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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. Retrovirology 2022; 19:28. [PMID: 36514107 PMCID: PMC9746199 DOI: 10.1186/s12977-022-00612-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 11/12/2022] [Indexed: 12/15/2022] Open
Abstract
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.
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Optimized phylogenetic clustering of HIV-1 sequence data for public health applications. PLoS Comput Biol 2022; 18:e1010745. [PMID: 36449514 PMCID: PMC9744331 DOI: 10.1371/journal.pcbi.1010745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 12/12/2022] [Accepted: 11/17/2022] [Indexed: 12/02/2022] Open
Abstract
Clusters of genetically similar infections suggest rapid transmission and may indicate priorities for public health action or reveal underlying epidemiological processes. However, clusters often require user-defined thresholds and are sensitive to non-epidemiological factors, such as non-random sampling. Consequently the ideal threshold for public health applications varies substantially across settings. Here, we show a method which selects optimal thresholds for phylogenetic (subset tree) clustering based on population. We evaluated this method on HIV-1 pol datasets (n = 14, 221 sequences) from four sites in USA (Tennessee, Washington), Canada (Northern Alberta) and China (Beijing). Clusters were defined by tips descending from an ancestral node (with a minimum bootstrap support of 95%) through a series of branches, each with a length below a given threshold. Next, we used pplacer to graft new cases to the fixed tree by maximum likelihood. We evaluated the effect of varying branch-length thresholds on cluster growth as a count outcome by fitting two Poisson regression models: a null model that predicts growth from cluster size, and an alternative model that includes mean collection date as an additional covariate. The alternative model was favoured by AIC across most thresholds, with optimal (greatest difference in AIC) thresholds ranging 0.007-0.013 across sites. The range of optimal thresholds was more variable when re-sampling 80% of the data by location (IQR 0.008 - 0.016, n = 100 replicates). Our results use prospective phylogenetic cluster growth and suggest that there is more variation in effective thresholds for public health than those typically used in clustering studies.
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Cuadros DF, de Oliveira T, Gräf T, Junqueira DM, Wilkinson E, Lemey P, Bärnighausen T, Kim HY, Tanser F. The role of high-risk geographies in the perpetuation of the HIV epidemic in rural South Africa: A spatial molecular epidemiology study. PLOS GLOBAL PUBLIC HEALTH 2022; 2:e0000105. [PMID: 36962341 PMCID: PMC10021703 DOI: 10.1371/journal.pgph.0000105] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 11/15/2021] [Indexed: 11/18/2022]
Abstract
In this study, we hypothesize that HIV geographical clusters (geospatial areas with significantly higher numbers of HIV positive individuals) can behave as the highly connected nodes in the transmission network. Using data come from one of the most comprehensive demographic surveillance systems in Africa, we found that more than 70% of the HIV transmission links identified were directly connected to an HIV geographical cluster located in a peri-urban area. Moreover, we identified a single central large community of highly connected nodes located within the HIV cluster. This module was composed by nodes highly connected among them, forming a central structure of the network that was also connected with the small sparser modules located outside of the HIV geographical cluster. Our study supports the evidence of the high level of connectivity between HIV geographical high-risk populations and the entire community.
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Affiliation(s)
- Diego F. Cuadros
- Department of Geography and Geographic Information Science, University of Cincinnati, Cincinnati, OH, United States of America
- Health Geography and Disease Modeling Laboratory, University of Cincinnati, Cincinnati, OH, United States of America
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- School of Laboratory Medicine and Medical Science, Department of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Tiago Gräf
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- Fundação Oswaldo Cruz (FIOCRUZ), Instituto Gonçalo Moniz, Salvador, Brazil
| | - Dennis M. Junqueira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- School of Laboratory Medicine and Medical Science, Department of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Eduan Wilkinson
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- School of Laboratory Medicine and Medical Science, Department of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Philippe Lemey
- Department of Microbiology and Immunology, Rega Institute for Medical Research, University of Leuven, Leuven, Belgium
| | - Till Bärnighausen
- Africa Health Research Institute, University of KwaZulu-Natal, Durban, South Africa
- Heidelberg Institute for Public Health, University of Heidelberg, Heidelberg, Germany
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America
| | - Hae-Young Kim
- Africa Health Research Institute, University of KwaZulu-Natal, Durban, South Africa
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, United States of America
| | - Frank Tanser
- Africa Health Research Institute, University of KwaZulu-Natal, Durban, South Africa
- School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa
- Lincoln International Institute for Rural Health, University of Lincoln, Lincoln, United Kingdom
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa
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Hughes SD, Woods WJ, O'Keefe KJ, Delgado V, Pipkin S, Scheer S, Truong HHM. Integrating Phylogenetic Biomarker Data and Qualitative Approaches: An example of HIV Transmission Clusters as a Sampling Frame for Semistructured Interviews and Implications for the COVID-19 Era. JOURNAL OF MIXED METHODS RESEARCH 2021; 15:327-347. [PMID: 38883973 PMCID: PMC11178346 DOI: 10.1177/15586898211012786] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
Mixed methods studies of human disease that combine surveillance, biomarker, and qualitative data can help elucidate what drives epidemiological trends. Viral genetic data are rarely coupled with other types of data due to legal and ethical concerns about patient privacy. We developed a novel approach to integrate phylogenetic and qualitative methods in order to better target HIV prevention efforts. The overall aim of our mixed methods study was to characterize HIV transmission clusters. We combined surveillance data with HIV genomic data to identify cases whose viruses share enough similarities to suggest a recent common source of infection or participation in linked transmission chains. Cases were recruited through a multi-phase process to obtain consent for recruitment to semi-structured interviews. Through linkage of viral genetic sequences with epidemiological data, we identified individuals in large transmission clusters, which then served as a sampling frame for the interviews. In this article, we describe the multi-phase process and the limitations and challenges encountered. Our approach contributes to the mixed methods research field by demonstrating that phylogenetic analysis and surveillance data can be harnessed to generate a sampling frame for subsequent qualitative data collection, using an explanatory sequential design. The process we developed also respected protections of patient confidentiality. The novel method we devised may offer an opportunity to implement a sampling frame that allows for the recruitment and interview of individuals in high-transmission clusters to better understand what contributes to spread of other infectious diseases, including COVID-19.
