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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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Cholette F, Lazarus L, Macharia P, Thompson LH, Githaiga S, Mathenge J, Walimbwa J, Kuria I, Okoth S, Wambua S, Albert H, Mwangi P, Adhiambo J, Kasiba R, Juma E, Battacharjee P, Kimani J, Sandstrom P, Meyers AFA, Joy JB, Thomann M, McLaren PJ, Shaw S, Mishra S, Becker ML, McKinnon L, Lorway R. Community Insights in Phylogenetic HIV Research: The CIPHR Project Protocol. Glob Public Health 2023; 18:2269435. [PMID: 37851872 DOI: 10.1080/17441692.2023.2269435] [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: 03/01/2023] [Accepted: 10/04/2023] [Indexed: 10/20/2023]
Abstract
Inferring HIV transmission networks from HIV sequences is gaining popularity in the field of HIV molecular epidemiology. However, HIV sequences are often analyzed at distance from those affected by HIV epidemics, namely without the involvement of communities most affected by HIV. These remote analyses often mean that knowledge is generated in absence of lived experiences and socio-economic realities that could inform the ethical application of network-derived information in 'real world' programmes. Procedures to engage communities are noticeably absent from the HIV molecular epidemiology literature. Here we present our team's protocol for engaging community activists living in Nairobi, Kenya in a knowledge exchange process - The CIPHR Project (Community Insights in Phylogenetic HIV Research). Drawing upon a community-based participatory approach, our team will (1) explore the possibilities and limitations of HIV molecular epidemiology for key population programmes, (2) pilot a community-based HIV molecular study, and (3) co-develop policy guidelines on conducting ethically safe HIV molecular epidemiology. Critical dialogue with activist communities will offer insight into the potential uses and abuses of using such information to sharpen HIV prevention programmes. The outcome of this process holds importance to the development of policy frameworks that will guide the next generation of the global response.
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Affiliation(s)
- François Cholette
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Sexually Transmitted and Blood-Borne Infections, National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, Canada
| | - Lisa Lazarus
- Institute for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Pascal Macharia
- Health Options for Young Men on HIV/AIDS and STIs (HOYMAS), Nairobi, Kenya
| | - Laura H Thompson
- Sexually Transmitted and Blood-Borne Infections Surveillance Division, Centre for Communicable Diseases and Infection Control, Public Health Agency of Canada, Ottawa, Canada
| | - Samuel Githaiga
- Health Options for Young Men on HIV/AIDS and STIs (HOYMAS), Nairobi, Kenya
| | - John Mathenge
- Health Options for Young Men on HIV/AIDS and STIs (HOYMAS), Nairobi, Kenya
| | | | - Irene Kuria
- Key Population Consortium of Kenya, Nairobi, Kenya
| | - Silvia Okoth
- Bar Hostess Empowerment and Support Programme, Nairobi, Kenya
| | | | - Harrison Albert
- Health Options for Young Men on HIV/AIDS and STIs (HOYMAS), Nairobi, Kenya
| | - Peninah Mwangi
- Bar Hostess Empowerment and Support Programme, Nairobi, Kenya
| | - Joyce Adhiambo
- Partners for Health Development in Africa (PHDA), Nairobi, Kenya
- Sex Worker Outreach Programme (SWOP), Nairobi, Kenya
| | | | - Esther Juma
- Sex Worker Outreach Programme (SWOP), Nairobi, Kenya
| | | | - Joshua Kimani
- Sex Worker Outreach Programme (SWOP), Nairobi, Kenya
- Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya
| | - Paul Sandstrom
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Sexually Transmitted and Blood-Borne Infections, National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, Canada
| | - Adrienne F A Meyers
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Sexually Transmitted and Blood-Borne Infections, National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, Canada
| | - Jeffrey B Joy
- British Columbia Centre for Excellence in HIV/AIDS (BCCfE), St. Paul's Hospital, Vancouver, Canada
- Division of Infectious Diseases, Department of Medicine, University of British Columbia, Vancouver, Canada
- Bioinformatics Programme, University of British Columbia, Vancouver, Canada
| | - Matthew Thomann
- Department of Anthropology, University of Maryland, College Park, MD, USA
| | - Paul J McLaren
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Sexually Transmitted and Blood-Borne Infections, National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, Canada
| | - Souradet Shaw
- Institute for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Sharmistha Mishra
- MAP Centre for Urban Health Solutions, St. Michael's Hospital, Toronto, Canada
- Department of Medicine, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
| | - Marissa L Becker
