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He Y, Tang Y, Hua Q, Li X, Ge Y, Liu Y, Tang R, Tian Y, Li W. Exploring Dynamic Changes in HIV-1 Molecular Transmission Networks and Key Influencing Factors: Cross-Sectional Study. JMIR Public Health Surveill 2024; 10:e56593. [PMID: 38810253 PMCID: PMC11170051 DOI: 10.2196/56593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 02/19/2024] [Accepted: 05/05/2024] [Indexed: 05/31/2024] Open
Abstract
BACKGROUND The HIV-1 molecular network is an innovative tool, using gene sequences to understand transmission attributes and complementing social and sexual network studies. While previous research focused on static network characteristics, recent studies' emphasis on dynamic features enhances our understanding of real-time changes, offering insights for targeted interventions and efficient allocation of public health resources. OBJECTIVE This study aims to identify the dynamic changes occurring in HIV-1 molecular transmission networks and analyze the primary influencing factors driving the dynamics of HIV-1 molecular networks. METHODS We analyzed and compared the dynamic changes in the molecular network over a specific time period between the baseline and observed end point. The primary factors influencing the dynamic changes in the HIV-1 molecular network were identified through univariate analysis and multivariate analysis. RESULTS A total of 955 HIV-1 polymerase fragments were successfully amplified from 1013 specimens; CRF01_AE and CRF07_BC were the predominant subtypes, accounting for 40.8% (n=390) and 33.6% (n=321) of the specimens, respectively. Through the analysis and comparison of the basic and terminal molecular networks, it was discovered that 144 sequences constituted static molecular networks, and 487 sequences contributed to the formation of dynamic molecular networks. The findings of the multivariate analysis indicated that the factors occupation as a student, floating population, Han ethnicity, engagement in occasional or multiple sexual partnerships, participation in anal sex, and being single were independent risk factors for the dynamic changes observed in the HIV-1 molecular network, and the odds ratio (OR; 95% CIs) values were 2.63 (1.54-4.47), 1.83 (1.17-2.84), 2.91 (1.09-7.79), 1.75 (1.06-2.90), 4.12 (2.48-6.87), 5.58 (2.43-12.80), and 2.10 (1.25-3.54), respectively. Heterosexuality and homosexuality seem to exhibit protective effects when compared to bisexuality, with OR values of 0.12 (95% CI 0.05-0.32) and 0.26 (95% CI 0.11-0.64), respectively. Additionally, the National Eight-Item score and sex education experience were also identified as protective factors against dynamic changes in the HIV-1 molecular network, with OR values of 0.12 (95% CI 0.05-0.32) and 0.26 (95% CI 0.11-0.64), respectively. CONCLUSIONS The HIV-1 molecular network analysis showed 144 sequences in static networks and 487 in dynamic networks. Multivariate analysis revealed that occupation as a student, floating population, Han ethnicity, and risky sexual behavior were independent risk factors for dynamic changes, while heterosexuality and homosexuality were protective compared to bisexuality. A higher National Eight-Item score and sex education experience were also protective factors. The identification of HIV dynamic molecular networks has provided valuable insights into the characteristics of individuals undergoing dynamic alterations. These findings contribute to a better understanding of HIV-1 transmission dynamics and could inform targeted prevention strategies.
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Affiliation(s)
- Yan He
- Department of Infection Management, Nanjing Drum Tower Hospital, Nanjing, China
| | - Ying Tang
- Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Qun Hua
- Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Xin Li
- Nanjing Municipal Center for Disease Control and Prevention, Nanjing, China
| | - You Ge
- School of Public Health, Southeast University, Nanjing, China
| | - Yangyang Liu
- School of Public Health, Southeast University, Nanjing, China
| | - Rong Tang
- Nanjing Qixia District Center for Disease Control and Prevention, Nanjing, China
| | - Ye Tian
- Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Wei Li
- Children's Hospital of Nanjing Medical University, Nanjing, China
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Nascimento FF, Mehta SR, Little SJ, Volz EM. Assessing transmission attribution risk from simulated sequencing data in HIV molecular epidemiology. AIDS 2024; 38:865-873. [PMID: 38126363 PMCID: PMC10994139 DOI: 10.1097/qad.0000000000003820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 12/08/2023] [Accepted: 12/14/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND HIV molecular epidemiology (ME) is the analysis of sequence data together with individual-level clinical, demographic, and behavioral data to understand HIV epidemiology. The use of ME has raised concerns regarding identification of the putative source in direct transmission events. This could result in harm ranging from stigma to criminal prosecution in some jurisdictions. Here we assessed the risks of ME using simulated HIV genetic sequencing data. METHODS We simulated social networks of men-who-have-sex-with-men, calibrating the simulations to data from San Diego. We used these networks to simulate consensus and next-generation sequence (NGS) data to evaluate the risks of identifying direct transmissions using different HIV sequence lengths, and population sampling depths. To identify the source of transmissions, we calculated infector probability and used phyloscanner software for the analysis of consensus and NGS data, respectively. RESULTS Consensus sequence analyses showed that the risk of correctly inferring the source (direct transmission) within identified transmission pairs was very small and independent of sampling depth. Alternatively, NGS analyses showed that identification of the source of a transmission was very accurate, but only for 6.5% of inferred pairs. False positive transmissions were also observed, where one or more unobserved intermediaries were present when compared to the true network. CONCLUSION Source attribution using consensus sequences rarely infers direct transmission pairs with high confidence but is still useful for population studies. In contrast, source attribution using NGS data was much more accurate in identifying direct transmission pairs, but for only a small percentage of transmission pairs analyzed.
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Affiliation(s)
- Fabrícia F. Nascimento
- MRC Centre for Global Infectious Disease Analysis and the Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sanjay R. Mehta
- Division of Infectious Diseases, University of California San Diego, San Diego, CA, USA
| | - Susan J. Little
- Division of Infectious Diseases, University of California San Diego, San Diego, CA, USA
| | - Erik M. Volz
- MRC Centre for Global Infectious Disease Analysis and the Department of Infectious Disease Epidemiology, Imperial College London, London, UK
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Weber A, Översti S, Kühnert D. Reconstructing relative transmission rates in Bayesian phylodynamics: Two-fold transmission advantage of Omicron in Berlin, Germany during December 2021. Virus Evol 2023; 9:vead070. [PMID: 38107332 PMCID: PMC10725310 DOI: 10.1093/ve/vead070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 11/08/2023] [Accepted: 11/27/2023] [Indexed: 12/19/2023] Open
Abstract
Phylodynamic methods have lately played a key role in understanding the spread of infectious diseases. During the coronavirus disease (COVID-19) pandemic, large scale genomic surveillance has further increased the potential of dynamic inference from viral genomes. With the continual emergence of novel severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) variants, explicitly allowing transmission rate differences between simultaneously circulating variants in phylodynamic inference is crucial. In this study, we present and empirically validate an extension to the BEAST2 package birth-death skyline model (BDSKY), BDSKY[Formula: see text], which introduces a scaling factor for the transmission rate between independent, jointly inferred trees. In an extensive simulation study, we show that BDSKY[Formula: see text] robustly infers the relative transmission rates under different epidemic scenarios. Using publicly available genome data of SARS-CoV-2, we apply BDSKY[Formula: see text] to quantify the transmission advantage of the Omicron over the Delta variant in Berlin, Germany. We find the overall transmission rate of Omicron to be scaled by a factor of two with pronounced variation between the individual clusters of each variant. These results quantify the transmission advantage of Omicron over the previously circulating Delta variant, in a crucial period of pre-established non-pharmaceutical interventions. By inferring variant- as well as cluster-specific transmission rate scaling factors, we show the differences in transmission dynamics for each variant. This highlights the importance of incorporating lineage-specific transmission differences in phylodynamic inference.
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Affiliation(s)
- Ariane Weber
- Transmission, Infection, Diversification & Evolution Group (tide), Max Planck Institute of Geoanthropology, Kahlaische Strasse 10, Jena, Thuringia 07745, Germany
- Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, Leipzig, Saxony 04103, Germany
| | | | - Denise Kühnert
- Transmission, Infection, Diversification & Evolution Group (tide), Max Planck Institute of Geoanthropology, Kahlaische Strasse 10, Jena, Thuringia 07745, Germany
- Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, Leipzig, Saxony 04103, Germany
- Centre for Artificial Intelligence in Public Health Research, Robert Koch Institute, Ludwig-Witthöft-Straße 14, Wildau, Brandenburg 15745, Germany
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Zhang J, Xu K, Jiang J, Fan Q, Ding X, Zhong P, Xing H, Chai C, Pan X. Combining molecular network analysis and field epidemiology to quantify local HIV transmission and highlight ongoing epidemics. Int J Infect Dis 2023; 128:187-193. [PMID: 36587840 DOI: 10.1016/j.ijid.2022.12.033] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 12/06/2022] [Accepted: 12/25/2022] [Indexed: 12/31/2022] Open
Abstract
OBJECTIVES This study aimed to establish a collaborative approach to quantify local HIV transmission, which is an issue of great concern to public health. METHODS We linked HIV-1 pol gene sequences to demographic information and epidemiological investigations in Hangzhou (a central city in East China). We estimated local acquisition rates from a collaboration of molecular network analysis (with a distance-based approach) and epidemiological investigations. RESULTS Among 1064 newly diagnosed patients with HIV, 857 pol sequences were acquired and subsequently analyzed. Multiple subtypes were identified, with circulating recombinant form (CRF)07_BC (42.5%) and CRF01_AE (39.2%) predominating, followed by 13 other subtypes and 26 unique recombinant forms. By integrating the molecular network analysis and epidemiological investigations, we estimated that the proportion of local infection was 63.2%. The multivariable analyses revealed that individuals in clusters were more likely to be local residents, be aged 50 years or older, work as farmers, and have a higher first cluster of differentiation 4 count level (P <0.05). The proportions of local acquisitions over 70% were observed in local residents (79.9%, 242/303), individuals aged 50 years or older (73.6%, 181/246), and farmers (75.6%, 99/131). CONCLUSION The molecular network analysis can augment traditional HIV epidemic surveillance. This study establishes a paradigm for quantifying local HIV transmission for generalization in other areas.
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Affiliation(s)
- Jiafeng Zhang
- Department of HIV/AIDS Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Ke Xu
- Department of HIV/AIDS Control and Prevention, Hangzhou Municipal Center for Disease Control and Prevention, Hangzhou, China
| | - Jun Jiang
- Department of HIV/AIDS Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Qin Fan
- Department of HIV/AIDS Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Xiaobei Ding
- Department of HIV/AIDS Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Ping Zhong
- Shanghai Municipal Center for Diseases Control and Prevention, Shanghai, China
| | - Hui Xing
- Division of Virology and Immunology, National Center for AIDS/STD Control and Prevention (NCAIDS), Beijing, China
| | - Chengliang Chai
- Department of HIV/AIDS Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
| | - Xiaohong Pan
- Department of HIV/AIDS Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
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Labarile M, Loosli T, Zeeb M, Kusejko K, Huber M, Hirsch HH, Perreau M, Ramette A, Yerly S, Cavassini M, Battegay M, Rauch A, Calmy A, Notter J, Bernasconi E, Fux C, Günthard HF, Pasin C, Kouyos RD, Aebi-Popp K, Anagnostopoulos A, Battegay M, Bernasconi E, Braun DL, Bucher HC, Calmy A, Cavassini M, Ciuffi A, Dollenmaier G, Egger M, Elzi L, Fehr J, Fellay J, Furrer H, Fux CA, Günthard HF, Hachfeld A, Haerry D, Hasse B, Hirsch HH, Hoffmann M, Hösli I, Huber M, Kahlert CR, Kaiser L, Keiser O, Klimkait T, Kouyos RD, Kovari H, Kusejko K, Martinetti G, Martinez de Tejada B, Marzolini C, Metzner KJ, Müller N, Nemeth J, Nicca D, Paioni P, Pantaleo G, Perreau M, Rauch A, Schmid P, Speck R, Stöckle M, Tarr P, Trkola A, Wandeler G, Yerly S. Quantifying and Predicting Ongoing Human Immunodeficiency Virus Type 1 Transmission Dynamics in Switzerland Using a Distance-Based Clustering Approach. J Infect Dis 2023; 227:554-564. [PMID: 36433831 DOI: 10.1093/infdis/jiac457] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 11/11/2022] [Accepted: 11/25/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Despite effective prevention approaches, ongoing human immunodeficiency virus 1 (HIV-1) transmission remains a public health concern indicating a need for identifying its drivers. METHODS We combined a network-based clustering method using evolutionary distances between viral sequences with statistical learning approaches to investigate the dynamics of HIV transmission in the Swiss HIV Cohort Study and to predict the drivers of ongoing transmission. RESULTS We found that only a minority of clusters and patients acquired links to new infections between 2007 and 2020. While the growth of clusters and the probability of individual patients acquiring new links in the transmission network was associated with epidemiological, behavioral, and virological predictors, the strength of these associations decreased substantially when adjusting for network characteristics. Thus, these network characteristics can capture major heterogeneities beyond classical epidemiological parameters. When modeling the probability of a newly diagnosed patient being linked with future infections, we found that the best predictive performance (median area under the curve receiver operating characteristic AUCROC = 0.77) was achieved by models including characteristics of the network as predictors and that models excluding them performed substantially worse (median AUCROC = 0.54). CONCLUSIONS These results highlight the utility of molecular epidemiology-based network approaches for analyzing and predicting ongoing HIV transmission dynamics. This approach may serve for real-time prospective assessment of HIV transmission.
