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Rich SN, Prosperi MCF, Dellicour S, Vrancken B, Cook RL, Spencer EC, Salemi M, Mavian C. Molecular Epidemiology of HIV-1 Subtype B Infection across Florida Reveals Few Large Superclusters with Metropolitan Origin. Microbiol Spectr 2022; 10:e0188922. [PMID: 36222706 PMCID: PMC9769514 DOI: 10.1128/spectrum.01889-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 09/26/2022] [Indexed: 02/03/2023] Open
Abstract
Florida is considered an epicenter of HIV in the United States. The U.S. federal plan for Ending the HIV Epidemic (EHE) within 10 years prioritizes seven of Florida's 67 counties for intervention. We applied molecular epidemiology methods to characterize the HIV infection networks in the state and infer whether the results support the EHE. HIV sequences (N = 34,446) and associated clinical/demographic metadata of diagnosed people with HIV (PWH), during 2007 to 2017, were retrieved from the Florida Department of Health. HIV genetic networks were investigated using MicrobeTrace. Associates of clustering were identified through boosted logistic regression. Assortative trait mixing was also assessed. Bayesian phylogeographic methods were applied to evaluate evidence of imported HIV-1 lineages and illustrate spatiotemporal flows within Florida. We identified nine large clusters spanning all seven EHE counties but little evidence of external introductions, suggesting-in the absence of undersampling-an epidemic that evolved independently from the rest of the country or other external influences. Clusters were highly assortative by geography. Most of the sampled infections (82%) did not cluster with others in the state using standard molecular surveillance methods despite satisfactory sequence sampling in the state. The odds of being unclustered were higher among PWH in rural regions, and depending on demographics. A significant number of unclustered sequences were observed in counties omitted from EHE. The large number of missing sequence links may impact timely detection of emerging transmission clusters and ultimately hinder the success of EHE in Florida. Molecular epidemiology may help better understand infection dynamics at the population level and underlying disparities in disease transmission among subpopulations; however, there is also a continuous need to conduct ethical discussions to avoid possible harm of advanced methodologies to vulnerable groups, especially in the context of HIV stigmatization. IMPORTANCE The large number of missing phylogenetic linkages in rural Florida counties and among women and Black persons with HIV may impact timely detection of ongoing and emerging transmission clusters and ultimately hinder the success of epidemic elimination goals in Florida.
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Affiliation(s)
- Shannan N. Rich
- Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - Mattia C. F. Prosperi
- Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven-University of Leuven, Leuven, Belgium
| | - Bram Vrancken
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven-University of Leuven, Leuven, Belgium
| | - Robert L. Cook
- Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - Emma C. Spencer
- Florida Department of Health, Division of Disease Control and Health Protection, Bureau of Communicable Diseases, Tallahassee, Florida, USA
| | - Marco Salemi
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Carla Mavian
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, Florida, USA
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Chato C, Feng Y, Ruan Y, Xing H, Herbeck J, Kalish M, Poon AFY. Optimized phylogenetic clustering of HIV-1 sequence data for public health applications. PLoS Comput Biol 2022; 18:e1010745. [PMID: 36449514 DOI: 10.1371/journal.pcbi.1010745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [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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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Patil A, Patil S, Rao A, Gadhe S, Kurle S, Panda S. Exploring the Evolutionary History and Phylodynamics of Human Immunodeficiency Virus Type 1 Outbreak From Unnao, India Using Phylogenetic Approach. Front Microbiol 2022; 13:848250. [PMID: 35663884 PMCID: PMC9158528 DOI: 10.3389/fmicb.2022.848250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
Certain rural and semiurban settings in the Unnao district, Uttar Pradesh, India observed an unprecedented increase in the detection of HIV cases during July 2017. Subsequent investigations through health camps and a follow-up case-control study attributed the outbreak to the unsafe injection exposures during treatment. In this study, we have undertaken a secondary analysis to understand the phylogenetic aspects of the outbreak-associated HIV-1 sequences along with the origin and phylodynamics of these sequences. The initial phylogenetic analysis indicated separate monophyletic grouping and there was no mixing of outbreak-associated sequences with sequences from other parts of India. Transmission network analysis using distance-based and non-distance-based methods revealed the existence of transmission clusters within the monophyletic Unnao clade. The median time to the most recent common ancestor (tMRCA) for sequences from Unnao using the pol gene region was observed to be 2011.87 [95% highest posterior density (HPD): 2010.09–2013.53], while the estimates using envelope (env) gene region sequences traced the tMRCA to 2010.33 (95% HPD: 2007.76–2012.99). Phylodynamics estimates demonstrated that the pace of this local epidemic has slowed down in recent times before the time of sampling, but was certainly on an upward track since its inception till 2014.