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Affiliation(s)
| | | | - Kara J O'Keefe
- San Francisco Department of Public Health, San Francisco, CA, USA
| | - Viva Delgado
- San Francisco Department of Public Health, San Francisco, CA, USA
| | - Sharon Pipkin
- San Francisco Department of Public Health, San Francisco, CA, USA
| | - Susan Scheer
- San Francisco Department of Public Health, San Francisco, CA, USA
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Nduva GM, Nazziwa J, Hassan AS, Sanders EJ, Esbjörnsson J. The Role of Phylogenetics in Discerning HIV-1 Mixing among Vulnerable Populations and Geographic Regions in Sub-Saharan Africa: A Systematic Review. Viruses 2021; 13:1174. [PMID: 34205246 PMCID: PMC8235305 DOI: 10.3390/v13061174] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 06/09/2021] [Accepted: 06/10/2021] [Indexed: 12/19/2022] Open
Abstract
To reduce global HIV-1 incidence, there is a need to understand and disentangle HIV-1 transmission dynamics and to determine the geographic areas and populations that act as hubs or drivers of HIV-1 spread. In Sub-Saharan Africa (sSA), the region with the highest HIV-1 burden, information about such transmission dynamics is sparse. Phylogenetic inference is a powerful method for the study of HIV-1 transmission networks and source attribution. In this review, we assessed available phylogenetic data on mixing between HIV-1 hotspots (geographic areas and populations with high HIV-1 incidence and prevalence) and areas or populations with lower HIV-1 burden in sSA. We searched PubMed and identified and reviewed 64 studies on HIV-1 transmission dynamics within and between risk groups and geographic locations in sSA (published 1995-2021). We describe HIV-1 transmission from both a geographic and a risk group perspective in sSA. Finally, we discuss the challenges facing phylogenetic inference in mixed epidemics in sSA and offer our perspectives and potential solutions to the identified challenges.
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Affiliation(s)
- George M. Nduva
- Department of Translational Medicine, Lund University, 205 02 Malmö, Sweden; (G.M.N.); (J.N.); (A.S.H.)
- Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi 80108, Kenya;
| | - Jamirah Nazziwa
- Department of Translational Medicine, Lund University, 205 02 Malmö, Sweden; (G.M.N.); (J.N.); (A.S.H.)
| | - Amin S. Hassan
- Department of Translational Medicine, Lund University, 205 02 Malmö, Sweden; (G.M.N.); (J.N.); (A.S.H.)
- Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi 80108, Kenya;
| | - Eduard J. Sanders
- Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Kilifi 80108, Kenya;
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, The University of Oxford, Oxford OX1 2JD, UK
| | - Joakim Esbjörnsson
- Department of Translational Medicine, Lund University, 205 02 Malmö, Sweden; (G.M.N.); (J.N.); (A.S.H.)
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, The University of Oxford, Oxford OX1 2JD, UK
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Phylogenetic Networks and Parameters Inferred from HIV Nucleotide Sequences of High-Risk and General Population Groups in Uganda: Implications for Epidemic Control. Viruses 2021; 13:v13060970. [PMID: 34073846 PMCID: PMC8225143 DOI: 10.3390/v13060970] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 05/13/2021] [Accepted: 05/18/2021] [Indexed: 12/17/2022] Open
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.
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Valdano E, Okano JT, Colizza V, Mitonga HK, Blower S. Using mobile phone data to reveal risk flow networks underlying the HIV epidemic in Namibia. Nat Commun 2021; 12:2837. [PMID: 33990578 PMCID: PMC8121904 DOI: 10.1038/s41467-021-23051-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 04/08/2021] [Indexed: 12/22/2022] Open
Abstract
Twenty-six million people are living with HIV in sub-Saharan Africa; epidemics are widely dispersed, due to high levels of mobility. However, global elimination strategies do not consider mobility. We use Call Detail Records from 9 billion calls/texts to model mobility in Namibia; we quantify the epidemic-level impact by using a mathematical framework based on spatial networks. We find complex networks of risk flows dispersed risk countrywide: increasing the risk of acquiring HIV in some areas, decreasing it in others. Overall, 40% of risk was mobility-driven. Networks contained multiple risk hubs. All constituencies (administrative units) imported and exported risk, to varying degrees. A few exported very high levels of risk: their residents infected many residents of other constituencies. Notably, prevalence in the constituency exporting the most risk was below average. Large-scale networks of mobility-driven risk flows underlie generalized HIV epidemics in sub-Saharan Africa. In order to eliminate HIV, it is likely to become increasingly important to implement innovative control strategies that focus on disrupting risk flows.