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Affiliation(s)
- Marco Labarile
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Tom Loosli
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Marius Zeeb
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Katharina Kusejko
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Michael Huber
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Hans H Hirsch
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland.,Transplantation and Clinical Virology, Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Matthieu Perreau
- Division of Immunology and Allergy, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland
| | - Alban Ramette
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Sabine Yerly
- Laboratory of Virology and Division of Infectious Diseases, Geneva University Hospital, University of Geneva, Geneva, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, Lausanne University Hospital, Lausanne, Switzerland
| | - Manuel Battegay
- Transplantation and Clinical Virology, Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Andri Rauch
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Alexandra Calmy
- Laboratory of Virology and Division of Infectious Diseases, Geneva University Hospital, University of Geneva, Geneva, Switzerland
| | - Julia Notter
- Division of Infectious Diseases, Cantonal Hospital St Gallen, St Gallen, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland
| | - Christoph Fux
- Department of Infectious Diseases, Kantonsspital Aarau, Aarau, Switzerland
| | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Chloé Pasin
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Roger D Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
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Rich SN, Prosperi MCF, Dellicour S, Vrancken B, Cook RL, Spencer EC, Salemi M, Mavian C. Molecular Epidemiology of HIV-1 Subtype B Infection across Florida Reveals Few Large Superclusters with Metropolitan Origin. Microbiol Spectr 2022; 10:e0188922. [PMID: 36222706 PMCID: PMC9769514 DOI: 10.1128/spectrum.01889-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 09/26/2022] [Indexed: 02/03/2023] Open
Abstract
Florida is considered an epicenter of HIV in the United States. The U.S. federal plan for Ending the HIV Epidemic (EHE) within 10 years prioritizes seven of Florida's 67 counties for intervention. We applied molecular epidemiology methods to characterize the HIV infection networks in the state and infer whether the results support the EHE. HIV sequences (N = 34,446) and associated clinical/demographic metadata of diagnosed people with HIV (PWH), during 2007 to 2017, were retrieved from the Florida Department of Health. HIV genetic networks were investigated using MicrobeTrace. Associates of clustering were identified through boosted logistic regression. Assortative trait mixing was also assessed. Bayesian phylogeographic methods were applied to evaluate evidence of imported HIV-1 lineages and illustrate spatiotemporal flows within Florida. We identified nine large clusters spanning all seven EHE counties but little evidence of external introductions, suggesting-in the absence of undersampling-an epidemic that evolved independently from the rest of the country or other external influences. Clusters were highly assortative by geography. Most of the sampled infections (82%) did not cluster with others in the state using standard molecular surveillance methods despite satisfactory sequence sampling in the state. The odds of being unclustered were higher among PWH in rural regions, and depending on demographics. A significant number of unclustered sequences were observed in counties omitted from EHE. The large number of missing sequence links may impact timely detection of emerging transmission clusters and ultimately hinder the success of EHE in Florida. Molecular epidemiology may help better understand infection dynamics at the population level and underlying disparities in disease transmission among subpopulations; however, there is also a continuous need to conduct ethical discussions to avoid possible harm of advanced methodologies to vulnerable groups, especially in the context of HIV stigmatization. IMPORTANCE The large number of missing phylogenetic linkages in rural Florida counties and among women and Black persons with HIV may impact timely detection of ongoing and emerging transmission clusters and ultimately hinder the success of epidemic elimination goals in Florida.
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Affiliation(s)
- Shannan N. Rich
- Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - Mattia C. F. Prosperi
- Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven-University of Leuven, Leuven, Belgium
| | - Bram Vrancken
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven-University of Leuven, Leuven, Belgium
| | - Robert L. Cook
- Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - Emma C. Spencer
- Florida Department of Health, Division of Disease Control and Health Protection, Bureau of Communicable Diseases, Tallahassee, Florida, USA
| | - Marco Salemi
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Carla Mavian
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, Florida, USA
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Characterization of HIV-1 Transmission Clusters Inferred from the Brazilian Nationwide Genotyping Service Database. Viruses 2022; 14:v14122768. [PMID: 36560771 PMCID: PMC9783618 DOI: 10.3390/v14122768] [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: 10/05/2022] [Revised: 11/23/2022] [Accepted: 11/28/2022] [Indexed: 12/14/2022] Open
Abstract
The study of HIV-1 transmission networks inferred from viral genetic data can be used to clarify important factors about the dynamics of HIV-1 transmission, such as network growth rate and demographic composition. In Brazil, HIV transmission has been stable since the early 2000s and the study of transmission clusters can provide valuable data to understand the drivers of virus spread. In this work, we analyzed a nation-wide database of approximately 53,000 HIV-1 nucleotide pol sequences sampled from genotyped patients from 2008-2017. Phylogenetic trees were reconstructed for the HIV-1 subtypes B, C and F1 in Brazil and transmission clusters were inferred by applying genetic distances thresholds of 1.5%, 3.0% and 4.5%, as well as high (>0.9) cluster statistical support. An odds ratio test revealed that young men (15-24 years) and individuals with more years of education presented higher odds to cluster. The assortativity coefficient revealed that individuals with similar demographic features tended to cluster together, with emphasis on features, such as place of residence and age. We also observed that assortativity weakens as the genetic distance threshold increases. Our results indicate that the phylogenetic clusters identified here are likely representative of the contact networks that shape HIV transmission, and this is a valuable tool even in sites with low sampling density, such as Brazil.
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Using phylogenetics to infer HIV-1 transmission direction between known transmission pairs. Proc Natl Acad Sci U S A 2022; 119:e2210604119. [PMID: 36103580 PMCID: PMC9499565 DOI: 10.1073/pnas.2210604119] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Identifying the transmission direction between individuals provides unparalleled power to understand infectious disease epidemiology. With epidemiological and clinical information typically unavailable to infer transmission direction, phylogenetic analysis of pathogen sequence data offers an alternative approach. While the success of this phylogenetic analysis varies, the reasons remain unknown. We analyze sequence data from over 100 transmission pairs for which both the transmission direction of HIV is known and detailed additional information is available. We find that easily quantifiable phylogenetic and sampling characteristics discriminate whether a phylogenetically inferred transmission direction is correct. Our analysis highlights that while phylogenetic approaches to infer transmission direction are unsuitable for individual-level analysis, such as forensic investigations, confidence in source attribution can be incorporated in population-level analyses. Inferring the transmission direction between linked individuals living with HIV provides unparalleled power to understand the epidemiology that determines transmission. Phylogenetic ancestral-state reconstruction approaches infer the transmission direction by identifying the individual in whom the most recent common ancestor of the virus populations originated. While these methods vary in accuracy, it is unclear why. To evaluate the performance of phylogenetic ancestral-state reconstruction to determine the transmission direction of HIV-1 infection, we inferred the transmission direction for 112 transmission pairs where transmission direction and detailed additional information were available. We then fit a statistical model to evaluate the extent to which epidemiological, sampling, genetic, and phylogenetic factors influenced the outcome of the inference. Finally, we repeated the analysis under real-life conditions with only routinely available data. We found that whether ancestral-state reconstruction correctly infers the transmission direction depends principally on the phylogeny's topology. For example, under real-life conditions, the probability of identifying the correct transmission direction increases from 32%—when a monophyletic–monophyletic or paraphyletic–polyphyletic tree topology is observed and when the tip closest to the root does not agree with the state at the root—to 93% when a paraphyletic–monophyletic topology is observed and when the tip closest to the root agrees with the root state. Our results suggest that documenting larger differences in relative intrahost diversity increases our confidence in the transmission direction inference of linked pairs for population-level studies of HIV. These findings provide a practical starting point to determine our confidence in transmission direction inference from ancestral-state reconstruction.
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Magosi LE, Zhang Y, Golubchik T, DeGruttola V, Tchetgen Tchetgen E, Novitsky V, Moore J, Bachanas P, Segolodi T, Lebelonyane R, Pretorius Holme M, Moyo S, Makhema J, Lockman S, Fraser C, Essex MM, Lipsitch M. Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial - BCPP/ Ya Tsie trial. eLife 2022; 11:72657. [PMID: 35229714 PMCID: PMC8912920 DOI: 10.7554/elife.72657] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 02/08/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Mathematical models predict that community-wide access to HIV testing-and-treatment can rapidly and substantially reduce new HIV infections. Yet several large universal test-and-treat HIV prevention trials in high-prevalence epidemics demonstrated variable reduction in population-level incidence. Methods: To elucidate patterns of HIV spread in universal test-and-treat trials we quantified the contribution of geographic-location, gender, age and randomized-HIV-intervention to HIV transmissions in the 30-community Ya Tsie trial in Botswana. We sequenced HIV viral whole genomes from 5,114 trial participants among the 30 trial communities. Results: Deep-sequence phylogenetic analysis revealed that most inferred HIV transmissions within the trial occurred within the same or between neighboring communities, and between similarly-aged partners. Transmissions into intervention communities from control communities were more common than the reverse post-baseline (30% [12.2 - 56.7] versus 3% [0.1 - 27.3]) than at baseline (7% [1.5 - 25.3] versus 5% [0.9 - 22.9]) compatible with a benefit from treatment-as-prevention. Conclusion: Our findings suggest that population mobility patterns are fundamental to HIV transmission dynamics and to the impact of HIV control strategies. Funding: This study was supported by the National Institute of General Medical Sciences (U54GM088558); the Fogarty International Center (FIC) of the U.S. National Institutes of Health (D43 TW009610); and the President's Emergency Plan for AIDS Relief through the Centers for Disease Control and Prevention (CDC) (Cooperative agreements U01 GH000447 and U2G GH001911).
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Affiliation(s)
- Lerato E Magosi
- Department of Epidemiology, Harvard University, Boston, United States
| | - Yinfeng Zhang
- Division of Molecular and Genomic Pathology, University of Pittsburgh Medical Center, Pittsburgh, United States
| | - Tanya Golubchik
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Victor DeGruttola
- Department of Biostatistics, Harvard T H Chan School of Public Health, Boston, United States
| | | | - Vladimir Novitsky
- Department of Immunology and Infectious Disease, Harvard T H Chan School of Public Health, Boston, United States
| | - Janet Moore
- Division of Global HIV/AIDS and TB, Centers for Disease Control and Prevention, Atlanta, United States
| | - Pam Bachanas
- Division of Global HIV/AIDS and TB, Centers for Disease Control and Prevention, Atlanta, United States
| | - Tebogo Segolodi
- HIV Prevention Research Unit, Centers for Disease Control and Prevention, Gaborone, Botswana
| | | | - Molly Pretorius Holme
- epartment of Immunology and Infectious Disease, Harvard T H Chan School of Public Health, Boston, United States
| | - Sikhulile Moyo
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
| | - Joseph Makhema
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana
| | - Shahin Lockman
- Division of Infectious Diseases, Brigham and Women's Hospital, Boston, United States
| | - Christophe Fraser
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Myron Max Essex
- Department of Immunology and Infectious Disease, Harvard T H Chan School of Public Health, Boston, United States
| | - Marc Lipsitch
- Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, United States
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Wilbourn B, Saafir-Callaway B, Jair K, Wertheim JO, Laeyendeker O, Jordan JA, Kharfen M, Castel A. Characterization of HIV Risk Behaviors and Clusters Using HIV-Transmission Cluster Engine Among a Cohort of Persons Living with HIV in Washington, DC. AIDS Res Hum Retroviruses 2021; 37:706-715. [PMID: 34157853 PMCID: PMC8501467 DOI: 10.1089/aid.2021.0031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Molecular epidemiology (ME) is one tool used to end the HIV epidemic in the United States. We combined clinical and behavioral data with HIV sequence data to identify any overlap in clusters generated from different sequence datasets; to characterize HIV transmission clusters; and to identify correlates of clustering among people living with HIV (PLWH) in Washington, District of Columbia (DC). First, Sanger sequences from DC Cohort participants, a longitudinal HIV study, were combined with next-generation sequences (NGS) from participants in a ME substudy to identify clusters. Next, demographic and self-reported behavioral data from ME substudy participants were used to identify risks of secondary transmission. Finally, we combined NGS from ME substudy participants with Sanger sequences in the DC Molecular HIV Surveillance database to identify clusters. Cluster analyses used HIV-Transmission Cluster Engine to identify linked pairs of sequences (defined as distance ≤1.5%). Twenty-eight clusters of ≥3 sequences (size range: 3-12) representing 108 (3%) participants were identified. None of the five largest clusters (size range: 5-12) included newly diagnosed PLWH. Thirty-four percent of ME substudy participants (n = 213) reported condomless sex during their last sexual encounter and 14% reported a Syphilis diagnosis in the past year. Seven transmission clusters (size range: 2-19) were identified in the final analysis, each containing at least one ME substudy participant. Substudy participants in clusters from the third analysis were present in clusters from the first analysis. Combining HIV sequence, clinical and behavioral data provided insights into HIV transmission that may not be identified using traditional epidemiological methods alone. Specifically, the sexual risk behaviors and STI diagnoses reported in the substudy survey may not have been disclosed during Partner Services activities and the survey data complemented clinical data to fully characterize transmission clusters. These findings can be used to enhance local efforts to interrupt transmission and avert new infections.
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Affiliation(s)
- Brittany Wilbourn
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia, USA
| | - Brittani Saafir-Callaway
- HIV/AIDS, Hepatitis, STD and TB Administration, DC Health, Washington, District of Columbia, USA
| | - Kamwing Jair
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia, USA
| | - Joel O. Wertheim
- Department of Medicine, University of California San Diego, LA Jolla, California, USA
| | - Oliver Laeyendeker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, Maryland, USA
| | - Jeanne A. Jordan
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia, USA
| | - Michael Kharfen
- HIV/AIDS, Hepatitis, STD and TB Administration, DC Health, Washington, District of Columbia, USA
| | - Amanda Castel
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia, USA
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11
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Novitsky V, Steingrimsson J, Howison M, Dunn C, Gillani FS, Manne A, Li Y, Spence M, Parillo Z, Fulton J, Marak T, Chan P, Bertrand T, Bandy U, Alexander-Scott N, Hogan J, Kantor R. Longitudinal typing of molecular HIV clusters in a statewide epidemic. AIDS 2021; 35:1711-1722. [PMID: 34033589 PMCID: PMC8373695 DOI: 10.1097/qad.0000000000002953] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND HIV molecular epidemiology is increasingly integrated into public health prevention. We conducted cluster typing to enhance characterization of a densely sampled statewide epidemic towards informing public health. METHODS We identified HIV clusters, categorized them into types, and evaluated their dynamics between 2004 and 2019 in Rhode Island. We grouped sequences by diagnosis year, assessed cluster changes between paired phylogenies, t0 and t1, representing adjacent years and categorized clusters as stable (cluster in t0 phylogeny = cluster in t1 phylogeny) or unstable (cluster in t0 ≠ cluster in t1). Unstable clusters were further categorized as emerging (t1 phylogeny only) or growing (larger in t1 phylogeny). We determined proportions of each cluster type, of individuals in each cluster type, and of newly diagnosed individuals in each cluster type, and assessed trends over time. RESULTS A total of 1727 individuals with available HIV-1 subtype B pol sequences were diagnosed in Rhode Island by 2019. Over time, stable clusters and individuals in them dominated the epidemic, increasing over time, with reciprocally decreasing unstable clusters and individuals in them. Conversely, proportions of newly diagnosed individuals in unstable clusters significantly increased. Within unstable clusters, proportions of emerging clusters and of individuals in them declined; whereas proportions of newly diagnosed individuals in growing clusters significantly increased over time. CONCLUSION Distinct molecular cluster types were identified in the Rhode Island epidemic. Cluster dynamics demonstrated increasing stable and decreasing unstable clusters driven by growing, rather than emerging clusters, suggesting consistent in-state transmission networks. Cluster typing could inform public health beyond conventional approaches and direct interventions.