- Institute for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Lyle McKinnon
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Canada
- Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya
- Centre for the AIDS Programme of Research in South Africa, Durban, South Africa
| | - Robert Lorway
- Institute for Global Public Health, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada
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Liu M, Chato C, Poon AFY. From components to communities: bringing network science to clustering for molecular epidemiology. Virus Evol 2023; 9:vead026. [PMID: 37187604 PMCID: PMC10175948 DOI: 10.1093/ve/vead026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 01/30/2023] [Accepted: 04/17/2023] [Indexed: 05/17/2023] Open
Abstract
Defining clusters of epidemiologically related infections is a common problem in the surveillance of infectious disease. A popular method for generating clusters is pairwise distance clustering, which assigns pairs of sequences to the same cluster if their genetic distance falls below some threshold. The result is often represented as a network or graph of nodes. A connected component is a set of interconnected nodes in a graph that are not connected to any other node. The prevailing approach to pairwise clustering is to map clusters to the connected components of the graph on a one-to-one basis. We propose that this definition of clusters is unnecessarily rigid. For instance, the connected components can collapse into one cluster by the addition of a single sequence that bridges nodes in the respective components. Moreover, the distance thresholds typically used for viruses like HIV-1 tend to exclude a large proportion of new sequences, making it difficult to train models for predicting cluster growth. These issues may be resolved by revisiting how we define clusters from genetic distances. Community detection is a promising class of clustering methods from the field of network science. A community is a set of nodes that are more densely inter-connected relative to the number of their connections to external nodes. Thus, a connected component may be partitioned into two or more communities. Here we describe community detection methods in the context of genetic clustering for epidemiology, demonstrate how a popular method (Markov clustering) enables us to resolve variation in transmission rates within a giant connected component of HIV-1 sequences, and identify current challenges and directions for further work.
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Affiliation(s)
- Molly Liu
- Department of Pathology and Laboratory Medicine, Western University, Dental Sciences Building, Rm. 4044, London, ON N6A 5C1, Canada
| | - Connor Chato
- Department of Pathology and Laboratory Medicine, Western University, Dental Sciences Building, Rm. 4044, London, ON N6A 5C1, Canada
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4
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Optimized phylogenetic clustering of HIV-1 sequence data for public health applications. PLoS Comput Biol 2022; 18:e1010745. [PMID: 36449514 PMCID: PMC9744331 DOI: 10.1371/journal.pcbi.1010745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 12/12/2022] [Accepted: 11/17/2022] [Indexed: 12/02/2022] Open
Abstract
Clusters of genetically similar infections suggest rapid transmission and may indicate priorities for public health action or reveal underlying epidemiological processes. However, clusters often require user-defined thresholds and are sensitive to non-epidemiological factors, such as non-random sampling. Consequently the ideal threshold for public health applications varies substantially across settings. Here, we show a method which selects optimal thresholds for phylogenetic (subset tree) clustering based on population. We evaluated this method on HIV-1 pol datasets (n = 14, 221 sequences) from four sites in USA (Tennessee, Washington), Canada (Northern Alberta) and China (Beijing). Clusters were defined by tips descending from an ancestral node (with a minimum bootstrap support of 95%) through a series of branches, each with a length below a given threshold. Next, we used pplacer to graft new cases to the fixed tree by maximum likelihood. We evaluated the effect of varying branch-length thresholds on cluster growth as a count outcome by fitting two Poisson regression models: a null model that predicts growth from cluster size, and an alternative model that includes mean collection date as an additional covariate. The alternative model was favoured by AIC across most thresholds, with optimal (greatest difference in AIC) thresholds ranging 0.007-0.013 across sites. The range of optimal thresholds was more variable when re-sampling 80% of the data by location (IQR 0.008 - 0.016, n = 100 replicates). Our results use prospective phylogenetic cluster growth and suggest that there is more variation in effective thresholds for public health than those typically used in clustering studies.
