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Hehe Z, Minna Z, Qin F, Tielin N, Yi F, Liping F, Fangfang C, Houlin T, Shi W, Maohe Y, Fan L. Application of molecular epidemiology in revealing HIV-1 transmission network and recombination patterns in Tianjin, China. J Med Virol 2024; 96:e29824. [PMID: 39072805 DOI: 10.1002/jmv.29824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 06/24/2024] [Accepted: 07/16/2024] [Indexed: 07/30/2024]
Abstract
Using a comprehensive molecular epidemiological approach, we characterized the transmission dynamics of HIV-1 among the MSM population in Tianjin, China. Our findings revealed that 38.56% (386/1001) of individuals clustered across 109 molecular transmission clusters (TCs), with MSM aged 50 and below being the group most commonly transmitting HIV-1. Among the identified TCs, CRF01_AE predominated, followed by CRF07_BC. Notably, CRF07_BC demonstrated a higher propensity for forming large clusters compared to CRF01_AE. Birth-death skyline analyses of the two largest clusters indicated that the HIV/AIDS transmission may be at a critical point, nearly all had Re approximately 1 by now. A retrospective analysis revealed that the rapid expansion of these large clusters was primarily driven by the introduction of viruses in 2021, highlighting the crucial importance of continuous molecular surveillance in identifying newly emerging high-risk transmission chains and adapting measures to address evolving epidemic dynamics. Furthermore, we detected the transmission of drug-resistant mutations (DRMs) within the TCs, particularly in the CRF07_BC clusters (K103N, Y181C, and K101E) and CRF01_AE clusters (P225H and K219R), emphasizing the importance of monitoring to support the continued efficacy of first-line therapies and pre-exposure prophylaxis (PrEP). Recombination analyses indicated that complex recombinant patterns, associated with increased amino acid variability, could confer adaptive traits to the viruses, potentially providing a competitive advantage in certain host populations or regions. Our study highlights the potential of integrating molecular epidemiological and phylodynamic approaches to inform targeted interventions.
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Affiliation(s)
- Zhao Hehe
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zheng Minna
- Department of HIV/AIDS and STDs Control and Prevention, Tianjin Provincial Center for Disease Control and Prevention, Tianjin, China
- Tianjin Key Laboratory of Pathogenic Microbiology of Infectious Disease, Tianjin, China
| | - Fan Qin
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Ning Tielin
- Department of HIV/AIDS and STDs Control and Prevention, Tianjin Provincial Center for Disease Control and Prevention, Tianjin, China
- Tianjin Key Laboratory of Pathogenic Microbiology of Infectious Disease, Tianjin, China
| | - Feng Yi
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- State Key Laboratory for Infectious Disease Prevention and Control, Beijing, China
| | - Fei Liping
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Chen Fangfang
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Tang Houlin
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wang Shi
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yu Maohe
- Department of HIV/AIDS and STDs Control and Prevention, Tianjin Provincial Center for Disease Control and Prevention, Tianjin, China
- Tianjin Key Laboratory of Pathogenic Microbiology of Infectious Disease, Tianjin, China
| | - Lyu Fan
- National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Beijing, China
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Satcher Johnson A, Peruski A, Oster AM, Balaji A, Siddiqi AEA, Sweeney P, Hernandez AL. Enhancements to the National HIV Surveillance System, United States, 2013-2023. Public Health Rep 2024:333549241253092. [PMID: 38822672 DOI: 10.1177/00333549241253092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2024] Open
Abstract
HIV infection is monitored through the National HIV Surveillance System (NHSS) to help improve the health of people with HIV and reduce transmission. NHSS data are routinely used at federal, state, and local levels to monitor the distribution and transmission of HIV, plan and evaluate prevention and care programs, allocate resources, inform policy development, and identify and respond to rapid transmission in the United States. We describe the expanded use of HIV surveillance data since the 2013 NHSS status update, during which time the Centers for Disease Control and Prevention (CDC) coordinated to revise the HIV surveillance case definition to support the detection of early infection and reporting of laboratory data, expanded data collection to include information on sexual orientation and gender identity, enhanced data deduplication processes to improve quality, and expanded reporting to include social determinants of health and health equity measures. CDC maximized the effects of federal funding by integrating funding for HIV prevention and surveillance into a single program; the integration of program funding has expanded the use of HIV surveillance data and strengthened surveillance, resulting in enhanced cluster response capacity and intensified data-to-care activities to ensure sustained viral suppression. NHSS data serve as the primary source for monitoring HIV trends and progress toward achieving national initiatives, including the US Department of Health and Human Services' Ending the HIV Epidemic in the United States initiative, the White House's National HIV/AIDS Strategy (2022-2025), and Healthy People 2030. The NHSS will continue to modernize, adapt, and broaden its scope as the need for high-quality HIV surveillance data remains.
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Affiliation(s)
- Anna Satcher Johnson
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Anne Peruski
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Alexandra M Oster
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Alexandra Balaji
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Azfar-E-Alam Siddiqi
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Patricia Sweeney
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Angela L Hernandez
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
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Cheng P, He BC, Liu JF, Wang JL, Yang CX, Ma S, Zhang M, Dong XQ, Li JJ. Using the Molecular Transmission Networks to Analyze the Epidemic Characteristics of HIV-1 CRF08_BC in Kunming, Yunnan. AIDS Res Hum Retroviruses 2024; 40:353-362. [PMID: 37658836 DOI: 10.1089/aid.2023.0060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2023] Open
Abstract
HIV-1CRF08_BC is the most prevalent epidemic subtype among heterosexual (HET) and intravenous drug users (IDUs) in Kunming, Yunnan. Using the pol region of gene sequences derived from molecular epidemiological surveys, we developed a molecular transmission network for the purpose of analyzing its epidemiological characteristics, assessing its epidemiological trends, identifying its potential transmission relationships, and developing targeted interventions. HyPhy 2.2.4 was used to calculate pairwise genetic distances between sequences; GraphPad-Prism 8.0 was employed to determine the standard genetic distance; and Cytoscope 3.7.2 was applied to visualize the network. We used the network analysis tools to investigate network characteristics and the Molecular Complex Detection (MCODE) tool to observe the growth of the network. We utilized a logistic regression model to examine the factors influencing clustering and a zero-inflated Poisson model to investigate the factors influencing potential transmission links. At the standard genetic distance threshold of 0.008, 406 out of 858 study participants were clustered in 132 dissemination networks with a total network linkage of 868, and the number of links per sequence ranged from 1 to 19. The MCODE analysis identified three significant modular clusters in the networks, with network scores ranging from 4.9 to 7. In models of logistic regression, HET, middle-aged and elderly individuals, and residents of northern and southeastern Kunming were more likely to enter the transmission network. According to the zero-inflated Poisson model, age, transmission category, sampling year, marital status, and CD4+ T level had a significant effect on the size of links. The molecular clusters in Kunming's molecular transmission network are specific and aggregate to a certain extent. HIV-1 molecular network analysis provided information on local transmission characteristics, and these findings helped to determine the priority of transmission-reduction interventions.
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Affiliation(s)
- Peng Cheng
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
- School of Public Health, Kunming Medical University, Kunming, P.R. China
| | - Bao-Cui He
- School of Public Health, Kunming Medical University, Kunming, P.R. China
| | - Jia-Fa Liu
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
| | - Jia-Li Wang
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
| | - Cui-Xian Yang
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
| | - Sha Ma
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
| | - Mi Zhang
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
| | - Xing-Qi Dong
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
- School of Public Health, Kunming Medical University, Kunming, P.R. China
| | - Jian-Jian Li
- Department of Laboratory Medicine, Yunnan Provincial Hospital of Infectious Diseases, Kungming, P.R. China
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Sun C, Fang R, Salemi M, Prosperi M, Rife Magalis B. DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction. PLoS Comput Biol 2024; 20:e1011351. [PMID: 38598563 PMCID: PMC11034642 DOI: 10.1371/journal.pcbi.1011351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 04/22/2024] [Accepted: 03/11/2024] [Indexed: 04/12/2024] Open
Abstract
In the midst of an outbreak or sustained epidemic, reliable prediction of transmission risks and patterns of spread is critical to inform public health programs. Projections of transmission growth or decline among specific risk groups can aid in optimizing interventions, particularly when resources are limited. Phylogenetic trees have been widely used in the detection of transmission chains and high-risk populations. Moreover, tree topology and the incorporation of population parameters (phylodynamics) can be useful in reconstructing the evolutionary dynamics of an epidemic across space and time among individuals. We now demonstrate the utility of phylodynamic trees for transmission modeling and forecasting, developing a phylogeny-based deep learning system, referred to as DeepDynaForecast. Our approach leverages a primal-dual graph learning structure with shortcut multi-layer aggregation, which is suited for the early identification and prediction of transmission dynamics in emerging high-risk groups. We demonstrate the accuracy of DeepDynaForecast using simulated outbreak data and the utility of the learned model using empirical, large-scale data from the human immunodeficiency virus epidemic in Florida between 2012 and 2020. Our framework is available as open-source software (MIT license) at github.com/lab-smile/DeepDynaForcast.
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Affiliation(s)
- Chaoyue Sun
- Department of Electrical and Computer Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, Florida, United States of America
| | - Ruogu Fang
- Department of Electrical and Computer Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, Florida, United States of America
- J. Crayton Pruitt Family Department of Biomedical Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, Florida, United States of America
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, Florida, United States of America
| | - Marco Salemi
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Mattia Prosperi
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- Department of Epidemiology, University of Florida, Gainesville, Florida, United States of America
| | - Brittany Rife Magalis
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
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5
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France AM, Panneer N, Farnham PG, Oster AM, Viguerie A, Gopalappa C. Simulation of Full HIV Cluster Networks in a Nationally Representative Model Indicates Intervention Opportunities. J Acquir Immune Defic Syndr 2024; 95:355-361. [PMID: 38412046 PMCID: PMC10901443 DOI: 10.1097/qai.0000000000003367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 12/07/2023] [Indexed: 02/29/2024]
Abstract
BACKGROUND Clusters of rapid HIV transmission in the United States are increasingly recognized through analysis of HIV molecular sequence data reported to the National HIV Surveillance System. Understanding the full extent of cluster networks is important to assess intervention opportunities. However, full cluster networks include undiagnosed and other infections that cannot be systematically observed in real life. METHODS We replicated HIV molecular cluster networks during 2015-2017 in the United States using a stochastic dynamic network simulation model of sexual transmission of HIV. Clusters were defined at the 0.5% genetic distance threshold. Ongoing priority clusters had growth of ≥3 diagnoses/year in multiple years; new priority clusters first had ≥3 diagnoses/year in 2017. We assessed the full extent, composition, and transmission rates of new and ongoing priority clusters. RESULTS Full clusters were 3-9 times larger than detected clusters, with median detected cluster sizes in new and ongoing priority clusters of 4 (range 3-9) and 11 (range 3-33), respectively, corresponding to full cluster sizes with a median of 14 (3-74) and 94 (7-318), respectively. A median of 36.3% (range 11.1%-72.6%) of infections in the full new priority clusters were undiagnosed. HIV transmission rates in these clusters were >4 times the overall rate observed in the entire simulation. CONCLUSIONS Priority clusters reflect networks with rapid HIV transmission. The substantially larger full extent of these clusters, high proportion of undiagnosed infections, and high transmission rates indicate opportunities for public health intervention and impact.
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Affiliation(s)
- Anne Marie France
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention
| | - Nivedha Panneer
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention
| | - Paul G. Farnham
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention
| | - Alexandra M. Oster
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention
| | - Alex Viguerie
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention
| | - Chaitra Gopalappa
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention
- University of Massachusetts Amherst, Amherst, MA, United States
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Weaver S, Dávila-Conn V, Ji D, Verdonk H, Ávila-Ríos S, Leigh Brown AJ, Wertheim JO, Kosakovsky Pond SL. AUTO-TUNE: SELECTING THE DISTANCE THRESHOLD FOR INFERRING HIV TRANSMISSION CLUSTERS. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.11.584522. [PMID: 38559140 PMCID: PMC10979987 DOI: 10.1101/2024.03.11.584522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanism's suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained hetero-sexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.
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Affiliation(s)
- Steven Weaver
- Center for Viral Evolution, Temple University, Philadelphia, PA, USA
| | - Vanessa Dávila-Conn
- Center for Research in Infectious Diseases, National Institute of Respiratory Diseases, Mexico City, Mexico
| | - Daniel Ji
- Department of Computer Science & Engineering, UC San Diego, La Jolla, CA 92093, USA
| | - Hannah Verdonk
- Center for Viral Evolution, Temple University, Philadelphia, PA, USA
| | - Santiago Ávila-Ríos
- Center for Research in Infectious Diseases, National Institute of Respiratory Diseases, Mexico City, Mexico
| | - Andrew J Leigh Brown
- School of Biological Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Joel O Wertheim
- Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA
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Obeng BM, Kelleher AD, Di Giallonardo F. Molecular epidemiology to aid virtual elimination of HIV transmission in Australia. Virus Res 2024; 341:199310. [PMID: 38185332 PMCID: PMC10825322 DOI: 10.1016/j.virusres.2024.199310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 01/03/2024] [Accepted: 01/04/2024] [Indexed: 01/09/2024]
Abstract
The Global UNAIDS 95/95/95 targets aim to increase the percentage of persons who know their HIV status, receive antiretroviral therapy, and have achieved viral suppression. Achieving these targets requires efforts to improve the public health response to increase access to care for those living with HIV, identify those yet undiagnosed with HIV early, and increase access to prevention for those most at risk of HIV acquisition. HIV infections in Australia are among the lowest globally having recorded significant declines in new diagnoses in the last decade. However, the HIV epidemic has changed with an increasing proportion of newly diagnosed infections among those born outside Australia observed in the last five years. Thus, the current prevention efforts are not enough to achieve the UNAIDS targets and virtual elimination across all population groups. We believe both are possible by including molecular epidemiology in the public health response. Molecular epidemiology methods have been crucial in the field of HIV prevention, particularly in demonstrating the efficacy of treatment as prevention. Cluster detection using molecular epidemiology can provide opportunities for the real-time detection of new outbreaks before they grow, and cluster detection programs are now part of the public health response in the USA and Canada. Here, we review what molecular epidemiology has taught us about HIV evolution and spread. We summarize how we can use this knowledge to improve public health measures by presenting case studies from the USA and Canada. We discuss the successes and challenges of current public health programs in Australia, and how we could use cluster detection as an add-on to identify gaps in current prevention measures easier and respond quicker to growing clusters. Lastly, we raise important ethical and legal challenges that need to be addressed when HIV genotypic data is used in combination with personal data.