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Affiliation(s)
- Eugenio Valdano
- Center for Biomedical Modeling, The Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Justin T Okano
- Center for Biomedical Modeling, The Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Vittoria Colizza
- INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique, IPLESP, Paris, France
| | - Honore K Mitonga
- Department of Epidemiology and Biostatistics, School of Public Health, University of Namibia, Windhoek, Namibia
| | - Sally Blower
- Center for Biomedical Modeling, The Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
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HIV epidemic in fishing communities in Uganda: A scoping review. PLoS One 2021; 16:e0249465. [PMID: 33793652 PMCID: PMC8016276 DOI: 10.1371/journal.pone.0249465] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 03/18/2021] [Indexed: 11/26/2022] Open
Abstract
Background Fishing communities in many Sub-Saharan African countries are a high-risk population group disproportionately affected by the HIV epidemic. In Uganda, literature on HIV in fishing communities has grown extensively since the first country’s documented case of HIV in a fishing community in 1985. The current study describes the status of the HIV burden, prevention, and treatment in Ugandan fishing communities. Method This scoping review was conducted based on the York Framework outlined by Arksey and O’Malley. We searched the PubMed, Embase, and Web of Science databases to identify relevant quantitative and qualitative studies on HIV incidence, HIV prevalence, HIV-related risk factors, HIV testing, antiretroviral therapy coverage and adherence, and interventions to improve treatment outcomes and reduce HIV risk factors. Results & conclusion We identified 52 papers and 2 reports. Thirty-four were quantitative, 17 qualitative, and 3 had a mixed-methods design. Eleven studies reported on the prevalence of HIV and 8 on HIV incidence; 9 studies documented factors associated with HIV incidence or HIV positive status; 10 studies reported on HIV testing coverage and/or associated factors; 7 reported on antiretroviral therapy coverage/adherence/outcomes; and 1 study reported on the impact of combination HIV interventions in fishing communities. This scoping review revealed a significant lack of evidence in terms of what works in HIV prevention and for improving adherence to ART, in contrast to the relatively large amount of evidence from observational quantitative and qualitative studies on HIV prevalence, incidence and related risk factors in Ugandan fishing communities. Intervention studies are urgently needed to fill the current evidence gaps in HIV prevention and ART adherence.
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Ssemwanga D, Bbosa N, Nsubuga RN, Ssekagiri A, Kapaata A, Nannyonjo M, Nassolo F, Karabarinde A, Mugisha J, Seeley J, Yebra G, Leigh Brown A, Kaleebu P. The Molecular Epidemiology and Transmission Dynamics of HIV Type 1 in a General Population Cohort in Uganda. Viruses 2020; 12:v12111283. [PMID: 33182587 PMCID: PMC7697205 DOI: 10.3390/v12111283] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 10/01/2020] [Accepted: 10/02/2020] [Indexed: 12/13/2022] Open
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.
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Affiliation(s)
- Deogratius Ssemwanga
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe 256, Uganda; (N.B.); (R.N.N.); (A.K.); (M.N.); (F.N.); (A.K.); (J.M.); (J.S.); (P.K.)
- Department of General Virology, Uganda Virus Research Institute, Entebbe 256, Uganda;
- Correspondence: ; Tel.: +256-(0)-417-704000
| | - Nicholas Bbosa
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe 256, Uganda; (N.B.); (R.N.N.); (A.K.); (M.N.); (F.N.); (A.K.); (J.M.); (J.S.); (P.K.)
| | - Rebecca N. Nsubuga
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe 256, Uganda; (N.B.); (R.N.N.); (A.K.); (M.N.); (F.N.); (A.K.); (J.M.); (J.S.); (P.K.)
| | - Alfred Ssekagiri
- Department of General Virology, Uganda Virus Research Institute, Entebbe 256, Uganda;
| | - Anne Kapaata
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe 256, Uganda; (N.B.); (R.N.N.); (A.K.); (M.N.); (F.N.); (A.K.); (J.M.); (J.S.); (P.K.)
| | - Maria Nannyonjo
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe 256, Uganda; (N.B.); (R.N.N.); (A.K.); (M.N.); (F.N.); (A.K.); (J.M.); (J.S.); (P.K.)
| | - Faridah Nassolo
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe 256, Uganda; (N.B.); (R.N.N.); (A.K.); (M.N.); (F.N.); (A.K.); (J.M.); (J.S.); (P.K.)
| | - Alex Karabarinde
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe 256, Uganda; (N.B.); (R.N.N.); (A.K.); (M.N.); (F.N.); (A.K.); (J.M.); (J.S.); (P.K.)
| | - Joseph Mugisha
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe 256, Uganda; (N.B.); (R.N.N.); (A.K.); (M.N.); (F.N.); (A.K.); (J.M.); (J.S.); (P.K.)
| | - Janet Seeley
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe 256, Uganda; (N.B.); (R.N.N.); (A.K.); (M.N.); (F.N.); (A.K.); (J.M.); (J.S.); (P.K.)
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London WC1H 9SH, UK
| | - Gonzalo Yebra
- The Roslin Institute, Royal (Dick) School of Veterinary Medicine, University of Edinburgh, Easter Bush Campus, Edinburgh EH25 9RG, UK;
| | - Andrew Leigh Brown
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK;
| | - Pontiano Kaleebu
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe 256, Uganda; (N.B.); (R.N.N.); (A.K.); (M.N.); (F.N.); (A.K.); (J.M.); (J.S.); (P.K.)
- Department of General Virology, Uganda Virus Research Institute, Entebbe 256, Uganda;
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Zheng M, Yu M, Cheng S, Zhou N, Ning T, Li L, Zhao F, Zhao X, Zhu J, Jiang G. Characteristics of HIV-1 molecular transmission networks and drug resistance among men who have sex with men in Tianjin, China (2014-2018). Virol J 2020; 17:169. [PMID: 33143744 PMCID: PMC7640427 DOI: 10.1186/s12985-020-01441-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 10/27/2020] [Indexed: 11/25/2022] Open
Abstract
Background In Tianjin, China, there is a relatively high prevalence of HIV in men who have sex with men (MSM). The number of HIV cases in Tianjin is also increasing. We investigated the HIV molecular transmission network, genetic tropisms, and drug resistance mutations in Tianjin.
