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Gonçalves P, Barreto J, Santos M, Leal S, Marcelino J, Abecasis A, Palladino C, Taveira N. HIV-1 drug resistance and genetic diversity in people with HIV-1 in Cape Verde. AIDS 2024; 38:1101-1110. [PMID: 38349224 DOI: 10.1097/qad.0000000000003866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
OBJECTIVES To characterize the genetic diversity and drug resistance profiles of people with HIV-1 failing ART in Cape Verde (CV). DESIGN Cross-sectional study conducted between January 2019 and December 2021 in 24 health centres on the islands of Santiago and São Vicente. METHODS The HIV-1 pol gene was sequenced in individuals with a detectable viral load. HIV-1 genetic diversity was determined by phylogenetic analysis. Drug resistance mutation patterns and resistance phenotypes were estimated using the Stanford algorithm. RESULTS Viral load was detected in 73 of 252 (29%) enrolled participants and sequencing data were produced for 58 (79%) participants. CRF02 AG strains predominated (46.5%), followed by subtype G (22.4%). Most patients (80%) had mutations conferring resistance to nonnucleoside reverse transcriptase inhibitors (NNRTIs) (67%), nucleoside reverse transcriptase inhibitors (55%), integrase inhibitors (10%) and/or protease inhibitors (7%) used in Cape Verde, a significant increase compared with a study conducted in 2010-2011. The most common mutations were M184V/I (43%), K103N/S (36%) and G190A/S (19%). NNRTI resistance was associated with younger age and exposure to two or more drug regimens. CONCLUSION The HIV-1 epidemic in Cape Verde is mainly driven by CRF02_AG and subtype G. Resistance to NNRTIs and/or NRTIs is highly prevalent and resistance to LPV/r and DTG is emerging. Our results support the use of DTG-based first-line ART and protease inhibitor-based regimens for patients with virological failure, but emerging resistance to LPV/r and DTG is a concern. Continued monitoring of drug resistance is essential to ensure adequate healthcare for PWH in Cape Verde.
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Affiliation(s)
- Paloma Gonçalves
- Instituto de Investigação do Medicamento (iMed.Ulisboa), Faculdade de Farmácia de Lisboa, Lisbon, Portugal
| | | | - Menilita Santos
- Instituto Nacional de Saúde Pública de Cabo Verde, Praia, Cape Verde
| | - Silvania Leal
- Instituto Nacional de Saúde Pública de Cabo Verde, Praia, Cape Verde
| | - José Marcelino
- Instituto de Investigação do Medicamento (iMed.Ulisboa), Faculdade de Farmácia de Lisboa, Lisbon, Portugal
- Centro de Investigação Interdisciplinar Egas Moniz (CiiEM), Instituto Superior de Ciências da Saúde Egas Moniz, Monte de Caparica
| | - Ana Abecasis
- Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical/Universidade Nova de Lisboa (IHMT/UNL), Lisboa, Portugal
| | - Claudia Palladino
- Instituto de Investigação do Medicamento (iMed.Ulisboa), Faculdade de Farmácia de Lisboa, Lisbon, Portugal
| | - Nuno Taveira
- Instituto de Investigação do Medicamento (iMed.Ulisboa), Faculdade de Farmácia de Lisboa, Lisbon, Portugal
- Centro de Investigação Interdisciplinar Egas Moniz (CiiEM), Instituto Superior de Ciências da Saúde Egas Moniz, Monte de Caparica
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Skaathun B, Strathdee SA, Shrader CH, Nacht CL, Borquez A, Artamonova I, Harvey-Vera A, Vera CF, Rangel G, Ignacio C, Woodworth B, Chaillon A, Vasylyeva TI. HIV-1 transmission dynamics among people who inject drugs on the US/Mexico border during the COVID-19 pandemic: a prosepective cohort study. LANCET REGIONAL HEALTH. AMERICAS 2024; 33:100751. [PMID: 38711788 PMCID: PMC11070707 DOI: 10.1016/j.lana.2024.100751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 04/11/2024] [Accepted: 04/12/2024] [Indexed: 05/08/2024]
Abstract
Background We examined HIV prevalence and transmission dynamics among people who inject drugs in the U.S./Mexico border region during the COVID-19 pandemic. Methods People who inject drugs aged ≥18 years from 3 groups were recruited: people who inject drugs who live in San Diego (SD) and engaged in cross-border drug use in Tijuana, Mexico (SD CBDUs), and people who inject drugs in SD and Tijuana (TJ) who did not engage in cross-border drug use (NCBDUs). We computed HIV prevalence at baseline and bivariate incidence-density rates (IR) at 18-month follow-up. Bayesian phylogenetic analysis was used to identify local transmission clusters, estimate their age, and effective reproductive number (Re) over time within the clusters. Findings At baseline (n = 612), 26% of participants were female, 9% engaged in sex work, and HIV prevalence was 8% (4% SD CBDU, 4% SD NCBDU, 16% TJ NCBDU). Nine HIV seroconversions occurred over 18 months, IR: 1.357 per 100 person-years (95% CI: 0.470, 2.243); 7 in TJ NCBDU and 2 in SD CBDU. Out of 16 identified phylogenetic clusters, 9 (56%) had sequences from both the U.S. and Mexico (mixed-country). The age of three youngest mixed-country dyads (2018-2021) overlapped with the COVID-related US-Mexico border closure in 2020. One large mixed-country cluster (N = 15) continued to grow during the border closure (Re = 4.8, 95% Highest Posterior Density (HPD) 1.5-9.1) with 47% engaging in sex work. Interpretation Amidst the COVID-19 pandemic and the border closure, cross-border HIV clusters grew. Efforts to end the HIV epidemic in the U.S. should take into account cross-border HIV-1 transmission from Tijuana. Mobile harm reduction services and coordination with municipal HIV programs to initiate anti-retroviral therapy and pre-exposure prophylaxisis are needed to reduce transmission. Funding This research was supported by the James B. Pendleton Charitable Trust and the San Diego Center for AIDS Research.