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Affiliation(s)
- Billal M Obeng
- The Kirby Institute, University of New South Wales, Sydney, Australia
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8
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Zhao X, Gopalappa C. Joint modeling HIV and HPV using a new hybrid agent-based network and compartmental simulation technique. PLoS One 2023; 18:e0288141. [PMID: 37922306 PMCID: PMC10624270 DOI: 10.1371/journal.pone.0288141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 06/20/2023] [Indexed: 11/05/2023] Open
Abstract
Persons living with human immunodeficiency virus (HIV) have a disproportionately higher burden of human papillomavirus infection (HPV)-related cancers. Causal factors include both behavioral and biological. While pharmaceutical and care support interventions help address biological risk of coinfection, as social conditions are common drivers of behaviors, structural interventions are key part of behavioral interventions. Our objective is to develop a joint HIV-HPV model to evaluate the contribution of each factor, to subsequently inform intervention analyses. While compartmental modeling is sufficient for faster spreading HPV, network modeling is suitable for slower spreading HIV. However, using network modeling for jointly modeling HIV and HPV can generate computational complexities given their vastly varying disease epidemiology and disease burden across sub-population groups. We applied a recently developed mixed agent-based compartmental (MAC) simulation technique, which simulates persons with at least one slower spreading disease and their immediate contacts as agents in a network, and all other persons including those with faster spreading diseases in a compartmental model, with an evolving contact network algorithm maintaining the dynamics between the two models. We simulated HIV and HPV in the U.S. among heterosexual female, heterosexual male, and men who have sex with men (men only and men and women) (MSM), sub-populations that mix but have varying HIV burden, and cervical cancer among women. We conducted numerical analyses to evaluate the contribution of behavioral and biological factors to risk of cervical cancer among women with HIV. The model outputs for HIV, HPV, and cervical cancer compared well with surveillance estimates. Model estimates for relative prevalence of HPV (1.67 times) and relative incidence of cervical cancer (3.6 times), among women with HIV compared to women without, were also similar to that reported in observational studies in the literature. The fraction attributed to biological factors ranged from 22-38% for increased HPV prevalence and 80% for increased cervical cancer incidence, the remaining attributed to behavioral. The attribution of both behavioral and biological factors to increased HPV prevalence and cervical cancer incidence suggest the need for behavioral, structural, and pharmaceutical interventions. Validity of model results related to both individual and joint disease metrics serves as proof-of-concept of the MAC simulation technique. Understanding the contribution of behavioral and biological factors of risk helps inform interventions. Future work can expand the model to simulate sexual and care behaviors as functions of social conditions to jointly evaluate behavioral, structural, and pharmaceutical interventions for HIV and cervical cancer prevention.
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Affiliation(s)
- Xinmeng Zhao
- Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA, United States of America
| | - Chaitra Gopalappa
- Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA, United States of America
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Collura R, O'Grady T, Swain CA, Patterson W, Rajulu DT. Molecular HIV Clustering Among Individuals with Mpox and HIV Co-Morbidity in New York State, Excluding New York City. AIDS Res Hum Retroviruses 2023; 39:601-603. [PMID: 37658837 DOI: 10.1089/aid.2023.0009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2023] Open
Abstract
The 2022 global mpox outbreak created an opportunity to test the utility of molecular HIV surveillance (MHS) to identify high-risk transmission networks. Individuals diagnosed with mpox in New York State (NYS) outside New York City-[Rest of State (ROS)] were matched to the NYS HIV and sexually transmitted infection registries. The demographic characteristics of individuals diagnosed with mpox in ROS mirror national trends. HIV-mpox comorbid individuals were more likely to be included in HIV molecular clusters compared to persons living with diagnosed HIV in ROS overall, men who have sex with men (MSM) in ROS, and age-adjusted MSM (to match individuals with mpox diagnosis) in ROS. For the 3-year 0.5% clusters, which are used to define national priority clusters, the HIV-mpox comorbid individuals clustered 2.4 times more frequently than the age/risk-adjusted control group. This study supports the use of HIV MHS to identify populations for priority public health interventions.
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Affiliation(s)
- Randall Collura
- Division of Epidemiology, Evaluation and Partner Services, New York State Department of Health, Albany, New York, USA
| | - Thomas O'Grady
- Division of Epidemiology, Evaluation and Partner Services, New York State Department of Health, Albany, New York, USA
- Department of Epidemiology and Biostatistics, University at Albany School of Public Health, Albany, New York, USA
| | - Carol-Ann Swain
- Division of Epidemiology, Evaluation and Partner Services, New York State Department of Health, Albany, New York, USA
| | - Wendy Patterson
- Division of Epidemiology, Evaluation and Partner Services, New York State Department of Health, Albany, New York, USA
| | - Deepa T Rajulu
- Division of Epidemiology, Evaluation and Partner Services, New York State Department of Health, Albany, New York, USA
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DeGruttola V, Nakazawa M, Lin T, Liu J, Goyal R, Little S, Tu X, Mehta S. Modeling homophily in dynamic networks with application to HIV molecular surveillance. BMC Infect Dis 2023; 23:656. [PMID: 37794364 PMCID: PMC10548762 DOI: 10.1186/s12879-023-08598-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 09/11/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Efforts to control the HIV epidemic can benefit from knowledge of the relationships between the characteristics of people who have transmitted HIV and those who became infected by them. Investigation of this relationship is facilitated by the use of HIV genetic linkage analyses, which allows inference about possible transmission events among people with HIV infection. Two persons with HIV (PWH) are considered linked if the genetic distance between their HIV sequences is less than a given threshold, which implies proximity in a transmission network. The tendency of pairs of nodes (in our case PWH) that share (or differ in) certain attributes to be linked is denoted homophily. Below, we describe a novel approach to modeling homophily with application to analyses of HIV viral genetic sequences from clinical series of participants followed in San Diego. Over the 22-year period of follow-up, increases in cluster size results from HIV transmissions to new people from those already in the cluster-either directly or through intermediaries. METHODS Our analytical approach makes use of a logistic model to describe homophily with regard to demographic, clinical, and behavioral characteristics-that is we investigate whether similarities (or differences) between PWH in these characteristics are associated with their sequences being linked. To investigate the performance of our methods, we conducted on a simulation study for which data sets were generated in a way that reproduced the structure of the observed database. RESULTS Our results demonstrated strong positive homophily associated with hispanic ethnicity, and strong negative homophily, with birth year difference. The second result implies that the larger the difference between the age of a newly-infected PWH and the average age for an available cluster, the lower the odds of a newly infected person joining that cluster. We did not observe homophily associated with prior diagnosis of sexually transmitted diseases. Our simulation studies demonstrated the validity of our approach for modeling homophily, by showing that the estimates it produced matched the specified values of the statistical network generating model. CONCLUSIONS Our novel methods provide a simple and flexible statistical network-based approach for modeling the growth of viral (or other microbial) genetic clusters from linkage to new infections based on genetic distance.
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Affiliation(s)
- Victor DeGruttola
- Division of Biostatistics and Bioinformatics Herbert Wertheim School of Public Health and Human Longevity Science, University of California, 9500 Gilman Dr., 92093-0628, San Diego, La Jolla, CA, USA.
| | | | - Tuo Lin
- Division of Biostatistics and Bioinformatics Herbert Wertheim School of Public Health and Human Longevity Science, University of California, 9500 Gilman Dr., 92093-0628, San Diego, La Jolla, CA, USA
| | - Jinyuan Liu
- Vanderbilt University, Department of Medicine, Nashville, USA
| | - Ravi Goyal
- Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA, USA
| | - Susan Little
- Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA, USA
| | - Xin Tu
- Division of Biostatistics and Bioinformatics Herbert Wertheim School of Public Health and Human Longevity Science, University of California, 9500 Gilman Dr., 92093-0628, San Diego, La Jolla, CA, USA
| | - Sanjay Mehta
- Veterans Affairs, San Diego Healthcare System, San Diego, CA, USA
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Rich SN, Cook RL, Mavian CN, Garrett K, Spencer EC, Salemi M, Prosperi M. Network typologies predict future molecular linkages in the network of HIV transmission. AIDS 2023; 37:1739-1746. [PMID: 37289578 PMCID: PMC10399949 DOI: 10.1097/qad.0000000000003621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 05/30/2023] [Accepted: 06/02/2023] [Indexed: 06/10/2023]
Abstract
OBJECTIVE HIV molecular transmission network typologies have previously demonstrated associations to transmission risk; however, few studies have evaluated their predictive potential in anticipating future transmission events. To assess this, we tested multiple models on statewide surveillance data from the Florida Department of Health. DESIGN This was a retrospective, observational cohort study examining the incidence of new HIV molecular linkages within the existing molecular network of persons with HIV (PWH) in Florida. METHODS HIV-1 molecular transmission clusters were reconstructed for PWH diagnosed in Florida from 2006 to 2017 using the HIV-TRAnsmission Cluster Engine (HIV-TRACE). A suite of machine-learning models designed to predict linkage to a new diagnosis were internally and temporally externally validated using a variety of demographic, clinical, and network-derived parameters. RESULTS Of the 9897 individuals who received a genotype within 12 months of diagnosis during 2012-2017, 2611 (26.4%) were molecularly linked to another case within 1 year at 1.5% genetic distance. The best performing model, trained on two years of data, was high performing (area under the receiving operating curve = 0.96, sensitivity = 0.91, and specificity = 0.90) and included the following variables: age group, exposure group, node degree, betweenness, transitivity, and neighborhood. CONCLUSIONS In the molecular network of HIV transmission in Florida, individuals' network position and connectivity predicted future molecular linkages. Machine-learned models using network typologies performed superior to models using individual data alone. These models can be used to more precisely identify subpopulations for intervention.
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Affiliation(s)
- Shannan N. Rich
- Department of Epidemiology, Colleges of Public Health and Health Professions and Medicine
- Emerging Pathogens Institute
| | - Robert L. Cook
- Department of Epidemiology, Colleges of Public Health and Health Professions and Medicine
- Emerging Pathogens Institute
| | - Carla N. Mavian
- Emerging Pathogens Institute
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine
| | - Karen Garrett
- Emerging Pathogens Institute
- Department of Plant Pathology, University of Florida, Gainesville
| | - 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
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine
| | - Mattia Prosperi
- Department of Epidemiology, Colleges of Public Health and Health Professions and Medicine
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12
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Tang ME, Goyal R, Anderson CM, Mehta SR, Little SJ. Assessing the reliability of the CD4 depletion model in the presence of Ending the HIV Epidemic initiatives. AIDS 2023; 37:1617-1624. [PMID: 37260256 PMCID: PMC10524824 DOI: 10.1097/qad.0000000000003614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
BACKGROUND Accurate estimates of HIV incidence are necessary to monitor progress towards Ending the HIV Epidemic (EHE) initiative targets (90% decline by 2030). U.S. incidence estimates are derived from a CD4 depletion model (CD4 model). We performed simulation-based analyses to investigate the ability of this model to estimate HIV incidence when implementing EHE interventions that have the potential to shorten the duration between HIV infection and diagnosis (diagnosis delay). METHODS Our simulation study evaluates the impact of three parameters on the accuracy of incidence estimates derived from the CD4 model: rate of HIV incidence decline, length of diagnosis delay, and sensitivity of using CD4 + cell counts to identify new infections (recency error). We model HIV incidence and diagnoses after the implementation of a theoretical prevention intervention and compare HIV incidence estimates derived from the CD4 model to simulated incidence. RESULTS Theoretical interventions that shortened the diagnosis delay (10-50%) result in overestimation of HIV incidence by the CD4 model (10-92%) in the first year and by more than 10% for the first 6 years after implementation of the intervention. Changes in the rate of HIV incidence decline and the presence of recency error had minimal impact on the accuracy of incidence estimates derived from the CD4 model. CONCLUSION In the setting of EHE interventions to identify persons with HIV earlier during infection, the CD4 model overestimates HIV incidence. Alternative methods to estimate incidence based on objective measures of incidence are needed to assess and monitor EHE interventions.
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Affiliation(s)
- Michael E Tang
- University of California San Diego, San Diego, California, USA
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Dennis AM, Mobley V. Interrupting HIV transmission networks: how can we design and implement timely and effective interventions? Expert Rev Anti Infect Ther 2023; 21:691-693. [PMID: 37272332 PMCID: PMC10330925 DOI: 10.1080/14787210.2023.2221850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/01/2023] [Indexed: 06/06/2023]
Affiliation(s)
- Ann M. Dennis
- Division of Infectious Diseases, University of North Carolina at Chapel Hill
| | - Victoria Mobley
- Division of Public Health, Communicable Disease Branch, North Carolina Department of Health and Human Services
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Saldana C, Philpott DC, Mauck DE, Hershow RB, Garlow E, Gettings J, Freeman D, France AM, Johnson EN, Ajmal A, Elimam D, Reed K, Sulka A, Adame JF, Andía JF, Gutierrez M, Padilla M, Jimenez NG, Hayes C, McClung RP, Cantos VD, Holland DP, Scott JY, Oster AM, Curran KG, Hassan R, Wortley P. Public Health Response to Clusters of Rapid HIV Transmission Among Hispanic or Latino Gay, Bisexual, and Other Men Who Have Sex with Men - Metropolitan Atlanta, Georgia, 2021-2022. MMWR. MORBIDITY AND MORTALITY WEEKLY REPORT 2023; 72:261-264. [PMID: 36893048 PMCID: PMC10010755 DOI: 10.15585/mmwr.mm7210a3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
Abstract
During February 2021-June 2022, the Georgia Department of Public Health (GDPH) detected five clusters of rapid HIV transmission concentrated among Hispanic or Latino (Hispanic) gay, bisexual, and other men who have sex with men (MSM) in metropolitan Atlanta. The clusters were detected through routine analysis of HIV-1 nucleotide sequence data obtained through public health surveillance (1,2). Beginning in spring 2021, GDPH partnered with health districts with jurisdiction in four metropolitan Atlanta counties (Cobb, DeKalb, Fulton, and Gwinnett) and CDC to investigate factors contributing to HIV spread, epidemiologic characteristics, and transmission patterns. Activities included review of surveillance and partner services interview data,† medical chart reviews, and qualitative interviews with service providers and Hispanic MSM community members. By June 2022, these clusters included 75 persons, including 56% who identified as Hispanic, 96% who reported male sex at birth, 81% who reported male-to-male sexual contact, and 84% of whom resided in the four metropolitan Atlanta counties. Qualitative interviews identified barriers to accessing HIV prevention and care services, including language barriers, immigration- and deportation-related concerns, and cultural norms regarding sexuality-related stigma. GDPH and the health districts expanded coordination, initiated culturally concordant HIV prevention marketing and educational activities, developed partnerships with organizations serving Hispanic communities to enhance outreach and services, and obtained funding for a bilingual patient navigation program with academic partners to provide staff members to help persons overcome barriers and understand the health care system. HIV molecular cluster detection can identify rapid HIV transmission among sexual networks involving ethnic and sexual minority groups, draw attention to the needs of affected populations, and advance health equity through tailored responses that address those needs.
