SDRMs, expanding the HIV DRM profile of this cohort. NGS could improve HIV genotyping to guide treatment decisions for enhancing ART efficacy, a cardinal pre-requisite in the pursuit of the UNAIDS 95-95-95 targets.

Sequence Notes: 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 nine 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Evaluation of the performance of 25 SARS-CoV-2 serological rapid diagnostic tests using a reference panel of plasma specimens at the Uganda Virus Research Institute.

INTRODUCTION: Serological testing is needed to better understand the epidemiology of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Rapid diagnostic tests (RDTs) have been developed to detect specific antibodies, IgM and IgG, to the virus. The performance of 25 of these RDTs was evaluated. METHODS: A serological reference panel of 50 positive and 100 negative plasma specimens was developed from SARS-CoV-2 PCR and antibody positive patients and pre-pandemic SARS-CoV-2-negative specimens collected in 2016. Test performance of the 25 RDTs was evaluated against this panel. RESULTS: A total of 10 RDTs had a sensitivity ≥98%, while 13 RDTs had a specificity ≥98% to anti-SARS-CoV-2 IgG antibodies. Four RDTs (Boson, MultiG, Standard Q, and VivaDiag) had both sensitivity and specificity ≥98% to anti-SARS-CoV-2 IgG antibodies. Only three RDTs had a sensitivity ≥98%, while 10 RDTs had a specificity ≥98% to anti-SARS-CoV-2 IgM antibodies. Three RDTs (Autobio, MultiG, and Standard Q) had sensitivity and specificity ≥98% to combined IgG/IgM. The RDTs that performed well also had perfect or almost perfect inter-reader agreement. CONCLUSIONS: This evaluation identified three RDTs with a sensitivity and specificity to IgM/IgG antibodies of ≥98% with the potential for widespread antibody testing in Uganda.

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.

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.

Short Communication: Validation of the Asante HIV-1 Rapid Recency Assay for Detection of Recent HIV-1 Infections in Uganda.

Point of care rapid recency testing for HIV-1 may be a cost-effective tool to identify recently infected individuals for incidence estimation, and focused HIV prevention through intensified contact tracing. We validated the Asante™ HIV-1 rapid recency® assay for use in Uganda. Archived specimens (serum/plasma), collected from longitudinally observed HIV-1 recently and long-term infected participants, were tested with the Asante HIV-1 rapid recency assay per manufacturer's instructions. Previously identified antiretroviral therapy (ART)-naive samples with known seroconversions within 6 months of follow-up were tested in independent laboratories: the Rakai Health Sciences Program (RHSP) and the Uganda Virus Research Institute HIV Reference Laboratory (UVRI-HRL). In addition, samples from participants who seroconverted within 6-18 months and samples from individuals with chronic HIV-1 infection of at least 18 months duration were classified into three categories: ART naive, ART exposed with suppressed viral loads, and ART exposed with detectable viremia. Of the 85 samples seroconverting in ≤6 months, 27 and 42 samples were identified as "recent" by the Asante HIV-1 rapid recency test at the RHSP laboratory and UVRI-HRL, corresponding to sensitivities of 32% and 49%, respectively. There was 72% agreement between the laboratories (Cohen's kappa = 0.481, 95% CI = 0.317-0.646, p < .0001). Specificity was 100% (200/200) among chronically infected ART-naive samples. The Asante HIV-1 rapid recency assay had low sensitivity for detection of recent HIV-1 infections in Uganda, with substantial interlaboratory variability due to differential interpretation of the test strip bands. Specificity was excellent. Assessment of assay performance in other settings is needed to guide decisions on test utility.

Field evaluation of the performance of a SARS-CoV-2 antigen rapid diagnostic test in Uganda using nasopharyngeal samples.