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Affiliation(s)
| | | | - Mark Howison
- Research Improving People’s Life, Providence, RI, USA
| | | | | | | | | | | | | | | | | | - Philip Chan
- Brown University, Providence, RI, USA
- Rhode Island Department of Health, Providence, RI, USA
| | | | - Utpala Bandy
- Rhode Island Department of Health, Providence, RI, USA
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12
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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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13
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Chen Y, Shen Z, Feng Y, Ruan Y, Li J, Tang S, Tang K, Liang S, Pang X, McNeil EB, Xing H, Chongsuvivatwong V, Lin M, Lan G. HIV-1 subtype diversity and transmission strain source among men who have sex with men in Guangxi, China. Sci Rep 2021; 11:8319. [PMID: 33859273 PMCID: PMC8050077 DOI: 10.1038/s41598-021-87745-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 03/30/2021] [Indexed: 11/08/2022] Open
Abstract
With the rapid increase in HIV prevalence of men who have sex with men (MSM) in recent years and common human migration and travelling across different provinces in China, MSM are now finding it easier to meet each other, which might contribute to local HIV epidemics as well as fueling cross-province transmission. We performed a cross-sectional survey in 2018-2019 to investigate the current HIV subtype diversity and inferred HIV strain transmission origin among MSM in Guangxi province, China based on a phylogenetic analysis. Based on 238 samples, we found that the HIV-1 subtype diversity was more complicated than before, except for three major HIV subtypes/circulating recombinant forms (CRFs): CRF07_BC, CRF01_AE, CRF55_01B, five other subtypes/CRFs (CRF59_01B, B, CRF08_BC, CRF67_01B, CRF68_01B) and five unique recombinant forms (URFs) were detected. In total, 76.8% (169/220) of samples were infected with HIV from local circulating strains, while others originated from other provinces, predominantly Guangdong and Shanghai. The high diversity of HIV recombinants and complicated HIV transmission sources in Guangxi MSM indicates that there has been an active sexual network between HIV positive MSM both within and outside Guangxi without any effective prevention. Inter-province collaboration must be enforced to provide tailored HIV prevention and control services to MSM in China.
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Affiliation(s)
- Yi Chen
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Zhiyong Shen
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Yi Feng
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, 102206, China
| | - Yuhua Ruan
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, 102206, China
| | - Jianjun Li
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Shuai Tang
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Kailing Tang
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Shujia Liang
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Xianwu Pang
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Edward B McNeil
- Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, Hat Yai, 90110, Thailand
| | - Hui Xing
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, 102206, China
| | | | - Mei Lin
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China.
| | - Guanghua Lan
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China.
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14
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Fritsch HM, Tanuri A, Pinto AR, Gräf T. Transmission dynamics and molecular characterization of HIV-1 epidemic among therapeutic failure patients in Santa Catarina state, southern Brazil. INFECTION GENETICS AND EVOLUTION 2021; 92:104854. [PMID: 33839313 DOI: 10.1016/j.meegid.2021.104854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 03/28/2021] [Accepted: 04/05/2021] [Indexed: 10/21/2022]
Abstract
The HIV-1 epidemic in southern Brazil is mostly caused by subtype C, which contrasts the dominance of subtype B in the other regions of the country. Santa Catarina (SC), although the smallest state in the southern region, presents one of the highest incidences and mortality rates in Brazil due to AIDS. This work investigated the HIV-1 molecular diversity and phylogenetic transmission networks in SC state by analyzing a database of 3070 sequences of the national genotyping service. HIV-1C proved to be the most frequent subtype, with a significant increase in prevalence over time. HIV-1B was observed to be associated with highly educated men, suggesting a compartmentalization from other subtypes. Such observation was confirmed by the high frequency of HIV-1B circulating in MSM transmission networks. Identified transmission clusters were majority composed by individuals living up to 25 km away and interstate linkages were mainly between southern neighbor states. In general, individuals between 25 and 40 years old and sequences sampled after 2014 were more likely to be in transmission chains, in agreement with the universal treatment protocol launched in 2014. The present study brings new insights about HIV-1 transmission dynamics in southern Brazil.
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Affiliation(s)
- Hegger M Fritsch
- Laboratório de Imunologia Aplicada, Universidade Federal de Santa Catarina, Florianópolis, Santa Catarina, Brazil
| | - Amilcar Tanuri
- Laboratório de Virologia Molecular, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil
| | - Aguinaldo R Pinto
- Laboratório de Imunologia Aplicada, Universidade Federal de Santa Catarina, Florianópolis, Santa Catarina, Brazil.
| | - Tiago Gräf
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.
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15
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Zhang Y, Wymant C, Laeyendecker O, Grabowski MK, Hall M, Hudelson S, Piwowar-Manning E, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, Hakim JG, Kumwenda J, Mills LA, Santos BR, Grinsztejn B, Pilotto JH, Chariyalertsak S, Makhema J, Chen YQ, Cohen MS, Fraser C, Eshleman SH. Evaluation of Phylogenetic Methods for Inferring the Direction of Human Immunodeficiency Virus (HIV) Transmission: HIV Prevention Trials Network (HPTN) 052. Clin Infect Dis 2021; 72:30-37. [PMID: 31922537 PMCID: PMC7823077 DOI: 10.1093/cid/ciz1247] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 01/07/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Phylogenetic analysis can be used to assess human immunodeficiency virus (HIV) transmission in populations. We inferred the direction of HIV transmission using whole-genome HIV sequences from couples with known linked infection and known transmission direction. METHODS Complete next-generation sequencing (NGS) data were obtained for 105 unique index-partner sample pairs from 32 couples enrolled in the HIV Prevention Trials Network (HPTN) 052 study (up to 2 samples/person). Index samples were obtained up to 5.5 years before partner infection; partner samples were obtained near the time of seroconversion. The bioinformatics method, phyloscanner, was used to infer transmission direction. Analyses were performed using samples from individual sample pairs, samples from all couples (1 sample/person; group analysis), and all available samples (multisample group analysis). Analysis was also performed using NGS data from defined regions of the HIV genome (gag, pol, env). RESULTS Using whole-genome NGS data, transmission direction was inferred correctly (index to partner) for 98 of 105 (93.3%) of the individual sample pairs, 99 of 105 (94.3%) sample pairs using group analysis, and 31 of the 32 couples (96.9%) using multisample group analysis. There were no cases where the incorrect transmission direction (partner to index) was inferred. The accuracy of the method was higher with greater time between index and partner sample collection. Pol region sequences performed better than env or gag sequences for inferring transmission direction. CONCLUSIONS We demonstrate the potential of a phylogenetic method to infer the direction of HIV transmission between 2 individuals using whole-genome and pol NGS data.
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Affiliation(s)
- Yinfeng Zhang
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Chris Wymant
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Oliver Laeyendecker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - M Kathryn Grabowski
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Matthew Hall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Sarah Hudelson
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Estelle Piwowar-Manning
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Marybeth McCauley
- HIV Prevention Trials Network Leadership and Operations Center, FHI, Washington, District of Columbia, USA
| | - Theresa Gamble
- HIV Prevention Trials Network Leadership and Operations Center, FHI, Durham, North Carolina, USA
| | - Mina C Hosseinipour
- Division of Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- University of North Carolina Project–Malawi, Institute for Global Health and Infectious Diseases, Lilongwe, Malawi
| | - Nagalingeswaran Kumarasamy
- Chennai Antiviral Research and Treatment Clinical Research Site, Infectious Diseases Medical Centre, Voluntary Health Services, Chennai, India
| | - James G Hakim
- Department of Medicine, University of Zimbabwe, Harare, Zimbabwe
| | | | - Lisa A Mills
- US Centers for Disease Control and Prevention, HIV Research Branch, Kisumu, Kenya
| | - Breno R Santos
- Department of Infectious Diseases, Hospital Nossa Senhora da Conceição, Porto Alegre, Brazil
| | - Beatriz Grinsztejn
- Instituto Nacional de Infectologia Evandro Chagas-Fiocruz, Rio de Janeiro, Brazil
| | - Jose H Pilotto
- Hospital Geral de Nova Iguacu and Laboratorio de AIDS e Imunologia Molecular–Instituto Oswaldo Cruz/Fiocruz, Rio de Janeiro, Brazil
| | - Suwat Chariyalertsak
- Research Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand
| | - Joseph Makhema
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
| | - Ying Q Chen
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Myron S Cohen
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Susan H Eshleman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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16
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Volz EM, Carsten W, Grad YH, Frost SDW, Dennis AM, Didelot X. Identification of Hidden Population Structure in Time-Scaled Phylogenies. Syst Biol 2021; 69:884-896. [PMID: 32049340 PMCID: PMC8559910 DOI: 10.1093/sysbio/syaa009] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 01/09/2020] [Accepted: 01/23/2020] [Indexed: 11/13/2022] Open
Abstract
Population structure influences genealogical patterns, however, data pertaining to how populations are structured are often unavailable or not directly observable. Inference of population structure is highly important in molecular epidemiology where pathogen phylogenetics is increasingly used to infer transmission patterns and detect outbreaks. Discrepancies between observed and idealized genealogies, such as those generated by the coalescent process, can be quantified, and where significant differences occur, may reveal the action of natural selection, host population structure, or other demographic and epidemiological heterogeneities. We have developed a fast non-parametric statistical test for detection of cryptic population structure in time-scaled phylogenetic trees. The test is based on contrasting estimated phylogenies with the theoretically expected phylodynamic ordering of common ancestors in two clades within a coalescent framework. These statistical tests have also motivated the development of algorithms which can be used to quickly screen a phylogenetic tree for clades which are likely to share a distinct demographic or epidemiological history. Epidemiological applications include identification of outbreaks in vulnerable host populations or rapid expansion of genotypes with a fitness advantage. To demonstrate the utility of these methods for outbreak detection, we applied the new methods to large phylogenies reconstructed from thousands of HIV-1 partial pol sequences. This revealed the presence of clades which had grown rapidly in the recent past and was significantly concentrated in young men, suggesting recent and rapid transmission in that group. Furthermore, to demonstrate the utility of these methods for the study of antimicrobial resistance, we applied the new methods to a large phylogeny reconstructed from whole genome Neisseria gonorrhoeae sequences. We find that population structure detected using these methods closely overlaps with the appearance and expansion of mutations conferring antimicrobial resistance. [Antimicrobial resistance; coalescent; HIV; population structure.].
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Affiliation(s)
- Erik M Volz
- Department of Infectious Disease Epidemiology and MRC Centre for Global Infectious Disease Analysis, Imperial College London, Norfolk Place, W2 1PG London, UK
| | - Wiuf Carsten
- Department of Mathematical Sciences, University of Copenhagen, Universitetsparken 5, DK-2100 Copenhagen, Denmark
| | - Yonatan H Grad
- Department of Immunology and Infectious Diseases, TH Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, MA 02115, USA
| | - Simon D W Frost
- Department of Veterinary Medicine, University of Cambridge, Madingley Rd, Cambridge CB3 0ES, UK.,The Alan Turing Institute, 96 Euston Rd, London NW1 2DB, London, UK
| | - Ann M Dennis
- Department of Medicine, University of North Carolina Chapel Hill, 321 S Columbia St, Chapel Hill, NC 27516, USA
| | - Xavier Didelot
- School of Life Sciences and Department of Statistics, University of Warwick, Coventry, CV4 7AL, UK
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Factors Associated With Human Immunodeficiency Virus Infections Linked in Genetic Clusters But Disconnected in Partner Tracing. Sex Transm Dis 2020; 47:80-87. [PMID: 31934954 DOI: 10.1097/olq.0000000000001094] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
BACKGROUND Successful partner notification can improve community-level outcomes by increasing the proportion of persons living with human immunodeficiency virus (HIV) who are linked to HIV care and virally suppressed, but it is resource intensive. Understanding where HIV transmission pathways may be undetected by routine partner notification may help improve case finding strategies. METHODS We combined partner notification interview and HIV sequence data for persons diagnosed with HIV in Wake County, NC in 2012 to 2013 to evaluate partner contact networks among persons with HIV pol gene sequences 2% or less pairwise genetic distance. We applied a set of multivariable generalized estimating equations to identify correlates of disparate membership in genetic versus partner contact networks. RESULTS In the multivariable model, being in a male-male pair (adjusted odds ratio [AOR], 16.7; P = 0.01), chronic HIV infection status (AOR, 4.5; P < 0.01), and increasing percent genetic distance between each dyad member's HIV pol gene sequence (AOR, 8.3 per each 1% increase, P < 0.01) were all associated with persons with HIV clustering but not being identified in the partner notification network component. Having anonymous partners or other factors typically associated with risk behavior were not associated. CONCLUSIONS Based on genetic networks, partnerships which may be stigmatized, may have occurred farther back in time or may have an intervening partner were more likely to be unobserved in the partner contact network. The HIV genetic cluster information contributes to public health understanding of HIV transmission networks in these settings where partner identifying information is not available.