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Affiliation(s)
- Britt Skaathun
- Division of Infectious Diseases and Global Public Health, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
| | - Steffanie A. Strathdee
- Division of Infectious Diseases and Global Public Health, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
| | - Cho-Hee Shrader
- Department of Epidemiology, Columbia University, 116th and Broadway, New York, NY 10027, United States
| | - Carrie L. Nacht
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
| | - Annick Borquez
- Division of Infectious Diseases and Global Public Health, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
| | - Irina Artamonova
- Division of Infectious Diseases and Global Public Health, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
| | - Alicia Harvey-Vera
- Division of Infectious Diseases and Global Public Health, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
- U.S.-Mexico Border Health Commission, Paseo del Centenario 10851, Zona Urbana Rio Tijuana, Tijuana, BC 22320, Mexico
| | - Carlos F. Vera
- Division of Infectious Diseases and Global Public Health, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
| | - Gudelia Rangel
- U.S.-Mexico Border Health Commission, Paseo del Centenario 10851, Zona Urbana Rio Tijuana, Tijuana, BC 22320, Mexico
- El Colegio de la Frontera Norte, Carretera Escenica Tijuana-Ensenada Toll Boot Escenica Tijuana-Ensenada Sn San Antonio del Mar, Tijuana, BC 22560, Mexico
| | - Caroline Ignacio
- Division of Infectious Diseases and Global Public Health, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
| | - Brendon Woodworth
- Division of Infectious Diseases and Global Public Health, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
| | - Antoine Chaillon
- Division of Infectious Diseases and Global Public Health, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093, United States
| | - Tetyana I. Vasylyeva
- Department of Population Health and Disease Prevention, University of California Irvine, Irvine, CA 92617, United States
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3
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Hill V, Githinji G, Vogels CBF, Bento AI, Chaguza C, Carrington CVF, Grubaugh ND. Toward a global virus genomic surveillance network. Cell Host Microbe 2023; 31:861-873. [PMID: 36921604 PMCID: PMC9986120 DOI: 10.1016/j.chom.2023.03.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
Abstract
The COVID-19 pandemic galvanized the field of virus genomic surveillance, demonstrating its utility for public health. Now, we must harness the momentum that led to increased infrastructure, training, and political will to build a sustainable global genomic surveillance network for other epidemic and endemic viruses. We suggest a generalizable modular sequencing framework wherein users can easily switch between virus targets to maximize cost-effectiveness and maintain readiness for new threats. We also highlight challenges associated with genomic surveillance and when global inequalities persist. We propose solutions to mitigate some of these issues, including training and multilateral partnerships. Exploring alternatives to clinical sequencing can also reduce the cost of surveillance programs. Finally, we discuss how establishing genomic surveillance would aid control programs and potentially provide a warning system for outbreaks, using a global respiratory virus (RSV), an arbovirus (dengue virus), and a regional zoonotic virus (Lassa virus) as examples.
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Affiliation(s)
- Verity Hill
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
| | - George Githinji
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya; Department of Biochemistry and Biotechnology, Pwani University, Kilifi, Kenya
| | - Chantal B F Vogels
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA; Yale Institute for Global Health, Yale University, New Haven, CT, USA
| | - Ana I Bento
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, IN, USA; The Rockefeller Foundation, New York, NY, USA
| | - Chrispin Chaguza
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA; Yale Institute for Global Health, Yale University, New Haven, CT, USA
| | - Christine V F Carrington
- Department of Preclinical Sciences, The University of the West Indies, St. Augustine Campus, St. Augustine, Trinidad and Tobago
| | - Nathan D Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA; Yale Institute for Global Health, Yale University, New Haven, CT, USA; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA; Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA.
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4
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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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5
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Featherstone LA, Zhang JM, Vaughan TG, Duchene S. Epidemiological Inference From Pathogen Genomes: A Review of Phylodynamic Models and Applications. Virus Evol 2022; 8:veac045. [PMID: 35775026 PMCID: PMC9241095 DOI: 10.1093/ve/veac045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 05/23/2022] [Accepted: 06/02/2022] [Indexed: 11/24/2022] Open
Abstract
Phylodynamics requires an interdisciplinary understanding of phylogenetics, epidemiology, and statistical inference. It has also experienced more intense application than ever before amid the SARS-CoV-2 pandemic. In light of this, we present a review of phylodynamic models beginning with foundational models and assumptions. Our target audience is public health researchers, epidemiologists, and biologists seeking a working knowledge of the links between epidemiology, evolutionary models, and resulting epidemiological inference. We discuss the assumptions linking evolutionary models of pathogen population size to epidemiological models of the infected population size. We then describe statistical inference for phylodynamic models and list how output parameters can be rearranged for epidemiological interpretation. We go on to cover more sophisticated models and finish by highlighting future directions.