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Affiliation(s)
- Ajit Patil
- HIV Drug Resistance Laboratory, Indian Council of Medical Research (ICMR)-National AIDS Research Institute, Pune, India
| | - Sandip Patil
- Division of Clinical Sciences, Indian Council of Medical Research (ICMR)-National AIDS Research Institute, Pune, India
| | - Amrita Rao
- Division of Clinical Sciences, Indian Council of Medical Research (ICMR)-National AIDS Research Institute, Pune, India
| | - Sharda Gadhe
- HIV Drug Resistance Laboratory, Indian Council of Medical Research (ICMR)-National AIDS Research Institute, Pune, India
| | - Swarali Kurle
- HIV Drug Resistance Laboratory, Indian Council of Medical Research (ICMR)-National AIDS Research Institute, Pune, India
- *Correspondence: Swarali Kurle
| | - Samiran Panda
- Indian Council of Medical Research Headquarter, New Delhi, India
- Samiran Panda ;
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5
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Novitsky V, Steingrimsson J, Gillani FS, Howison M, Aung S, Solomon M, Won CY, Brotherton A, Shah R, Dunn C, Fulton J, Bertrand T, Civitarese A, Howe K, Marak T, Chan P, Bandy U, Alexander-Scott N, Hogan J, Kantor R. Statewide Longitudinal Trends in Transmitted HIV-1 Drug Resistance in Rhode Island, USA. Open Forum Infect Dis 2022; 9:ofab587. [PMID: 34988256 PMCID: PMC8709897 DOI: 10.1093/ofid/ofab587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 12/06/2021] [Indexed: 11/14/2022] Open
Abstract
Background HIV-1 transmitted drug resistance (TDR) remains a global challenge that can impact care, yet its comprehensive assessment is limited and heterogenous. We longitudinally characterized statewide TDR in Rhode Island. Methods Demographic and clinical data from treatment-naïve individuals were linked to protease, reverse transcriptase, and integrase sequences routinely obtained over 2004-2020. TDR extent, trends, impact on first-line regimens, and association with transmission networks were assessed using the Stanford Database, Mann-Kendall statistic, and phylogenetic tools. Results In 1123 individuals, TDR to any antiretroviral increased from 8% (2004) to 26% (2020), driven by non-nucleotide reverse transcriptase inhibitor (NNRTI; 5%-18%) and, to a lesser extent, nucleotide reverse transcriptase inhibitor (NRTI; 2%-8%) TDR. Dual- and triple-class TDR rates were low, and major integrase strand transfer inhibitor resistance was absent. Predicted intermediate to high resistance was in 77% of those with TDR, with differential suppression patterns. Among all individuals, 34% were in molecular clusters, some only with members with TDR who shared mutations. Among clustered individuals, people with TDR were more likely in small clusters. Conclusions In a unique (statewide) assessment over 2004-2020, TDR increased; this was primarily, but not solely, driven by NNRTIs, impacting antiretroviral regimens. Limited TDR to multiclass regimens and pre-exposure prophylaxis are encouraging; however, surveillance and its integration with molecular epidemiology should continue in order to potentially improve care and prevention interventions.