OBJECTIVES: There is a high demand for SARS-CoV-2 testing to identify COVID-19 cases. Real-time quantitative PCR (qRT-PCR) is the recommended diagnostic test but a number of constraints prevent its widespread implementation, including cost. The aim of this study was to evaluate a low cost and easy to use rapid antigen test for diagnosing COVID-19 at the point of care. METHODS: Nasopharyngeal swabs from suspected COVID-19 cases and low-risk volunteers were tested with the STANDARD Q COVID-19 Ag Test and the results were compared with the qRT-PCR results. RESULTS: In total, 262 samples were collected, including 90 qRT-PCR positives. The majority of samples were from males (89%) with a mean age of 34 years and only 13 (14%) of the positives were mildly symptomatic. The sensitivity and specificity of the antigen test were 70.0% (95% confidence interval (CI): 60-79) and 92% (95% CI: 87-96), respectively, and the diagnostic accuracy was 84% (95% CI: 79-88). The antigen test was more likely to be positive for samples with qRT-PCR Ct values ≤29, with a sensitivity of 92%. CONCLUSIONS: The STANDARD Q COVID-19 Ag Test performed less than optimally in this evaluation. However, the test may still have an important role to play early in infection when timely access to molecular testing is not available but the results should be confirmed by qRT-PCR.

The Molecular Epidemiology and Transmission Dynamics of HIV Type 1 in a General Population Cohort in Uganda.

The General Population Cohort (GPC) in south-western Uganda has a low HIV-1 incidence rate (<1%). However, new infections continue to emerge. In this research, 3796 HIV-1 pol sequences (GPC: n = 1418, non-GPC sites: n = 1223, Central Uganda: n = 1010 and Eastern Uganda: n = 145) generated between 2003-2015 were analysed using phylogenetic methods with demographic data to understand HIV-1 transmission in this cohort and inform the epidemic response. HIV-1 subtype A1 was the most prevalent strain in the GPC area (GPC and non-GPC sites) (39.8%), central (45.9%) and eastern (52.4%) Uganda. However, in the GPC alone, subtype D was the predominant subtype (39.1%). Of the 524 transmission clusters identified by Cluster Picker, all large clusters (≥5 individuals, n = 8) involved individuals from the GPC. In a multivariate analysis, clustering was strongly associated with being female (adjusted Odds Ratio, aOR = 1.28; 95% CI, 1.06-1.54), being >25 years (aOR = 1.52; 95% CI, 1.16-2.0) and being a resident in the GPC (aOR = 6.90; 95% CI, 5.22-9.21). Phylogeographic analysis showed significant viral dissemination (Bayes Factor test, BF > 3) from the GPC without significant viral introductions (BF < 3) into the GPC. The findings suggest localized HIV-1 transmission in the GPC. Intensifying geographically focused combination interventions in the GPC would contribute towards controlling HIV-1 infections.

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.

Short Communication: Choosing the Right Program for the Identification of HIV-1 Transmission Networks from Nucleotide Sequences Sampled from Different Populations.

HIV-TRAnsmission Cluster Engine (HIV-TRACE) and Cluster Picker are some of the most widely used programs for identifying HIV-1 transmission networks from nucleotide sequences. However, choosing between these tools is subjective and often a matter of personal preference. Because these software use different algorithms to detect HIV-1 transmission networks, their optimal use is better suited with different sequence data sets and under different scenarios. The performance of these tools has previously been evaluated across a range of genetic distance thresholds without an assessment of the differences in the structure of networks identified. In this study, we tested both programs on the same HIV-1 pol sequence data set (n = 2,017) from three Ugandan populations to examine their performance across different risk groups and evaluate the structure of networks identified. HIV-TRACE that uses a single-linkage algorithm identified more nodes in the same networks that were connected by sparse links than Cluster Picker. This suggests that the choice of the program used for identifying networks should depend on the study aims, the characteristics of the population being investigated, dynamics of the epidemic, sampling design, and the nature of research questions being addressed for optimum results. HIV-TRACE could be more applicable with larger data sets where the aim is to identify larger clusters that represent distinct transmission chains and in more diverse populations where infection has occurred over a period of time. In contrast, Cluster Picker is applicable in situations where more closely connected clusters are expected in the studied populations.