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Novitsky V, Steingrimsson J, Howison M, Dunn CW, Gillani FS, Fulton J, Bertrand T, Howe K, Bhattarai L, Ronquillo G, MacAskill M, Bandy U, Hogan J, Kantor R. Not all clusters are equal: dynamics of molecular HIV-1 clusters in a statewide Rhode Island epidemic. AIDS 2023; 37:389-399. [PMID: 36695355 PMCID: PMC9881752 DOI: 10.1097/qad.0000000000003426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
OBJECTIVES Molecular epidemiology is a powerful tool to characterize HIV epidemics and prioritize public health interventions. Typically, HIV clusters are assumed to have uniform patterns over time. We hypothesized that assessment of cluster evolution would reveal distinct cluster behavior, possibly improving molecular epidemic characterization, towards disrupting HIV transmission. DESIGN Retrospective cohort. METHODS Annual phylogenies were inferred by cumulative aggregation of all available HIV-1 pol sequences of individuals with HIV-1 in Rhode Island (RI) between 1990 and 2020, representing a statewide epidemic. Molecular clusters were detected in annual phylogenies by strict and relaxed cluster definition criteria, and the impact of annual newly-diagnosed HIV-1 cases to the structure of individual clusters was examined over time. RESULTS Of 2153 individuals, 31% (strict criteria) - 47% (relaxed criteria) clustered. Longitudinal tracking of individual clusters identified three cluster types: normal, semi-normal and abnormal. Normal clusters (83-87% of all identified clusters) showed predicted growing/plateauing dynamics, with approximately three-fold higher growth rates in large (15-18%) vs. small (∼5%) clusters. Semi-normal clusters (1-2% of all clusters) temporarily fluctuated in size and composition. Abnormal clusters (11-16% of all clusters) demonstrated collapses and re-arrangements over time. Borderline values of cluster-defining parameters explained dynamics of non-normal clusters. CONCLUSIONS Comprehensive tracing of molecular HIV clusters over time in a statewide epidemic identified distinct cluster types, likely missed in cross-sectional analyses, demonstrating that not all clusters are equal. This knowledge challenges current perceptions of consistent cluster behavior over time and could improve molecular surveillance of local HIV epidemics to better inform public health strategies.
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Affiliation(s)
| | | | - Mark Howison
- Research Improving People’s Lives, Providence, RI, USA
| | | | | | | | | | | | | | | | | | - Utpala Bandy
- Rhode Island Department of Health, Providence, RI, USA
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16
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Webale SK, Kilongosi M, Munyekenye G, Onyango D, Marwa I, Bowen N. HIV-1 Transmission Cluster in Injection Drug Users in Nairobi City, Kenya. Ethiop J Health Sci 2023; 33:203-210. [PMID: 37484179 PMCID: PMC10358376 DOI: 10.4314/ejhs.v33i2.4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 12/20/2022] [Indexed: 07/25/2023] Open
Abstract
Background While there is a striking increase in the prevalence of HIV in injection drug users, information on envelope-gene subtypes and transmission clusters in injection drug users is scarce. Method In a cross-sectional study, 247 injection drug users were recruited via out-rich method. Deoxyribonucleic acid was extracted from dry blood spot samples, amplified by Polymerase Chain Reaction and sequenced. Subtyping was performed using COntext-based Modeling for Expeditious Typing (COMET) and Recombinant Identification Program (RIP) tools. Phylogenetic diversity and Transmission clusters were identified using MEGA version 6.0 and TreeLink, respectively. Results Overall, 42 (17.0%) injection drug users were sero-positive for HIV-1. Of the 37 samples successfully sequenced, 29 (78.4%) sequences were identified as A1, 6 (16.2%) as AG while 1 (2.7%) as A1/G/AE and A1/C recombinants. The HIV subtypes formed clusters with little genetic diversity. Conclusion The high HIV prevalence was associated with transmission clusters and diversity in subtypes indicating ongoing local transmission. Therefore, there is need for comprehensive HIV care tailored to this population.
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Affiliation(s)
- Sella K Webale
- School of Biological sciences, Maseno University, Maseno, Kenya
| | - Mark Kilongosi
- School of Health Sciences, Kirinyaga University, Kutus, Kenya
| | | | - David Onyango
- School of Biological sciences, Maseno University, Maseno, Kenya
| | | | - Nancy Bowen
- National HIV Reference Laboratories, Ministry of Health, Nairobi city, Kenya
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Labarile M, Loosli T, Zeeb M, Kusejko K, Huber M, Hirsch HH, Perreau M, Ramette A, Yerly S, Cavassini M, Battegay M, Rauch A, Calmy A, Notter J, Bernasconi E, Fux C, Günthard HF, Pasin C, Kouyos RD, Aebi-Popp K, Anagnostopoulos A, Battegay M, Bernasconi E, Braun DL, Bucher HC, Calmy A, Cavassini M, Ciuffi A, Dollenmaier G, Egger M, Elzi L, Fehr J, Fellay J, Furrer H, Fux CA, Günthard HF, Hachfeld A, Haerry D, Hasse B, Hirsch HH, Hoffmann M, Hösli I, Huber M, Kahlert CR, Kaiser L, Keiser O, Klimkait T, Kouyos RD, Kovari H, Kusejko K, Martinetti G, Martinez de Tejada B, Marzolini C, Metzner KJ, Müller N, Nemeth J, Nicca D, Paioni P, Pantaleo G, Perreau M, Rauch A, Schmid P, Speck R, Stöckle M, Tarr P, Trkola A, Wandeler G, Yerly S. Quantifying and Predicting Ongoing Human Immunodeficiency Virus Type 1 Transmission Dynamics in Switzerland Using a Distance-Based Clustering Approach. J Infect Dis 2023; 227:554-564. [PMID: 36433831 DOI: 10.1093/infdis/jiac457] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 11/11/2022] [Accepted: 11/25/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Despite effective prevention approaches, ongoing human immunodeficiency virus 1 (HIV-1) transmission remains a public health concern indicating a need for identifying its drivers. METHODS We combined a network-based clustering method using evolutionary distances between viral sequences with statistical learning approaches to investigate the dynamics of HIV transmission in the Swiss HIV Cohort Study and to predict the drivers of ongoing transmission. RESULTS We found that only a minority of clusters and patients acquired links to new infections between 2007 and 2020. While the growth of clusters and the probability of individual patients acquiring new links in the transmission network was associated with epidemiological, behavioral, and virological predictors, the strength of these associations decreased substantially when adjusting for network characteristics. Thus, these network characteristics can capture major heterogeneities beyond classical epidemiological parameters. When modeling the probability of a newly diagnosed patient being linked with future infections, we found that the best predictive performance (median area under the curve receiver operating characteristic AUCROC = 0.77) was achieved by models including characteristics of the network as predictors and that models excluding them performed substantially worse (median AUCROC = 0.54). CONCLUSIONS These results highlight the utility of molecular epidemiology-based network approaches for analyzing and predicting ongoing HIV transmission dynamics. This approach may serve for real-time prospective assessment of HIV transmission.
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Affiliation(s)
- Marco Labarile
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Tom Loosli
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Marius Zeeb
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Katharina Kusejko
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Michael Huber
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Hans H Hirsch
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland.,Transplantation and Clinical Virology, Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Matthieu Perreau
- Division of Immunology and Allergy, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland
| | - Alban Ramette
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Sabine Yerly
- Laboratory of Virology and Division of Infectious Diseases, Geneva University Hospital, University of Geneva, Geneva, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, Lausanne University Hospital, Lausanne, Switzerland
| | - Manuel Battegay
- Transplantation and Clinical Virology, Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Andri Rauch
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Alexandra Calmy
- Laboratory of Virology and Division of Infectious Diseases, Geneva University Hospital, University of Geneva, Geneva, Switzerland
| | - Julia Notter
- Division of Infectious Diseases, Cantonal Hospital St Gallen, St Gallen, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland
| | - Christoph Fux
- Department of Infectious Diseases, Kantonsspital Aarau, Aarau, Switzerland
| | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Chloé Pasin
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Roger D Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
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18
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Garcia M, Devlin S, Kerman J, Fujimoto K, Hirschhorn LR, Phillips II G, Schneider J, McNulty MC. Ending the HIV Epidemic: Identifying Barriers and Facilitators to Implement Molecular HIV Surveillance to Develop Real-Time Cluster Detection and Response Interventions for Local Communities. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3269. [PMID: 36833963 PMCID: PMC9964218 DOI: 10.3390/ijerph20043269] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/08/2023] [Accepted: 02/10/2023] [Indexed: 06/18/2023]
Abstract
The rapid implementation of molecular HIV surveillance (MHS) has resulted in significant challenges for local health departments to develop real-time cluster detection and response (CDR) interventions for priority populations impacted by HIV. This study is among the first to explore professionals' strategies to implement MHS and develop CDR interventions in real-world public health settings. Methods: Semi-structured qualitative interviews were completed by 21 public health stakeholders in the United States' southern and midwestern regions throughout 2020-2022 to identify themes related to the implementation and development of MHS and CDR. Results for the thematic analysis revealed (1) strengths and limitations in utilizing HIV surveillance data for real-time CDR; (2) limitations of MHS data due to medical provider and staff concerns related to CDR; (3) divergent perspectives on the effectiveness of partner services; (4) optimism, but reluctance about the social network strategy; and (5) enhanced partnerships with community stakeholders to address MHS-related concerns. Conclusions: Enhancing MHS and CDR efforts requires a centralized system for staff to access public health data from multiple databases to develop CDR interventions; designating staff dedicated to CDR interventions; and establishing equitable meaningful partnerships with local community stakeholders to address MHS concerns and develop culturally informed CDR interventions.
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Affiliation(s)
- Moctezuma Garcia
- Department of Social Work, College of Health & Sciences, San José State University, San Jose, CA 95112, USA
| | - Samantha Devlin
- The Chicago Center for HIV Elimination, University of Chicago, Chicago, IL 60637, USA
| | - Jared Kerman
- The Chicago Center for HIV Elimination, University of Chicago, Chicago, IL 60637, USA
| | - Kayo Fujimoto
- Department of Health Promotion & Behavioral Sciences, University of Texas Health Sciences Center, Houston, TX 77030, USA
| | - Lisa R. Hirschhorn
- Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Gregory Phillips II
- Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - John Schneider
- The Chicago Center for HIV Elimination, University of Chicago, Chicago, IL 60637, USA
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Moira C. McNulty
- The Chicago Center for HIV Elimination, University of Chicago, Chicago, IL 60637, USA
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
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Kassaye SG, Grossman Z, Vengurlekar P, Chai W, Wallace M, Rhee SY, Meyer WA, Kaufman HW, Castel A, Jordan J, Crandall KA, Kang A, Kumar P, Katzenstein DA, Shafer RW, Maldarelli F. Insights into HIV-1 Transmission Dynamics Using Routinely Collected Data in the Mid-Atlantic United States. Viruses 2022; 15:68. [PMID: 36680108 PMCID: PMC9863702 DOI: 10.3390/v15010068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 12/21/2022] [Accepted: 12/23/2022] [Indexed: 12/28/2022] Open
Abstract
Background: Molecular epidemiological approaches provide opportunities to characterize HIV transmission dynamics. We analyzed HIV sequences and virus load (VL) results obtained during routine clinical care, and individual’s zip-code location to determine utility of this approach. Methods: HIV-1 pol sequences aligned using ClustalW were subtyped using REGA. A maximum likelihood (ML) tree was generated using IQTree. Transmission clusters with ≤3% genetic distance (GD) and ≥90% bootstrap support were identified using ClusterPicker. We conducted Bayesian analysis using BEAST to confirm transmission clusters. The proportion of nucleotides with ambiguity ≤0.5% was considered indicative of early infection. Descriptive statistics were applied to characterize clusters and group comparisons were performed using chi-square or t-test. Results: Among 2775 adults with data from 2014−2015, 2589 (93%) had subtype B HIV-1, mean age was 44 years (SD 12.7), 66.4% were male, and 25% had nucleotide ambiguity ≤0.5. There were 456 individuals in 193 clusters: 149 dyads, 32 triads, and 12 groups with ≥ four individuals per cluster. More commonly in clusters were males than females, 349 (76.5%) vs. 107 (23.5%), p < 0.0001; younger individuals, 35.3 years (SD 12.1) vs. 44.7 (SD 12.3), p < 0.0001; and those with early HIV-1 infection by nucleotide ambiguity, 202/456 (44.3%) vs. 442/2133 (20.7%), p < 0.0001. Members of 43/193 (22.3%) of clusters included individuals in different jurisdictions. Clusters ≥ four individuals were similarly found using BEAST. HIV-1 viral load (VL) ≥3.0 log10 c/mL was most common among individuals in clusters ≥ four, 18/21, (85.7%) compared to 137/208 (65.8%) in clusters sized 2−3, and 927/1169 (79.3%) who were not in a cluster (p < 0.0001). Discussion: HIV sequence data obtained for HIV clinical management provide insights into regional transmission dynamics. Our findings demonstrate the additional utility of HIV-1 VL data in combination with phylogenetic inferences as an enhanced contact tracing tool to direct HIV treatment and prevention services. Trans-jurisdictional approaches are needed to optimize efforts to end the HIV epidemic.
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Affiliation(s)
- Seble G. Kassaye
- Department of Medicine, Georgetown University, Washington, DC 20057, USA
| | - Zehava Grossman
- HIV Dynamics and Replication Program, National Cancer Institute, Frederick, MD 21702, USA
- School of Public Health, Tel Aviv University, Tel Aviv 69978, Israel
| | | | - William Chai
- Warren Alpert Medical School, Brown University, Providence, RI 02912, USA
| | - Megan Wallace
- Department of Medicine, Georgetown University, Washington, DC 20057, USA
| | - Soo-Yon Rhee
- Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | | | | | - Amanda Castel
- Department of Epidemiology, George Washington University, Washington, DC 20052, USA
| | - Jeanne Jordan
- Department of Epidemiology, George Washington University, Washington, DC 20052, USA
| | - Keith A. Crandall
- Computational Biology Institute, George Washington University, Ashburn, VA 20147, USA
| | - Alisa Kang
- Department of Medicine, Georgetown University, Washington, DC 20057, USA
| | - Princy Kumar
- Department of Medicine, Georgetown University, Washington, DC 20057, USA
| | | | - Robert W. Shafer
- Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Frank Maldarelli
- HIV Dynamics and Replication Program, National Cancer Institute, Frederick, MD 21702, USA
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20
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Rich SN, Prosperi MCF, Dellicour S, Vrancken B, Cook RL, Spencer EC, Salemi M, Mavian C. Molecular Epidemiology of HIV-1 Subtype B Infection across Florida Reveals Few Large Superclusters with Metropolitan Origin. Microbiol Spectr 2022; 10:e0188922. [PMID: 36222706 PMCID: PMC9769514 DOI: 10.1128/spectrum.01889-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 09/26/2022] [Indexed: 02/03/2023] Open
Abstract
Florida is considered an epicenter of HIV in the United States. The U.S. federal plan for Ending the HIV Epidemic (EHE) within 10 years prioritizes seven of Florida's 67 counties for intervention. We applied molecular epidemiology methods to characterize the HIV infection networks in the state and infer whether the results support the EHE. HIV sequences (N = 34,446) and associated clinical/demographic metadata of diagnosed people with HIV (PWH), during 2007 to 2017, were retrieved from the Florida Department of Health. HIV genetic networks were investigated using MicrobeTrace. Associates of clustering were identified through boosted logistic regression. Assortative trait mixing was also assessed. Bayesian phylogeographic methods were applied to evaluate evidence of imported HIV-1 lineages and illustrate spatiotemporal flows within Florida. We identified nine large clusters spanning all seven EHE counties but little evidence of external introductions, suggesting-in the absence of undersampling-an epidemic that evolved independently from the rest of the country or other external influences. Clusters were highly assortative by geography. Most of the sampled infections (82%) did not cluster with others in the state using standard molecular surveillance methods despite satisfactory sequence sampling in the state. The odds of being unclustered were higher among PWH in rural regions, and depending on demographics. A significant number of unclustered sequences were observed in counties omitted from EHE. The large number of missing sequence links may impact timely detection of emerging transmission clusters and ultimately hinder the success of EHE in Florida. Molecular epidemiology may help better understand infection dynamics at the population level and underlying disparities in disease transmission among subpopulations; however, there is also a continuous need to conduct ethical discussions to avoid possible harm of advanced methodologies to vulnerable groups, especially in the context of HIV stigmatization. IMPORTANCE The large number of missing phylogenetic linkages in rural Florida counties and among women and Black persons with HIV may impact timely detection of ongoing and emerging transmission clusters and ultimately hinder the success of epidemic elimination goals in Florida.