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Affiliation(s)
| | | | | | - Mark Howison
- Research Improving People's Life, Providence, Rhode Island, USA
| | - Su Aung
- Brown University, Providence, Rhode Island, USA
| | | | - Cindy Y Won
- Brown University, Providence, Rhode Island, USA
| | | | - Rajeev Shah
- Brown University, Providence, Rhode Island, USA
| | - Casey Dunn
- Yale University, New Haven, Connecticut, USA
| | - John Fulton
- Brown University, Providence, Rhode Island, USA
| | - Thomas Bertrand
- Rhode Island Department of Health, Providence, Rhode Island, USA
| | - Anna Civitarese
- Rhode Island Department of Health, Providence, Rhode Island, USA
| | - Katharine Howe
- Rhode Island Department of Health, Providence, Rhode Island, USA
| | - Theodore Marak
- Rhode Island Department of Health, Providence, Rhode Island, USA
| | - Philip Chan
- Brown University, Providence, Rhode Island, USA.,Rhode Island Department of Health, Providence, Rhode Island, USA
| | - Utpala Bandy
- Rhode Island Department of Health, Providence, Rhode Island, USA
| | | | | | - Rami Kantor
- Brown University, Providence, Rhode Island, USA
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6
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Skaathun B, Ragonnet-Cronin M, Poortinga K, Sheng Z, Hu YW, Wertheim JO. Interplay Between Geography and HIV Transmission Clusters in Los Angeles County. Open Forum Infect Dis 2021; 8:ofab211. [PMID: 34159215 PMCID: PMC8212943 DOI: 10.1093/ofid/ofab211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 04/20/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Clusters of HIV diagnoses in time and space and clusters of genetically linked cases can both serve as alerts for directing prevention and treatment activities. We assessed the interplay between geography and transmission across the Los Angeles County (LAC) HIV genetic transmission network. METHODS Deidentified surveillance data reported for 8186 people with HIV residing in LAC from 2010 through 2016 were used to construct a transmission network using HIV-TRACE. We explored geographic assortativity, the tendency for people to link within the same geographic region; concordant time-space pairs, the proportion of genetically linked pairs from the same geographic region and diagnosis year; and Jaccard coefficient, the overlap between geographical and genetic clusters. RESULTS Geography was assortative in the genetic transmission network but less so than either race/ethnicity or transmission risk. Only 18% of individuals were diagnosed in the same year and location as a genetically linked partner. Jaccard analysis revealed that cis-men and younger age at diagnosis had more overlap between genetic clusters and geography; the inverse association was observed for trans-women and Blacks/African Americans. CONCLUSIONS Within an urban setting with endemic HIV, genetic clustering may serve as a better indicator than time-space clustering to understand HIV transmission patterns and guide public health action.
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Affiliation(s)
- Britt Skaathun
- Department of Medicine, University of California San Diego, La Jolla, California, USA
| | - Manon Ragonnet-Cronin
- Department of Medicine, University of California San Diego, La Jolla, California, USA
- Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Kathleen Poortinga
- Division of HIV and STD Programs, Department of Public Health, Los Angeles County, California, USA
| | - Zhijuan Sheng
- Division of HIV and STD Programs, Department of Public Health, Los Angeles County, California, USA
| | - Yunyin W Hu
- Division of HIV and STD Programs, Department of Public Health, Los Angeles County, California, USA
| | - Joel O Wertheim
- Department of Medicine, University of California San Diego, La Jolla, California, USA
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7
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Hassan A, De Gruttola V, Hu YW, Sheng Z, Poortinga K, Wertheim JO. The Relationship Between the Human Immunodeficiency Virus-1 Transmission Network and the HIV Care Continuum in Los Angeles County. Clin Infect Dis 2020; 71:e384-e391. [PMID: 32020172 PMCID: PMC7904072 DOI: 10.1093/cid/ciaa114] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 02/03/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Public health action combating human immunodeficiency virus (HIV) includes facilitating navigation through the HIV continuum of care: timely diagnosis followed by linkage to care and initiation of antiretroviral therapy to suppress viral replication. Molecular epidemiology can identify rapidly growing HIV genetic transmission clusters. How progression through the care continuum relates to transmission clusters has not been previously characterized. METHODS We performed a retrospective study on HIV surveillance data from 5226 adult cases in Los Angeles County diagnosed from 2010 through 2014. Genetic transmission clusters were constructed using HIV-TRACE. Cox proportional hazard models were used to estimate the impact of transmission cluster growth on the time intervals between care continuum events. Gamma frailty models incorporated the effect of heterogeneity associated with genetic transmission clusters. RESULTS In contrast to our expectations, there were no differences in time to the care continuum events among individuals in clusters with different growth dynamics. However, upon achieving viral suppression, individuals in high growth clusters were slower to experience viral rebound (hazard ratio 0.83, P = .011) compared with individuals in low growth clusters. Heterogeneity associated with cluster membership in the timing to each event in the care continuum was highly significant (P < .001), with and without adjustment for transmission risk and demographics. CONCLUSIONS Individuals within the same transmission cluster have more similar trajectories through the HIV care continuum than those across transmission clusters. These findings suggest molecular epidemiology can assist public health officials in identifying clusters of individuals who may benefit from assistance in navigating the HIV care continuum.
