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  • 1
    In: Emerging Infectious Diseases, Centers for Disease Control and Prevention (CDC), Vol. 28, No. 5 ( 2022-05), p. 1021-1025
    Type of Medium: Online Resource
    ISSN: 1080-6040 , 1080-6059
    Language: English
    Publisher: Centers for Disease Control and Prevention (CDC)
    Publication Date: 2022
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  • 2
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 378, No. 6615 ( 2022-10-07)
    Abstract: Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century. Expanse of SARS-CoV-2 sequencing capacity in Africa. ( A ) African countries (shaded in gray) and institutions (red circles) with on-site sequencing facilities that are capable of producing SARS-CoV-2 whole genomes locally. ( B ) The number of SARS-CoV-2 genomes produced per country and the proportion of those genomes that were produced locally, regionally within Africa, or abroad. ( C ) Decreased turnaround time of sequencing output in Africa to an almost real-time release of genomic data.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2022
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  • 3
    In: Bioinformatics Advances, Oxford University Press (OUP)
    Abstract: 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, browsing and visualizing of analysis results. Each function of HIVseqDB corresponds to an individual Django application. This ensures efficient incor-poration 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 HIVseqDB is available at https://github.com/AlfredUg/HIVseqDB. A deployed instance of HIVseqDB is available at https://hivseqdb.org. Supplementary information Supplementary data are available at Bioinformatics Advances online.
    Type of Medium: Online Resource
    ISSN: 2635-0041
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2024
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  • 4
    In: Viruses, MDPI AG, Vol. 12, No. 11 ( 2020-11-10), p. 1283-
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 1999-4915
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
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  • 5
    In: Viruses, MDPI AG, Vol. 13, No. 6 ( 2021-05-24), p. 970-
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 1999-4915
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
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  • 6
    In: Bioinformatics Advances, Oxford University Press (OUP), Vol. 2, No. 1 ( 2022-01-10)
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 2635-0041
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
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  • 7
    In: The Journal of Infectious Diseases, Oxford University Press (OUP), ( 2023-08-18)
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0022-1899 , 1537-6613
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    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
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  • 8
    In: Journal of Antimicrobial Chemotherapy, Oxford University Press (OUP), Vol. 74, No. 10 ( 2019-10-01), p. 3021-3029
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0305-7453 , 1460-2091
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
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  • 9
    In: BMC Bioinformatics, Springer Science and Business Media LLC, Vol. 22, No. 1 ( 2021-11-10)
    Abstract: 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 ( $$R_0$$ R 0 ) 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 $$92.3\%$$ 92.3 % using SVM-polynomial classifier.
    Type of Medium: Online Resource
    ISSN: 1471-2105
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
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    SSG: 12
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  • 10
    In: BMC Infectious Diseases, Springer Science and Business Media LLC, Vol. 22, No. 1 ( 2022-12)
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 1471-2334
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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