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Affiliation(s)
- Leo A Featherstone
- Peter Doherty Institute for Infection and Immunity, University of Melbourne , Australia
| | - Joshua M Zhang
- Peter Doherty Institute for Infection and Immunity, University of Melbourne , Australia
| | - Timothy G Vaughan
- Department of Biosystems Science and Engineering, ETH Zurich , Basel, Switzerland
- Swiss Institute of Bioinformatics
| | - Sebastian Duchene
- Peter Doherty Institute for Infection and Immunity, University of Melbourne , Australia
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6
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Arimide DA, Esquivel-Gómez LR, Kebede Y, Sasinovich S, Balcha T, Björkman P, Kühnert D, Medstrand P. Molecular Epidemiology and Transmission Dynamics of the HIV-1 Epidemic in Ethiopia: Epidemic Decline Coincided With Behavioral Interventions Before ART Scale-Up. Front Microbiol 2022; 13:821006. [PMID: 35283836 PMCID: PMC8914292 DOI: 10.3389/fmicb.2022.821006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 01/24/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundEthiopia is one of the sub-Saharan countries hit hard by the HIV epidemic. Previous studies have shown that subtype C dominates the Ethiopian HIV-1 epidemic, but the evolutionary and temporal dynamics of HIV-1 in Ethiopia have not been closely scrutinized. Understanding the evolutionary and epidemiological pattern of HIV is vital to monitor the spread, evaluate and implement HIV prevention strategies.MethodsWe analyzed 1,276 Ethiopian HIV-1 subtype C polymerase (pol sequences), including 144 newly generated sequences, collected from different parts of the country from 1986 to 2017. We employed state-of-art maximum likelihood and Bayesian phylodynamic analyses to comprehensively describe the evolutionary dynamics of the HIV-1 epidemic in Ethiopia. We used Bayesian phylodynamic models to estimate the dynamics of the effective population size (Ne) and reproductive numbers (Re) through time for the HIV epidemic in Ethiopia.ResultsOur analysis revealed that the Ethiopian HIV-1 epidemic originated from two independent introductions at the beginning of the 1970s and 1980s from eastern and southern African countries, respectively, followed by epidemic growth reaching its maximum in the early 1990s. We identified three large clusters with a majority of Ethiopian sequences. Phylodynamic analyses revealed that all three clusters were characterized by high transmission rates during the early epidemic, followed by a decline in HIV-1 transmissions after 1990. Re was high (4–6) during the earlier time of the epidemic but dropped significantly and remained low (Re < 1) after the mid-1990. Similarly, with an expected shift in time, the effective population size (Ne) steadily increased until the beginning of 2000, followed by a decline and stabilization until recent years. The phylodynamic analyses corroborated the modeled UNAIDS incidence and prevalence estimates.ConclusionThe rapid decline in the HIV epidemic took place a decade before introducing antiretroviral therapy in Ethiopia and coincided with early behavioral, preventive, and awareness interventions implemented in the country. Our findings highlight the importance of behavioral interventions and antiretroviral therapy scale-up to halt and maintain HIV transmissions at low levels (Re < 1). The phylodynamic analyses provide epidemiological insights not directly available using standard surveillance and may inform the adjustment of public health strategies in HIV prevention in Ethiopia.
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Affiliation(s)
- Dawit Assefa Arimide
- Department of Translational Medicine, Lund University, Malmo, Sweden
- TB/HIV Department, Ethiopian Public Health Institute, Addis Ababa, Ethiopia
| | - Luis Roger Esquivel-Gómez
- Transmission, Infection, Diversification and Evolution Group, Max-Planck Institute for the Science of Human History, Jena, Germany
| | - Yenew Kebede
- Africa Centre for Disease Prevention and Control, Africa Union Commission, Addis Ababa, Ethiopia
| | | | - Taye Balcha
- Department of Translational Medicine, Lund University, Malmo, Sweden
| | - Per Björkman
- Department of Translational Medicine, Lund University, Malmo, Sweden
| | - Denise Kühnert
- Transmission, Infection, Diversification and Evolution Group, Max-Planck Institute for the Science of Human History, Jena, Germany
| | - Patrik Medstrand
- Department of Translational Medicine, Lund University, Malmo, Sweden
- *Correspondence: Patrik Medstrand,
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7
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An M, Zhao B, Wang L, Chu Z, Xu J, Ding H, Han X, Shang H. The Viral Founder Effect and Economic-Driven Human Mobility Shaped the Distinct Epidemic Pattern of HIV-1 CRF01_AE in Northeast China. Front Med (Lausanne) 2021; 8:769535. [PMID: 34926511 PMCID: PMC8678122 DOI: 10.3389/fmed.2021.769535] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Accepted: 11/11/2021] [Indexed: 11/13/2022] Open
Abstract
Background: In China, two distinct lineages shaped the epidemic of HIV-1 CRF01_AE among men who have sex with men (MSM), of which the uneven distributions were observed geographically. One lineage spread across China, while another dominated in Northeast China. Understanding the drivers of viral diffusion would provide guidelines for identifying the source and hotspots of HIV transmission among MSM to target interventions in China. Methods: We collected the pol sequences between 2002–2017 to reconstruct the spatiotemporal history of CRF01_AE lineages in Shenyang, one economic center of Northeast China, using the Bayesian phylogeographic and phylodynamic approaches. Importantly, for the datasets with the high sample density, we did the down-sampling to avoid the sampling bias. Results: Two lineages accounted for 97%, including 426 and 1516 sequences, and homosexuals and bisexuals were above 80%. One lineage appeared earlier 7 years than another (1993 vs. 2002) among homosexuals and bisexuals, whereas among heterosexuals, both lineages were observed firstly in 2002. 96% viral migrations within one lineage were from homosexuals toward bisexuals (49%) and male-heterosexuals (46%). Within another, except for homosexuals (72%), bisexuals (23%) served as the top second source, and female-heterosexuals (11%) were the third recipients following bisexuals (44%) and male-heterosexuals (39%). Although the basic reproduction number (R0) of two lineages were similar and both of the effective production number (Re) fell below 1 at the most recent sampling time, the starts of the Re declining varied. Conclusions: Our findings revealed that throughout the viral national spread chain, Shenyang is the source for the initial expanding of one lineage, where is only a sink of another, proving that the viral founder effect and regional human mobility contributed to the uneven distribution of two lineages, and emphasizing the important roles of the area where the virus originated and economy-driven migrants in HIV transmission.