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Affiliation(s)
- Shannan N. Rich
- Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - Mattia C. F. Prosperi
- Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven-University of Leuven, Leuven, Belgium
| | - Bram Vrancken
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven-University of Leuven, Leuven, Belgium
| | - Robert L. Cook
- Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, Florida, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - Emma C. Spencer
- Florida Department of Health, Division of Disease Control and Health Protection, Bureau of Communicable Diseases, Tallahassee, Florida, USA
| | - Marco Salemi
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Carla Mavian
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, Florida, USA
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Optimized phylogenetic clustering of HIV-1 sequence data for public health applications. PLoS Comput Biol 2022; 18:e1010745. [PMID: 36449514 PMCID: PMC9744331 DOI: 10.1371/journal.pcbi.1010745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 12/12/2022] [Accepted: 11/17/2022] [Indexed: 12/02/2022] Open
Abstract
Clusters of genetically similar infections suggest rapid transmission and may indicate priorities for public health action or reveal underlying epidemiological processes. However, clusters often require user-defined thresholds and are sensitive to non-epidemiological factors, such as non-random sampling. Consequently the ideal threshold for public health applications varies substantially across settings. Here, we show a method which selects optimal thresholds for phylogenetic (subset tree) clustering based on population. We evaluated this method on HIV-1 pol datasets (n = 14, 221 sequences) from four sites in USA (Tennessee, Washington), Canada (Northern Alberta) and China (Beijing). Clusters were defined by tips descending from an ancestral node (with a minimum bootstrap support of 95%) through a series of branches, each with a length below a given threshold. Next, we used pplacer to graft new cases to the fixed tree by maximum likelihood. We evaluated the effect of varying branch-length thresholds on cluster growth as a count outcome by fitting two Poisson regression models: a null model that predicts growth from cluster size, and an alternative model that includes mean collection date as an additional covariate. The alternative model was favoured by AIC across most thresholds, with optimal (greatest difference in AIC) thresholds ranging 0.007-0.013 across sites. The range of optimal thresholds was more variable when re-sampling 80% of the data by location (IQR 0.008 - 0.016, n = 100 replicates). Our results use prospective phylogenetic cluster growth and suggest that there is more variation in effective thresholds for public health than those typically used in clustering studies.
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22
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Chao E, Chato C, Vender R, Olabode AS, Ferreira RC, Poon AFY. Molecular source attribution. PLoS Comput Biol 2022; 18:e1010649. [PMID: 36395093 PMCID: PMC9671344 DOI: 10.1371/journal.pcbi.1010649] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Elisa Chao
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
| | - Connor Chato
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
| | - Reid Vender
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
- School of Medicine, Queen’s University, Kingston, Ontario, Canada
| | - Abayomi S. Olabode
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
| | - Roux-Cil Ferreira
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
| | - Art F. Y. Poon
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, Canada
- * E-mail:
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23
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Mazrouee S, Hallmark CJ, Mora R, Del Vecchio N, Carrasco Hernandez R, Carr M, McNeese M, Fujimoto K, Wertheim JO. Impact of molecular sequence data completeness on HIV cluster detection and a network science approach to enhance detection. Sci Rep 2022; 12:19230. [PMID: 36357480 PMCID: PMC9648870 DOI: 10.1038/s41598-022-21924-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 10/05/2022] [Indexed: 11/11/2022] Open
Abstract
Detection of viral transmission clusters using molecular epidemiology is critical to the response pillar of the Ending the HIV Epidemic initiative. Here, we studied whether inference with an incomplete dataset would influence the accuracy of the reconstructed molecular transmission network. We analyzed viral sequence data available from ~ 13,000 individuals with diagnosed HIV (2012-2019) from Houston Health Department surveillance data with 53% completeness (n = 6852 individuals with sequences). We extracted random subsamples and compared the resulting reconstructed networks versus the full-size network. Increasing simulated completeness was associated with an increase in the number of detected clusters. We also subsampled based on the network node influence in the transmission of the virus where we measured Expected Force (ExF) for each node in the network. We simulated the removal of nodes with the highest and then lowest ExF from the full dataset and discovered that 4.7% and 60% of priority clusters were detected respectively. These results highlight the non-uniform impact of capturing high influence nodes in identifying transmission clusters. Although increasing sequence reporting completeness is the way to fully detect HIV transmission patterns, reaching high completeness has remained challenging in the real world. Hence, we suggest taking a network science approach to enhance performance of molecular cluster detection, augmented by node influence information.
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Affiliation(s)
- Sepideh Mazrouee
- Department of Medicine, University of California San Diego, San Diego, CA, USA.
| | | | | | | | - Rocio Carrasco Hernandez
- Department of Medicine, University of California San Diego, San Diego, CA, USA
- Instituto Nacional de Enfermedades Respiratorias "Ismael Cosío Villegas", Mexico City, México
| | | | | | - Kayo Fujimoto
- Department of Health Promotion and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Joel O Wertheim
- Department of Medicine, University of California San Diego, San Diego, CA, USA
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24
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A deep learning approach to real-time HIV outbreak detection using genetic data. PLoS Comput Biol 2022; 18:e1010598. [PMID: 36240224 PMCID: PMC9604978 DOI: 10.1371/journal.pcbi.1010598] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 10/26/2022] [Accepted: 09/23/2022] [Indexed: 12/15/2022] Open
Abstract
Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential of infectious disease outbreaks. While popular methods to analyze sequence data often involve phylogenetic tree inference, they are vulnerable to errors from recombination and impose a high computational cost, making it difficult to obtain real-time results when the number of sequences is in or above the thousands. Here, we propose an alternative strategy to outbreak detection using genomic data based on deep learning methods developed for image classification. The key idea is to use a pairwise genetic distance matrix calculated from viral sequences as an image, and develop convolutional neutral network (CNN) models to classify areas of the images that show signatures of active outbreak, leading to identification of subsets of sequences taken from an active outbreak. We showed that our method is efficient in finding HIV-1 outbreaks with R0 ≥ 2.5, and overall a specificity exceeding 98% and sensitivity better than 92%. We validated our approach using data from HIV-1 CRF01 in Europe, containing both endemic sequences and a well-known dual outbreak in intravenous drug users. Our model accurately identified known outbreak sequences in the background of slower spreading HIV. Importantly, we detected both outbreaks early on, before they were over, implying that had this method been applied in real-time as data became available, one would have been able to intervene and possibly prevent the extent of these outbreaks. This approach is scalable to processing hundreds of thousands of sequences, making it useful for current and future real-time epidemiological investigations, including public health monitoring using large databases and especially for rapid outbreak identification.
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25
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Perez SM, Panneer N, France AM, Carnes N, Curran KG, Denson DJ, Oster AM. Clusters of Rapid HIV Transmission Among Gay, Bisexual, and Other Men Who Have Sex with Men — United States, 2018–2021. MMWR. MORBIDITY AND MORTALITY WEEKLY REPORT 2022; 71:1201-1206. [PMID: 36136909 PMCID: PMC9531569 DOI: 10.15585/mmwr.mm7138a1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Stephen M. Perez
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, CDC
| | - Nivedha Panneer
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, CDC
| | - Anne Marie France
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, CDC
| | - Neal Carnes
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, CDC
| | - Kathryn G. Curran
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, CDC
| | - Damian J. Denson
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, CDC
| | - Alexandra M. Oster
- Division of HIV Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, CDC
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26
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Msukwa MT, MacLachlan EW, Gugsa ST, Theu J, Namakhoma I, Bangara F, Blair CL, Payne D, Curran KG, Arons M, Namachapa K, Wadonda N, Kabaghe AN, Dobbs T, Shanmugam V, Kim E, Auld A, Babaye Y, O'Malley G, Nyirenda R, Bello G. Characterising persons diagnosed with HIV as either recent or long-term using a cross-sectional analysis of recent infection surveillance data collected in Malawi from September 2019 to March 2020. BMJ Open 2022; 12:e064707. [PMID: 36153024 PMCID: PMC9511604 DOI: 10.1136/bmjopen-2022-064707] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVES In Malawi, a recent infection testing algorithm (RITA) is used to characterise infections of persons newly diagnosed with HIV as recent or long term. This paper shares results from recent HIV infection surveillance and describes distribution and predictors. SETTING Data from 155 health facilities in 11 districts in Malawi were pooled from September 2019 to March 2020. PARTICIPANTS Eligible participants were ≥13 years, and newly diagnosed with HIV. Clients had RITA recent infections if the rapid test for recent infection (RTRI) test result was recent and viral load (VL) ≥1000 copies/mL; if VL was <1000 copies/mL the RTRI result was reclassified as long-term. Results were stratified by age, sex, pregnancy/breastfeeding status and district. RESULTS 13 838 persons consented to RTRI testing and 12 703 had valid RTRI test results and VL results after excluding clients not newly HIV-positive, RTRI negative or missing data (n=1135). A total of 12 365 of the 12 703 were included in the analysis after excluding those whose RTRI results were reclassified as long term (n=338/784 or 43.1%). The remainder, 446/12 703 or 3.5%, met the definition of RITA recent infection. The highest percentage of recent infections was among breastfeeding women (crude OR (COR) 3.2; 95% CI 2.0 to 5.0), young people aged 15-24 years (COR 1.6; 95% CI 1.3 to 1.9) and persons who reported a negative HIV test within the past 12 months (COR 3.3; 95% CI 2.6 to 4.2). Factors associated with recent infection in multivariable analysis included being a non-pregnant female (adjusted OR (AOR) 1.4; 95% CI 1.2 to 1.8), a breastfeeding female (AOR 2.2; 95% CI 1.4 to 3.5), aged 15-24 years (AOR 1.6; 95% CI 1.3 to 1.9) and residents of Machinga (AOR 2.0; 95% CI 1.2 to 3.5) and Mzimba (AOR 2.4; 95% CI 1.3 to 4.5) districts. CONCLUSIONS Malawi's recent HIV infection surveillance system demonstrated high uptake and identified sub-populations of new HIV diagnoses with a higher percentage of recent infections.
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Affiliation(s)
- Malango T Msukwa
- Department of Global Health, I-TECH, University of Washington, Lilongwe, Malawi
| | - Ellen W MacLachlan
- Department of Global Health, I-TECH, University of Washington, Seattle, Washington, USA
| | - Salem T Gugsa
- Department of Global Health, University of Washington, Seattle, Washington, USA
| | - Joe Theu
- Department of Global Health, I-TECH, University of Washington, Lilongwe, Malawi
| | - Ireen Namakhoma
- Department of Global Health, I-TECH, University of Washington, Lilongwe, Malawi
| | - Fred Bangara
- Department of Global Health, I-TECH, University of Washington, Lilongwe, Malawi
| | - Christopher L Blair
- Department of Global Health, I-TECH, University of Washington, Lilongwe, Malawi
| | - Danielle Payne
- Centers for Disease Control and Prevention, Lilongwe, Malawi
| | - Kathryn G Curran
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Melissa Arons
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Khumbo Namachapa
- Department of HIV and AIDS, Ministry of Health, Lilongwe, Central Region, Malawi
| | - Nellie Wadonda
- Centers for Disease Control and Prevention, Lilongwe, Malawi
| | | | - Trudy Dobbs
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | - Evelyn Kim
- Centers for Disease Control and Prevention, Lilongwe, Malawi
| | - Andrew Auld
- Centers for Disease Control and Prevention, Lilongwe, Malawi
| | - Yusuf Babaye
- Department of Global Health, I-TECH, University of Washington, Lilongwe, Malawi
| | - Gabrielle O'Malley
- Department of Global Health, I-TECH, University of Washington, Seattle, Washington, USA
| | - Rose Nyirenda
- Department of HIV and AIDS, Ministry of Health, Lilongwe, Central Region, Malawi
| | - George Bello
- Department of Global Health, I-TECH, University of Washington, Lilongwe, Malawi
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27
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Fan Q, Zhang J, Luo M, Feng Y, Ge R, Yan Y, Zhong P, Ding X, Xia Y, Guo Z, Pan X, Chai C. Molecular Genetics and Epidemiological Characteristics of HIV-1 Epidemic Strains in Various Sexual Risk Behaviour Groups in Developed Eastern China, 2017-2020. Emerg Microbes Infect 2022; 11:2326-2339. [PMID: 36032035 PMCID: PMC9542350 DOI: 10.1080/22221751.2022.2119167] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Qin Fan
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Jiafeng Zhang
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Mingyu Luo
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Yi Feng
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People’s Republic of China
| | - Rui Ge
- Division of AIDS/TB Prevention and Control, Jiaxing Municipal Center for Disease Control and Prevention, Jiaxing 314050, People’s Republic of China
| | - Yong Yan
- Division of AIDS/TB Prevention and Control, Jiaxing Municipal Center for Disease Control and Prevention, Jiaxing 314050, People’s Republic of China
| | - Ping Zhong
- Department of AIDS and STD, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200051, People’s Republic of China
| | - Xiaobei Ding
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Yan Xia
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Zhihong Guo
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Xiaohong Pan
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
| | - Chengliang Chai
- Department of HIV/AIDS and STDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, People’s Republic of China
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28
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Zhang D, Li H, Zheng C, Han J, Li H, Liu Y, Wang X, Jia L, Li S, Li T, Zhang B, Chen L, Yang Z, Gan Y, Zhong Y, Li J, Zhao J, Li L. Analysis of HIV-1 molecular transmission network reveals the prevalence characteristics of three main HIV-1 subtypes in Shenzhen, China. J Infect 2022; 85:e190-e192. [PMID: 36031153 DOI: 10.1016/j.jinf.2022.08.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Accepted: 08/19/2022] [Indexed: 11/25/2022]
Affiliation(s)
- Dong Zhang
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Hanping Li
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Chenli Zheng
- Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong 518055, China
| | - Jingwan Han
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Hao Li
- Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong 518055, China
| | - Yongjian Liu
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Xiaolin Wang
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Lei Jia
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Siqi Li
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Tianyi Li
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Bohan Zhang
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China
| | - Lin Chen
- Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong 518055, China
| | - Zhengrong Yang
- Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong 518055, China
| | - Yongxia Gan
- Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong 518055, China
| | - Yifan Zhong
- Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong 518055, China
| | - Jingyun Li
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China.
| | - Jin Zhao
- Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong 518055, China.
| | - Lin Li
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing 100071, China.