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5
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Zhao B, Qiu Y, Song W, Kang M, Dong X, Li X, Wang L, Liu J, Ding H, Chu Z, Wang L, Tian W, Shang H, Han X. Undiagnosed HIV Infections May Drive HIV Transmission in the Era of "Treat All": A Deep-Sampling Molecular Network Study in Northeast China during 2016 to 2019. Viruses 2022; 14:v14091895. [PMID: 36146701 PMCID: PMC9502473 DOI: 10.3390/v14091895] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 08/24/2022] [Accepted: 08/24/2022] [Indexed: 11/23/2022] Open
Abstract
Universal antiretroviral therapy (ART, “treat all”) was recommended by the World Health Organization in 2015; however, HIV-1 transmission is still ongoing. This study characterizes the drivers of HIV transmission in the “treat all” era. Demographic and clinical information and HIV pol gene were collected from all newly diagnosed cases in Shenyang, the largest city in Northeast China, during 2016 to 2019. Molecular networks were constructed based on genetic distance and logistic regression analysis was used to assess potential transmission source characteristics. The cumulative ART coverage in Shenyang increased significantly from 77.0% (485/630) in 2016 to 93.0% (2598/2794) in 2019 (p < 0.001). Molecular networks showed that recent HIV infections linked to untreated individuals decreased from 61.6% in 2017 to 28.9% in 2019, while linking to individuals with viral suppression (VS) increased from 9.0% to 49.0% during the same time frame (p < 0.001). Undiagnosed people living with HIV (PLWH) hidden behind the links between index cases and individuals with VS were likely to be male, younger than 25 years of age, with Manchu nationality (p < 0.05). HIV transmission has declined significantly in the era of “treat all”. Undiagnosed PLWH may drive HIV transmission and should be the target for early detection and intervention.
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Affiliation(s)
- Bin Zhao
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, Shenyang 110001, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang 110001, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang 110001, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 79 Qingchun Street, Hangzhou 310003, China
| | - Yu Qiu
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, Shenyang 110001, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang 110001, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang 110001, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 79 Qingchun Street, Hangzhou 310003, China
| | - Wei Song
- Department of Food Safety and Nutrition, Shenyang Center for Health Service and Administrative Law Enforcement (Shenyang Center for Disease Control and Prevention), Shenyang 110031, China
| | - Mingming Kang
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, Shenyang 110001, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang 110001, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 79 Qingchun Street, Hangzhou 310003, China
| | - Xue Dong
- Department of Food Safety and Nutrition, Shenyang Center for Health Service and Administrative Law Enforcement (Shenyang Center for Disease Control and Prevention), Shenyang 110031, China
| | - Xin Li
- Department of Food Safety and Nutrition, Shenyang Center for Health Service and Administrative Law Enforcement (Shenyang Center for Disease Control and Prevention), Shenyang 110031, China
| | - Lu Wang
- Department of Food Safety and Nutrition, Shenyang Center for Health Service and Administrative Law Enforcement (Shenyang Center for Disease Control and Prevention), Shenyang 110031, China
| | - Jianmin Liu
- Department of Food Safety and Nutrition, Shenyang Center for Health Service and Administrative Law Enforcement (Shenyang Center for Disease Control and Prevention), Shenyang 110031, China
| | - Haibo Ding
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, Shenyang 110001, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang 110001, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang 110001, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 79 Qingchun Street, Hangzhou 310003, China
| | - Zhenxing Chu
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, Shenyang 110001, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang 110001, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang 110001, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 79 Qingchun Street, Hangzhou 310003, China
| | - Lin Wang
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, Shenyang 110001, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang 110001, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang 110001, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 79 Qingchun Street, Hangzhou 310003, China
| | - Wen Tian
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, Shenyang 110001, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang 110001, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang 110001, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 79 Qingchun Street, Hangzhou 310003, China
| | - Hong Shang
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, Shenyang 110001, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang 110001, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang 110001, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 79 Qingchun Street, Hangzhou 310003, China
- Correspondence: (H.S.); (X.H.); Tel./Fax: +86-(24)-8328-2634 (H.S. & X.H.)