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18
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Abstract
OBJECTIVE We investigated the duration of HIV transmission clusters. DESIGN Fifty-four individuals newly infected at enrollment in the ALIVE cohort were included, all of whom had sequences at an intake visit (T1) and from a second (T2) and/or a third (T3) follow-up visit, median 2.9 and 5.4 years later, respectively. METHODS Sequences were generated using the 454 DNA sequencing platform for portions of HIV pol and env (HXB2 positions 2717-3230; 7941-8264). Genetic distances were calculated using tn93 and sequences were clustered over a range of thresholds (1--5%) using HIV-TRACE. Analyses were performed separately for individuals with pol sequences for T1 + T2 (n = 40, 'Set 1') and T1 + T3 (n = 25; 'Set 2'), and env sequences for T1 + T2 (n = 47, 'Set 1'), and T1 + T3 (n = 30; 'Set 2'). RESULTS For pol, with one exception, a single cluster contained more than 75% of samples at all thresholds, and cluster composition was at least 90% concordant between time points/thresholds. For env, two major clusters (A and B) were observed at T1 and T2/T3, although cluster composition concordance between time points/thresholds was low (<60%) at lower thresholds for both sets 1 and 2. In addition, several individuals were included in clusters at T2/T3, although not at T1. CONCLUSION Caution should be used in applying a single threshold in population studies where seroconversion dates are unknown. However, the retention of some clusters even after 5 + years is evidence for the robustness of the clustering approach in general.
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Brief Report: Temporal Changes in HIV Transmission Patterns Among Young Men Who Have Sex With Men, United States, 2009-2016. J Acquir Immune Defic Syndr 2020; 84:1-4. [PMID: 31977598 DOI: 10.1097/qai.0000000000002305] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND In the United States, young men (aged 13-24 years) who have sex with men (MSM) bear a disproportionate burden of HIV. Transmission among MSM has been found to be disassortative by age. METHODS We analyzed HIV-1 pol sequences reported to the US National HIV Surveillance System from MSM with HIV diagnosed during 2009-2016. Using an HIV genetic transmission network, we identified persons with closely related viruses (ie, genetic distance ≤1.5%) and used multivariable logistic regression to examine changes from 2009-2012 to 2013-2016 in proportions of MSM linked to young MSM who were >5 years older or of the same race/ethnicity. RESULTS Among 9510 young MSM linked to another MSM with a closely related virus, 37% linked to an older MSM and 62% linked to an MSM of the same race/ethnicity. Comparing 2013-2016 with 2009-2012, we found increases in linkage of older MSM to young MSM, with the most substantial increases seen in Hispanic/Latinos aged 13-19 [adjusted prevalence ratio (APR) = 1.31, 95% confidence interval (CI) = 1.11 to 1.56] and blacks aged 13-19 (APR = 1.23, CI = 1.06 to 1.41) and 20-24 years (APR = 1.14, CI = 1.02 to 1.28). By contrast, change in linkage patterns among racial/ethnic groups was unremarkable. CONCLUSIONS We found evidence of increased age mixing among MSM with respect to HIV transmission over time, which coincides temporally with changes in partner-seeking behavior such as increased use of mobile applications. These findings indicate the importance of social factors on HIV sexual and transmission networks and suggest that prevention efforts need to effectively reach MSM of all ages.
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20
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Bonsall D, Golubchik T, de Cesare M, Limbada M, Kosloff B, MacIntyre-Cockett G, Hall M, Wymant C, Ansari MA, Abeler-Dörner L, Schaap A, Brown A, Barnes E, Piwowar-Manning E, Eshleman S, Wilson E, Emel L, Hayes R, Fidler S, Ayles H, Bowden R, Fraser C. A Comprehensive Genomics Solution for HIV Surveillance and Clinical Monitoring in Low-Income Settings. J Clin Microbiol 2020; 58:e00382-20. [PMID: 32669382 PMCID: PMC7512176 DOI: 10.1128/jcm.00382-20] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 07/10/2020] [Indexed: 01/01/2023] Open
Abstract
Viral genetic sequencing can be used to monitor the spread of HIV drug resistance, identify appropriate antiretroviral regimes, and characterize transmission dynamics. Despite decreasing costs, next-generation sequencing (NGS) is still prohibitively costly for routine use in generalized HIV epidemics in low- and middle-income countries. Here, we present veSEQ-HIV, a high-throughput, cost-effective NGS sequencing method and computational pipeline tailored specifically to HIV, which can be performed using leftover blood drawn for routine CD4 cell count testing. This method overcomes several major technical challenges that have prevented HIV sequencing from being used routinely in public health efforts; it is fast, robust, and cost-efficient, and generates full genomic sequences of diverse strains of HIV without bias. The complete veSEQ-HIV pipeline provides viral load estimates and quantitative summaries of drug resistance mutations; it also exploits information on within-host viral diversity to construct directed transmission networks. We evaluated the method's performance using 1,620 plasma samples collected from individuals attending 10 large urban clinics in Zambia as part of the HPTN 071-2 study (PopART Phylogenetics). Whole HIV genomes were recovered from 91% of samples with a viral load of >1,000 copies/ml. The cost of the assay (30 GBP per sample) compares favorably with existing VL and HIV genotyping tests, proving an affordable option for combining HIV clinical monitoring with molecular epidemiology and drug resistance surveillance in low-income settings.
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Affiliation(s)
- David Bonsall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Tanya Golubchik
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Mariateresa de Cesare
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Mohammed Limbada
- ZAMBART, University of Zambia, Lusaka, Zambia
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Barry Kosloff
- ZAMBART, University of Zambia, Lusaka, Zambia
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - George MacIntyre-Cockett
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Matthew Hall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Chris Wymant
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - M Azim Ansari
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Peter Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom
| | - Lucie Abeler-Dörner
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Ab Schaap
- ZAMBART, University of Zambia, Lusaka, Zambia
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Anthony Brown
- Peter Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom
| | - Eleanor Barnes
- Peter Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom
| | | | - Susan Eshleman
- Dept. of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Ethan Wilson
- Statistical Centre for HIV/AIDS Research, Fred Hutchinson Cancer Research Centre, Seattle, Washington, USA
| | - Lynda Emel
- Statistical Centre for HIV/AIDS Research, Fred Hutchinson Cancer Research Centre, Seattle, Washington, USA
| | - Richard Hayes
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Sarah Fidler
- Department of Infectious Disease, Imperial College London, Imperial College NIHR BRC, London, United Kingdom
| | - Helen Ayles
- ZAMBART, University of Zambia, Lusaka, Zambia
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Rory Bowden
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
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21
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Dennis AM, Cohen MS, Rucinski KB, Rutstein SE, Powers KA, Pasquale DK, Phiri S, Hosseinipour MC, Kamanga G, Nsona D, Massa C, Hoffman IF, Pettifor AE, Miller WC. Human Immunodeficiency Virus (HIV)-1 Transmission Among Persons With Acute HIV-1 Infection in Malawi: Demographic, Behavioral, and Phylogenetic Relationships. Clin Infect Dis 2020; 69:853-860. [PMID: 30476007 DOI: 10.1093/cid/ciy1006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Accepted: 11/22/2018] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Understanding sexual networks involving acute human immunodeficiency virus (HIV)-1 infections (AHI) may lead to prevention opportunities to mitigate high rates of onward transmission. We evaluated HIV-1 phylogenetic and behavioral characteristics among persons with AHI and their referred partners. METHODS Between 2012 and 2014, 46 persons with AHI in Malawi participated in a combined behavioral and biomedical intervention. Participants referred sexual partners by passive referral. Demographics and sexual behaviors were collected through interviews and HIV-1 genetic relationships were assessed with phylogenetics. RESULTS Among 45 AHI participants with HIV-1 sequences, none was phylogenetically-linked with another AHI index. There were 19 (42%) AHI participants who referred a single partner that returned for testing. Most partners (n = 17) were HIV-infected, with 15 (88%) presenting with an established infection. There were 14 index-partner pairs that had sequences available; 13 (93%) pairs were phylogenetically-linked dyads. The AHI index was female in 7/13 (54%) dyads. Age-disparate relationships among dyads were common (≥5-year age difference in 67% of dyads), including 3/6 dyads involving a male index and a younger woman. Index participants with a referred partner were more likely to report no casual partners and to be living with their current partner than participants not in dyads. CONCLUSIONS Passive-partner referral successfully identified partners with genetically-similar HIV infections-the likely source of infection-but only 40% of index cases referred partners who presented for HIV-1 testing. Future work evaluating assisted partner notification may help reach susceptible partners or more people with untreated HIV-1 infections connected to acute transmission. CLINICAL TRIALS REGISTRATION NCT01450189.
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Affiliation(s)
- Ann M Dennis
- Division of Infectious Diseases, University of North Carolina at Chapel Hill
| | - Myron S Cohen
- Division of Infectious Diseases, University of North Carolina at Chapel Hill
| | - Katherine B Rucinski
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Sarah E Rutstein
- Division of Infectious Diseases, University of North Carolina at Chapel Hill
| | - Kimberly A Powers
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
| | - Dana K Pasquale
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
| | - Sam Phiri
- Lighthouse Trust, University of North Carolina Project, Lilongwe, Malawi
| | - Mina C Hosseinipour
- Division of Infectious Diseases, University of North Carolina at Chapel Hill.,University of North Carolina Project, Lilongwe, Malawi
| | - Gift Kamanga
- University of North Carolina Project, Lilongwe, Malawi
| | - Dominic Nsona
- Lighthouse Trust, University of North Carolina Project, Lilongwe, Malawi
| | - Cecilia Massa
- University of North Carolina Project, Lilongwe, Malawi
| | - Irving F Hoffman
- Division of Infectious Diseases, University of North Carolina at Chapel Hill
| | - Audrey E Pettifor
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
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22
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Rudolph AE, Martinez O, Davison R, Amuchi CB. Informed consent for HIV phylogenetic research: A case study of urban individuals living with HIV approached for enrollment in an HIV study. EHQUIDAD 2020; 2020:129-143. [PMID: 32954381 PMCID: PMC7497840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
INTRODUCTION Phylogenetic analyses can provide insights on HIV tansmission dynamics. Country and state-level differences in HIV criminalization and disclosure laws and advances in next generation sequencing could impact perceived study risks. METHODS We present study opt-out rates and the reasons provided during enrollment for a study conducted in Boston (6/2017-8/2018). RESULTS Of 90 patients approached to participate, 45 did not consent to participate. Reasons for not participating included unwillingness to discuss their HIV status, privacy and confidentiality concerns, disinterest, and lack of time. CONLUSIONS Given low participation rates and concerns related to HIV disclosure, privacy, and confidentiality, these questions remain (1) should informed consent be required for all phylogenetic analyses, including deidentified and surveillance data? (2) what additional steps can researchers take to protect the privacy of individuals, particularly in contexts where HIV is criminalized or there have been civil/criminal cases investigating HIV transmission? And (3) what role can community members play to minimize the potential risks, particularly for those most marginalized? These questions require input from both researchers and community members living with HIV/AIDS.
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Affiliation(s)
- Abby E. Rudolph
- Department of Epidemiology and Biostatistics, Temple
University College of Public Health, Philadelphia, USA
| | - Omar Martinez
- School of Social Work, Temple University College of Public
Health, Philadelphia, USA
| | - Robin Davison
- School of Social Work, Temple University College of Public
Health, Philadelphia, USA
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23
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Zhang J, Yao J, Jiang J, Pan X, Luo M, Xia Y, Fan Q, Ding X, Ruan J, Handel A, Bahl J, Chen W, Zha L, Fu T. Migration interacts with the local transmission of HIV in developed trade areas: A molecular transmission network analysis in China. INFECTION GENETICS AND EVOLUTION 2020; 84:104376. [PMID: 32454244 DOI: 10.1016/j.meegid.2020.104376] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Revised: 05/12/2020] [Accepted: 05/20/2020] [Indexed: 11/16/2022]
Abstract
The HIV-1 epidemic is a remarkable public health concern in China, especially in developed trade areas. We aimed to investigate the interaction of migration with the local transmission network in a typical trade area, Yiwu City, the world's largest commodity distribution center. Based on 390 pol sequences from 413 participants diagnosed between 2014 and 2016, putative transmission clusters and the underlying demographic and behavioral characteristics were analyzed. Recent infection status was determined by HIV-1 limiting antigen avidity enzyme immunoassay to identify active clusters. Multiple subtypes were identified, with a predominance of CRF01_AE (47.4%) and CRF07_BC (40.8%), followed by 9 other subtypes and 8 URFs. Multivariable analyses revealed that individuals in clusters were more likely to be local residents, infected through heterosexual behaviors, and infected with CRF01_AE (P < .05). Of men who have sex with men (MSM), 81% were linked to other MSM, and only 3% were linked to heterosexual women. Of heterosexual women, 67% were linked to heterosexual men, and 11% to MSM. Yiwu residents were more likely to link to locals than that of migrants (43% vs 20%, P < .001). By contrast, local MSM and migrant MSM all had high percentages of linkage to migrant MSM (57% vs 69%, P = .069). Our findings reveal that migration promotes the dissemination and dynamic change of HIV, which are interwoven between locals and migrants. The results highlight the far-reaching influence of migrant MSM on the local HIV transmission network.
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Affiliation(s)
- Jiafeng Zhang
- Department of HIV/AIDS & STD control and prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Jiaming Yao
- Department of HIV/AIDS & STD control and prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Jun Jiang
- Department of HIV/AIDS & STD control and prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Xiaohong Pan
- Department of HIV/AIDS & STD control and prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China.
| | - Mingyu Luo
- Department of HIV/AIDS & STD control and prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Yan Xia
- Department of HIV/AIDS & STD control and prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Qin Fan
- Department of HIV/AIDS & STD control and prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Xiaobei Ding
- Department of HIV/AIDS & STD control and prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Jianjun Ruan
- Yiwu Municipal Center for Disease Control and Prevention, Yiwu 322000, China
| | - Andreas Handel
- Department of Epidemiology and Biostatistics, Health Informatics Institute, Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA, USA
| | - Justin Bahl
- Center for the Ecology of Infectious Diseases, Department of Infectious Disease, Department of Epidemiology and Biostatistics, Institute of Bioinformatics, University of Georgia, Athens, GA, USA; Duke-NUS Graduate Medical School, Singapore
| | - Wanjun Chen
- Department of HIV/AIDS & STD control and prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Lianqi Zha
- Yiwu Municipal Center for Disease Control and Prevention, Yiwu 322000, China
| | - Tao Fu
- Yiwu Municipal Center for Disease Control and Prevention, Yiwu 322000, China.