Methods Blood samples were collected from 510 newly diagnosed antiretroviral therapy (ART)-naïve HIV-1-infected subjects among MSM in Tianjin. Partial pol and env genes were sequenced and used for phylogenetic, genetic tropism, and genotypic drug resistance analyses. Molecular clusters were identified with 1.5% genetic distance and 90% bootstrap support. Results Among the 436 HIV-1 pol sequences obtained from the study participants, various genotypes were identified, including CRF01_AE (56.9%), CRF07_BC (27.8%), B (7.3%), CRF55_01B (4.1%), unique recombinant forms (URFs) (3.7%), and CRF59_01B (0.2%). A higher prevalence of X4 viruses was observed in individuals infected with CRF55_01B (56.3%) and CRF01_AE (46.2%) than with other subtypes. Of all 110 sequences in the 36 clusters, 62 (56.4%) were observed in 23 CRF01_AE clusters and 18 (16.4%) in four CRF07_BC clusters. Eight sequences clustered with at least one other shared the same drug resistance mutation (DRM). In different cluster sizes, the distributions of individuals by age, presence of sexually transmitted disease, and presence of DRMs, were significantly different. Conclusion We revealed the characteristics of HIV molecular transmission, tropism, and DRMs of ART-naïve HIV-infected individuals among the MSM population in Tianjin. Identifying infected persons at risk of transmission is necessary for proposing counseling and treating these patients to reduce the risk of HIV transmission.
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Affiliation(s)
- Minna Zheng
- Department for AIDS/STD Control and Prevention, Tianjin Centers for Disease Control and Prevention, No.6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Maohe Yu
- Department for AIDS/STD Control and Prevention, Tianjin Centers for Disease Control and Prevention, No.6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Shaohui Cheng
- Department for AIDS/STD Control and Prevention, Tianjin Centers for Disease Control and Prevention, No.6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Ning Zhou
- Department for AIDS/STD Control and Prevention, Tianjin Centers for Disease Control and Prevention, No.6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Tielin Ning
- Department for AIDS/STD Control and Prevention, Tianjin Centers for Disease Control and Prevention, No.6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Long Li
- Department for AIDS/STD Control and Prevention, Tianjin Centers for Disease Control and Prevention, No.6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Fangning Zhao
- Department for AIDS/STD Control and Prevention, Tianjin Centers for Disease Control and Prevention, No.6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Xuan Zhao
- Department for AIDS/STD Control and Prevention, Tianjin Centers for Disease Control and Prevention, No.6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Jingjin Zhu
- Department for AIDS/STD Control and Prevention, Tianjin Centers for Disease Control and Prevention, No.6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Guohong Jiang
- Tianjin Centers for Disease Control and Prevention, No.6 Huayue Road, Hedong District, Tianjin, 300011, China.
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Nanvubya A, Wanyenze RK, Nakaweesa T, Mpendo J, Kawoozo B, Matovu F, Nabukalu S, Omoding G, Kaweesi J, Ndugga J, Kamacooko O, Chinyenze K, Price M, Van Geertruyden JP. Correlates of knowledge of family planning among people living in fishing communities of Lake Victoria, Uganda. BMC Public Health 2020; 20:1642. [PMID: 33143684 PMCID: PMC7607714 DOI: 10.1186/s12889-020-09762-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 10/25/2020] [Indexed: 11/23/2022] Open
Abstract
Background Knowledge of family planning (FP) is a key determinant of contraceptive use which ultimately plays a role in attainment of good health and in conduct of clinical research. People living in fishing communities (FCs) have limited access to health services including FP and are targeted for future clinical research but their knowledge of FP and its correlates are scantily known. We determined correlates of knowledge of FP among people living in FCs of L. victoria in Uganda to inform future FP education programs in FCs. Methods We conducted a comparative cross-sectional survey among participants aged 15–49 years from Kigungu and Nsazi. Participants were asked if they were aware of any FP method. All those who responded in the affirmative were further asked to mention what FP methods they had heard of or knew. Those who reported knowledge of at least one FP method were asked a series of questions about FP methods and their side effects. Knowledge was categorized into good or poor knowledge based on their mean total score. Poor knowledge constituted a score below the mean while good knowledge constituted a score of more than or equal to the mean total score. To further explore attitudes and perceptions of FP, ten in-depth interviews and four focus group discussions were conducted. Results Of the 1410 screened participants, 94.5% were aware of at least one FP method. Pills and injectable hormonal methods were the most commonly known methods. Slightly over a third (38%) had good knowledge of FP. Correlates of knowledge of FP were; being female (aOR: 1.92 95% CI: 1.39–2.67), residing in Kigungu (aOR: 4.01 95% CI: 2.77–5.81), being married (aOR: 1.59 95% CI: 1.11–2.28) and currently being in a sexual relationship (aOR: 1.75 95% CI: 1.18–2.60). Concerns about safety and effectiveness of some modern FP methods exist. Misconceptions on effects of FP like sterility, cancers and foetal abnormalities were common. Conclusion FP awareness among people living in FCs of L. Victoria in Uganda is high. However, good knowledge about specific methods tends to be low. Correlates of knowledge of FP include gender, residence, marital status and sexual engagement. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-020-09762-7.
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Affiliation(s)
- Annet Nanvubya
- UVRI-IAVI HIV Vaccine Program, Plot 51-59, Nakiwogo Road, P.O Box 49, Entebbe, Uganda. .,Global Health Institute, University of Antwerp, Antwerp, Belgium.