| | - Xiaoxu Han
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Hospital of China Medical University, Shenyang 110001, China
- Laboratory Medicine Innovation Unit, Chinese Academy of Medical Sciences, Shenyang 110001, China
- Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang 110001, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, 79 Qingchun Street, Hangzhou 310003, China
- Correspondence: (H.S.); (X.H.); Tel./Fax: +86-(24)-8328-2634 (H.S. & X.H.)
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Salazar-Vizcaya L, Kusejko K, Günthard HF, Böni J, Metzner KJ, Braun DL, Nicca D, Bernasconi E, Calmy A, Darling KEA, Wandeler G, Kouyos RD, Rauch A. An Approach to Quantifying the Interaction between Behavioral and Transmission Clusters. Viruses 2022; 14:v14040784. [PMID: 35458514 PMCID: PMC9032082 DOI: 10.3390/v14040784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 04/05/2022] [Accepted: 04/06/2022] [Indexed: 02/04/2023] Open
Abstract
We hypothesize that patterns of sexual behavior play a role in the conformation of transmission networks, i.e., the way you behave might influence whom you have sex with. If that was the case, behavioral grouping might in turn correlate with, and potentially predict transmission networking, e.g., proximity in a viral phylogeny. We rigorously present an intuitive approach to address this hypothesis by quantifying mapped interactions between groups defined by similarities in sexual behavior along a virus phylogeny while discussing power and sample size considerations. Data from the Swiss HIV Cohort Study on condom use and hepatitis C virus (HCV) sequences served as proof-of-concept. In this case, a strict inclusion criteria contrasting with low HCV prevalence hindered our possibilities to identify significant relationships. This manuscript serves as guide for studies aimed at characterizing interactions between behavioral patterns and transmission networks. Large transmission networks such as those of HIV or COVID-19 are prime candidates for applying this methodological approach.
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Affiliation(s)
- Luisa Salazar-Vizcaya
- Department of Infectious Diseases, Bern University Hospital Inselspital, University of Bern, 3010 Bern, Switzerland; (G.W.); (A.R.)
- Correspondence:
| | - Katharina Kusejko
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland; (K.K.); (H.F.G.); (K.J.M.); (D.L.B.); (R.D.K.)
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland;
| | - Huldrych F. Günthard
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland; (K.K.); (H.F.G.); (K.J.M.); (D.L.B.); (R.D.K.)
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland;
| | - Jürg Böni
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland;
| | - Karin J. Metzner
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland; (K.K.); (H.F.G.); (K.J.M.); (D.L.B.); (R.D.K.)
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland;
| | - Dominique L. Braun
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland; (K.K.); (H.F.G.); (K.J.M.); (D.L.B.); (R.D.K.)