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Affiliation(s)
- Minghui An
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
| | - Bin Zhao
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
| | - Lin Wang
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
| | - Zhenxing Chu
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
| | - Junjie Xu
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
| | - Haibo Ding
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
| | - Xiaoxu Han
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
| | - Hong Shang
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China
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8
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Zheng S, Wu J, Hu Z, Gan M, Liu L, Song C, Lei Y, Wang H, Liao L, Feng Y, Shao Y, Ruan Y, Xing H. Epidemiology and Molecular Transmission Characteristics of HIV in the Capital City of Anhui Province in China. Pathogens 2021; 10:pathogens10121554. [PMID: 34959509 PMCID: PMC8708547 DOI: 10.3390/pathogens10121554] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 11/19/2021] [Accepted: 11/25/2021] [Indexed: 01/29/2023] Open
Abstract
Hefei, Anhui province, is one of the cities in the Yangtze River Delta, where many people migrate to Jiangsu, Zhejiang and Shanghai. High migration also contributes to the HIV epidemic. This study explored the HIV prevalence in Hefei to provide a reference for other provinces and assist in the prevention and control of HIV in China. A total of 816 newly reported people with HIV in Hefei from 2017 to 2020 were recruited as subjects. HIV subtypes were identified by a phylogenetic tree. The most prevalent subtypes were CRF07_BC (41.4%), CRF01_AE (38.1%) and CRF55_01B (6.3%). Molecular networks were inferred using HIV-TRACE. The largest and most active transmission cluster was CRF55_01B in Hefei’s network. A Chinese national database (50,798 sequences) was also subjected to molecular network analysis to study the relationship between patients in Hefei and other provinces. CRF55_01B and CRF07_BC-N had higher clustered and interprovincial transmission rates in the national molecular network. People with HIV in Hefei mainly transmitted the disease within the province. Finally, we displayed the epidemic trend of HIV in Hefei in recent years with the dynamic change of effective reproductive number (Re). The weighted overall Re increased rapidly from 2012 to 2015, with a peak value of 3.20 (95% BCI, 2.18–3.85). After 2015, Re began to decline and remained stable at around 1.80. In addition, the Re of CRF55_01B was calculated to be between 2.0 and 4.0 in 2018 and 2019. More attention needs to be paid to the rapid spread of CRF55_01B and CRF07_BC-N strains among people with HIV and the high Re in Hefei. These data provide necessary support to guide the targeted prevention and control of HIV.
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Affiliation(s)
- Shan Zheng
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Jianjun Wu
- Anhui Provincial Center for Disease Control and Prevention, Hefei 230601, China;
| | - Zhongwang Hu
- Hefei Center for Disease Control and Prevention, Hefei 230061, China; (Z.H.); (Y.L.); (H.W.)
| | - Mengze Gan
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Lei Liu
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Chang Song
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Yanhua Lei
- Hefei Center for Disease Control and Prevention, Hefei 230061, China; (Z.H.); (Y.L.); (H.W.)
| | - Hai Wang
- Hefei Center for Disease Control and Prevention, Hefei 230061, China; (Z.H.); (Y.L.); (H.W.)
| | - Lingjie Liao
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Yi Feng
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Yiming Shao
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Yuhua Ruan
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
| | - Hui Xing
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (S.Z.); (M.G.); (L.L.); (C.S.); (L.L.); (Y.F.); (Y.S.); (Y.R.)
- Correspondence:
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9
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An M, Zheng C, Li H, Chen L, Yang Z, Gan Y, Han X, Zhao J, Shang H. Independent epidemic patterns of HIV-1 CRF01_AE lineages driven by mobile population in Shenzhen, an immigrant city of China. Virus Evol 2021; 7:veab094. [PMID: 35299786 PMCID: PMC8923236 DOI: 10.1093/ve/veab094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 10/19/2021] [Accepted: 11/08/2021] [Indexed: 12/14/2022] Open
Abstract
Abstract
Shenzhen, a city with >12 million migrant population, may play a key role in the spread of human immunodeficiency virus (HIV)-1 in China. The transmission dynamics of CRF01_AE, a predominant subtype in Shenzhen, is a good model to characterize the impact of human mobility on HIV-1 epidemic locally and nationally. We used phylodynamic and phylogeographic methods to estimate the viral transmission dynamics and migration trajectory of variable lineages based on 1,423 CRF01_AE sequences in Shenzhen sampled between 2006 and 2015. Eleven lineages of CRF01_AE were detected in Shenzhen. Of those, four main lineages originated during the 1990s. Their basic viral reproduction number (R0) ranged 1.96–3.92. The effective viral reproduction number (Re) of two lineages prevalent among heterosexuals/people who inject drugs had reduced <1 at the end of sampling, and the main sources were the intra-provincial immigrants (72 per cent) for one and local residents of Shenzhen (91 per cent) for another. Within two lineages among men who have sex with men (MSM), Re had been above or close to 1 at the end of sampling, and the immigrants from Jiangxi/Shaanxi and Hubei as sources accounted for 93 per cent and 68 per cent of all viral migration events, respectively. Moreover, no obvious recipients were found throughout the viral migration history for any lineage. Our findings demonstrate that HIV epidemic is declining in Shenzhen, which coincided with the initiation of the interventions during the 2000s. However, the obvious differences of the epidemic patterns between lineages emphasize the importance of further targeting interventions and continued molecular tracing, focusing on high-risk transmission sources among MSM.