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29
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Chen J, Chen H, Li J, Luo L, Kang R, Liang S, Zhu Q, Lu H, Zhu J, Shen Z, Feng Y, Liao L, Xing H, Shao Y, Ruan Y, Lan G. Genetic network analysis of human immunodeficiency virus sexual transmission in rural Southwest China after the expansion of antiretroviral therapy: A population-based study. Front Microbiol 2022; 13:962477. [PMID: 36060743 PMCID: PMC9434148 DOI: 10.3389/fmicb.2022.962477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 07/26/2022] [Indexed: 11/28/2022] Open
Abstract
Background This study is used to analyze the genetic network of HIV sexual transmission in rural areas of Southwest China after expanding antiretroviral therapy (ART) and to investigate the factors associated with HIV sexual transmission through the genetic network. Materials and methods This was a longitudinal genetic network study in Guangxi, China. The baseline survey and follow-up study were conducted among patients with HIV in 2015, and among those newly diagnosed from 2016 to 2018, respectively. A generalized estimating equation model was employed to explore the factors associated with HIV transmission through the genetic linkage between newly diagnosed patients with HIV (2016-2018) and those at baseline (2015-2017), respectively. Results Of 3,259 identified HIV patient sequences, 2,714 patients were at baseline, and 545 were newly diagnosed patients with HIV at follow-up. A total of 8,691 baseline objectives were observed by repeated measurement analysis. The prevention efficacy in HIV transmission for treated HIV patients was 33% [adjusted odds ratio (AOR): 0.67, 95% confidence interval (CI): 0.48-0.93]. Stratified analyses indicated the prevention efficacy in HIV transmission for treated HIV patients with a viral load (VL) of <50 copies/ml and those treated for 4 years with a VL of <50 copies/ml to be 41 [AOR: 0.59, 95% CI: 0.43-0.82] and 65% [AOR: 0.35, 95% CI: 0.24-0.50], respectively. No significant reduction in HIV transmission occurred among treated HIV patients with VL missing or treated HIV patients on dropout. Some factors were associated with HIV transmission, including over 50 years old, men, Zhuang and other nationalities, with less than secondary schooling, working as a farmer, and heterosexual transmission. Conclusion This study reveals the role of ART in reducing HIV transmission, and those older male farmers with less than secondary schooling are at high risk of HIV infection at a population level. Improvements to ART efficacy for patients with HIV and precision intervention on high-risk individuals during the expansion of ART are urgently required.
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Affiliation(s)
- Jin Chen
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (STD) Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Huanhuan Chen
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Jianjun Li
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Liuhong Luo
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Ruihua Kang
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (STD) Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Shujia Liang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Qiuying Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Huaxiang Lu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Jinhui Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Zhiyong Shen
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
| | - Yi Feng
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (STD) Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Lingjie Liao
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (STD) Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Hui Xing
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (STD) Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Yiming Shao
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (STD) Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Yuhua Ruan
- State Key Laboratory of Infectious Disease Prevention and Control, National Center for Acquired Immune Deficiency Syndrome (AIDS)/Sexually Transmitted Disease (STD) Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, China
| | - Guanghua Lan
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Control and Prevention, Nanning, China
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30
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Wood BR, Stekler JD. Baseline HIV genotype drug resistance testing: is it time for more or less? AIDS 2022; 36:1449-1451. [PMID: 35876702 DOI: 10.1097/qad.0000000000003228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Brian R Wood
- Department of Medicine, University of Washington
- Mountain West AIDS Education and Training Center
| | - Joanne D Stekler
- Department of Medicine, University of Washington
- Mountain West AIDS Education and Training Center
- Department of Global Health, University of Washington, Seattle, WA, USA
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31
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Walters J, Busy L, Hamel C, Junge K, Menza T, Mitchell J, Pinsent T, Toevs K, Vines J. Use of Injection Drugs and Any Form of Methamphetamine in the Portland, OR Metro Area as a Driver of an HIV Time-Space Cluster: Clackamas, Multnomah, and Washington Counties, 2018-2020. AIDS Behav 2022; 26:1717-1726. [PMID: 34757494 PMCID: PMC8579413 DOI: 10.1007/s10461-021-03522-3] [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] [Accepted: 10/23/2021] [Indexed: 11/24/2022]
Abstract
We describe the response to detection of a time-space cluster of new HIV infection in the Portland, OR metro area among people who inject drugs (PWID) and/or people who use any form of methamphetamine. This time-space cluster took place in a region with a syndemic of homelessness and drug use. The investigation included new HIV diagnoses in 2018, 2019, and 2020 in Clackamas, Multnomah, and Washington Counties. Public health response included activating incident command, development and implementation of an enhanced interview tool, outreach testing, and stakeholder engagement. We identified 396 new cases of HIV infection, 116 (29%) of which met the cluster definition. Most cluster cases had no molecular relationships to previous cases. Persons responding to the enhanced interview tool reported behaviors associated with HIV acquisition. Field outreach testing did not identify any new HIV cases but did identify hepatitis C and syphilis infections. We show the importance of a robust public health response to a time-space cluster of new HIV infections in an urban area.
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Affiliation(s)
- Jaime Walters
- Multnomah County Health Department, Epidemiology, Analytics, and Evaluation, Community Epidemiology Services, 619 NW 6th Avenue, 6th Floor, Portland, OR, 97209, USA.
| | - Lea Busy
- Public Health Division, HIV/STD/TB Program, Oregon Health Authority, Portland, OR, USA
| | - Christopher Hamel
- Public Health Division, Multnomah County Health Department, Communicable Disease/STD/HIV, Portland, OR, USA
| | - Kelsi Junge
- Public Health Division, Multnomah County Health Department, Communicable Disease/STD/HIV, Portland, OR, USA
| | - Timothy Menza
- Public Health Division, HIV/STD/TB Program, Oregon Health Authority, Portland, OR, USA
| | - Jaxon Mitchell
- Public Health Division, Multnomah County Health Department, Communicable Disease/STD/HIV, Portland, OR, USA
| | - Taylor Pinsent
- Public Health Division, Multnomah County Health Department, Communicable Disease/STD/HIV, Portland, OR, USA
| | - Kim Toevs
- Public Health Division, Multnomah County Health Department, Communicable Disease/STD/HIV, Portland, OR, USA
| | - Jennifer Vines
- Health Officer Division, Multnomah County Health Department, Portland, OR, USA
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Zhang Y, Dai J, Li Z, Ma Y, Chen H, Dong L, Jin X, Yang M, Zeng Z, Sun P, Hu A, Chen M. Using molecular network analysis to explore the characteristics of HIV-1 transmission in a China-Myanmar border area. PLoS One 2022; 17:e0268143. [PMID: 35522692 PMCID: PMC9075624 DOI: 10.1371/journal.pone.0268143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 04/23/2022] [Indexed: 11/19/2022] Open
Abstract
Background The China-Myanmar border area is considered a hot spot of active HIV-1 recombination in Southeast Asia. To better understand the characteristics of HIV-1 transmission in this area, a cross-sectional HIV-1 molecular epidemiological survey was conducted in Baoshan Prefecture of Yunnan Province. Methods In total, 708 newly reported HIV-1 cases in Baoshan Prefecture from 2019 to 2020 were included in this study. HIV-1 gag, pol and env genes were sequenced, and the spatial and demographic distributions of HIV-1 genotypes were analyzed. The characteristics of HIV-1 transmission were investigated using the HIV-1 molecular network method. Results In the 497 samples with genotyping results, 19 HIV-1 genotypes were found, with URFs being the predominant strains (30.2%, 150/497). The main circulating HIV-1 strains were mostly distributed in the northern area of Baoshan. URFs were more likely identified in Burmese individuals, intravenous drug users and those younger than 50 years old. CRF08_BC was more likely detected in farmers and those of Han ethnicity, CRF01_AE in the young and those of Han ethnicity, and CRF07_BC in the subpopulation with junior middle school education and higher. Moreover, CRF118_BC and CRF64_BC were more likely found in the subpopulation aged ≥40 years and ≥50 years, respectively. Among 480 individuals with pol sequence detection, 179 (37.3%) were grouped into 78 clusters, with Baoshan natives being more likely to be in the network. The proportion of the linked individuals showed significant differences when stratified by the regional origin, marital status, age and county of case reporting. In the molecular network, recent infections were more likely to occur among nonfarmers and individuals aged below 30 years. Conclusions HIV-1 genetics has become complex in Baoshan. HIV-1 molecular network analysis provided transmission characteristics in the local area, and these findings provided information to prioritize transmission-reduction interventions.
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Affiliation(s)
- Yuying Zhang
- School of Public Health, Kunming Medical University, Kunming, Yunnan, China
| | - Jie Dai
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China
| | - Zhengxu Li
- Division for AIDS/STD Control and Prevention, Baoshan Center for Disease Control and Prevention, Baoshan, Yunnan, China
| | - Yanling Ma
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China
| | - Huichao Chen
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China
| | - Lijuan Dong
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China
| | - Xiaomei Jin
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China
| | - Min Yang
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China
| | - Zhijun Zeng
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China
| | - Pengyan Sun
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China
| | - Anyan Hu
- Division for AIDS/STD Control and Prevention, Baoshan Center for Disease Control and Prevention, Baoshan, Yunnan, China
- * E-mail: (MC); (AH)
| | - Min Chen
- Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, Yunnan, China
- * E-mail: (MC); (AH)
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Schneider JA, Hayford C, Hotton A, Tabidze I, Wertheim JO, Ramani S, Hallmark C, Morgan E, Janulis P, Khanna A, Ozik J, Fujimoto K, Flores R, D'aquila R, Benbow N. Do partner services linked to molecular clusters yield people with viremia or new HIV? AIDS 2022; 36:845-852. [PMID: 34873085 PMCID: PMC9397139 DOI: 10.1097/qad.0000000000003140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
OBJECTIVES We examined whether molecular cluster membership was associated with public health identification of HIV transmission potential among named partners in Chicago. DESIGN Historical cohort study. METHODS We matched and analyzed HIV surveillance and partner services data from HIV diagnoses (2012-2016) prior to implementation of cluster detection and response interventions. We constructed molecular clusters using HIV-TRACE at a pairwise genetic distance threshold of 0.5% and identified clusters exhibiting recent and rapid growth according to the Centers for Disease Control and Prevention definition (three new cases diagnosed in past year). Factors associated with identification of partners with HIV transmission potential were examined using multivariable Poisson regression. RESULTS There were 5208 newly diagnosed index clients over this time period. Average age of index clients in clusters was 28; 47% were Black, 29% Latinx/Hispanic, 6% female and 89% MSM. Of the 537 named partners, 191 (35.6%) were linked to index cases in a cluster and of those 16% were either new diagnoses or viremic. There was no statistically significant difference in the probability of identifying partners with HIV transmission potential among index clients in a rapidly growing cluster versus those not in a cluster [adjusted relative risk 1.82, (0.81-4.06)]. CONCLUSION Partner services that were initiated from index clients in a molecular cluster yielded similar new HIV case finding or identification of those with viremia as did interviews with index clients not in clusters. It remains unclear whether these findings are due to temporal disconnects between diagnoses and cluster identification, unobserved cluster members, or challenges with partner services implementation.
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Affiliation(s)
- John A Schneider
- University of Chicago Medicine
- Chicago Center for HIV Elimination
| | | | | | | | - Joel O Wertheim
- Department of Medicine, University of California, San Diego, La Jolla, California
| | | | | | - Ethan Morgan
- College of Public Health, Ohio State University, Columbus, Ohio
| | | | - Aditya Khanna
- School of Public Health, Brown University, Providence, Rhode Island
| | - Jonathan Ozik
- Chicago Center for HIV Elimination
- Department of Public Health Science, University of Chicago, Chicago, Illinois
| | - Kayo Fujimoto
- University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Rey Flores
- University of Chicago Medicine
- Chicago Center for HIV Elimination
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Steingrimsson JA, Fulton J, Howison M, Novitsky V, Gillani FS, Bertrand T, Civitarese A, Howe K, Ronquillo G, Lafazia B, Parillo Z, Marak T, Chan PA, Bhattarai L, Dunn C, Bandy U, Scott NA, Hogan JW, Kantor R. Beyond HIV outbreaks: protocol, rationale and implementation of a prospective study quantifying the benefit of incorporating viral sequence clustering analysis into routine public health interventions. BMJ Open 2022; 12:e060184. [PMID: 35450916 PMCID: PMC9024226 DOI: 10.1136/bmjopen-2021-060184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 03/29/2022] [Indexed: 11/04/2022] Open
Abstract
INTRODUCTION HIV continues to have great impact on millions of lives. Novel methods are needed to disrupt HIV transmission networks. In the USA, public health departments routinely conduct contact tracing and partner services and interview newly HIV-diagnosed index cases to obtain information on social networks and guide prevention interventions. Sequence clustering methods able to infer HIV networks have been used to investigate and halt outbreaks. Incorporation of such methods into routine, not only outbreak-driven, contact tracing and partner services holds promise for further disruption of HIV transmissions. METHODS AND ANALYSIS Building on a strong academic-public health collaboration in Rhode Island, we designed and have implemented a state-wide prospective study to evaluate an intervention that incorporates real-time HIV molecular clustering information with routine contact tracing and partner services. We present the rationale and study design of our approach to integrate sequence clustering methods into routine public health interventions as well as related important ethical considerations. This prospective study addresses key questions about the benefit of incorporating a clustering analysis triggered intervention into the routine workflow of public health departments, going beyond outbreak-only circumstances. By developing an intervention triggered by, and incorporating information from, viral sequence clustering analysis, and evaluating it with a novel design that avoids randomisation while allowing for methods comparison, we are confident that this study will inform how viral sequence clustering analysis can be routinely integrated into public health to support the ending of the HIV pandemic in the USA and beyond. ETHICS AND DISSEMINATION The study was approved by both the Lifespan and Rhode Island Department of Health Human Subjects Research Institutional Review Boards and study results will be published in peer-reviewed journals.