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland;
| | - Dunja Nicca
- Institute of Nursing Science, University of Basel, 4056 Basel, Switzerland;
- Department of Public Health, Epidemiology, Biostatistics and Public Health Institute, University of Zurich, 8001 Zurich, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Ente Ospedaliero Cantonale, 6900 Lugano, Switzerland;
- University of Southern Switzerland, 6928 Manno, Switzerland
- Division of Infectious Diseases, Geneva University Hospitals, 1205 Geneva, Switzerland;
| | - Alexandra Calmy
- Division of Infectious Diseases, Geneva University Hospitals, 1205 Geneva, Switzerland;
| | - Katharine E. A. Darling
- Infectious Diseases Service, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland;
- University of Lausanne, 1015 Lausanne, Switzerland
| | - Gilles Wandeler
- Department of Infectious Diseases, Bern University Hospital Inselspital, University of Bern, 3010 Bern, Switzerland; (G.W.); (A.R.)
| | - Roger D. Kouyos
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland; (K.K.); (H.F.G.); (K.J.M.); (D.L.B.); (R.D.K.)
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland;
| | - Andri Rauch
- Department of Infectious Diseases, Bern University Hospital Inselspital, University of Bern, 3010 Bern, Switzerland; (G.W.); (A.R.)
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7
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Duran Ramirez JJ, Ballouz T, Nguyen H, Kusejko K, Chaudron SE, Huber M, Hirsch HH, Perreau M, Ramette A, Yerly S, Cavassini M, Stöckle M, Furrer H, Vernazza P, Bernasconi E, Günthard HF, Kouyos RD. Increasing Frequency and Transmission of HIV-1 Non-B Subtypes among Men Who Have Sex with Men in the Swiss HIV Cohort Study. J Infect Dis 2021; 225:306-316. [PMID: 34260728 DOI: 10.1093/infdis/jiab360] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 07/13/2021] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND In Switzerland, HIV-1 transmission among men who have sex with men (MSM) has been dominated by subtype B, whilst non-B subtypes are commonly attributed to infections acquired abroad among heterosexuals. Here, we evaluated the temporal trends of non-B subtypes and the characteristics of molecular transmission clusters (MTCs) among MSM. METHODS Sociodemographic and clinical data and partial pol sequences were obtained from participants enrolled in the Swiss HIV Cohort Study (SHCS). For non-B subtypes, maximum likelihood trees were constructed, from which Swiss MTCs were identified and analysed by transmission group. RESULTS Non-B subtypes were identified in 8.1% (416/5,116) of MSM participants. CRF01_AE was the most prevalent strain (3.5%), followed by A (1.2%), F (1.1%), CRF02_AG (1.1%), C (0.9%), and G (0.3%). Between 1990 and 2019, an increase in the proportion of newly diagnosed individuals (0/123[0%] to 11/32 [34%]) with non-B subtypes in MSM was found. Across all non-B subtypes, the majority of MSM MTCs were European. Larger MTCs were observed for MSM than heterosexuals. CONCLUSIONS We found a substantial increase in HIV-1 non-B subtypes among MSM in Switzerland and the occurrence of large MTCs, highlighting the importance of molecular surveillance in guiding public health strategies targeting the HIV-1 epidemic.
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Affiliation(s)
- Jessy J Duran Ramirez
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Tala Ballouz
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland.,Epidemiology, Biostatistics and Prevention Institute, University of Zurich, 8001 Zurich, Switzerland
| | - Huyen Nguyen
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Katharina Kusejko
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Sandra E Chaudron
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Michael Huber
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Hans H Hirsch
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, 4031 Basel, Switzerland.,Transplantation and Clinical Virology, Department of Biomedicine, University of Basel, 4009 Basel, Switzerland
| | - Matthieu Perreau
- Division of Immunology and Allergy, Lausanne University Hospital, University of Lausanne, 1011 Lausanne, Switzerland
| | - Alban Ramette
- Institute for Infectious Diseases, University of Bern, 3001 Bern, Switzerland
| | - Sabine Yerly
- Laboratory of Virology and Division of Infectious Diseases, Geneva University Hospital, University of Geneva, 1205 Geneva, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, Lausanne University Hospital, 1011 Lausanne, Switzerland
| | - Marcel Stöckle
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, 4031 Basel, Switzerland
| | - Hansjakob Furrer
- Department of Infectious Diseases, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
| | - Pietro Vernazza
- Division of Infectious Diseases, Cantonal Hospital St. Gallen, 9007 St. Gallen, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, 6900 Lugano, Switzerland
| | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Roger D Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
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8
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Mehta SR, Little SJ. Phylogenetic Cluster Analysis: Persons With Undiagnosed Infection Drive Human Immunodeficiency Virus Transmission in a Population With High Levels of Virologic Suppression. Clin Infect Dis 2021; 72:2184-2186. [PMID: 32266376 PMCID: PMC8204770 DOI: 10.1093/cid/ciaa401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 04/06/2020] [Indexed: 11/13/2022] Open
Affiliation(s)
- Sanjay R Mehta
- Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California, San Diego, La Jolla, California, USA
- San Diego Veterans Affairs Healthcare System, San Diego, California, USA
| | - Susan J Little
- Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California, San Diego, La Jolla, California, USA
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9
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Reichmuth ML, Chaudron SE, Bachmann N, Nguyen H, Böni J, Metzner KJ, Perreau M, Klimkait T, Yerly S, Hirsch HH, Hauser C, Ramette A, Vernazza P, Cavassini M, Bernasconi E, Günthard HF, Kusejko K, Kouyos RD. Using longitudinally sampled viral nucleotide sequences to characterize the drivers of HIV-1 transmission. HIV Med 2020; 22:346-359. [PMID: 33368946 DOI: 10.1111/hiv.13030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 10/17/2020] [Accepted: 10/21/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVES Understanding the drivers of HIV-1 transmission is of importance for curbing the ongoing epidemic. Phylogenetic methods based on single viral sequences allow us to assess whether two individuals are part of the same viral outbreak, but cannot on their own assess who potentially transmitted the virus. We developed and assessed a molecular epidemiology method with the main aim to screen cohort studies for and to characterize individuals who are 'potential HIV-1 transmitters', in order to understand the drivers of HIV-1 transmission. METHODS We developed and validated a molecular epidemiology approach using longitudinally sampled viral Sanger sequences to characterize potential HIV-1 transmitters in the Swiss HIV Cohort Study. RESULTS Our method was able to identify 279 potential HIV-1 transmitters and allowed us to determine the main epidemiological and virological drivers of transmission. We found that the directionality of transmission was consistent with infection times for 72.9% of 85 potential HIV-1 transmissions with accurate infection date estimates. Being a potential HIV-1 transmitter was associated with risk factors including viral load [adjusted odds ratiomultivariable (95% confidence interval): 1.86 (1.49-2.32)], syphilis coinfection [1.52 (1.06-2.19)], and recreational drug use [1.45 (1.06-1.98)]. By contrast for the potential HIV-1 recipients, this association was weaker or even absent [1.18 (0.82-1.72), 0.89 (0.52-1.55) and 1.53 (0.98-2.39), respectively], indicating that inferred directionality of transmission is useful at the population level. CONCLUSIONS Our results indicate that longitudinally sampled Sanger sequences do not provide sufficient information to identify transmitters with high certainty at the individual level, but that they allow the drivers of transmission at the population level to be characterized.
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Affiliation(s)
- M L Reichmuth
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - S E Chaudron
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - N Bachmann
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - H Nguyen
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - J Böni
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - K J Metzner
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - M Perreau
- Service of Immunology and Allergy, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland
| | - T Klimkait
- Department of Biomedicine, University of Basel, Basel, Switzerland
| | - S Yerly
- Laboratory of Virology, Geneva University Hospital, Geneva, Switzerland
| | - H H Hirsch
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland.,Clinical Virology, Laboratory Medicine, University Hospital Basel, Basel, Switzerland
| | - C Hauser
- Department of Infectious Diseases, Bern University Hospital, Bern, Switzerland
| | - A Ramette
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - P Vernazza
- Division of Infectious Diseases, Cantonal Hospital St Gallen, St Gallen, Switzerland
| | - M Cavassini
- Service of Infectious Diseases, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland
| | - E Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland
| | - H F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - K Kusejko
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - R 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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