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24
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Characteristics Associated With Human Immunodeficiency Virus Transmission Networks Involving Adolescent Girls and Young Women in Human Immunodeficiency Virus Prevention Trials Network 068 Study. Sex Transm Dis 2020; 46:e46-e49. [PMID: 30985638 DOI: 10.1097/olq.0000000000000954] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
We combined behavioral survey data from the human immunodeficiency virus (HIV) Prevention Trials Network 068 study with phylogenetic information to determine if cluster membership was associated with characteristics of young women and their partners. Clusters were more likely to involve young women from specific villages and schools, indicating some localized transmission.Supplemental digital content is available in the text.
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25
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Understanding disclosed and cryptic HIV transmission risk via genetic analysis: what are we missing and when does it matter? Curr Opin HIV AIDS 2020; 14:205-212. [PMID: 30946142 DOI: 10.1097/coh.0000000000000537] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
PURPOSE OF REVIEW To discuss the recent HIV phylogenetic analyses examining HIV transmission patterns among and within risk groups. RECENT FINDINGS Phylodynamic analysis has recently been applied to multiple HIV outbreaks among people who inject drugs to determine whether HIV transmission is ongoing. Large-scale analyses of datasets of HIV sequences collected for drug-resistance testing provide population-level insights into transmission patterns. One focus across world regions has been to investigate whether age-disparity is a driver of HIV transmission. In sub-Saharan Africa, researchers have examined transmission between heterosexuals and MSM and between high prevalence fishing communities and inland communities. In the US and the UK, cryptic risk groups such as nondisclosed MSM and the partners of transgender women are increasingly being uncovered based on their position in densely sampled molecular transmission networks. SUMMARY Analysis of HIV genetic sequence can resolve viral transmission patterns between risk groups at unprecedented scales and levels of detail. Future research should focus on understanding the effect of missing data on inferences and the biases of different methods. Uncovering groups and patterns obscured from traditional epidemiolocal analyses is exciting but should not compromise the privacy of the groups in question.
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26
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Mak L, Perera D, Lang R, Kossinna P, He J, Gill MJ, Long Q, van Marle G. Evaluation of A Phylogenetic Pipeline to Examine Transmission Networks in A Canadian HIV Cohort. Microorganisms 2020; 8:E196. [PMID: 32023939 PMCID: PMC7074708 DOI: 10.3390/microorganisms8020196] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 01/23/2020] [Accepted: 01/29/2020] [Indexed: 01/08/2023] Open
Abstract
Keywords: HIV; Canada; molecular phylogenetics; viral evolution; person-to-person transmission inference; transmission network; summary statistics.
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Affiliation(s)
- Lauren Mak
- Department of Biochemistry & Molecular Biology, Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada (P.K.)
| | - Deshan Perera
- Department of Biochemistry & Molecular Biology, Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada (P.K.)
| | - Raynell Lang
- Department of Medicine, Cumming School of Medicine, University of Calgary and Alberta Health Services, Calgary, AB T2N 4N1, Canada
| | - Pathum Kossinna
- Department of Biochemistry & Molecular Biology, Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada (P.K.)
| | - Jingni He
- Department of Biochemistry & Molecular Biology, Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada (P.K.)
| | - M. John Gill
- Department of Medicine, Cumming School of Medicine, University of Calgary and Alberta Health Services, Calgary, AB T2N 4N1, Canada
| | - Quan Long
- Department of Biochemistry & Molecular Biology, Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB T2N 4N1, Canada (P.K.)
- Department of Medical Genetics, and Mathematics & Statistics, Alberta Children’s Hospital Research Institute, O’Brien Institute for Public Health, University of Calgary, Calgary, AB T2N 4N1, Canada
- Department of Mathematics & Statistics, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Guido van Marle
- Department of Microbiology, Immunology, and Infectious Diseases, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
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27
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Han AX, Parker E, Scholer F, Maurer-Stroh S, Russell CA. Phylogenetic Clustering by Linear Integer Programming (PhyCLIP). Mol Biol Evol 2020; 36:1580-1595. [PMID: 30854550 PMCID: PMC6573476 DOI: 10.1093/molbev/msz053] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Subspecies nomenclature systems of pathogens are increasingly based on sequence data. The use of phylogenetics to identify and differentiate between clusters of genetically similar pathogens is particularly prevalent in virology from the nomenclature of human papillomaviruses to highly pathogenic avian influenza (HPAI) H5Nx viruses. These nomenclature systems rely on absolute genetic distance thresholds to define the maximum genetic divergence tolerated between viruses designated as closely related. However, the phylogenetic clustering methods used in these nomenclature systems are limited by the arbitrariness of setting intra and intercluster diversity thresholds. The lack of a consensus ground truth to define well-delineated, meaningful phylogenetic subpopulations amplifies the difficulties in identifying an informative distance threshold. Consequently, phylogenetic clustering often becomes an exploratory, ad hoc exercise. Phylogenetic Clustering by Linear Integer Programming (PhyCLIP) was developed to provide a statistically principled phylogenetic clustering framework that negates the need for an arbitrarily defined distance threshold. Using the pairwise patristic distance distributions of an input phylogeny, PhyCLIP parameterizes the intra and intercluster divergence limits as statistical bounds in an integer linear programming model which is subsequently optimized to cluster as many sequences as possible. When applied to the hemagglutinin phylogeny of HPAI H5Nx viruses, PhyCLIP was not only able to recapitulate the current WHO/OIE/FAO H5 nomenclature system but also further delineated informative higher resolution clusters that capture geographically distinct subpopulations of viruses. PhyCLIP is pathogen-agnostic and can be generalized to a wide variety of research questions concerning the identification of biologically informative clusters in pathogen phylogenies. PhyCLIP is freely available at http://github.com/alvinxhan/PhyCLIP, last accessed March 15, 2019.
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Affiliation(s)
- Alvin X Han
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore.,NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore (NUS), Singapore.,Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| | - Edyth Parker
- Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.,Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Frits Scholer
- Department of Medical Microbiology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| | - Sebastian Maurer-Stroh
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore.,NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore (NUS), Singapore.,Department of Biological Sciences, National University of Singapore, Singapore
| | - Colin A Russell
- Laboratory of Applied Evolutionary Biology, Department of Medical Microbiology, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
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28
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Distinct rates and patterns of spread of the major HIV-1 subtypes in Central and East Africa. PLoS Pathog 2019; 15:e1007976. [PMID: 31809523 PMCID: PMC6897401 DOI: 10.1371/journal.ppat.1007976] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 07/11/2019] [Indexed: 12/21/2022] Open
Abstract
Since the ignition of the HIV-1 group M pandemic in the beginning of the 20th century, group M lineages have spread heterogeneously throughout the world. Subtype C spread rapidly through sub-Saharan Africa and is currently the dominant HIV lineage worldwide. Yet the epidemiological and evolutionary circumstances that contributed to its epidemiological expansion remain poorly understood. Here, we analyse 346 novel pol sequences from the DRC to compare the evolutionary dynamics of the main HIV-1 lineages, subtypes A1, C and D. Our results place the origins of subtype C in the 1950s in Mbuji-Mayi, the mining city of southern DRC, while subtypes A1 and D emerged in the capital city of Kinshasa, and subtypes H and J in the less accessible port city of Matadi. Following a 15-year period of local transmission in southern DRC, we find that subtype C spread at least three-fold faster than other subtypes circulating in Central and East Africa. In conclusion, our results shed light on the origins of HIV-1 main lineages and suggest that socio-historical rather than evolutionary factors may have determined the epidemiological fate of subtype C in sub-Saharan Africa.
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29
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Verhofstede C, Mortier V, Dauwe K, Callens S, Deblonde J, Dessilly G, Delforge ML, Fransen K, Sasse A, Stoffels K, Van Beckhoven D, Vanroye F, Vaira D, Vancutsem E, Van Laethem K. Exploring HIV-1 Transmission Dynamics by Combining Phylogenetic Analysis and Infection Timing. Viruses 2019; 11:v11121096. [PMID: 31779195 PMCID: PMC6950120 DOI: 10.3390/v11121096] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 11/21/2019] [Accepted: 11/22/2019] [Indexed: 12/12/2022] Open
Abstract
HIV-1 pol sequences obtained through baseline drug resistance testing of patients newly diagnosed between 2013 and 2017 were analyzed for genetic similarity. For 927 patients the information on genetic similarity was combined with demographic data and with information on the recency of infection. Overall, 48.3% of the patients were genetically linked with 11.4% belonging to a pair and 36.9% involved in a cluster of ≥3 members. The percentage of early diagnosed (≤4 months after infection) was 28.6%. Patients of Belgian origin were more frequently involved in transmission clusters (49.7% compared to 15.3%) and diagnosed earlier (37.4% compared to 12.2%) than patients of Sub-Saharan African origin. Of the infections reported to be locally acquired, 69.5% were linked (14.1% paired and 55.4% in a cluster). Equal parts of early and late diagnosed individuals (59.9% and 52.4%, respectively) were involved in clusters. The identification of a genetically linked individual for the majority of locally infected patients suggests a high rate of diagnosis in this population. Diagnosis however is often delayed for >4 months after infection increasing the opportunities for onward transmission. Prevention of local infection should focus on earlier diagnosis and protection of the still uninfected members of sexual networks with human immunodeficiency virus (HIV)-infected members.
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Affiliation(s)
- Chris Verhofstede
- Aids Reference Laboratory, Department of Diagnostic Sciences, Ghent University, 9000 Ghent, Belgium; (V.M.); (K.D.)
- Correspondence:
| | - Virginie Mortier
- Aids Reference Laboratory, Department of Diagnostic Sciences, Ghent University, 9000 Ghent, Belgium; (V.M.); (K.D.)
| | - Kenny Dauwe
- Aids Reference Laboratory, Department of Diagnostic Sciences, Ghent University, 9000 Ghent, Belgium; (V.M.); (K.D.)
| | - Steven Callens
- Aids Reference Center, Department of Internal Medicine, Ghent University Hospital, 9000 Ghent, Belgium;
| | - Jessika Deblonde
- Epidemiology of Infectious Diseases Unit, Scientific Institute of Public Health Sciensano, 1050 Brussels, Belgium; (J.D.); (A.S.); (D.V.B.)
| | - Géraldine Dessilly
- Aids Reference Laboratory, Medical Microbiology Unit, Université Catholique de Louvain, 1200 Brussels, Belgium;
| | - Marie-Luce Delforge
- Aids Reference Laboratory, Université Libre de Bruxelles, 1050 Brussels, Belgium;
| | - Katrien Fransen
- HIV/STD Reference Laboratory, Department of Clinical Sciences, Institute of Tropical Medicine, 2000 Antwerp, Belgium; (K.F.); (F.V.)
| | - André Sasse
- Epidemiology of Infectious Diseases Unit, Scientific Institute of Public Health Sciensano, 1050 Brussels, Belgium; (J.D.); (A.S.); (D.V.B.)
| | - Karolien Stoffels
- Aids Reference Laboratory, Centre Hospitalier Universitaire St. Pierre, 1000 Brussels, Belgium;
| | - Dominique Van Beckhoven
- Epidemiology of Infectious Diseases Unit, Scientific Institute of Public Health Sciensano, 1050 Brussels, Belgium; (J.D.); (A.S.); (D.V.B.)
| | - Fien Vanroye
- HIV/STD Reference Laboratory, Department of Clinical Sciences, Institute of Tropical Medicine, 2000 Antwerp, Belgium; (K.F.); (F.V.)
| | - Dolores Vaira
- Aids Reference Laboratory, Centre Hospitalier Universitaire de Liège, 4000 Liège, Belgium;
| | - Ellen Vancutsem
- Aids Reference Laboratory, Vrije Universiteit Brussel VUB, 1090 Brussels, Belgium;
| | - Kristel Van Laethem
- Aids Reference Laboratory, University Hospital Leuven, 3000 Leuven, Belgium;
- Rega Institute for Medical Research, Department of Microbiology, Immunology and Transplantation, KU Leuven, 3000 Leuven, Belgium
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30
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Mutenherwa F, Wassenaar DR, de Oliveira T. Ethical issues associated with HIV molecular epidemiology: a qualitative exploratory study using inductive analytic approaches. BMC Med Ethics 2019; 20:67. [PMID: 31590695 PMCID: PMC6781327 DOI: 10.1186/s12910-019-0403-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 08/30/2019] [Indexed: 11/30/2022] Open
Abstract
Background HIV molecular epidemiology is increasingly recognized as a vital source of information for understanding HIV transmission dynamics. Despite extensive use of these data-intensive techniques in both research and public health settings, the ethical issues associated with this science have received minimal attention. As the discipline evolves, there is reasonable concern that existing ethical and legal frameworks and standards might lag behind the rapid methodological developments in this field. This is a follow-up on our earlier work that applied a predetermined analytical framework to examine the perspectives of a sample of scientists from the fields of epidemiology, public health, virology and bioethics on key ethical issues associated with HIV molecular epidemiology in HIV network research. Methods Fourteen in-depth interviews were conducted with scientists from the fields of molecular epidemiology, public health, virology and bioethics. Inductive analytical approaches were applied to identify key themes that emerged from the data. Results Our interviewees acknowledged the potential positive impact of molecular epidemiology in the fight against HIV. However, they were concerned that HIV phylogenetics research messages may be incorrectly interpreted if not presented at the appropriate level. There was consensus that HIV phylogenetics research presents a potential risk to privacy, but the probability and magnitude of this risk was less obvious. Although participants acknowledged the social value that could be realized from the analysis of HIV genetic sequences, there was a perceived fear that the boundaries for use of HIV sequence data were not clearly defined. Conclusions Our findings highlight distinct ethical issues arising from HIV molecular epidemiology. As the discipline evolves and HIV sequence data become increasingly available, it is critical to ensure that ethical standards keep pace with biomedical advancements. We argue that the ethical issues raised in this study, whether real or perceived, require further conceptual and empirical examination.