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Affiliation(s)
- Jon A Steingrimsson
- Biostatistics, Brown University School of Public Health, Providence, Rhode Island, USA
| | - John Fulton
- Department of Behavioral and Social Sciences, Brown University, Providence, Rhode Island, USA
| | - Mark Howison
- Research Improving People's Lives, Providence, Rhode Island, USA
| | - Vlad Novitsky
- Department of Medicine, Brown University, Providence, Rhode Island, USA
| | - Fizza S Gillani
- Department of Medicine, 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
| | | | - Benjamin Lafazia
- Rhode Island Department of Health, Providence, Rhode Island, USA
| | - Zoanne Parillo
- Rhode Island Department of Health, Providence, Rhode Island, USA
| | - Theodore Marak
- Rhode Island Department of Health, Providence, Rhode Island, USA
| | - Philip A Chan
- Department of Medicine, Brown University, Providence, Rhode Island, USA
- Rhode Island Department of Health, Providence, Rhode Island, USA
| | - Lila Bhattarai
- Rhode Island Department of Health, Providence, Rhode Island, USA
| | - Casey Dunn
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, USA
| | - Utpala Bandy
- Rhode Island Department of Health, Providence, Rhode Island, USA
| | | | - Joseph W Hogan
- Biostatistics, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Rami Kantor
- Department of Medicine, Brown University, Providence, Rhode Island, USA
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Cella E, Ali S, Schmedes SE, Rife Magalis B, Marini S, Salemi M, Blanton J, Azarian T. Early Emergence Phase of SARS-CoV-2 Delta Variant in Florida, US. Viruses 2022; 14:766. [PMID: 35458495 PMCID: PMC9028683 DOI: 10.3390/v14040766] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 03/24/2022] [Accepted: 04/04/2022] [Indexed: 12/04/2022] Open
Abstract
SARS-CoV-2, the causative agent of COVID-19, emerged in late 2019. The highly contagious B.1.617.2 (Delta) variant of concern (VOC) was first identified in October 2020 in India and subsequently disseminated worldwide, later becoming the dominant lineage in the US. Understanding the local transmission dynamics of early SARS-CoV-2 introductions may inform actionable mitigation efforts during subsequent pandemic waves. Yet, despite considerable genomic analysis of SARS-CoV-2 in the US, several gaps remain. Here, we explore the early emergence of the Delta variant in Florida, US using phylogenetic analysis of representative Florida and globally sampled genomes. We find multiple independent introductions into Florida primarily from North America and Europe, with a minority originating from Asia. These introductions led to three distinct clades that demonstrated varying relative rates of transmission and possessed five distinct substitutions that were 3-21 times more prevalent in the Florida sample as compared to the global sample. Our results underscore the benefits of routine viral genomic surveillance to monitor epidemic spread and support the need for more comprehensive genomic epidemiology studies of emerging variants. In addition, we provide a model of epidemic spread of newly emerging VOCs that can inform future public health responses.
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Affiliation(s)
- Eleonora Cella
- Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL 32827, USA; (E.C.); (S.A.)
| | - Sobur Ali
- Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL 32827, USA; (E.C.); (S.A.)
| | - Sarah E. Schmedes
- Bureau of Public Health Laboratories, Florida Department of Health, Jacksonville, FL 32202, USA; (S.E.S.); (J.B.)
| | - Brittany Rife Magalis
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32608, USA; (B.R.M.); (M.S.)
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL 32608, USA
| | - Simone Marini
- Department of Epidemiology, University of Florida, Gainesville, FL 32608, USA;
| | - Marco Salemi
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32608, USA; (B.R.M.); (M.S.)
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL 32608, USA
| | - Jason Blanton
- Bureau of Public Health Laboratories, Florida Department of Health, Jacksonville, FL 32202, USA; (S.E.S.); (J.B.)
| | - Taj Azarian
- Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL 32827, USA; (E.C.); (S.A.)
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Gil H, Delgado E, Benito S, Georgalis L, Montero V, Sánchez M, Cañada-García JE, García-Bodas E, Díaz A, Thomson MM. Transmission Clusters, Predominantly Associated With Men Who Have Sex With Men, Play a Main Role in the Propagation of HIV-1 in Northern Spain (2013–2018). Front Microbiol 2022; 13:782609. [PMID: 35432279 PMCID: PMC9009226 DOI: 10.3389/fmicb.2022.782609] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 03/14/2022] [Indexed: 11/13/2022] Open
Abstract
Viruses of HIV-1-infected individuals whose transmission is related group phylogenetically in transmission clusters (TCs). The study of the phylogenetic relations of these viruses and the factors associated with these individuals is essential to analyze the HIV-1 epidemic. In this study, we examine the role of TCs in the epidemiology of HIV-1 infection in Galicia and the Basque County, two regions of northern Spain. A total of 1,158 HIV-1-infected patients from both regions with new diagnoses (NDs) in 2013–2018 were included in the study. Partial HIV-1 pol sequences were analyzed phylogenetically by approximately maximum-likelihood with FastTree 2. In this analysis, 10,687 additional sequences from samples from HIV-1-infected individuals collected in Spain in 1999–2019 were also included to assign TC membership and to determine TCs’ sizes. TCs were defined as those which included viruses from ≥4 individuals, at least 50% of them Spaniards, and with ≥0.95 Shimodaira-Hasegawa-like node support in the phylogenetic tree. Factors associated to TCs were evaluated using odds ratios (OR) and their 95% CI. Fifty-one percent of NDs grouped in 162 TCs. Male patients (OR: 2.6; 95% CI: 1.5–4.7) and men having sex with men (MSM; OR: 2.1; 95% CI: 1.4–3.2) had higher odds of belonging to a TC compared to female and heterosexual patients, respectively. Individuals from Latin America (OR: 0.3; 95% CI: 0.2–0.4), North Africa (OR: 0.4; 95% CI: 0.2–1.0), and especially Sub-Saharan Africa (OR: 0.02; 95% CI: 0.003–0.2) were inversely associated to belonging to TCs compared to native Spaniards. Our results show that TCs are important components of the HIV-1 epidemics in the two Spanish regions studied, where transmission between MSM is predominant. The majority of migrants were infected with viruses not belonging to TCs that expand in Spain. Molecular epidemiology is essential to identify local peculiarities of HIV-1 propagation. The early detection of TCs and prevention of their expansion, implementing effective control measures, could reduce HIV-1 infections.
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Affiliation(s)
- Horacio Gil
- HIV Biology and Variability Unit, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
- *Correspondence: Michael M. Thomson, ; Horacio Gil,
| | - Elena Delgado
- HIV Biology and Variability Unit, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
| | - Sonia Benito
- HIV Biology and Variability Unit, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
| | - Leonidas Georgalis
- HIV Biology and Variability Unit, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
| | - Vanessa Montero
- HIV Biology and Variability Unit, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
| | - Mónica Sánchez
- HIV Biology and Variability Unit, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
| | - Javier E. Cañada-García
- HIV Biology and Variability Unit, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
| | - Elena García-Bodas
- HIV Biology and Variability Unit, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
| | - Asunción Díaz
- HIV Surveillance and Behavioral Monitoring Unit, Centro Nacional de Epidemiología, Instituto de Salud Carlos III, Madrid, Spain
| | - Michael M. Thomson
- HIV Biology and Variability Unit, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
- *Correspondence: Michael M. Thomson, ; Horacio Gil,
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Jiang H, Lan G, Zhu Q, Liang S, Li J, Feng Y, Lin M, Xing H, Shao Y. Non-student young men put students at high risk of human immunodeficiency virus acquisition in Guangxi, China: a phylogenetic analysis of surveillance data. Open Forum Infect Dis 2022; 9:ofac042. [PMID: 35198650 PMCID: PMC8860155 DOI: 10.1093/ofid/ofac042] [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: 11/12/2021] [Accepted: 01/24/2022] [Indexed: 11/27/2022] Open
Abstract
Background We sought to identify students and their sexual partners in a molecular transmission network. Methods We obtained 5996 HIV protease and reverse transcriptase gene sequences in Guangxi (165 from students and 5831 from the general populations) and the relevant demographic data. We constructed a molecular transmission network and introduced a permutation test to assess the robust genetic linkages. We calculated the centrality measures to describe the transmission patterns in clusters. Results At the network level, 68 (41.2%) students fell within the network across 43 (8.1%) clusters. Of 141 genetic linkages between students and their partners, only 25 (17.7%) occurred within students. Students were more likely than random permutations to link to other students (odds ratio [OR], 7.2; P < .001), private company employees aged 16–24 years (OR, 3.3; P = .01), private company or government employees aged 25–49 years (OR, 1.7; P = .03), and freelancers or unemployed individuals aged 16–24 years (OR, 5.0; P < .001). At the cluster level, the median age of nonstudents directly linked to students (interquartile range) was 25 (22–30) years, and 80.3% of them had a high school or higher education background. Compared with students, they showed a significantly higher median degree (4.0 vs 2.0; P < .001) but an equivalent median Eigenvector Centrality (0.83 vs 0.81; P = .60). Conclusions The tendency of genetic linkage between students and nonstudent young men and their important position in the HIV transmission network emphasizes the urgent need for 2-pronged public health interventions based on both school and society.
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Affiliation(s)
- He Jiang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Prevention and Control, Nanning, China
- State of Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Guangxi Key Laboratory of AIDS Prevention and Treatment & Guangxi Universities Key Laboratory of Prevention and Control of Highly Prevalent Disease, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Guanghua Lan
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Prevention and Control, Nanning, China
| | - Qiuying Zhu
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Prevention and Control, Nanning, China
| | - Shujia Liang
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Prevention and Control, Nanning, China
| | - Jianjun Li
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Prevention and Control, Nanning, China
| | - Yi Feng
- State of Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Mei Lin
- Guangxi Key Laboratory of Major Infectious Disease Prevention Control and Biosafety Emergency Response, Guangxi Center for Disease Prevention and Control, Nanning, China
| | - Hui Xing
- State of Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yiming Shao
- State of Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Guangxi Key Laboratory of AIDS Prevention and Treatment & Guangxi Universities Key Laboratory of Prevention and Control of Highly Prevalent Disease, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
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Limnaios S, Kostaki EG, Adamis G, Astriti M, Chini M, Mangafas N, Lazanas M, Patrinos S, Metallidis S, Tsachouridou O, Papastamopoulos V, Kakalou E, Chatzidimitriou D, Antoniadou A, Papadopoulos A, Psichogiou M, Basoulis D, Gova M, Pilalas D, Paraskeva D, Chrysos G, Paparizos V, Kourkounti S, Sambatakou H, Bolanos V, Sipsas NV, Lada M, Barbounakis E, Kantzilaki E, Panagopoulos P, Maltezos E, Drimis S, Sypsa V, Lagiou P, Magiorkinis G, Hatzakis A, Skoura L, Paraskevis D. Dating the Origin and Estimating the Transmission Rates of the Major HIV-1 Clusters in Greece: Evidence about the Earliest Subtype A1 Epidemic in Europe. Viruses 2022; 14:v14010101. [PMID: 35062305 PMCID: PMC8782043 DOI: 10.3390/v14010101] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 12/20/2021] [Accepted: 12/30/2021] [Indexed: 12/16/2022] Open
Abstract
Our aim was to estimate the date of the origin and the transmission rates of the major local clusters of subtypes A1 and B in Greece. Phylodynamic analyses were conducted in 14 subtype A1 and 31 subtype B clusters. The earliest dates of origin for subtypes A1 and B were in 1982.6 and in 1985.5, respectively. The transmission rate for the subtype A1 clusters ranged between 7.54 and 39.61 infections/100 person years (IQR: 9.39, 15.88), and for subtype B clusters between 4.42 and 36.44 infections/100 person years (IQR: 7.38, 15.04). Statistical analysis revealed that the average difference in the transmission rate between the PWID and the MSM clusters was 6.73 (95% CI: 0.86 to 12.60; p = 0.026). Our study provides evidence that the date of introduction of subtype A1 in Greece was the earliest in Europe. Transmission rates were significantly higher for PWID than MSM clusters due to the conditions that gave rise to an extensive PWID HIV-1 outbreak ten years ago in Athens, Greece. Transmission rate can be considered as a valuable measure for public health since it provides a proxy of the rate of epidemic growth within a cluster and, therefore, it can be useful for targeted HIV prevention programs.
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Affiliation(s)
- Stefanos Limnaios
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (S.L.); (E.G.K.); (M.G.); (V.S.); (P.L.); (G.M.); (A.H.)
| | - Evangelia Georgia Kostaki
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (S.L.); (E.G.K.); (M.G.); (V.S.); (P.L.); (G.M.); (A.H.)
| | - Georgios Adamis
- 1st Department of Internal Medicine, G. Gennimatas General Hospital, 11527 Athens, Greece; (G.A.); (M.A.)
| | - Myrto Astriti
- 1st Department of Internal Medicine, G. Gennimatas General Hospital, 11527 Athens, Greece; (G.A.); (M.A.)
| | - Maria Chini
- 3rd Department of Internal Medicine-Infectious Diseases Unit, “Korgialeneio-Benakeio” Red Cross General Hospital, 11526 Athens, Greece; (M.C.); (N.M.); (M.L.)
| | - Nikos Mangafas
- 3rd Department of Internal Medicine-Infectious Diseases Unit, “Korgialeneio-Benakeio” Red Cross General Hospital, 11526 Athens, Greece; (M.C.); (N.M.); (M.L.)
| | - Marios Lazanas
- 3rd Department of Internal Medicine-Infectious Diseases Unit, “Korgialeneio-Benakeio” Red Cross General Hospital, 11526 Athens, Greece; (M.C.); (N.M.); (M.L.)
| | | | - Simeon Metallidis
- 1st Department of Internal Medicine, AHEPA University Hospital, Medical School, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece; (S.M.); (O.T.)
| | - Olga Tsachouridou
- 1st Department of Internal Medicine, AHEPA University Hospital, Medical School, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece; (S.M.); (O.T.)
| | - Vasileios Papastamopoulos
- 5th Department of Internal Medicine and Infectious Diseases, Evaggelismos General Hospital, 10676 Athens, Greece; (V.P.); (E.K.)
| | - Eleni Kakalou
- 5th Department of Internal Medicine and Infectious Diseases, Evaggelismos General Hospital, 10676 Athens, Greece; (V.P.); (E.K.)
| | - Dimitrios Chatzidimitriou
- National AIDS Reference Centre of Northern Greece, Department of Microbiology, Medical School, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (D.C.); (L.S.)
| | - Anastasia Antoniadou
- 4th Department of Medicine, Attikon University General Hospital, Medical School, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.A.); (A.P.)
| | - Antonios Papadopoulos
- 4th Department of Medicine, Attikon University General Hospital, Medical School, National and Kapodistrian University of Athens, 12462 Athens, Greece; (A.A.); (A.P.)
| | - Mina Psichogiou
- 1st Department of Medicine, Laikon General Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (M.P.); (D.B.)