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Affiliation(s)
- Minghui An
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, No 155, Nanjing North Street, Shenyang, Liaoning 110001, China
- Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, No 155, Nanjing North Street, Shenyang, Liaoning 110001, China
| | - Chenli Zheng
- Shenzhen Center for Disease Control and Prevention, No 8, Longyuan Road, Shenzhen, Guangdong 518055, China
| | - Hao Li
- Shenzhen Center for Disease Control and Prevention, No 8, Longyuan Road, Shenzhen, Guangdong 518055, China
| | - Lin Chen
- Shenzhen Center for Disease Control and Prevention, No 8, Longyuan Road, Shenzhen, Guangdong 518055, China
| | - Zhengrong Yang
- Shenzhen Center for Disease Control and Prevention, No 8, Longyuan Road, Shenzhen, Guangdong 518055, China
| | - Yongxia Gan
- Shenzhen Center for Disease Control and Prevention, No 8, Longyuan Road, Shenzhen, Guangdong 518055, China
| | - Xiaoxu Han
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, No 155, Nanjing North Street, Shenyang, Liaoning 110001, China
- Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, No 155, Nanjing North Street, Shenyang, Liaoning 110001, China
| | - Jin Zhao
- Shenzhen Center for Disease Control and Prevention, No 8, Longyuan Road, Shenzhen, Guangdong 518055, China
| | - Hong Shang
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, No 155, Nanjing North Street, Shenyang, Liaoning 110001, China
- Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, No 155, Nanjing North Street, Shenyang, Liaoning 110001, China
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10
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Louca S, McLaughlin A, MacPherson A, Joy JB, Pennell MW. Fundamental Identifiability Limits in Molecular Epidemiology. Mol Biol Evol 2021; 38:4010-4024. [PMID: 34009339 PMCID: PMC8382926 DOI: 10.1093/molbev/msab149] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Viral phylogenies provide crucial information on the spread of infectious diseases, and many studies fit mathematical models to phylogenetic data to estimate epidemiological parameters such as the effective reproduction ratio (Re) over time. Such phylodynamic inferences often complement or even substitute for conventional surveillance data, particularly when sampling is poor or delayed. It remains generally unknown, however, how robust phylodynamic epidemiological inferences are, especially when there is uncertainty regarding pathogen prevalence and sampling intensity. Here, we use recently developed mathematical techniques to fully characterize the information that can possibly be extracted from serially collected viral phylogenetic data, in the context of the commonly used birth-death-sampling model. We show that for any candidate epidemiological scenario, there exists a myriad of alternative, markedly different, and yet plausible "congruent" scenarios that cannot be distinguished using phylogenetic data alone, no matter how large the data set. In the absence of strong constraints or rate priors across the entire study period, neither maximum-likelihood fitting nor Bayesian inference can reliably reconstruct the true epidemiological dynamics from phylogenetic data alone; rather, estimators can only converge to the "congruence class" of the true dynamics. We propose concrete and feasible strategies for making more robust epidemiological inferences from viral phylogenetic data.
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Affiliation(s)
- Stilianos Louca
- Department of Biology, University of Oregon, Eugene, OR, USA
- Institute of Ecology and Evolution, University of Oregon, Eugene, OR, USA
| | - Angela McLaughlin
- British Columbia Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada
- Bioinformatics, University of British Columbia, Vancouver, BC, Canada
| | - Ailene MacPherson
- Biodiversity Research Centre, University of British Columbia, Vancouver, BC, Canada
- Department of Zoology, University of British Columbia, Vancouver, BC, Canada
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada
| | - Jeffrey B Joy
- British Columbia Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada
- Bioinformatics, University of British Columbia, Vancouver, BC, Canada
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Matthew W Pennell
- Biodiversity Research Centre, University of British Columbia, Vancouver, BC, Canada
- Department of Zoology, University of British Columbia, Vancouver, BC, Canada
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11
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Featherstone LA, Di Giallonardo F, Holmes EC, Vaughan TG, Duchêne S. Infectious disease phylodynamics with occurrence data. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13620] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Leo A. Featherstone
- Department of Microbiology and Immunology Peter Doherty Institute for Infection and Immunity University of Melbourne Melbourne Vic. Australia
| | | | - Edward C. Holmes
- Marie Bashir Institute for Infectious Diseases and BiosecurityThe University of Sydney Sydney NSW Australia
- Charles Perkins Centre School of Life and Environmental Sciences The University of Sydney Sydney NSW Australia
- School of Medical Sciences The University of Sydney Sydney NSW Australia
| | - Timothy G. Vaughan
- Department of Biosystems Science and Engineering ETH Zurich Basel Switzerland
- Swiss Institute of Bioinformatics (SIB) Lausanne Switzerland
| | - Sebastián Duchêne
- Department of Microbiology and Immunology Peter Doherty Institute for Infection and Immunity University of Melbourne Melbourne Vic. Australia
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12