| | - Rhoda K Wanyenze
- School of Public Health, Makerere University College of Health Sciences, Kampala, Uganda
| | - Teddy Nakaweesa
- UVRI-IAVI HIV Vaccine Program, Plot 51-59, Nakiwogo Road, P.O Box 49, Entebbe, Uganda
| | - Juliet Mpendo
- UVRI-IAVI HIV Vaccine Program, Plot 51-59, Nakiwogo Road, P.O Box 49, Entebbe, Uganda
| | - Barbarah Kawoozo
- UVRI-IAVI HIV Vaccine Program, Plot 51-59, Nakiwogo Road, P.O Box 49, Entebbe, Uganda
| | - Francis Matovu
- UVRI-IAVI HIV Vaccine Program, Plot 51-59, Nakiwogo Road, P.O Box 49, Entebbe, Uganda
| | - Sarah Nabukalu
- UVRI-IAVI HIV Vaccine Program, Plot 51-59, Nakiwogo Road, P.O Box 49, Entebbe, Uganda
| | - Geoffrey Omoding
- UVRI-IAVI HIV Vaccine Program, Plot 51-59, Nakiwogo Road, P.O Box 49, Entebbe, Uganda
| | - Jed Kaweesi
- UVRI-IAVI HIV Vaccine Program, Plot 51-59, Nakiwogo Road, P.O Box 49, Entebbe, Uganda
| | - John Ndugga
- UVRI-IAVI HIV Vaccine Program, Plot 51-59, Nakiwogo Road, P.O Box 49, Entebbe, Uganda
| | | | | | - Matt Price
- IAVI, New York, NY, USA.,Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA, USA
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12
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Bbosa N, Ssemwanga D, Kaleebu P. Short Communication: Choosing the Right Program for the Identification of HIV-1 Transmission Networks from Nucleotide Sequences Sampled from Different Populations. AIDS Res Hum Retroviruses 2020; 36:948-951. [PMID: 32693608 PMCID: PMC7698971 DOI: 10.1089/aid.2020.0033] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Abstract
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.
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Affiliation(s)
- Nicholas Bbosa
- Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe, Uganda
- Address correspondence to: Nicholas Bbosa, PhD, Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene & Tropical Medicine (LSHTM) Uganda Research Unit, Plot 51-59 Nakiwogo Road, P. O. Box 49, Entebbe 256, Uganda
| | - Deogratius Ssemwanga
- Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe, Uganda
- Uganda Virus Research Institute, Entebbe, Uganda
| | - Pontiano Kaleebu
- Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe, Uganda
- Uganda Virus Research Institute, Entebbe, Uganda
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13
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Edoul G, Chia JE, Vidal N, Guichet E, Montavon C, Delaporte E, Mpoudi Ngole E, Ayouba A, Peeters M. High HIV burden and recent transmission chains in rural forest areas in southern Cameroon, where ancestors of HIV-1 have been identified in ape populations. INFECTION GENETICS AND EVOLUTION 2020; 84:104358. [PMID: 32439500 DOI: 10.1016/j.meegid.2020.104358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 05/06/2020] [Accepted: 05/08/2020] [Indexed: 11/18/2022]
Abstract
We studied HIV prevalence and genetic diversity in rural forest areas in Cameroon, where chimpanzee and gorilla populations infected with the ancestors of the different HIV-1 groups have been identified and transmitted to humans during the 20th century. A total of 2812 individuals were studied, 924 from south-central, 1116 from south-east and 772 from south-west Cameroon. Of 208 (7.4%) samples that were confirmed for HIV-1 infection all belong to HIV-1 group M. In all sites and in all age categories, HIV-1 prevalence was higher in women (160/1599 (10.0%)) as compared to men (48/1213 (4.0%)) with the highest prevalence in women aged between 25 and 34 years (>17%). For 188/208 (92.3%) HIV-1 positive individuals, a fragment of the pol gene was successfully amplified and sequenced. Phylogenetic analysis showed predominance of CRF02_AG (58%), a large diversity of subtypes (A, D, F2 and G), nine different CRFs and more than 12% URFs. Interestingly, 35/188 (18.6%) HIV-1 strains form 12 recent transmission chains. The majority of the clusters are composed of two (n = 8) or three (n = 3) sequences but one cluster included ten HIV-1 strains from women living in four different villages on a major road for logging concessions in the south-east (60 km distance). In the three regions of Cameroon where the ancestors of the four HIV-1 groups have been transmitted to humans, we observed a high HIV prevalence, especially in the southeast where HIV-1 M originated. Many factors allowing rapid establishment in the human population and subsequent rapid spread to urban areas of a new retrovirus or other pathogens of zoonotic origin are now present. Our study shows clearly that some rural areas should also be considered as hot-spots for HIV infection. Prevention efforts together with growing access to HIV diagnosis and antiretroviral treatment are urgently needed in these remote areas.
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Affiliation(s)
- Ginette Edoul
- Centre de Recherche sur les Maladies Emergentes et Reemergentes (CREMER), Virology Laboratory IMPM-IRD, IMPM, Yaoundé, Cameroon
| | - Julius Ebua Chia
- Centre de Recherche sur les Maladies Emergentes et Reemergentes (CREMER), Virology Laboratory IMPM-IRD, IMPM, Yaoundé, Cameroon
| | - Nicole Vidal
- TransVIHMI, Institut de Recherche pour le Développement (IRD), INSERM, Université de Montpellier, Montpellier, France
| | - Emilande Guichet
- Centre de Recherche sur les Maladies Emergentes et Reemergentes (CREMER), Virology Laboratory IMPM-IRD, IMPM, Yaoundé, Cameroon
| | - Celine Montavon
- TransVIHMI, Institut de Recherche pour le Développement (IRD), INSERM, Université de Montpellier, Montpellier, France
| | - Eric Delaporte
- TransVIHMI, Institut de Recherche pour le Développement (IRD), INSERM, Université de Montpellier, Montpellier, France
| | - Eitel Mpoudi Ngole
- Centre de Recherche sur les Maladies Emergentes et Reemergentes (CREMER), Virology Laboratory IMPM-IRD, IMPM, Yaoundé, Cameroon
| | - Ahidjo Ayouba
- TransVIHMI, Institut de Recherche pour le Développement (IRD), INSERM, Université de Montpellier, Montpellier, France
| | - Martine Peeters
- TransVIHMI, Institut de Recherche pour le Développement (IRD), INSERM, Université de Montpellier, Montpellier, France.