| | - Dimitrios Basoulis
- 1st Department of Medicine, Laikon General Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (M.P.); (D.B.)
| | - Maria Gova
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (S.L.); (E.G.K.); (M.G.); (V.S.); (P.L.); (G.M.); (A.H.)
| | - Dimitrios Pilalas
- Medical School, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
| | - Dimitra Paraskeva
- Department of Internal Medicine, Tzaneio General Hospital, 18536 Piraeus, Greece; (D.P.); (G.C.); (S.D.)
| | - Georgios Chrysos
- Department of Internal Medicine, Tzaneio General Hospital, 18536 Piraeus, Greece; (D.P.); (G.C.); (S.D.)
| | - Vasileios Paparizos
- HIV/AIDS Unit, A. Syngros Hospital of Dermatology and Venereology, 16121 Athens, Greece; (V.P.); (S.K.)
| | - Sofia Kourkounti
- HIV/AIDS Unit, A. Syngros Hospital of Dermatology and Venereology, 16121 Athens, Greece; (V.P.); (S.K.)
| | - Helen Sambatakou
- HIV Unit, 2nd Department of Internal Medicine, Hippokration General Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (H.S.); (V.B.)
| | - Vasileios Bolanos
- HIV Unit, 2nd Department of Internal Medicine, Hippokration General Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (H.S.); (V.B.)
| | - Nikolaos V. Sipsas
- Department of Pathophysiology, Laikon General Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece;
| | - Malvina Lada
- 2nd Department of Internal Medicine, Sismanogleion General Hospital, 15126 Marousi, Greece;
| | - Emmanouil Barbounakis
- Department of Internal Medicine, University Hospital of Heraklion “PAGNI”, Medical School, University of Crete, 71110 Heraklion, Greece; (E.B.); (E.K.)
| | - Evrikleia Kantzilaki
- Department of Internal Medicine, University Hospital of Heraklion “PAGNI”, Medical School, University of Crete, 71110 Heraklion, Greece; (E.B.); (E.K.)
| | - Periklis Panagopoulos
- Department of Internal Medicine, University General Hospital, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (P.P.); (E.M.)
| | - Efstratios Maltezos
- Department of Internal Medicine, University General Hospital, Democritus University of Thrace, 68100 Alexandroupolis, Greece; (P.P.); (E.M.)
| | - Stelios Drimis
- Department of Internal Medicine, Tzaneio General Hospital, 18536 Piraeus, Greece; (D.P.); (G.C.); (S.D.)
| | - Vana Sypsa
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (S.L.); (E.G.K.); (M.G.); (V.S.); (P.L.); (G.M.); (A.H.)
| | - Pagona Lagiou
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (S.L.); (E.G.K.); (M.G.); (V.S.); (P.L.); (G.M.); (A.H.)
| | - Gkikas Magiorkinis
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (S.L.); (E.G.K.); (M.G.); (V.S.); (P.L.); (G.M.); (A.H.)
| | - Angelos Hatzakis
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (S.L.); (E.G.K.); (M.G.); (V.S.); (P.L.); (G.M.); (A.H.)
| | - Lemonia Skoura
- National AIDS Reference Centre of Northern Greece, Department of Microbiology, Medical School, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (D.C.); (L.S.)
| | - Dimitrios Paraskevis
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece; (S.L.); (E.G.K.); (M.G.); (V.S.); (P.L.); (G.M.); (A.H.)
- Correspondence:
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Miller RL, McLaughlin A, Liang RH, Harding J, Wong J, Le AQ, Brumme CJ, Montaner JSG, Joy JB. Phylogenetic prioritization of HIV-1 transmission clusters with viral lineage-level diversification rates. Evol Med Public Health 2022; 10:305-315. [PMID: 35899097 PMCID: PMC9311310 DOI: 10.1093/emph/eoac026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 07/07/2022] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background and objectives
Public health officials faced with a large number of transmission clusters require a rapid, scalable and unbiased way to prioritize distribution of limited resources to maximize benefits. We hypothesize that transmission cluster prioritization based on phylogenetically derived lineage-level diversification rates will perform as well as or better than commonly used growth-based prioritization measures, without need for historical data or subjective interpretation.
Methodology
9822 HIV pol sequences collected during routine drug resistance genotyping were used alongside simulated sequence data to infer sets of phylogenetic transmission clusters via patristic distance threshold. Prioritized clusters inferred from empirical data were compared to those prioritized by the current public health protocols. Prioritization of simulated clusters was evaluated based on correlation of a given prioritization measure with future cluster growth, as well as the number of direct downstream transmissions from cluster members.
Results
Empirical data suggest diversification rate-based measures perform comparably to growth-based measures in recreating public heath prioritization choices. However, unbiased simulated data reveals phylogenetic diversification rate-based measures perform better in predicting future cluster growth relative to growth-based measures, particularly long-term growth. Diversification rate-based measures also display advantages over growth-based measures in highlighting groups with greater future transmission events compared to random groups of the same size. Furthermore, diversification rate measures were notably more robust to effects of decreased sampling proportion.
Conclusions and implications
Our findings indicate diversification rate-based measures frequently outperform growth-based measures in predicting future cluster growth and offer several additional advantages beneficial to optimizing the public health prioritization process.
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Affiliation(s)
- Rachel L Miller
- Molecular Epidemiology and Evolutionary Genetics, British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada
- Bioinformatics Program, University of British Columbia, Vancouver, Canada
| | - Angela McLaughlin
- Molecular Epidemiology and Evolutionary Genetics, British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada
- Bioinformatics Program, University of British Columbia, Vancouver, Canada
| | - Richard H Liang
- Laboratory Program, British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada
| | | | - Jason Wong
- Clinical Prevention Services, British Columbia Centre for Disease Control, Vancouver, Canada
| | - Anh Q Le
- Laboratory Program, British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada
| | - Chanson J Brumme
- Laboratory Program, British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada
- Department of Medicine, University of British Columbia, Vancouver, Canada
| | - Julio S G Montaner
- Department of Medicine, University of British Columbia, Vancouver, Canada
- British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada
| | - Jeffrey B Joy
- Corresponding author. Molecular Epidemiology and Evolutionary Genetics, BC Centre for Excellence in HIV/AIDS, 615-1033 Davie St, Vancouver, BC, V6E 1M5, Canada. Tel: +1-(604)-368-5569; E-mail:
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Ragonnet-Cronin M, Hayford C, D’Aquila R, Ma F, Ward C, Benbow N, Wertheim JO. Forecasting HIV-1 Genetic Cluster Growth in Illinois,United States. J Acquir Immune Defic Syndr 2022; 89:49-55. [PMID: 34878434 PMCID: PMC8667185 DOI: 10.1097/qai.0000000000002821] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 09/08/2021] [Indexed: 01/03/2023]
Abstract
BACKGROUND HIV intervention activities directed toward both those most likely to transmit and their HIV-negative partners have the potential to substantially disrupt HIV transmission. Using HIV sequence data to construct molecular transmission clusters can reveal individuals whose viruses are connected. The utility of various cluster prioritization schemes measuring cluster growth have been demonstrated using surveillance data in New York City and across the United States, by the Centers for Disease Control and Prevention (CDC). METHODS We examined clustering and cluster growth prioritization schemes using Illinois HIV sequence data that include cases from Chicago, a large urban center with high HIV prevalence, to compare their ability to predict future cluster growth. RESULTS We found that past cluster growth was a far better predictor of future cluster growth than cluster membership alone but found no substantive difference between the schemes used by CDC and the relative cluster growth scheme previously used in New York City (NYC). Focusing on individuals selected simultaneously by both the CDC and the NYC schemes did not provide additional improvements. CONCLUSION Growth-based prioritization schemes can easily be automated in HIV surveillance tools and can be used by health departments to identify and respond to clusters where HIV transmission may be actively occurring.
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Affiliation(s)
- Manon Ragonnet-Cronin
- Department of Medicine, University of California San Diego, San Diego, USA
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Christina Hayford
- Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, USA
| | - Richard D’Aquila
- Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, USA
| | - Fangchao Ma
- Illinois Department of Public Health, Chicago, USA
| | - Cheryl Ward
- Illinois Department of Public Health, Chicago, USA
| | - Nanette Benbow
- Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, USA
| | - Joel O. Wertheim
- Department of Medicine, University of California San Diego, San Diego, USA
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Yufenyuy EL, Detorio M, Dobbs T, Patel HK, Jackson K, Vedapuri S, Parekh BS. Performance evaluation of the Asante Rapid Recency Assay for verification of HIV diagnosis and detection of recent HIV-1 infections: Implications for epidemic control. PLOS GLOBAL PUBLIC HEALTH 2022; 2:e0000316. [PMID: 36962217 PMCID: PMC10021762 DOI: 10.1371/journal.pgph.0000316] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 03/09/2022] [Indexed: 11/18/2022]
Abstract
We previously described development of a rapid test for recent infection (RTRI) that can diagnose HIV infection and detect HIV-1 recent infections in a single device. This technology was transferred to a commercial partner as Asante Rapid Recency Assay (ARRA). We evaluated performance of the ARRA kits in the laboratory using a well-characterized panel of specimens. The plasma specimen panel (N = 1500) included HIV-1 (N = 570), HIV-2 (N = 10), and HIV-negatives (N = 920) representing multiple subtypes and geographic locations. Reference diagnostic data were generated using the Bio-Rad HIV-1-2-O EIA/Western blot algorithm with further serotyping performed using the Multispot HIV-1/2 assay. The LAg-Avidity EIA was used to generate reference data on recent and long-term infection for HIV-1 positive specimens at a normalized optical density (ODn) cutoff of 2.0 corresponding to a mean duration of about 6 months. All specimens were tested with ARRA according to the manufacturer's recommendations. Test strips were also read for line intensities using a reader and results were correlated with visual interpretation. ARRA's positive verification line (PVL) correctly classified 575 of 580 HIV-positive and 910 of 920 negative specimens resulting in a sensitivity of 99.1% (95% CI: 98.0-99.6) and specificity of 98.9% (95% CI: 98.1-99.4), respectively. The reader-based classification was similar for PVL with sensitivity of 99.3% (576/580) and specificity of 98.8% (909/920). ARRA's long-term line (LTL) classified 109 of 565 HIV-1 specimens as recent and 456 as long-term compared to 98 as recent and 467 as long-term (LT) by LAg-Avidity EIA (cutoff ODn = 2.0), suggesting a mean duration of recent infection (MDRI) close to 6 months. Agreement of ARRA with LAg recent cases was 81.6% (80/98) and LT cases was 93.8% (438/467), with an overall agreement of 91.7% (kappa = 0.72). The reader (cutoff 2.9) classified 109/566 specimens as recent infections compared to 99 by the LAg-Avidity EIA for recency agreement of 81.8% (81/99), LT agreement of 9% (439/467) with overall agreement of 91.9% (kappa = 0.72). The agreement between visual interpretation and strip reader was 99.9% (95% CI: 99.6-99.9) for the PVL and 98.1% (95% CI: 96.6-98.9) for the LTL. ARRA performed well with HIV diagnostic sensitivity >99% and specificity >98%. Its ability to identify recent infections is comparable to the LA-Avidity EIA corresponding to an MDRI of about 6 months. This point-of-care assay has implications for real-time surveillance of new infections among newly diagnosed individuals for targeted prevention and interrupting ongoing transmission thus accelerating epidemic control.
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Affiliation(s)
- Ernest L Yufenyuy
- Division of Global HIV and TB, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Mervi Detorio
- Division of Global HIV and TB, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Trudy Dobbs
- Division of Global HIV and TB, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Hetal K Patel
- Division of Global HIV and TB, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Keisha Jackson
- Division of Global HIV and TB, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Shanmugam Vedapuri
- Division of Global HIV and TB, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Bharat S Parekh
- Division of Global HIV and TB, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
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Beckwith CG, Min S, Manne A, Novitsky V, Howison M, Liu T, Kuo I, Kurth A, Bazerman L, Agopian A, Kantor R. HIV Drug Resistance and Transmission Networks Among a Justice-Involved Population at the Time of Community Reentry in Washington, D.C. AIDS Res Hum Retroviruses 2021; 37:903-912. [PMID: 33896212 PMCID: PMC8716515 DOI: 10.1089/aid.2020.0267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Justice-involved (JI) populations bear a disproportionate burden of HIV infection and are at risk of poor treatment outcomes. Drug resistance prevalence and emergence, and phylogenetic inference of transmission networks, understudied in vulnerable JI populations, can inform care and prevention interventions, particularly around the critical community reentry period. We analyzed banked blood specimens from CARE+ Corrections study participants in Washington, D.C. (DC) across three time points and conducted HIV drug resistance testing using next-generation sequencing (NGS) at 20% and 5% thresholds to identify prevalent and evolving resistance during community reentry. Phylogenetic analysis was used to identify molecular clusters within participants, and in an extended analysis between participants and publicly available DC sequences. HIV sequence data from 54 participants (99 specimens) were analyzed. The prevalence of transmitted drug resistance was 14% at both thresholds, and acquired drug resistance was 47% at 20%, and 57% at 5% NGS thresholds, respectively. The overall prevalence of drug resistance was 43% at 20%, and 52% at 5% NGS thresholds, respectively. Among 34 participants sampled longitudinally, 21%–35% accumulated 10–17 new resistance mutations during a mean 4.3 months. In phylogenetic analysis within the JI population, 11% were found in three molecular clusters. The extended phylogenetic analysis identified 46% of participants in 22 clusters, of which 21 also included publicly-available DC sequences, and one JI-only unique dyad. This is the first study to identify a high prevalence of HIV drug resistance and its accumulation in a JI population during community reentry and suggests phylogenetic integration of this population into the non-JI DC HIV community. These data support the need for new, effective, and timely interventions to improve HIV treatment during this vulnerable period, and for JI populations to be included in broader surveillance and prevention efforts.