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Affiliation(s)
- Farirai Mutenherwa
- School of Applied Human Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg, 3209, South Africa. .,KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa.
| | - Douglas R Wassenaar
- School of Applied Human Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg, 3209, South Africa
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa.,Department of Global Health, University of Washington, Seattle, USA.,Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
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Leveraging Phylogenetics to Understand HIV Transmission and Partner Notification Networks. J Acquir Immune Defic Syndr 2019; 78:367-375. [PMID: 29940601 DOI: 10.1097/qai.0000000000001695] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Partner notification is an important component of public health test and treat interventions. To enhance this essential function, we assessed the potential for molecular methods to supplement routine partner notification and corroborate HIV networks. METHODS All persons diagnosed with HIV infection in Wake County, NC, during 2012-2013 and their disclosed sexual partners were included in a sexual network. A data set containing HIV-1 pol sequences collected in NC during 1997-2014 from 15,246 persons was matched to HIV-positive persons in the network and used to identify putative transmission clusters. Both networks were compared. RESULTS The partner notification network comprised 280 index cases and 383 sexual partners and high-risk social contacts (n = 131 HIV-positive). Of the 411 HIV-positive persons in the partner notification network, 181 (44%) did not match to a HIV sequence, 61 (15%) had sequences but were not identified in a transmission cluster, and 169 (41%) were identified in a transmission cluster. More than half (59%) of transmission clusters bridged sexual network partnerships that were not recognized in the partner notification; most of these clusters were dominated by men who have sex with men. CONCLUSIONS Partner notification and HIV sequence analysis provide complementary representations of the existent partnerships underlying the HIV transmission network. The partner notification network components were bridged by transmission clusters, particularly among components dominated by men who have sex with men. Supplementing the partner notification network with phylogenetic data highlighted avenues for intervention.
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Kafando A, Serhir B, Doualla-Bell F, Fournier E, Sangaré MN, Martineau C, Sylla M, Chamberland A, El-Far M, Charest H, Tremblay CL. A Short-Term Assessment of Nascent HIV-1 Transmission Clusters Among Newly Diagnosed Individuals Using Envelope Sequence-Based Phylogenetic Analyses. AIDS Res Hum Retroviruses 2019; 35:906-919. [PMID: 31407606 PMCID: PMC6806616 DOI: 10.1089/aid.2019.0142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The identification of transmission clusters (TCs) of HIV-1 using phylogenetic analyses can provide insights into viral transmission network and help improve prevention strategies. We compared the use of partial HIV-1 envelope fragment of 1,070 bp with its loop 3 (108 bp) to determine its utility in inferring HIV-1 transmission clustering. Serum samples of recently (n = 106) and chronically (n = 156) HIV-1-infected patients with status confirmed were sequenced. HIV-1 envelope nucleotide-based phylogenetic analyses were used to infer HIV-1 TCs. Those were constructed using ClusterPickerGUI_1.2.3 considering a pairwise genetic distance of ≤10% threshold. Logistic regression analyses were used to examine the relationship between the demographic factors that were likely associated with HIV-1 clustering. Ninety-eight distinct consensus envelope sequences were subjected to phylogenetic analyses. Using a partial envelope fragment sequence, 42 sequences were grouped into 15 distinct small TCs while the V3 loop reproduces 10 clusters. The agreement between the partial envelope and the V3 loop fragments was significantly moderate with a Cohen's kappa (κ) coefficient of 0.59, p < .00001. The mean age (<38.8 years) and HIV-1 B subtype are two factors identified that were significantly associated with HIV-1 transmission clustering in the cohort, odds ratio (OR) = 0.25, 95% confidence interval (CI, 0.04–0.66), p = .002 and OR: 0.17, 95% CI (0.10–0.61), p = .011, respectively. The present study confirms that a partial fragment of the HIV-1 envelope sequence is a better predictor of transmission clustering. However, the loop 3 segment may be useful in screening purposes and may be more amenable to integration in surveillance programs.
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Affiliation(s)
- Alexis Kafando
- Département de Microbiologie, Infectiologie et Immunologie, Faculté de Médecine, Université de Montréal, Montréal, Canada
| | - Bouchra Serhir
- Laboratoire de Santé Publique du Québec, Institut National de Santé publique du Québec, Sainte-Anne-de-Bellevue, Canada
| | - Florence Doualla-Bell
- Laboratoire de Santé Publique du Québec, Institut National de Santé publique du Québec, Sainte-Anne-de-Bellevue, Canada
| | - Eric Fournier
- Laboratoire de Santé Publique du Québec, Institut National de Santé publique du Québec, Sainte-Anne-de-Bellevue, Canada
| | - Mohamed Ndongo Sangaré
- Département de Médecine Sociale et Préventive, École de Santé Publique, Université de Montréal, Montréal, Canada
| | - Christine Martineau
- Laboratoire de Santé Publique du Québec, Institut National de Santé publique du Québec, Sainte-Anne-de-Bellevue, Canada
| | - Mohamed Sylla
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada
| | - Annie Chamberland
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada
| | - Mohamed El-Far
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada
| | - Hugues Charest
- Département de Microbiologie, Infectiologie et Immunologie, Faculté de Médecine, Université de Montréal, Montréal, Canada
- Laboratoire de Santé Publique du Québec, Institut National de Santé publique du Québec, Sainte-Anne-de-Bellevue, Canada
| | - Cécile L. Tremblay
- Département de Microbiologie, Infectiologie et Immunologie, Faculté de Médecine, Université de Montréal, Montréal, Canada
- Laboratoire de Santé Publique du Québec, Institut National de Santé publique du Québec, Sainte-Anne-de-Bellevue, Canada
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Canada
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Volz EM, Le Vu S, Ratmann O, Tostevin A, Dunn D, Orkin C, O'Shea S, Delpech V, Brown A, Gill N, Fraser C. Molecular Epidemiology of HIV-1 Subtype B Reveals Heterogeneous Transmission Risk: Implications for Intervention and Control. J Infect Dis 2019; 217:1522-1529. [PMID: 29506269 PMCID: PMC5913615 DOI: 10.1093/infdis/jiy044] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Accepted: 01/22/2018] [Indexed: 11/25/2022] Open
Abstract
Background The impact of HIV pre-exposure prophylaxis (PrEP) depends on infections averted by protecting vulnerable individuals as well as infections averted by preventing transmission by those who would have been infected if not receiving PrEP. Analysis of HIV phylogenies reveals risk factors for transmission, which we examine as potential criteria for allocating PrEP. Methods We analyzed 6912 HIV-1 partial pol sequences from men who have sex with men (MSM) in the United Kingdom combined with global reference sequences and patient-level metadata. Population genetic models were developed that adjust for stage of infection, global migration of HIV lineages, and changing incidence of infection through time. Models were extended to simulate the effects of providing susceptible MSM with PrEP. Results We found that young age <25 years confers higher risk of HIV transmission (relative risk = 2.52 [95% confidence interval, 2.32–2.73]) and that young MSM are more likely to transmit to one another than expected by chance. Simulated interventions indicate that 4-fold more infections can be averted over 5 years by focusing PrEP on young MSM. Conclusions Concentrating PrEP doses on young individuals can avert more infections than random allocation.
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Affiliation(s)
- Erik M Volz
- Department of Infectious Disease Epidemiology and the National Institute for Health Research Health Protection Research Unit on Modeling Methodology, Imperial College London
| | - Stephane Le Vu
- Department of Infectious Disease Epidemiology and the National Institute for Health Research Health Protection Research Unit on Modeling Methodology, Imperial College London
| | - Oliver Ratmann
- Department of Infectious Disease Epidemiology and the National Institute for Health Research Health Protection Research Unit on Modeling Methodology, Imperial College London
| | - Anna Tostevin
- Institute for Global Health, University College London
| | - David Dunn
- Institute for Global Health, University College London
| | | | - Siobhan O'Shea
- Infection Sciences, Viapath Analytics, Guy's and St Thomas' NHS Foundation Trust, London
| | | | | | | | - Christophe Fraser
- Li Ka Shing Centre for Health Information and Discovery, Oxford University, United Kingdom
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German D, Grabowski MK, Beyrer C. Enhanced use of phylogenetic data to inform public health approaches to HIV among men who have sex with men. Sex Health 2019; 14:89-96. [PMID: 27584826 DOI: 10.1071/sh16056] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Accepted: 07/29/2016] [Indexed: 12/14/2022]
Abstract
The multidimensional nature and continued evolution of HIV epidemics among men who have sex with men (MSM) requires innovative intervention approaches. Strategies are needed that recognise the individual, social and structural factors driving HIV transmission; that can pinpoint networks with heightened transmission risk; and that can help target intervention in real time. HIV phylogenetics is a rapidly evolving field with strong promise for informing innovative responses to the HIV epidemic among MSM. Currently, HIV phylogenetic insights are providing new understandings of characteristics of HIV epidemics involving MSM, social networks influencing transmission, characteristics of HIV transmission clusters involving MSM, targets for antiretroviral and other prevention strategies and dynamics of emergent epidemics. Maximising the potential of HIV phylogenetics for HIV responses among MSM will require attention to key methodological challenges and ethical considerations, as well as resolving key implementation and scientific questions. Enhanced and integrated use of HIV surveillance, sociobehavioural and phylogenetic data resources are becoming increasingly critical for informing public health approaches to HIV among MSM.
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Affiliation(s)
- Danielle German
- Johns Hopkins Bloomberg School of Public Health, Department of Health, Behavior and Society, 624N. Broadway, Baltimore, MD 21205, USA
| | - Mary Kate Grabowski
- Johns Hopkins Bloomberg School of Public Health, Department of Health, Behavior and Society, 624N. Broadway, Baltimore, MD 21205, USA
| | - Chris Beyrer
- Johns Hopkins Bloomberg School of Public Health, Department of Health, Behavior and Society, 624N. Broadway, Baltimore, MD 21205, USA
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Kosakovsky Pond SL, Weaver S, Leigh Brown AJ, Wertheim JO. HIV-TRACE (TRAnsmission Cluster Engine): a Tool for Large Scale Molecular Epidemiology of HIV-1 and Other Rapidly Evolving Pathogens. Mol Biol Evol 2019; 35:1812-1819. [PMID: 29401317 DOI: 10.1093/molbev/msy016] [Citation(s) in RCA: 162] [Impact Index Per Article: 32.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
In modern applications of molecular epidemiology, genetic sequence data are routinely used to identify clusters of transmission in rapidly evolving pathogens, most notably HIV-1. Traditional 'shoe-leather' epidemiology infers transmission clusters by tracing chains of partners sharing epidemiological connections (e.g., sexual contact). Here, we present a computational tool for identifying a molecular transmission analog of such clusters: HIV-TRACE (TRAnsmission Cluster Engine). HIV-TRACE implements an approach inspired by traditional epidemiology, by identifying chains of partners whose viral genetic relatedness imply direct or indirect epidemiological connections. Molecular transmission clusters are constructed using codon-aware pairwise alignment to a reference sequence followed by pairwise genetic distance estimation among all sequences. This approach is computationally tractable and is capable of identifying HIV-1 transmission clusters in large surveillance databases comprising tens or hundreds of thousands of sequences in near real time, that is, on the order of minutes to hours. HIV-TRACE is available at www.hivtrace.org and from www.github.com/veg/hivtrace, along with the accompanying result visualization module from www.github.com/veg/hivtrace-viz. Importantly, the approach underlying HIV-TRACE is not limited to the study of HIV-1 and can be applied to study outbreaks and epidemics of other rapidly evolving pathogens.
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Affiliation(s)
| | - Steven Weaver
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
| | - Andrew J Leigh Brown
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
| | - Joel O Wertheim
- Department of Medicine, University of California, San Diego, CA
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Abstract
PURPOSE OF REVIEW This review summarizes the use of genetic similarity clusters to understand HIV transmission and inform prevention efforts. RECENT FINDINGS Recent emphases include the development of real-time cluster identification in order to interrupt transmission chains, the use of clusters to estimate rates of transmission along the HIV care cascade, and the extension of cluster analyses to understand transmission in the generalized epidemics of sub-Saharan Africa. Importantly, this recent empirical work has been accompanied by theoretical work that elucidates the processes that underlie HIV genetic similarity clusters; multiple studies suggest that clusters are not necessarily enriched with individuals with high transmission rates, but rather can reflect variation in sampling times within a population, with individuals sampled early in infection more likely to cluster. Analyses of genetic similarity clusters have great promise to inform HIV epidemiology and prevention. Future emphases should include the collection of additional sequence data from underrepresented populations, such as those in sub-Saharan Africa, and further development and evaluation of clustering methods.
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Affiliation(s)
- Mary Kate Grabowski
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Rakai Health Sciences Program, Baltimore, MD, USA
| | - Joshua T Herbeck
- International Clinical Research Center, Department of Global Health, University of Washington, Seattle, WA, USA.
| | - Art F Y Poon
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
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Using Contact Patterns to Inform HIV Interventions in Persons Who Inject Drugs in Northern Vietnam. J Acquir Immune Defic Syndr 2019; 78:1-8. [PMID: 29389769 DOI: 10.1097/qai.0000000000001632] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
OBJECTIVES Population mixing patterns can greatly inform allocation of HIV prevention interventions such as treatment as prevention or preexposure prophylaxis. Characterizing contact patterns among subgroups can help identify the specific combinations of contact expected to result in the greatest number of new infections. SETTING Baseline data from an intervention to reduce HIV-related risk behaviors in male persons who inject drugs (PWID) in the Northern Vietnamese province of Thai Nguyen were used for the analysis. METHODS Egocentric network data were provided by PWID who reported any drug-injection equipment sharing in the previous 3 months. Age-dependent mixing was assessed to explore its epidemiological implications on risk of HIV transmission risk (among those HIV-infected) and HIV acquisition risk (among those not infected) in PWID. RESULTS A total of 1139 PWID collectively reported 2070 equipment-sharing partnerships in the previous 3 months. Mixing by age identified the 30-34 and 35-39 years age groups as the groups from whom the largest number of new infections was transmitted, making them primary targets for treatment as prevention. Among the uninfected, 25-29, 30-35, and 35-39 years age groups had the highest HIV acquisition rate, making them the primary targets for preexposure prophylaxis. CONCLUSIONS Collection and analysis of contact patterns in PWID is feasible and can greatly inform infectious disease dynamics and targeting of appropriate interventions. Results presented also provide much needed empirical data on mixing to improve mathematical models of disease transmission in this population.