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Phylogenetic and Demographic Characterization of Directed HIV-1 Transmission Using Deep Sequences from High-Risk and General Population Cohorts/Groups in Uganda. Viruses 2020; 12:v12030331. [PMID: 32197553 PMCID: PMC7150763 DOI: 10.3390/v12030331] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 03/13/2020] [Accepted: 03/16/2020] [Indexed: 12/12/2022] Open
Abstract
Across sub-Saharan Africa, key populations with elevated HIV-1 incidence and/or prevalence have been identified, but their contribution to disease spread remains unclear. We performed viral deep-sequence phylogenetic analyses to quantify transmission dynamics between the general population (GP), fisherfolk communities (FF), and women at high risk of infection and their clients (WHR) in central and southwestern Uganda. Between August 2014 and August 2017, 6185 HIV-1 positive individuals were enrolled in 3 GP and 10 FF communities, 3 WHR enrollment sites. A total of 2531 antiretroviral therapy (ART) naïve participants with plasma viral load >1000 copies/mL were deep-sequenced. One hundred and twenty-three transmission networks were reconstructed, including 105 phylogenetically highly supported source–recipient pairs. Only one pair involved a WHR and male participant, suggesting that improved population sampling is needed to assess empirically the role of WHR to the transmission dynamics. More transmissions were observed from the GP communities to FF communities than vice versa, with an estimated flow ratio of 1.56 (95% CrI 0.68–3.72), indicating that fishing communities on Lake Victoria are not a net source of transmission flow to neighboring communities further inland. Men contributed disproportionally to HIV-1 transmission flow regardless of age, suggesting that prevention efforts need to better aid men to engage with and stay in care.
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15
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Okano JT, Sharp K, Valdano E, Palk L, Blower S. HIV transmission and source-sink dynamics in sub-Saharan Africa. Lancet HIV 2020; 7:e209-e214. [PMID: 32066532 DOI: 10.1016/s2352-3018(19)30407-2] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Revised: 10/17/2019] [Accepted: 10/31/2019] [Indexed: 12/01/2022]
Abstract
Multiple phylogenetic studies of HIV in sub-Saharan Africa have shown that mobility-driven transmission frequently occurs: many communities export and import strains. Mobility-driven transmission can result in source-sink dynamics: one community can sustain a micro-epidemic in another community in which transmission is too low to be self-sustaining. In epidemiology, the basic reproduction number (R0) is used to specify the sustainability threshold. R0 represents the average number of secondary infections generated by one infected individual in a community in which everyone is susceptible. If R0 is greater than 1, transmission is high enough to sustain an epidemic; if R0 is less than 1, it is not. Here, we discuss the conditions that are needed (in terms of R0) for source-sink transmission dynamics to occur in generalised HIV epidemics in sub-Saharan Africa, present an example of where these conditions could occur (ie, Namibia), and discuss the necessity of considering mobility-driven transmission when designing control strategies. Additionally, we discuss the need for a new generation of HIV transmission models that are more realistic than the current models. The new models should reflect not only geographical variation in epidemiology and demography, but also the spatial-temporal complexity of population-level movement patterns.
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Affiliation(s)
- Justin T Okano
- Center for Biomedical Modeling, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Katie Sharp
- Center for Biomedical Modeling, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Eugenio Valdano
- Center for Biomedical Modeling, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Laurence Palk
- Center for Biomedical Modeling, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Sally Blower
- Center for Biomedical Modeling, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
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16
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Genetic clustering analysis for HIV infection among MSM in Nigeria: implications for intervention. AIDS 2020; 34:227-236. [PMID: 31634185 DOI: 10.1097/qad.0000000000002409] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND The HIV epidemic continues to grow among MSM in countries across sub-Saharan Africa including Nigeria. To inform prevention efforts, we used a phylogenetic cluster method to characterize HIV genetic clusters and factors associated with cluster formation among MSM living with HIV in Nigeria. METHODS We analyzed HIV-1 pol sequences from 417 MSM living with HIV enrolled in the TRUST/RV368 cohort between 2013 and 2017 in Abuja and Lagos, Nigeria. A genetically linked cluster was defined among participants whose sequences had pairwise genetic distance of 1.5% or less. Binary and multinomial logistic regressions were used to estimate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for factors associated with HIV genetic cluster membership and size. RESULTS Among 417 MSM living with HIV, 153 (36.7%) were genetically linked. Participants with higher viral load (AOR = 1.72 95% CI: 1.04-2.86), no female partners (AOR = 3.66; 95% CI: 1.97-6.08), and self-identified as male sex (compared with self-identified as bigender) (AOR = 3.42; 95% CI: 1.08-10.78) had higher odds of being in a genetic cluster. Compared with unlinked participants, MSM who had high school education (AOR = 23.84; 95% CI: 2.66-213.49), were employed (AOR = 3.41; 95% CI: 1.89-10.70), had bacterial sexually transmitted infections (AOR = 3.98; 95% CI: 0.89-17.22) and were not taking antiretroviral therapy (AOR = 6.61; 95% CI: 2.25-19.37) had higher odds of being in a large cluster (size > 4). CONCLUSION Comprehensive HIV prevention packages should include behavioral and biological components, including early diagnosis and treatment of both HIV and bacterial sexually transmitted infections to optimally reduce the risk of HIV transmission and acquisition.