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Di Giallonardo F, Pinto AN, Keen P, Shaik A, Carrera A, Salem H, Selvey C, Nigro SJ, Fraser N, Price K, Holden J, Lee FJ, Dwyer DE, Bavinton BR, Geoghegan JL, Grulich AE, Kelleher AD. Subtype-specific differences in transmission cluster dynamics of HIV-1 B and CRF01_AE in New South Wales, Australia. J Int AIDS Soc 2021; 24:e25655. [PMID: 33474833 PMCID: PMC7817915 DOI: 10.1002/jia2.25655] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 10/27/2020] [Accepted: 11/23/2020] [Indexed: 12/13/2022] Open
Abstract
INTRODUCTION The human immunodeficiency virus 1 (HIV-1) pandemic is characterized by numerous distinct sub-epidemics (clusters) that continually fuel local transmission. The aims of this study were to identify active growing clusters, to understand which factors most influence the transmission dynamics, how these vary between different subtypes and how this information might contribute to effective public health responses. METHODS We used HIV-1 genomic sequence data linked to demographic factors that accounted for approximately 70% of all new HIV-1 notifications in New South Wales (NSW). We assessed differences in transmission cluster dynamics between subtype B and circulating recombinant form 01_AE (CRF01_AE). Separate phylogenetic trees were estimated using 2919 subtype B and 473 CRF01_AE sequences sampled between 2004 and 2018 in combination with global sequence data and NSW-specific clades were classified as clusters, pairs or singletons. Significant differences in demographics between subtypes were assessed with Chi-Square statistics. RESULTS We identified 104 subtype B and 11 CRF01_AE growing clusters containing a maximum of 29 and 11 sequences for subtype B and CRF01_AE respectively. We observed a > 2-fold increase in the number of NSW-specific CRF01_AE clades over time. Subtype B clusters were associated with individuals reporting men who have sex with men (MSM) as their transmission risk factor, being born in Australia, and being diagnosed during the early stage of infection (p < 0.01). CRF01_AE infections clusters were associated with infections among individuals diagnosed during the early stage of infection (p < 0.05) and CRF01_AE singletons were more likely to be from infections among individuals reporting heterosexual transmission (p < 0.05). We found six subtype B clusters with an above-average growth rate (>1.5 sequences / 6-months) and which consisted of a majority of infections among MSM. We also found four active growing CRF01_AE clusters containing only infections among MSM. Finally, we found 47 subtype B and seven CRF01_AE clusters that contained a large gap in time (>1 year) between infections and may be indicative of intermediate transmissions via undiagnosed individuals. CONCLUSIONS The large number of active and growing clusters among MSM are the driving force of the ongoing epidemic in NSW for subtype B and CRF01_AE.
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Affiliation(s)
| | - Angie N Pinto
- The Kirby InstituteThe University of New South WalesSydneyNSWAustralia
- Royal Prince Alfred HospitalSydneyNSWAustralia
| | - Phillip Keen
- The Kirby InstituteThe University of New South WalesSydneyNSWAustralia
| | - Ansari Shaik
- The Kirby InstituteThe University of New South WalesSydneyNSWAustralia
| | | | - Hanan Salem
- New South Wales Health Pathology‐RPARoyal Prince Alfred HospitalCamperdownNSWAustralia
| | | | | | - Neil Fraser
- Positive Life New South WalesSydneyNSWAustralia
| | | | | | - Frederick J Lee
- New South Wales Health Pathology‐RPARoyal Prince Alfred HospitalCamperdownNSWAustralia
- Sydney Medical SchoolUniversity of SydneySydneyNSWAustralia
| | - Dominic E Dwyer
- New South Wales Health Pathology‐ICPMRWestmead HospitalWestmeadNSWAustralia
| | | | - Jemma L Geoghegan
- Department of Microbiology and ImmunologyUniversity of OtagoDunedinNew Zealand
- Institute of Environmental Science and ResearchWellingtonNew Zealand
| | - Andrew E Grulich
- The Kirby InstituteThe University of New South WalesSydneyNSWAustralia
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13
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Liu M, Han X, Zhao B, An M, He W, Wang Z, Qiu Y, Ding H, Shang H. Dynamics of HIV-1 Molecular Networks Reveal Effective Control of Large Transmission Clusters in an Area Affected by an Epidemic of Multiple HIV Subtypes. Front Microbiol 2020; 11:604993. [PMID: 33281803 PMCID: PMC7691493 DOI: 10.3389/fmicb.2020.604993] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 10/27/2020] [Indexed: 01/20/2023] Open
Abstract
This study reconstructed molecular networks of human immunodeficiency virus (HIV) transmission history in an area affected by an epidemic of multiple HIV-1 subtypes and assessed the efficacy of strengthened early antiretroviral therapy (ART) and regular interventions in preventing HIV spread. We collected demographic and clinical data of 2221 treatment-naïve HIV-1–infected patients in a long-term cohort in Shenyang, Northeast China, between 2008 and 2016. HIV pol gene sequencing was performed and molecular networks of CRF01_AE, CRF07_BC, and subtype B were inferred using HIV-TRACE with separate optimized genetic distance threshold. We identified 168 clusters containing ≥ 2 cases among CRF01_AE-, CRF07_BC-, and subtype B-infected cases, including 13 large clusters (≥ 10 cases). Individuals in large clusters were characterized by younger age, homosexual behavior, more recent infection, higher CD4 counts, and delayed/no ART (P < 0.001). The dynamics of large clusters were estimated by proportional detection rate (PDR), cluster growth predictor, and effective reproductive number (Re). Most large clusters showed decreased or stable during the study period, indicating that expansion was slowing. The proportion of newly diagnosed cases in large clusters declined from 30 to 8% between 2008 and 2016, coinciding with an increase in early ART within 6 months after diagnosis from 24 to 79%, supporting the effectiveness of strengthened early ART and continuous regular interventions. In conclusion, molecular network analyses can thus be useful for evaluating the efficacy of interventions in epidemics with a complex HIV profile.