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38
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Dasgupta S, France AM, Brandt MG, Reuer J, Zhang T, Panneer N, Hernandez AL, Oster AM. Estimating Effects of HIV Sequencing Data Completeness on Transmission Network Patterns and Detection of Growing HIV Transmission Clusters. AIDS Res Hum Retroviruses 2019; 35:368-375. [PMID: 30403157 DOI: 10.1089/aid.2018.0181] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
HIV nucleotide sequence data can identify clusters of persons with genetically similar strains suggesting transmission. We simulated the effect of lowered data completeness, defined by the percent of persons with diagnosed HIV with a reported sequence, on transmission patterns and detection of growing HIV transmission clusters. We analyzed HIV surveillance data for persons with HIV diagnosed during 2008-2014 who resided in Michigan or Washington. We calculated genetic distances, constructed the inferred transmission network for each jurisdiction, and compared transmission network characteristics and detection of growing transmission clusters in the full dataset with artificially reduced datasets. Simulating lower levels of completeness resulted in decreased percentages of persons linked to a cluster from high completeness (full dataset) to low completeness (5%) (Michigan: 54%-18%; Washington, 46%-16%). Patterns of transmission between certain populations remained robust as data completeness level was reduced. As data completeness was artificially decreased, sensitivity of cluster detection substantially diminished in both states. In Michigan, sensitivity decreased from 100% with the full dataset, to 62% at 50% completeness and 21% at 25% completeness. In Washington, sensitivity decreased from 100% with the full dataset, to 71% at 50% completeness and 29% at 25% completeness. Lower sequence data completeness limits the ability to detect clusters that may benefit from investigation; however, inferences can be made about transmission patterns even with low data completeness, given sufficient numbers. Data completeness should be prioritized, as lack of or delays in detection of transmission clusters could result in additional infections.
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Affiliation(s)
- Sharoda Dasgupta
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Anne Marie France
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Mary-Grace Brandt
- Michigan Department of Health and Human Services, Southfield, Michigan
| | - Jennifer Reuer
- Washington State Department of Health, Tumwater, Washington
| | | | - Nivedha Panneer
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Angela L. Hernandez
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Alexandra M. Oster
- Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia
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Ratmann O, Grabowski MK, Hall M, Golubchik T, Wymant C, Abeler-Dörner L, Bonsall D, Hoppe A, Brown AL, de Oliveira T, Gall A, Kellam P, Pillay D, Kagaayi J, Kigozi G, Quinn TC, Wawer MJ, Laeyendecker O, Serwadda D, Gray RH, Fraser C. Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis. Nat Commun 2019; 10:1411. [PMID: 30926780 PMCID: PMC6441045 DOI: 10.1038/s41467-019-09139-4] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Accepted: 02/22/2019] [Indexed: 11/09/2022] Open
Abstract
To prevent new infections with human immunodeficiency virus type 1 (HIV-1) in sub-Saharan Africa, UNAIDS recommends targeting interventions to populations that are at high risk of acquiring and passing on the virus. Yet it is often unclear who and where these 'source' populations are. Here we demonstrate how viral deep-sequencing can be used to reconstruct HIV-1 transmission networks and to infer the direction of transmission in these networks. We are able to deep-sequence virus from a large population-based sample of infected individuals in Rakai District, Uganda, reconstruct partial transmission networks, and infer the direction of transmission within them at an estimated error rate of 16.3% [8.8-28.3%]. With this error rate, deep-sequence phylogenetics cannot be used against individuals in legal contexts, but is sufficiently low for population-level inferences into the sources of epidemic spread. The technique presents new opportunities for characterizing source populations and for targeting of HIV-1 prevention interventions in Africa.
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Affiliation(s)
- Oliver Ratmann
- Department of Mathematics, Imperial College London, London, SW72AZ, UK.
- Department of Infectious Disease, Epidemiology School of Public Health, Imperial College London, London, W21PG, UK.
| | - M Kate Grabowski
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, 21205-2196, USA
- Rakai Health Sciences Program, Entebbe, P.O.Box 49, Uganda
| | - Matthew Hall
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, OX3 7BN, UK
| | - Tanya Golubchik
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, OX3 7BN, UK
| | - Chris Wymant
- Department of Infectious Disease, Epidemiology School of Public Health, Imperial College London, London, W21PG, UK
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, OX3 7BN, UK
| | - Lucie Abeler-Dörner
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, OX3 7BN, UK
| | - David Bonsall
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, OX3 7BN, UK
| | - Anne Hoppe
- Division of Infection and Immunity, University College London, London, WC1E 6BT, UK
| | - Andrew Leigh Brown
- School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3FF, UK
| | - Tulio de Oliveira
- College of Health Sciences, University of KwaZulu-Natal, Durban, 4041, South Africa
| | - Astrid Gall
- European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Paul Kellam
- Department of Medicine, Imperial College London, London, W12 0HS, UK
| | - Deenan Pillay
- Division of Infection and Immunity, University College London, London, WC1E 6BT, UK
- Africa Health Research Institute, Private Bag X7, Durban, 4013, South Africa
| | - Joseph Kagaayi
- Rakai Health Sciences Program, Entebbe, P.O.Box 49, Uganda
| | - Godfrey Kigozi
- Rakai Health Sciences Program, Entebbe, P.O.Box 49, Uganda
| | - Thomas C Quinn
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, 21205-2196, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, 20892-9806, USA
| | - Maria J Wawer
- Rakai Health Sciences Program, Entebbe, P.O.Box 49, Uganda
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Oliver Laeyendecker
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, 21205-2196, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, 20892-9806, USA
| | - David Serwadda
- Rakai Health Sciences Program, Entebbe, P.O.Box 49, Uganda
- Makerere University School of Public Health, Kampala, 8HQG+3V, Uganda
| | - Ronald H Gray
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, 21205-2196, USA
- Rakai Health Sciences Program, Entebbe, P.O.Box 49, Uganda
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Christophe Fraser
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, Old Road Campus, University of Oxford, Oxford, OX3 7BN, UK
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Pérez AB, Vrancken B, Chueca N, Aguilera A, Reina G, García-del Toro M, Vera F, Von Wichman MA, Arenas JI, Téllez F, Pineda JA, Omar M, Bernal E, Rivero-Juárez A, Fernández-Fuertes E, de la Iglesia A, Pascasio JM, Lemey P, Garcia F, Cuypers L. Increasing importance of European lineages in seeding the hepatitis C virus subtype 1a epidemic in Spain. Euro Surveill 2019; 24:1800227. [PMID: 30862327 PMCID: PMC6402173 DOI: 10.2807/1560-7917.es.2019.24.9.1800227] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
BackgroundReducing the burden of the hepatitis C virus (HCV) requires large-scale deployment of intervention programmes, which can be informed by the dynamic pattern of HCV spread. In Spain, ongoing transmission of HCV is mostly fuelled by people who inject drugs (PWID) infected with subtype 1a (HCV1a).AimOur aim was to map how infections spread within and between populations, which could help formulate more effective intervention programmes to halt the HCV1a epidemic in Spain.MethodsEpidemiological links between HCV1a viruses from a convenience sample of 283 patients in Spain, mostly PWID, collected between 2014 and 2016, and 1,317, 1,291 and 1,009 samples collected abroad between 1989 and 2016 were reconstructed using sequences covering the NS3, NS5A and NS5B genes. To efficiently do so, fast maximum likelihood-based tree estimation was coupled to a flexible Bayesian discrete phylogeographic inference method.ResultsThe transmission network structure of the Spanish HCV1a epidemic was shaped by continuous seeding of HCV1a into Spain, almost exclusively from North America and European countries. The latter became increasingly relevant and have dominated in recent times. Export from Spain to other countries in Europe was also strongly supported, although Spain was a net sink for European HCV1a lineages. Spatial reconstructions showed that the epidemic in Spain is diffuse, without large, dominant within-country networks.ConclusionTo boost the effectiveness of local intervention efforts, concerted supra-national strategies to control HCV1a transmission are needed, with a strong focus on the most important drivers of ongoing transmission, i.e. PWID and other high-risk populations.
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Affiliation(s)
- Ana Belen Pérez
- Department of Microbiology, Institute of Bio Sanitary Research (IBIS), AIDS Research Network, University Hospital of Granada, Granada, Spain,These authors contributed equally to the article
| | - Bram Vrancken
- These authors contributed equally to the article,KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Evolutionary and Computational Virology, Leuven, Belgium
| | - Natalia Chueca
- Department of Microbiology, Institute of Bio Sanitary Research (IBIS), AIDS Research Network, University Hospital of Granada, Granada, Spain
| | - Antonio Aguilera
- Department of Microbiology, University Hospital of Santiago, Santiago de Compostela, Spain
| | - Gabriel Reina
- Department of Microbiology, University Hospital of Navarra, Institute for Health Research (IdisNA), Pamplona, Spain
| | | | - Francisco Vera
- Unit of Infectious Diseases, Internal Medicine, General Hospital of Rosell, Cartagena, Murcia, Spain
| | | | - Juan Ignacio Arenas
- Unit of Infectious Diseases, Hospital Universitario de San Sebastian, San Sebastian, Spain
| | - Francisco Téllez
- Unit of Infectious Diseases and Microbiology, University Hospital of Puerto Real, Cádiz, Spain
| | - Juan A Pineda
- Unit of Infectious Diseases, University Hospital of Valme, Sevilla, Spain (J.A. Pineda)
| | | | - Enrique Bernal
- Unit of Infectious Diseases, General University Hospital, Murcia, Spain
| | - Antonio Rivero-Juárez
- Unit of Infectious Diseases, University Hospital Reina Sofía of Córdoba, Maimonides Institute of Biomedical Research of Córdoba, University of Córdoba, Córdoba, Spain
| | | | | | - Juan Manuel Pascasio
- Clinical Management Unit of Digestive Diseases, University Hospital of Virgen del Rocío, Sevilla, Spain
| | - Philippe Lemey
- KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Evolutionary and Computational Virology, Leuven, Belgium
| | - Féderico Garcia
- Department of Microbiology, Institute of Bio Sanitary Research (IBIS), AIDS Research Network, University Hospital of Granada, Granada, Spain,These authors contributed equally to the article
| | - Lize Cuypers
- These authors contributed equally to the article,KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Clinical and Epidemiological Virology, Leuven, Belgium
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41
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Insights on transmission of HIV from phylogenetic analysis to locally optimize HIV prevention strategies. Curr Opin HIV AIDS 2019; 13:95-101. [PMID: 29266012 DOI: 10.1097/coh.0000000000000443] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE OF REVIEW Phylogenetic analysis can identify transmission networks by clustering genetically related HIV genotypes that are routinely collected. In this study, we will review phylogenetic insights gained on transmission of HIV and phylogenetically optimized HIV prevention strategies. RECENT FINDINGS Phylogenetic analysis reports that HIV transmission varies by geographical region and by route of transmission. In high-income countries, HIV is predominantly transmitted between recently infected MSM who live in the same country. In rural Uganda, transmission of HIV is frequently between different communities. Age-discrepant transmission has been reported across the world. Four studies have used phylogenetic optimization of HIV prevention. Three studies predict that immediate treatment after diagnosis would have prevented 19-42% of infections, and that preexposure prophylaxis would have prevented 66% of infections. One phylogenetic study guided a public health response to an actively ongoing HIV outbreak. Phylogenetic clustering requires a dense sample of patients and small time-gaps between infection and diagnosis. SUMMARY Phylogenetic analysis can be an important tool to identify a local strategy that prevents most infections. Future studies that use phylogenetic analysis for optimizing HIV prevention strategies should also include cost-effectiveness so that the most cost-effective prevention method is identified.
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42
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Mutenherwa F, Wassenaar DR, de Oliveira T. Experts' Perspectives on Key Ethical Issues Associated With HIV Phylogenetics as Applied in HIV Transmission Dynamics Research. J Empir Res Hum Res Ethics 2018; 14:61-77. [PMID: 30486713 DOI: 10.1177/1556264618809608] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The use of phylogenetics in HIV molecular epidemiology has considerably increased our ability to understand the origin, spread, and characteristics of HIV epidemics. Despite its potential to advance knowledge on HIV transmission dynamics, the ethical issues associated with HIV molecular epidemiology have received minimal attention. In-depth interviews were conducted with scientists from diverse backgrounds to explore their perspectives on ethical issues associated with phylogenetic analysis of HIV genetic data as applied to HIV transmission dynamics studies. The Emanuel framework was used as the analytical framework. Favorable risk-benefit ratio and informed consent were the most invoked ethical principles and fair participant selection the least. Fear of loss of privacy and disclosure of HIV transmission were invariably cited as key ethical concerns. As HIV sequence data become increasingly available, comprehensive guidelines should be developed to guide its access, sharing and use, cognizant of the potential harms that may result.
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Affiliation(s)
- Farirai Mutenherwa
- 1 University of KwaZulu-Natal, South Africa.,2 KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | | | - Tulio de Oliveira
- 1 University of KwaZulu-Natal, South Africa.,2 KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.,3 Centre for the AIDS Programme of Research in South Africa, Durban, South Africa
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43
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Wertheim JO, Murrell B, Mehta SR, Forgione LA, Kosakovsky Pond SL, Smith DM, Torian LV. Growth of HIV-1 Molecular Transmission Clusters in New York City. J Infect Dis 2018; 218:1943-1953. [PMID: 30010850 PMCID: PMC6217720 DOI: 10.1093/infdis/jiy431] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Accepted: 07/10/2018] [Indexed: 11/12/2022] Open
Abstract
Background HIV-1 genetic sequences can be used to infer viral transmission history and dynamics. Throughout the United States, HIV-1 sequences from drug resistance testing are reported to local public health departments. Methods We investigated whether inferred HIV transmission network dynamics can identify individuals and clusters of individuals most likely to give rise to future HIV cases in a surveillance setting. We used HIV-TRACE, a genetic distance-based clustering tool, to infer molecular transmission clusters from HIV-1 pro/RT sequences from 65736 people in the New York City surveillance registry. Logistic and LASSO regression analyses were used to identify correlates of clustering and cluster growth, respectively. We performed retrospective transmission network analyses to evaluate individual- and cluster-level prioritization schemes for identifying parts of the network most likely to give rise to new cases in the subsequent year. Results Individual-level prioritization schemes predicted network growth better than random targeting. Across the 3600 inferred molecular transmission clusters, previous growth dynamics were superior predictors of future transmission cluster growth compared to individual-level prediction schemes. Cluster-level prioritization schemes considering previous cluster growth relative to cluster size further improved network growth predictions. Conclusions Prevention efforts based on HIV molecular epidemiology may improve public health outcomes in a US surveillance setting.