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17
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Livelihood Risk, Culture, and the HIV Interface: Evidence from Lakeshore Border Communities in Buliisa District, Uganda. J Trop Med 2019; 2019:6496240. [PMID: 31223313 PMCID: PMC6541934 DOI: 10.1155/2019/6496240] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 04/28/2019] [Indexed: 01/22/2023] Open
Abstract
Background While studies have focused on HIV prevalence and incidence among fishing communities, there has been inadequate attention paid to the construction and perception of HIV risk among fisher folk. There has been limited research with respect to communities along Lake Albert on the border between Uganda and the Democratic Republic of Congo (DRC). Methods We conducted a qualitative study on three landing sites of Butiaba, Bugoigo, and Wanseko on the shores of Lake Albert along the border of Uganda and the Democratic Republic of Congo. Data were collected using 12 Focus Group Discussions and 15 key informant interviews. Analysis was done manually using content and thematic approaches. Results Lakeshore livelihoods split families between men, women, and children with varying degrees of exposure to HIV infection risk. Sustaining a thriving fish trade was dependent on taking high risks. For instance, profits were high when the lake was stormy. Landing sites were characterized by widespread prostitution, alcohol consumption, drug abuse, and child labour. Such behaviors negatively affected minors and in many ways predisposed them to HIV infection. The lake shore-border heterogeneity resulted in a population with varying HIV knowledge, attitudes, behavior, and competencies to risk perception and adaptation amidst negative masculinities and negative resilience. Conclusion The susceptibility of lakeshore communities to HIV is attributable to a complex combination of geo-socio, the available (health) services, economic, and cultural factors which converged around the fishing livelihood. This study reveals that HIV risk assessment is an interplay of plural rationalities within the circumstances and constraints that impinge on the daily lives by different actors. A lack of cohesion in a multiethnic setting with large numbers of outsiders and a large transient population made the available HIV interventions less effective.
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Abeler-Dörner L, Grabowski MK, Rambaut A, Pillay D, Fraser C. PANGEA-HIV 2: Phylogenetics And Networks for Generalised Epidemics in Africa. Curr Opin HIV AIDS 2019; 14:173-180. [PMID: 30946141 PMCID: PMC6629166 DOI: 10.1097/coh.0000000000000542] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
PURPOSE OF REVIEW The HIV epidemic in sub-Saharan Africa is far from being under control and the ambitious UNAIDS targets are unlikely to be met by 2020 as declines in per-capita incidence being largely offset by demographic trends. There is an increasing number of proven and specific HIV prevention tools, but little consensus on how best to deploy them. RECENT FINDINGS Traditionally, phylogenetics has been used in HIV research to reconstruct the history of the epidemic and date zoonotic infections, whereas more recent publications focus on HIV diversity and drug resistance. However, it is also the most powerful method of source attribution available for the study of HIV transmission. The PANGEA (Phylogenetics And Networks for Generalized Epidemics in Africa) consortium has generated over 18 000 NGS HIV sequences from five countries in sub-Saharan Africa. Using phylogenetic methods, we will identify characteristics of individuals or groups, which are most likely to be at risk of infection or at risk of infecting others. SUMMARY Combining phylogenetics, phylodynamics and epidemiology will allow PANGEA to highlight where prevention efforts should be focussed to reduce the HIV epidemic most effectively. To maximise the public health benefit of the data, PANGEA offers accreditation to external researchers, allowing them to access the data and join the consortium. We also welcome submissions of other HIV sequences from sub-Saharan Africa to the database.
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Affiliation(s)
- Lucie Abeler-Dörner
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Mary K. Grabowski
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Rakai Health Sciences Program, Baltimore, USA
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Ashworth Laboratories, Edinburgh, UK
| | - Deenan Pillay
- Africa Health Research Institute, KwaZulu-Natal, South Africa
- Division of Infection and Immunity, University College London, London, UK
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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19
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Abstract
HIV-1 env sequencing enables predictions of viral coreceptor tropism and phylogenetic investigations of transmission events. The aim of the study was to estimate the contribution of non-R5 strains to the viral spread in Poland. Partial proviral env sequences were retrieved from baseline blood samples of patients with newly diagnosed HIV-1 infection between 2008-2014, including 46 patients with recent HIV-1 infection (RHI), and 246 individuals with long-term infection (LTHI). These sequences were subjected to the genotypic coreceptor tropism predictions and phylogenetic analyses to identify transmission clusters. Overall, 27 clusters with 57 sequences (19.5%) were detected, including 15 sequences (26.3%) from patients with RHI. The proportion of non-R5 strains among all study participants was 23.3% (68/292), and was comparable between patients with RHI and LTHI (11/46, 23.9% vs 57/246, 23.2%; p = 1.000). All 11 patients with non-R5 strains and RHI were men having sex with men (MSM). Among these patients, 4 had viral sequences grouped within phylogenetic cluster with another sequence of non-R5 strain obtained from patient with LTHI, indicating potential acquisition of non-R5 HIV-1 for at least 4/46 (8.7%) patients with RHI. We were unable to confirm the contribution of patients with RHI to the forward transmission of non-R5 strains, but a relatively high proportion of non-R5 strains among them deserves attention due to the limited susceptibility to CCR5 antagonists.
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20
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Phylogeography of HIV-1 suggests that Ugandan fishing communities are a sink for, not a source of, virus from general populations. Sci Rep 2019; 9:1051. [PMID: 30705307 PMCID: PMC6355892 DOI: 10.1038/s41598-018-37458-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 12/03/2018] [Indexed: 11/21/2022] Open
Abstract
Although fishing communities (FCs) in Uganda are disproportionately affected by HIV-1 relative to the general population (GP), the transmission dynamics are not completely understood. We earlier found most HIV-1 transmissions to occur within FCs of Lake Victoria. Here, we test the hypothesis that HIV-1 transmission in FCs is isolated from networks in the GP. We used phylogeography to reconstruct the geospatial viral migration patterns in 8 FCs and 2 GP cohorts and a Bayesian phylogenetic inference in BEAST v1.8.4 to analyse the temporal dynamics of HIV-1 transmission. Subtype A1 (pol region) was most prevalent in the FCs (115, 45.1%) and GP (177, 50.4%). More recent HIV transmission pairs from FCs were found at a genetic distance (GD) <1.5% than in the GP (Fisher’s exact test, p = 0.001). The mean time depth for pairs was shorter in FCs (5 months) than in the GP (4 years). Phylogeographic analysis showed strong support for viral migration from the GP to FCs without evidence of substantial viral dissemination to the GP. This suggests that FCs are a sink for, not a source of, virus strains from the GP. Targeted interventions in FCs should be extended to include the neighbouring GP for effective epidemic control.