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Affiliation(s)
- Adiba Hassan
- Department of Medicine, University of California, San Diego, California, USA
| | - Victor De Gruttola
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Department of Family Medicine, University of California, San Diego, California, USA
| | - Yunyin W Hu
- Division of HIV and STD Programs, Los Angeles County Department of Public Health, Los Angeles, California, USA
| | - Zhijuan Sheng
- Division of HIV and STD Programs, Los Angeles County Department of Public Health, Los Angeles, California, USA
| | - Kathleen Poortinga
- Division of HIV and STD Programs, Los Angeles County Department of Public Health, Los Angeles, California, USA
| | - Joel O Wertheim
- Department of Medicine, University of California, San Diego, California, USA
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Han X, Zhao B, An M, Zhong P, Shang H. Molecular network-based intervention brings us closer to ending the HIV pandemic. Front Med 2020; 14:136-48. [PMID: 32206964 DOI: 10.1007/s11684-020-0756-y] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 02/13/2020] [Indexed: 01/08/2023]
Abstract
Precise identification of HIV transmission among populations is a key step in public health responses. However, the HIV transmission network is usually difficult to determine. HIV molecular networks can be determined by phylogenetic approach, genetic distance-based approach, and a combination of both approaches. These approaches are increasingly used to identify transmission networks among populations, reconstruct the history of HIV spread, monitor the dynamics of HIV transmission, guide targeted intervention on key subpopulations, and assess the effects of interventions. Simulation and retrospective studies have demonstrated that these molecular network-based interventions are more cost-effective than random or traditional interventions. However, we still need to address several challenges to improve the practice of molecular network-guided targeting interventions to finally end the HIV epidemic. The data remain limited or difficult to obtain, and more automatic real-time tools are required. In addition, molecular and social networks must be combined, and technical parameters and ethnic issues warrant further studies.
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Samoff E, Mobley V, Hudgins M, Cope AB, Adams ND, Caputo CR, Dennis AM, Billock RM, Crowley CA, Clymore JM, Foust E. HIV Outbreak Control With Effective Access to Care and Harm Reduction in North Carolina, 2017-2018. Am J Public Health 2020; 110:394-400. [PMID: 31944835 DOI: 10.2105/ajph.2019.305490] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Objectives. To assess and control a potential outbreak of HIV among people who inject drugs in Western North Carolina.Methods. Disease intervention specialists offered testing for hepatitis B and hepatitis C, harm reduction materials, and linkage to care to 7 linked people recently diagnosed with HIV who also injected drugs. Contacts were offered the same services and HIV testing. HIV genotype analysis was used to characterize HIV spread. We assessed testing and care outcomes by using state surveillance information.Results. Disease intervention specialists contacted 6 of 7 linked group members and received information on 177 contacts; among 96 prioritized contacts, 42 of 96 (44%) were exposed to or diagnosed with hepatitis C, 4 of 96 (4%) had hepatitis B, and 14 of 96 (15%) had HIV (2 newly diagnosed during the investigation). HIV genotype analysis suggested recent transmission to linked group members and 1 contact. Eleven of 14 with HIV were virally suppressed following the outbreak response.Conclusions. North Carolina identified and rapidly responded to an HIV outbreak among people reporting injecting drugs. Effective HIV care, the availability of syringe exchange services, and the rapid response likely contributed to controlling this outbreak.