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Affiliation(s)
| | - Ben Murrell
- Department of Medicine, University of California, San Diego
| | - Sanjay R Mehta
- Department of Medicine, University of California, San Diego
- Veterans Affairs Healthcare System San Diego, California
| | - Lisa A Forgione
- New York City Department of Health and Mental Hygiene, New York
| | | | - Davey M Smith
- Department of Medicine, University of California, San Diego
- Veterans Affairs Healthcare System San Diego, California
| | - Lucia V Torian
- New York City Department of Health and Mental Hygiene, New York
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44
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Coltart CEM, Hoppe A, Parker M, Dawson L, Amon JJ, Simwinga M, Geller G, Henderson G, Laeyendecker O, Tucker JD, Eba P, Novitsky V, Vandamme AM, Seeley J, Dallabetta G, Harling G, Grabowski MK, Godfrey-Faussett P, Fraser C, Cohen MS, Pillay D. Ethical considerations in global HIV phylogenetic research. Lancet HIV 2018; 5:e656-e666. [PMID: 30174214 PMCID: PMC7327184 DOI: 10.1016/s2352-3018(18)30134-6] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Revised: 05/28/2018] [Accepted: 06/06/2018] [Indexed: 01/01/2023]
Abstract
Phylogenetic analysis of pathogens is an increasingly powerful way to reduce the spread of epidemics, including HIV. As a result, phylogenetic approaches are becoming embedded in public health and research programmes, as well as outbreak responses, presenting unique ethical, legal, and social issues that are not adequately addressed by existing bioethics literature. We formed a multidisciplinary working group to explore the ethical issues arising from the design of, conduct in, and use of results from HIV phylogenetic studies, and to propose recommendations to minimise the associated risks to both individuals and groups. We identified eight key ethical domains, within which we highlighted factors that make HIV phylogenetic research unique. In this Review, we endeavoured to provide a framework to assist researchers, public health practitioners, and funding institutions to ensure that HIV phylogenetic studies are designed, done, and disseminated in an ethical manner. Our conclusions also have broader relevance for pathogen phylogenetics.
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Affiliation(s)
| | - Anne Hoppe
- Division of Infection and Immunity, University College London, London, UK.
| | - Michael Parker
- The Wellcome Centre for Ethics and Humanities (Ethox), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liza Dawson
- Division of AIDS, National Institutes of Health, Bethesda, MD, USA
| | - Joseph J Amon
- Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ, USA
| | | | - Gail Geller
- Berman Institute of Bioethics and School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Gail Henderson
- Center for Genomics and Society, Department of Social Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Oliver Laeyendecker
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Joseph D Tucker
- Institute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, NC, USA
| | - Patrick Eba
- Community Support, Social Justice and Inclusion Department, Geneva, Switzerland; School of Law, University of KwaZulu-Natal, Pietermaritzburg, South Africa
| | - Vladimir Novitsky
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Anne-Mieke Vandamme
- Clinical and Epidemiological Virology, Rega Institute for Medical Research, Department of Microbiology and Immunology, KU Leuven-University of Leuven, Leuven, Belgium; Center for Global Health and Tropical Medicine, Unidade de Microbiologia, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisbon, Portugal
| | - Janet Seeley
- Africa Health Research Institute, KwaZulu-Natal, South Africa; Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK
| | | | - Guy Harling
- Institute for Global Health, University College London, London, UK; Africa Health Research Institute, KwaZulu-Natal, South Africa
| | - M Kate Grabowski
- Department of Pathology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Rakai Community Cohort Study, Rakai Health Sciences Program, Kalisizo, Uganda
| | - Peter Godfrey-Faussett
- Joint United Nations Programme on HIV/AIDS, Geneva, Switzerland; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK
| | - Christophe Fraser
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Myron S Cohen
- Institute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, NC, USA; Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Deenan Pillay
- Division of Infection and Immunity, University College London, London, UK; Africa Health Research Institute, KwaZulu-Natal, South Africa
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45
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Transmission dynamics among participants initiating antiretroviral therapy upon diagnosis of early acute HIV-1 infection in Thailand. AIDS 2018; 32:2373-2381. [PMID: 30096068 DOI: 10.1097/qad.0000000000001956] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To assess transmission characteristics in a predominantly MSM cohort initiating antiretroviral therapy (ART) immediately following diagnosis of acute HIV-1infection (AHI). METHODS A longitudinal study (2009-2017) was performed in participants with AHI (n = 439) attending a single clinic in Bangkok. Plasma samples obtained prior to ART were used to obtain HIV-1 pol sequences and combined with clinical and epidemiologic data to assess transmission dynamics (cluster formation and size) using phylogenetic analysis. Clusters were estimated using maximum likelihood, genetic distance of 1.5% and visual inspection. The potential transmitter(s) in a cluster was determined using time to viral suppression and interview data. RESULTS The cohort was predominantly MSM (93%) and infected with HIV-1 CRF01_AE (87%). Medians (ranges) for age and viral load prior to ART were 26 (18-70) years and 5.9 (2.5-8.2) log10 HIV-1 RNA copies/ml. Median time from history of HIV-1 exposure to diagnosis was 19 (3-61) days. Viral suppression was observed in 388 of 412 (94%) participants at a median time of 12 weeks following ART. Twenty-six clusters with median cluster size of 2 (2-5) representing 62 of 439 (14%) participants were observed. Younger age was associated with cluster formation: median 28 versus 30 years for unique infections (P = 0.01). A potential transmitter was identified in 11 of 26 (42%) clusters. CONCLUSION Despite high rates of viral suppression following diagnosis and treatment of AHI within a cohort of young Thai MSM, HIV-1 transmission continued, reflecting the need to expand awareness and treatment access to the entire MSM population.
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46
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Bae JM. Introduction of Phylodynamics for Controlling the HIV/AIDS Epidemic in Korea. J Prev Med Public Health 2018; 51:326-328. [PMID: 30514063 PMCID: PMC6283738 DOI: 10.3961/jpmph.18.150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 10/22/2018] [Indexed: 11/09/2022] Open
Abstract
As over 1000 new cases of HIV/AIDS occur in Korea annually, preventive health programs against HIV/AIDS are urgently needed. Since phylodynamic studies have been suggested as a way to understand how infectious diseases are transmitted and evolve, phylodynamic inferences can be a useful tool for HIV/AIDS research. In particular, phylodynamic models are helpful for dating the origins of an epidemic and estimating its basic reproduction number. Thus, the introduction of phylodynamics would be a highly valuable step towards controlling the HIV/AIDS epidemic in Korea.
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Affiliation(s)
- Jong-Myon Bae
- Department of Preventive Medicine, Jeju National University School of Medicine, Jeju, Korea
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47
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HIV-1 diversity among young women in rural South Africa: HPTN 068. PLoS One 2018; 13:e0198999. [PMID: 29975689 PMCID: PMC6033411 DOI: 10.1371/journal.pone.0198999] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Accepted: 04/21/2018] [Indexed: 12/15/2022] Open
Abstract
Background South Africa has one of the highest rates of HIV-1 (HIV) infection world-wide, with the highest rates among young women. We analyzed the molecular epidemiology and evolutionary history of HIV in young women attending high school in rural South Africa. Methods Samples were obtained from the HPTN 068 randomized controlled trial, which evaluated the effect of cash transfers for school attendance on HIV incidence in women aged 13–20 years (Mpumalanga province, 2011–2015). Plasma samples from HIV-infected participants were analyzed using the ViroSeq HIV-1 Genotyping assay. Phylogenetic analysis was performed using 200 pol gene study sequences and 2,294 subtype C reference sequences from South Africa. Transmission clusters were identified using Cluster Picker and HIV-TRACE, and were characterized using demographic and other epidemiological data. Phylodynamic analyses were performed using the BEAST software. Results The study enrolled 2,533 young women who were followed through their expected high school graduation date (main study); some participants had a post-study assessment (follow-up study). Two-hundred-twelve of 2,533 enrolled young women had HIV infection. HIV pol sequences were obtained for 94% (n = 201/212) of the HIV-infected participants. All but one of the sequences were HIV-1 subtype C; the non-C subtype sequence was excluded from further analysis. Median pairwise genetic distance between the subtype C sequences was 6.4% (IQR: 5.6–7.2). Overall, 26% of study sequences fell into 21 phylogenetic clusters with 2–6 women per cluster. Thirteen (62%) clusters included women who were HIV-infected at enrollment. Clustering was not associated with study arm, demographic or other epidemiological factors. The estimated date of origin of HIV subtype C in the study population was 1958 (95% highest posterior density [HPD]: 1931–1980), and the median estimated substitution rate among study pol sequences was 1.98x10-3 (95% HPD: 1.15x10-3–2.81x10-3) per site per year. Conclusions Phylogenetic analysis suggests that multiple HIV subtype C sublineages circulate among school age girls in South Africa. There were no substantive differences in the molecular epidemiology of HIV between control and intervention arms in the HPTN 068 trial.
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48
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Rasmussen DA, Wilkinson E, Vandormael A, Tanser F, Pillay D, Stadler T, de Oliveira T. Tracking external introductions of HIV using phylodynamics reveals a major source of infections in rural KwaZulu-Natal, South Africa. Virus Evol 2018; 4:vey037. [PMID: 30555720 PMCID: PMC6290119 DOI: 10.1093/ve/vey037] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Despite increasing access to antiretrovirals, HIV incidence in rural KwaZulu-Natal remains among the highest ever reported in Africa. While many epidemiological factors have been invoked to explain such high incidence, widespread human mobility and viral movement suggest that transmission between communities may be a major source of new infections. High cross-community transmission rates call into question how effective increasing the coverage of antiretroviral therapy locally will be at preventing new infections, especially if many new cases arise from external introductions. To help address this question, we use a phylodynamic model to reconstruct epidemic dynamics and estimate the relative contribution of local transmission versus external introductions to overall incidence in KwaZulu-Natal from HIV-1 phylogenies. By comparing our results with population-based surveillance data, we show that we can reliably estimate incidence from viral phylogenies once viral movement in and out of the local population is accounted for. Our analysis reveals that early epidemic dynamics were largely driven by external introductions. More recently, we estimate that 35 per cent (95% confidence interval: 20-60%) of new infections arise from external introductions. These results highlight the growing need to consider larger-scale regional transmission dynamics when designing and testing prevention strategies.
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Affiliation(s)
- David A Rasmussen
- Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, USA
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
| | - Eduan Wilkinson
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Alain Vandormael
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
- School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa
| | - Frank Tanser
- School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa
- Africa Health Research Institute, Durban, South Africa
- Research Department of Infection & Population Health, University College London, UK
| | - Deenan Pillay
- Africa Health Research Institute, Durban, South Africa
- Division of Infection and Immunity, University College London, UK
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
- Department of Global Health, University of Washington, Seattle, USA
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49
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Patiño-Galindo JÁ, González-Candelas F. Molecular evolution methods to study HIV-1 epidemics. Future Virol 2018; 13:399-404. [PMID: 29967650 DOI: 10.2217/fvl-2017-0159] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2017] [Accepted: 04/04/2018] [Indexed: 01/17/2023]
Abstract
Nucleotide sequences of HIV isolates are obtained routinely to evaluate the presence of resistance mutations to antiretroviral drugs. But, beyond their clinical use, these and other viral sequences include a wealth of information that can be used to better understand and characterize the epidemiology of HIV in relevant populations. In this review, we provide a brief overview of the main methods used to analyze HIV sequences, the data bases where reference sequences can be obtained, and some caveats about the possible applications for public health of these analyses, along with some considerations about their limitations and correct usage to derive robust and reliable conclusions.
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Affiliation(s)
- Juan Á Patiño-Galindo
- Department of Systems Biology, Columbia University, New York, NY 10032, USA.,Department of Systems Biology, Columbia University, New York, NY 10032, USA
| | - Fernando González-Candelas
- Joint Research Unit "Infección y Salud Pública" FISABIO-Salud Pública/Universitat de València-Institute for Integrative Systems Biology (ISysBio, CSIC-UV) Valencia, Spain.,CIBER in Epidemiology & Public Health, Valencia, Spain.,Joint Research Unit "Infección y Salud Pública" FISABIO-Salud Pública/Universitat de València-Institute for Integrative Systems Biology (ISysBio, CSIC-UV) Valencia, Spain.,CIBER in Epidemiology & Public Health, Valencia, Spain
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50
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Abstract
The HIV pandemic has disproportionately impacted sub-Saharan Africa and Southern Africa in particular. The concurrent presence of overlapping epidemic drivers likely underpins how and why the HIV epidemic is so explosive in this region, with implications for understanding approaches to reduce transmission. In this review, we discuss the relative contribution and interaction between epidemic drivers in the Southern African context, including factors both distally and proximally associated with the likelihood and degree of exposure to HIV and factors that increase the probability of transmission when exposure occurs. In particular, we focus on young women as a key population in need of HIV prevention and highlight factors that increase their risk on several levels.
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Affiliation(s)
- Lyle R McKinnon
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Nelson R Mandela School of Medicine, 719 Umbilo Road, Private Bag X7, Congella, Durban, 4013, South Africa. .,Department of Medical Microbiology, University of Manitoba, Winnipeg, Canada.
| | - Quarraisha Abdool Karim
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Nelson R Mandela School of Medicine, 719 Umbilo Road, Private Bag X7, Congella, Durban, 4013, South Africa.,Department of Epidemiology, Columbia University, New York, USA
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