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21
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Kusejko K, Kadelka C, Marzel A, Battegay M, Bernasconi E, Calmy A, Cavassini M, Hoffmann M, Böni J, Yerly S, Klimkait T, Perreau M, Rauch A, Günthard HF, Kouyos RD. Inferring the age difference in HIV transmission pairs by applying phylogenetic methods on the HIV transmission network of the Swiss HIV Cohort Study. Virus Evol 2018; 4:vey024. [PMID: 30250751 PMCID: PMC6143731 DOI: 10.1093/ve/vey024] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Age-mixing patterns are of key importance for understanding the dynamics of human
immunodeficiency virus (HIV)-epidemics and target public health interventions. We use the
densely sampled Swiss HIV Cohort Study (SHCS) resistance database to study the age
difference at infection in HIV transmission pairs using phylogenetic methods. In addition,
we investigate whether the mean age difference of pairs in the phylogenetic tree is
influenced by sampling as well as by additional distance thresholds for including pairs.
HIV-1 pol-sequences of 11,922 SHCS patients and approximately 240,000 Los
Alamos background sequences were used to build a phylogenetic tree. Using this tree, 100
per cent down to 1 per cent of the tips were sampled repeatedly to generate pruned trees
(N = 500 for each sample proportion), of which pairs of SHCS patients
were extracted. The mean of the absolute age differences of the pairs, measured as the
absolute difference of the birth years, was analyzed with respect to this sample
proportion and a distance criterion for inclusion of the pairs. In addition, the
transmission groups men having sex with men (MSM), intravenous drug users (IDU), and
heterosexuals (HET) were analyzed separately. Considering the tree with all 11,922 SHCS
patients, 2,991 pairs could be extracted, with 954 (31.9 per cent) MSM-pairs, 635 (21.2
per cent) HET-pairs, 414 (13.8 per cent) IDU-pairs, and 352 (11.8 per cent) HET/IDU-pairs.
For all transmission groups, the age difference at infection was significantly
(P < 0.001) smaller for pairs in the tree compared with randomly assigned pairs,
meaning that patients of similar age are more likely to be pairs. The mean age difference
in the phylogenetic analysis, using a fixed distance of 0.05, was 9.2, 9.0, 7.3 and
5.6 years for MSM-, HET-, HET/IDU-, and IDU-pairs, respectively. Decreasing the cophenetic
distance threshold from 0.05 to 0.01 significantly decreased the mean age difference.
Similarly, repeated sampling of 100 per cent down to 1 per cent of the tips revealed an
increased age difference at lower sample proportions. HIV-transmission is age-assortative,
but the age difference of transmission pairs detected by phylogenetic analyses depends on
both sampling proportion and distance criterion. The mean age difference decreases when
using more conservative distance thresholds, implying an underestimation of
age-assortativity when using liberal distance criteria. Similarly, overestimation of the
mean age difference occurs for pairs from sparsely sampled trees, as it is often the case
in sub-Saharan Africa.
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Affiliation(s)
- Katharina Kusejko
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, Rämistrasse 100, Zürich, Switzerland.,Institute of Medical Virology, University of Zürich, Winterthurerstrasse 190, Zürich, Switzerland
| | - Claus Kadelka
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, Rämistrasse 100, Zürich, Switzerland.,Institute of Medical Virology, University of Zürich, Winterthurerstrasse 190, Zürich, Switzerland
| | - Alex Marzel
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, Rämistrasse 100, Zürich, Switzerland.,Institute of Medical Virology, University of Zürich, Winterthurerstrasse 190, Zürich, Switzerland
| | - Manuel Battegay
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Petersgraben 4, CH-4031 Basel; University of Basel, Petersplatz 1, Basel, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Via Tesserete 46, Lugano, Switzerland
| | - Alexandra Calmy
- Laboratory of Virology and Division of Infectious Diseases, Genève University Hospital, Rue Gabrielle-Perret-Gentil 4, CH-1205 Genève; University of Genève, 24 rue du Général-Dufour, Genève, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, Lausanne University Hospital, Rue du Bugnon 46, Lausanne, Switzerland
| | - Matthias Hoffmann
- Division of Infectious Diseases, Cantonal Hospital St Gallen, Rorschacher Strasse 95, St. Gallen, Switzerland
| | - Jürg Böni
- Institute of Medical Virology, University of Zürich, Winterthurerstrasse 190, Zürich, Switzerland
| | - Sabine Yerly
- Laboratory of Virology and Division of Infectious Diseases, Genève University Hospital, Rue Gabrielle-Perret-Gentil 4, CH-1205 Genève; University of Genève, 24 rue du Général-Dufour, Genève, Switzerland
| | - Thomas Klimkait
- Molecular Virology, Department of Biomedicine, University of Basel, Petersplatz 10, Basel, Switzerland
| | - Matthieu Perreau
- Division of Infectious Diseases, Lausanne University Hospital, Rue du Bugnon 46, Lausanne, Switzerland
| | - Andri Rauch
- Clinic for Infectious Diseases, Bern University Hospital, Freiburgstrasse 18, Bern; University of Bern, Hochschulstrasse 6, CH-3012 Bern, Switzerland
| | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, Rämistrasse 100, Zürich, Switzerland.,Institute of Medical Virology, University of Zürich, Winterthurerstrasse 190, Zürich, Switzerland
| | - Roger D Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zürich, Rämistrasse 100, Zürich, Switzerland.,Institute of Medical Virology, University of Zürich, Winterthurerstrasse 190, Zürich, Switzerland
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