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Affiliation(s)
- Mingchen Liu
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Xiaoxu Han
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Bin Zhao
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Minghui An
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Wei He
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Zhen Wang
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Yu Qiu
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Haibo Ding
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
| | - Hong Shang
- NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University, Shenyang, China.,Units of Medical Laboratory, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang, China.,Key Laboratory of AIDS Immunology of Liaoning Province, Shenyang, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, China
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14
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Vasylyeva TI, Zarebski A, Smyrnov P, Williams LD, Korobchuk A, Liulchuk M, Zadorozhna V, Nikolopoulos G, Paraskevis D, Schneider J, Skaathun B, Hatzakis A, Pybus OG, Friedman SR. Phylodynamics Helps to Evaluate the Impact of an HIV Prevention Intervention. Viruses 2020; 12:E469. [PMID: 32326127 PMCID: PMC7232463 DOI: 10.3390/v12040469] [Citation(s) in RCA: 12] [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: 01/30/2020] [Revised: 04/02/2020] [Accepted: 04/15/2020] [Indexed: 01/01/2023] Open
Abstract
Assessment of the long-term population-level effects of HIV interventions is an ongoing public health challenge. Following the implementation of a Transmission Reduction Intervention Project (TRIP) in Odessa, Ukraine, in 2013-2016, we obtained HIV pol gene sequences and used phylogenetics to identify HIV transmission clusters. We further applied the birth-death skyline model to the sequences from Odessa (n = 275) and Kyiv (n = 92) in order to estimate changes in the epidemic's effective reproductive number (Re) and rate of becoming uninfectious (δ). We identified 12 transmission clusters in Odessa; phylogenetic clustering was correlated with younger age and higher average viral load at the time of sampling. Estimated Re were similar in Odessa and Kyiv before the initiation of TRIP; Re started to decline in 2013 and is now below Re = 1 in Odessa (Re = 0.4, 95%HPD 0.06-0.75), but not in Kyiv (Re = 2.3, 95%HPD 0.2-5.4). Similarly, estimates of δ increased in Odessa after the initiation of TRIP. Given that both cities shared the same HIV prevention programs in 2013-2019, apart from TRIP, the observed changes in transmission parameters are likely attributable to the TRIP intervention. We propose that molecular epidemiology analysis can be used as a post-intervention effectiveness assessment tool.
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Affiliation(s)
- Tetyana I. Vasylyeva
- Department of Zoology, University of Oxford, OX1 3SY Oxford, UK
- New College, University of Oxford, OX1 3BN Oxford, UK
| | | | | | - Leslie D. Williams
- Division of Community Health Sciences, University of Illinois at Chicago School of Public Health, Chicago, IL 60612, USA
| | | | - Mariia Liulchuk
- State Institution “The L.V. Gromashevsky Institute of Epidemiology and Infectious Diseases of NAMS of Ukraine”, Kyiv 03038, Ukraine
| | - Viktoriia Zadorozhna
- State Institution “The L.V. Gromashevsky Institute of Epidemiology and Infectious Diseases of NAMS of Ukraine”, Kyiv 03038, Ukraine
| | | | - Dimitrios Paraskevis
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 157 72 Athens, Greece
| | - John Schneider
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Britt Skaathun
- Department of Medicine, University of California San Diego, San Diego, CA 92093, USA
| | - Angelos Hatzakis
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 157 72 Athens, Greece
| | - Oliver G. Pybus
- Department of Zoology, University of Oxford, OX1 3SY Oxford, UK
| | - Samuel R. Friedman
- Department of Population Health, New York University, New York, NY 10003, USA
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15
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Gräf T, Delatorre E, Bello G. Phylogenetics applied to the human immunodeficiency virus type 1 (HIV-1): from the cross-species transmissions to the contact network inferences. Mem Inst Oswaldo Cruz 2020; 115:e190461. [PMID: 32187328 PMCID: PMC7098263 DOI: 10.1590/0074-02760190461] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Accepted: 02/12/2020] [Indexed: 12/14/2022] Open
Abstract
Phylogenetic analyses were crucial to elucidate the origin and spread of the pandemic human immunodeficiency virus type 1 (HIV-1) group M virus, both during the pre-epidemic period of cryptic dissemination in human populations as well as during the epidemic phase of spread. The use of phylogenetics and phylodynamics approaches has provided important insights to track the founder events that resulted in the spread of HIV-1 strains across vast geographic areas, specific countries and within geographically restricted communities. In the recent years, the use of phylogenetic analysis combined with the huge availability of HIV sequences has become an increasingly important approach to reconstruct HIV transmission networks and understand transmission dynamics in concentrated and generalised epidemics. Significant efforts to obtain viral sequences from newly HIV-infected individuals could certainly contribute to detect rapidly expanding HIV-1 lineages, identify key populations at high-risk and understand what public health interventions should be prioritised in different scenarios.
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Affiliation(s)
- Tiago Gräf
- Fundação Oswaldo Cruz-Fiocruz, Instituto Gonçalo Moniz, Salvador, BA, Brasil
| | - Edson Delatorre
- Universidade Federal do Espírito Santo, Centro de Ciências Exatas, Naturais e da Saúde, Departamento de Biologia, Alegre, ES, Brasil
| | - Gonzalo Bello
- Fundação Oswaldo Cruz-Fiocruz, Instituto Oswaldo Cruz, Laboratório de AIDS e Imunologia Molecular, Rio de Janeiro, RJ, Brasil
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16
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Theys K, Lemey P, Vandamme AM, Baele G. Advances in Visualization Tools for Phylogenomic and Phylodynamic Studies of Viral Diseases. Front Public Health 2019; 7:208. [PMID: 31428595 PMCID: PMC6688121 DOI: 10.3389/fpubh.2019.00208] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2019] [Accepted: 07/12/2019] [Indexed: 01/28/2023] Open
Abstract
Genomic and epidemiological monitoring have become an integral part of our response to emerging and ongoing epidemics of viral infectious diseases. Advances in high-throughput sequencing, including portable genomic sequencing at reduced costs and turnaround time, are paralleled by continuing developments in methodology to infer evolutionary histories (dynamics/patterns) and to identify factors driving viral spread in space and time. The traditionally static nature of visualizing phylogenetic trees that represent these evolutionary relationships/processes has also evolved, albeit perhaps at a slower rate. Advanced visualization tools with increased resolution assist in drawing conclusions from phylogenetic estimates and may even have potential to better inform public health and treatment decisions, but the design (and choice of what analyses are shown) is hindered by the complexity of information embedded within current phylogenetic models and the integration of available meta-data. In this review, we discuss visualization challenges for the interpretation and exploration of reconstructed histories of viral epidemics that arose from increasing volumes of sequence data and the wealth of additional data layers that can be integrated. We focus on solutions that address joint temporal and spatial visualization but also consider what the future may bring in terms of visualization and how this may become of value for the coming era of real-time digital pathogen surveillance, where actionable results and adequate intervention strategies need to be obtained within days.