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Affiliation(s)
- Erika Samoff
- Erika Samoff, Victoria Mobley, Michelle Hudgins, Nicole Dzialowy Adams, Christina R. Caputo, Christy A. Crowley, Jacquelyn M. Clymore, and Evelyn Foust are with the Communicable Diseases Branch, Epidemiology Section, North Carolina Division of Public Health, Raleigh, NC. Anna Barry Cope is with the Division of Sexually Transmitted Disease Prevention, Centers for Disease Control and Prevention, Atlanta, GA. Rachael M. Billock is with the Department of Epidemiology, Gillings Global School for Public Health, University of North Carolina at Chapel Hill. Ann M. Dennis is with the Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill
| | - Victoria Mobley
- Erika Samoff, Victoria Mobley, Michelle Hudgins, Nicole Dzialowy Adams, Christina R. Caputo, Christy A. Crowley, Jacquelyn M. Clymore, and Evelyn Foust are with the Communicable Diseases Branch, Epidemiology Section, North Carolina Division of Public Health, Raleigh, NC. Anna Barry Cope is with the Division of Sexually Transmitted Disease Prevention, Centers for Disease Control and Prevention, Atlanta, GA. Rachael M. Billock is with the Department of Epidemiology, Gillings Global School for Public Health, University of North Carolina at Chapel Hill. Ann M. Dennis is with the Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill
| | - Michelle Hudgins
- Erika Samoff, Victoria Mobley, Michelle Hudgins, Nicole Dzialowy Adams, Christina R. Caputo, Christy A. Crowley, Jacquelyn M. Clymore, and Evelyn Foust are with the Communicable Diseases Branch, Epidemiology Section, North Carolina Division of Public Health, Raleigh, NC. Anna Barry Cope is with the Division of Sexually Transmitted Disease Prevention, Centers for Disease Control and Prevention, Atlanta, GA. Rachael M. Billock is with the Department of Epidemiology, Gillings Global School for Public Health, University of North Carolina at Chapel Hill. Ann M. Dennis is with the Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill
| | - Anna Barry Cope
- Erika Samoff, Victoria Mobley, Michelle Hudgins, Nicole Dzialowy Adams, Christina R. Caputo, Christy A. Crowley, Jacquelyn M. Clymore, and Evelyn Foust are with the Communicable Diseases Branch, Epidemiology Section, North Carolina Division of Public Health, Raleigh, NC. Anna Barry Cope is with the Division of Sexually Transmitted Disease Prevention, Centers for Disease Control and Prevention, Atlanta, GA. Rachael M. Billock is with the Department of Epidemiology, Gillings Global School for Public Health, University of North Carolina at Chapel Hill. Ann M. Dennis is with the Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill
| | - Nicole Dzialowy Adams
- Erika Samoff, Victoria Mobley, Michelle Hudgins, Nicole Dzialowy Adams, Christina R. Caputo, Christy A. Crowley, Jacquelyn M. Clymore, and Evelyn Foust are with the Communicable Diseases Branch, Epidemiology Section, North Carolina Division of Public Health, Raleigh, NC. Anna Barry Cope is with the Division of Sexually Transmitted Disease Prevention, Centers for Disease Control and Prevention, Atlanta, GA. Rachael M. Billock is with the Department of Epidemiology, Gillings Global School for Public Health, University of North Carolina at Chapel Hill. Ann M. Dennis is with the Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill
| | - Christina R Caputo