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Affiliation(s)
- Kristof Theys
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Anne-Mieke Vandamme
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
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17
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Di Giallonardo F, Pinto AN, Keen P, Shaik A, Carrera A, Salem H, Telfer B, Cooper C, Price K, Selvey C, Holden J, Bachmann N, Lee FJ, Dwyer DE, Duchêne S, Holmes EC, Grulich AE, Kelleher AD. Limited Sustained Local Transmission of HIV-1 CRF01_AE in New South Wales, Australia. Viruses 2019; 11:v11050482. [PMID: 31137836 PMCID: PMC6563510 DOI: 10.3390/v11050482] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Revised: 05/21/2019] [Accepted: 05/24/2019] [Indexed: 02/06/2023] Open
Abstract
Australia’s response to the human immunodeficiency virus type 1 (HIV-1) pandemic led to effective control of HIV transmission and one of the world’s lowest HIV incidence rates—0.14%. Although there has been a recent decline in new HIV diagnoses in New South Wales (NSW), the most populous state in Australia, there has been a concomitant increase with non-B subtype infections, particularly for the HIV-1 circulating recombinant form CRF01_AE. This aforementioned CRF01_AE sampled in NSW, were combined with those sampled globally to identify NSW-specific viral clades. The population growth of these clades was assessed in two-year period intervals from 2009 to 2017. Overall, 109 NSW-specific clades were identified, most comprising pairs of sequences; however, five large clades comprising ≥10 sequences were also found. Forty-four clades grew over time with one or two sequences added to each in different two-year periods. Importantly, while 10 of these clades have seemingly discontinued, the remaining 34 were still active in 2016/2017. Seven such clades each comprised ≥10 sequences, and are representative of individual sub-epidemics in NSW. Thus, although the majority of new CRF01_AE infections were associated with small clades that rarely establish ongoing chains of local transmission, individual sub-epidemics are present and should be closely monitored.
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Affiliation(s)
- Francesca Di Giallonardo
- The Kirby Institute, The University of New South Wales, Sydney, New South Wales 2052, Australia.
| | - Angie N Pinto
- The Kirby Institute, The University of New South Wales, Sydney, New South Wales 2052, Australia.
- Department of Infectious Diseases & Microbiology, Royal Prince Alfred Hospital, Camperdown, New South Wales 2050, Australia.
| | - Phillip Keen
- The Kirby Institute, The University of New South Wales, Sydney, New South Wales 2052, Australia.
| | - Ansari Shaik
- The Kirby Institute, The University of New South Wales, Sydney, New South Wales 2052, Australia.
| | - Alex Carrera
- New South Wales State Reference Laboratory for HIV/AIDS, Darlinghurst, New South Wales 2010, Australia.
| | - Hanan Salem
- New South Wales Health Pathology, Royal Prince Alfred Hospital, Camperdown, New South Wales 2050, Australia.
| | - Barbara Telfer
- Health Protection New South Wales, New South Wales Health, NSW, North Sydne, New South Wales 2060, Australia.
| | - Craig Cooper
- Positive Life New South Wales, Surry Hills, New South Wales 2010, Australia.
| | - Karen Price
- ACON Health Ltd., Surry Hills, New South Wales 2010, Australia.
| | - Christine Selvey
- Health Protection New South Wales, New South Wales Health, NSW, North Sydne, New South Wales 2060, Australia.
| | - Joanne Holden
- Centre for Population Health, New South Wales Ministry of Health, North Sydney, New South Wales 2059, Australia.
| | - Nadine Bachmann
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Institute of Medical Virology, University of Zurich, 8091 Zurich, Switzerland.
| | - Frederick J Lee
- New South Wales Health Pathology, Royal Prince Alfred Hospital, Camperdown, New South Wales 2050, Australia.
- Department of Clinical Immunology & Allergy, Royal Prince Alfred Hospital, Camperdown, New South Wales 2050, Australia.
- Sydney Medical School, University of Sydney, Sydney, New South Wales 2006, Australia.
| | - Dominic E Dwyer
- New South Wales Health Pathology-Institute of Clinical Pathology and Medical Research, Westmead Hospital, Westmead, New South Wales 2145, Australia.
| | - Sebastián Duchêne
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria 3000, Australia.
| | - Edward C Holmes
- Sydney Medical School, University of Sydney, Sydney, New South Wales 2006, Australia.
- Marie Bashir Institute for Infectious Diseases and Biosecurity, Charles Perkins Centre, School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales 2006, Australia.
| | - Andrew E Grulich
- The Kirby Institute, The University of New South Wales, Sydney, New South Wales 2052, Australia.
| | - Anthony D Kelleher
- The Kirby Institute, The University of New South Wales, Sydney, New South Wales 2052, Australia.
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