- Erika Samoff, Victoria Mobley, Michelle Hudgins, Nicole Dzialowy Adams, Christina R. Caputo, Christy A. Crowley, Jacquelyn M. Clymore, and Evelyn Foust are with the Communicable Diseases Branch, Epidemiology Section, North Carolina Division of Public Health, Raleigh, NC. Anna Barry Cope is with the Division of Sexually Transmitted Disease Prevention, Centers for Disease Control and Prevention, Atlanta, GA. Rachael M. Billock is with the Department of Epidemiology, Gillings Global School for Public Health, University of North Carolina at Chapel Hill. Ann M. Dennis is with the Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill
| | - Ann M Dennis
- Erika Samoff, Victoria Mobley, Michelle Hudgins, Nicole Dzialowy Adams, Christina R. Caputo, Christy A. Crowley, Jacquelyn M. Clymore, and Evelyn Foust are with the Communicable Diseases Branch, Epidemiology Section, North Carolina Division of Public Health, Raleigh, NC. Anna Barry Cope is with the Division of Sexually Transmitted Disease Prevention, Centers for Disease Control and Prevention, Atlanta, GA. Rachael M. Billock is with the Department of Epidemiology, Gillings Global School for Public Health, University of North Carolina at Chapel Hill. Ann M. Dennis is with the Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill
| | - Rachael M Billock
- Erika Samoff, Victoria Mobley, Michelle Hudgins, Nicole Dzialowy Adams, Christina R. Caputo, Christy A. Crowley, Jacquelyn M. Clymore, and Evelyn Foust are with the Communicable Diseases Branch, Epidemiology Section, North Carolina Division of Public Health, Raleigh, NC. Anna Barry Cope is with the Division of Sexually Transmitted Disease Prevention, Centers for Disease Control and Prevention, Atlanta, GA. Rachael M. Billock is with the Department of Epidemiology, Gillings Global School for Public Health, University of North Carolina at Chapel Hill. Ann M. Dennis is with the Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill
| | - Christy A Crowley
- Erika Samoff, Victoria Mobley, Michelle Hudgins, Nicole Dzialowy Adams, Christina R. Caputo, Christy A. Crowley, Jacquelyn M. Clymore, and Evelyn Foust are with the Communicable Diseases Branch, Epidemiology Section, North Carolina Division of Public Health, Raleigh, NC. Anna Barry Cope is with the Division of Sexually Transmitted Disease Prevention, Centers for Disease Control and Prevention, Atlanta, GA. Rachael M. Billock is with the Department of Epidemiology, Gillings Global School for Public Health, University of North Carolina at Chapel Hill. Ann M. Dennis is with the Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill
| | - Jacquelyn M Clymore
- Erika Samoff, Victoria Mobley, Michelle Hudgins, Nicole Dzialowy Adams, Christina R. Caputo, Christy A. Crowley, Jacquelyn M. Clymore, and Evelyn Foust are with the Communicable Diseases Branch, Epidemiology Section, North Carolina Division of Public Health, Raleigh, NC. Anna Barry Cope is with the Division of Sexually Transmitted Disease Prevention, Centers for Disease Control and Prevention, Atlanta, GA. Rachael M. Billock is with the Department of Epidemiology, Gillings Global School for Public Health, University of North Carolina at Chapel Hill. Ann M. Dennis is with the Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill
| | - Evelyn Foust
- Erika Samoff, Victoria Mobley, Michelle Hudgins, Nicole Dzialowy Adams, Christina R. Caputo, Christy A. Crowley, Jacquelyn M. Clymore, and Evelyn Foust are with the Communicable Diseases Branch, Epidemiology Section, North Carolina Division of Public Health, Raleigh, NC. Anna Barry Cope is with the Division of Sexually Transmitted Disease Prevention, Centers for Disease Control and Prevention, Atlanta, GA. Rachael M. Billock is with the Department of Epidemiology, Gillings Global School for Public Health, University of North Carolina at Chapel Hill. Ann M. Dennis is with the Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill
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