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Affiliation(s)
- Curt G. Beckwith
- Division of Infectious Diseases, The Miriam Hospital, Providence, Rhode Island, USA
- The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Sugi Min
- The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Akarsh Manne
- Division of Infectious Diseases, The Miriam Hospital, Providence, Rhode Island, USA
- The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Vladimir Novitsky
- Division of Infectious Diseases, The Miriam Hospital, Providence, Rhode Island, USA
- The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Mark Howison
- Research Improving People's Lives, Providence, Rhode Island, USA
| | - Tao Liu
- Department of Biostatistics, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Irene Kuo
- George Washington University Milken Institute School of Public Health, Washington, District of Columbia, USA
| | - Ann Kurth
- Yale University School of Nursing, Orange, Connecticut, USA
| | - Lauri Bazerman
- Division of Infectious Diseases, The Miriam Hospital, Providence, Rhode Island, USA
| | - Anya Agopian
- George Washington University Milken Institute School of Public Health, Washington, District of Columbia, USA
| | - Rami Kantor
- Division of Infectious Diseases, The Miriam Hospital, Providence, Rhode Island, USA
- The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
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Godin A, Eaton JW, Giguère K, Marsh K, Johnson LF, Jahn A, Mbofana F, Ehui E, Maheu-Giroux M. Inferring population HIV incidence trends from surveillance data of recent HIV infection among HIV testing clients. AIDS 2021; 35:2383-2388. [PMID: 34261098 PMCID: PMC8631145 DOI: 10.1097/qad.0000000000003021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 06/26/2021] [Accepted: 07/05/2021] [Indexed: 11/27/2022]
Abstract
BACKGROUND Measuring recent HIV infections from routine surveillance systems could allow timely and granular monitoring of HIV incidence patterns. We evaluated the relationship of two recent infection indicators with alternative denominators to true incidence patterns. METHODS We used a mathematical model of HIV testing behaviours, calibrated to population-based surveys and HIV testing services programme data, to estimate the number of recent infections diagnosed annually from 2010 to 2019 in Côte d'Ivoire, Malawi, and Mozambique. We compared two different denominators to interpret recency data: those at risk of HIV acquisition (HIV-negative tests and recent infections) and all people testing HIV positive. Sex and age-specific longitudinal trends in both interpretations were then compared with modelled trends in HIV incidence, testing efforts and HIV positivity among HIV testing services clients. RESULTS Over 2010-2019, the annual proportion of the eligible population tested increased in all countries, while positivity decreased. The proportion of recent infections among those at risk of HIV acquisition decreased, similar to declines in HIV incidence among adults (≥15 years old). Conversely, the proportion of recent infections among HIV-positive tests increased. The female-to-male ratio of the proportion testing recent among those at risk was closer to 1 than the true incidence sex ratio. CONCLUSION The proportion of recent infections among those at risk of HIV acquisition is more indicative of HIV incidence than the proportion among HIV-positive tests. However, interpreting the observed patterns as surrogate measures for incidence patterns may still be confounded by different HIV testing rates between population groups or over time.
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Affiliation(s)
- Arnaud Godin
- Department of Epidemiology, Biostatistics, and Occupational Health, School of Population and Global Health, Faculty of Medicine, McGill University, Montréal, Quebec, Canada
| | - Jeffrey W. Eaton
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
| | - Katia Giguère
- Centre de recherche du CHUM, Université de Montréal, Montréal, Quebec, Canada
| | | | - Leigh F. Johnson
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
| | - Andreas Jahn
- Department for HIV and AIDS, Ministry of Health and Population, Lilongwe, Malawi
- I-TECH, Department of Global Health, University of Washington, Seattle, Washington, USA
| | | | - Eboi Ehui
- Programme National de lutte contre le SIDA, Abidjan, Côte d’Ivoire
| | - Mathieu Maheu-Giroux
- Department of Epidemiology, Biostatistics, and Occupational Health, School of Population and Global Health, Faculty of Medicine, McGill University, Montréal, Quebec, Canada
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Dávila‐Conn V, García‐Morales C, Matías‐Florentino M, López‐Ortiz E, Paz‐Juárez HE, Beristain‐Barreda Á, Cárdenas‐Sandoval M, Tapia‐Trejo D, López‐Sánchez DM, Becerril‐Rodríguez M, García‐Esparza P, Macías‐González I, Iracheta‐Hernández P, Weaver S, Wertheim JO, Reyes‐Terán G, González‐Rodríguez A, Ávila‐Ríos S. Characteristics and growth of the genetic HIV transmission network of Mexico City during 2020. J Int AIDS Soc 2021; 24:e25836. [PMID: 34762774 PMCID: PMC8583431 DOI: 10.1002/jia2.25836] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 10/13/2021] [Indexed: 12/04/2022] Open
Abstract
INTRODUCTION Molecular surveillance systems could provide public health benefits to focus strategies to improve the HIV care continuum. Here, we infer the HIV genetic network of Mexico City in 2020, and identify actively growing clusters that could represent relevant targets for intervention. METHODS All new diagnoses, referrals from other institutions, as well as persons returning to care, enrolling at the largest HIV clinic in Mexico City were invited to participate in the study. The network was inferred from HIV pol sequences, using pairwise genetic distance methods, with a locally hosted, secure version of the HIV-TRACE tool: Seguro HIV-TRACE. Socio-demographic, clinical and behavioural metadata were overlaid across the network to design focused prevention interventions. RESULTS A total of 3168 HIV sequences from unique individuals were included. One thousand and one-hundred and fifty (36%) sequences formed 1361 links within 386 transmission clusters in the network. Cluster size varied from 2 to 14 (63% were dyads). After adjustment for covariates, lower age (adjusted odds ratio [aOR]: 0.37, p<0.001; >34 vs. <24 years), being a man who has sex with men (MSM) (aOR: 2.47, p = 0.004; MSM vs. cisgender women), having higher viral load (aOR: 1.28, p<0.001) and higher CD4+ T cell count (aOR: 1.80, p<0.001; ≥500 vs. <200 cells/mm3 ) remained associated with higher odds of clustering. Compared to MSM, cisgender women and heterosexual men had significantly lower education (none or any elementary: 59.1% and 54.2% vs. 16.6%, p<0.001) and socio-economic status (low income: 36.4% and 29.0% vs. 18.6%, p = 0.03) than MSM. We identified 10 (2.6%) clusters with constant growth, for prioritized intervention, that included intersecting sexual risk groups, highly connected nodes and bridge nodes between possible sub-clusters with high growth potential. CONCLUSIONS HIV transmission in Mexico City is strongly driven by young MSM with higher education level and recent infection. Nevertheless, leveraging network inference, we identified actively growing clusters that could be prioritized for focused intervention with demographic and risk characteristics that do not necessarily reflect the ones observed in the overall clustering population. Further studies evaluating different models to predict growing clusters are warranted. Focused interventions will have to consider structural and risk disparities between the MSM and the heterosexual populations.
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Affiliation(s)
- Vanessa Dávila‐Conn
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | - Claudia García‐Morales
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | | | - Eduardo López‐Ortiz
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | - Héctor E. Paz‐Juárez
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | - Ángeles Beristain‐Barreda
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | | | - Daniela Tapia‐Trejo
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | - Dulce M. López‐Sánchez
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | - Manuel Becerril‐Rodríguez
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | - Pedro García‐Esparza
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
| | | | | | - Steven Weaver
- Institute for Genomics and Evolutionary MedicineTemple UniversityPhiladelphiaPennsylvaniaUSA
| | - Joel O. Wertheim
- Department of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Gustavo Reyes‐Terán
- Coordinating Commission of the National Institutes of Health and High Specialty HospitalsMexico CityMexico
| | | | - Santiago Ávila‐Ríos
- Centre for Research in Infectious DiseasesNational Institute of Respiratory DiseasesMexico CityMexico
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Lyss SB, Zhang T, Oster AM. Brief Report: HIV Diagnoses Among Persons Who Inject Drugs by the Urban-Rural Classification-United States, 2010-2018. J Acquir Immune Defic Syndr 2021; 88:238-242. [PMID: 34310448 DOI: 10.1097/qai.0000000000002769] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 07/13/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND After many years of decline, HIV diagnoses attributed to injection drug use in the United States increased in 2015, the year of a large outbreak among persons who inject drugs (PWIDs) in Indiana. We assessed trends in HIV diagnoses among PWID across the urban-rural continuum. METHODS We conducted national and county-level analyses of diagnoses among persons aged ≥13 years with HIV attributed to injection drug use only and reported to the National HIV Surveillance System through December 2019; county of residence at diagnosis was classified according to the Centers for Disease Control and Prevention's National Center for Health Statistics Urban-Rural Classification Scheme. National trends for diagnoses occurring during 2010-2014 and 2014-2018 were assessed by the estimated annual percentage change (EAPC). Counties were considered to have an "alert" (ie, an increase above baseline) if the number of 2019 diagnoses among PWID was >2 SDs and >2 diagnoses greater than the mean of annual diagnoses during 2016-2018. RESULTS Nationally, HIV diagnoses among PWID declined 33% during 2010-2014 from 3314 to 2220 (EAPC: -9.7%; 95% confidence interval: -10.8 to -8.6); EAPCs declined significantly in 5 of 6 urban-rural strata. During 2014-2018, diagnoses increased 11% to 2465 (EAPC: 2.4%; 95% confidence interval: 1.1 to 3.8); EAPCs were >0 for all urban-rural strata, although most were nonsignificant. Alerts were detected in 23 counties, representing 5 urban-rural strata. CONCLUSIONS Vigilance is needed for increases in HIV among PWID in counties across the urban-rural continuum, particularly those with indicators of increased drug use. Prompt detection, investigation, and response are critical for stemming transmission.
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Affiliation(s)
- Sheryl B Lyss
- Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA
- U.S. Public Health Service, Atlanta, GA; and
| | - Tianchi Zhang
- ICF, Atlanta, GA. Tianchi Zhang is now with Georgia State University
| | - Alexandra M Oster
- Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA
- U.S. Public Health Service, Atlanta, GA; and
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Desai AN, Conyngham SC, Mashas A, Smith CR, Casademont IZ, Brown BA, Kim MM, Terrell C, Brady KA. Interdisciplinary HIV Sentinel Case Review: Identifying Practices to Prevent Outbreaks in Philadelphia. Am J Prev Med 2021; 61:S151-S159. [PMID: 34686284 DOI: 10.1016/j.amepre.2021.05.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 05/14/2021] [Accepted: 05/19/2021] [Indexed: 10/20/2022]
Abstract
INTRODUCTION The Ending the HIV Epidemic in the U.S. initiative considers cluster and outbreak response essential. This article describes the design, implementation, and early findings of a Philadelphia-based project to systematically assess sentinel cases among priority populations for improving public health infrastructure and preventing future outbreaks. METHODS Sentinel HIV cases (i.e., early-stage or acute infection or molecular cluster cases) were identified among priority populations (Black and Hispanic/Latino men who have sex with men, youth aged 18-24 years, and transgender people who have sex with men). Chart abstraction and structured interview data were reviewed to determine themes and service gaps and to identify, prioritize, and implement recommendations. Interdisciplinary review teams included individuals with lived experience, frontline staff, and local agency leadership. RESULTS Data were collected during July 2019-December 2020 and analyzed for 53 of 126 sentinel cases of HIV diagnosed since July 1, 2018. The majority were men who have sex with men (79.3%), those aged 18-24 years (67.9%), and non-Hispanic Black (67.9%). More than half received sexually transmitted infection and HIV testing ≤3 years preceding HIV diagnosis (56.6% and 54.7%, respectively), had a healthcare visit within 12 months before diagnosis (64.2%), and had no evidence of pre-exposure prophylaxis awareness (58.5%). Project recommendations effectuated actions to improve pre-exposure prophylaxis provision, integrate sexually transmitted infection and HIV testing, and educate primary care providers. CONCLUSIONS HIV sentinel case review is a model for health departments to rapidly respond to recent transmission, identify missed HIV prevention opportunities, strengthen community partnerships, and implement programmatic and policy changes. Such efforts may prevent outbreaks and inform longer-term strategies.
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Affiliation(s)
- Akash N Desai
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania.
| | | | - Antonios Mashas
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania
| | | | | | - Bikim A Brown
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania
| | - Melissa M Kim
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania
| | - Coleman Terrell
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania
| | - Kathleen A Brady
- Philadelphia Department of Public Health, Philadelphia, Pennsylvania
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McClung RP, Atkins AD, Kilkenny M, Bernstein KT, Willenburg KS, Weimer M, Robilotto S, Panneer N, Thomasson E, Adkins E, Lyss SB, Balleydier S, Edwards A, Chen M, Wilson S, Handanagic S, Hogan V, Watson M, Eubank S, Wright C, Thompson A, DiNenno E, Fanfair RN, Ridpath A, Oster AM. Response to a Large HIV Outbreak, Cabell County, West Virginia, 2018-2019. Am J Prev Med 2021; 61:S143-S150. [PMID: 34686283 DOI: 10.1016/j.amepre.2021.05.039] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/04/2021] [Accepted: 05/06/2021] [Indexed: 11/19/2022]
Abstract
INTRODUCTION In January 2019, the West Virginia Bureau for Public Health detected increased HIV diagnoses among people who inject drugs in Cabell County. Responding to HIV clusters and outbreaks is 1 of the 4 pillars of the Ending the HIV Epidemic in the U.S. initiative and requires activities from the Diagnose, Treat, and Prevent pillars. This article describes the design and implementation of a comprehensive response, featuring interventions from all pillars. METHODS This study used West Virginia Bureau for Public Health data to identify HIV diagnoses during January 1, 2018-October 9, 2019 among (1) people who inject drugs linked to Cabell County, (2) their sex or injecting partners, or (3) others with an HIV sequence linked to Cabell County people who inject drugs. Surveillance data, including HIV-1 polymerase sequences, were analyzed to estimate the transmission rate and timing of infections using molecular clock phylogenetic analysis. Federal, state, and local partners designed and implemented a comprehensive response during January 2019-October 2019. RESULTS Of 82 people identified in the outbreak, most were male (60%), were White (91%), and reported unstable housing (80%). In a large molecular cluster containing 56 of 60 (93%) available sequences, 93% of inferred transmissions occurred after January 1, 2018. HIV testing, HIV pre-exposure prophylaxis, and syringe services were rapidly expanded, leading to improved linkage to HIV care and viral suppression. CONCLUSIONS Evidence of rapid transmission in this outbreak galvanized robust collaboration among federal, state, and local partners, leading to critical improvements in HIV prevention and care services. HIV outbreak response requires increased coordination and creativity to improve service delivery to people affected by rapid HIV transmission.
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Affiliation(s)
- R Paul McClung
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia; U.S. Public Health Service Commissioned Corps, Atlanta, Georgia.
| | - Amy D Atkins
- West Virginia Department of Health & Human Resources, West Virginia Bureau for Public Health, Charleston, West Virginia
| | | | - Kyle T Bernstein
- Division of STD Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Kara S Willenburg
- Joan C. Edwards School of Medicine, Marshall University, Huntington, West Virginia
| | | | - Susan Robilotto
- HIV/AIDS Bureau, Health Resources & Services Administration, Rockville, Maryland
| | - Nivedha Panneer
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Erica Thomasson
- West Virginia Department of Health & Human Resources, West Virginia Bureau for Public Health, Charleston, West Virginia; Division of State and Local Readiness, Center for Preparedness and Response, Centers for Disease Control and Prevention, Atlanta, Georgia
| | | | - Sheryl B Lyss
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia; U.S. Public Health Service Commissioned Corps, Atlanta, Georgia
| | - Shawn Balleydier
- West Virginia Department of Health & Human Resources, West Virginia Bureau for Public Health, Charleston, West Virginia
| | - Anita Edwards
- U.S. Public Health Service Commissioned Corps, Atlanta, Georgia; HIV/AIDS Bureau, Health Resources & Services Administration, Rockville, Maryland
| | - Mi Chen
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Suzanne Wilson
- West Virginia Department of Health & Human Resources, West Virginia Bureau for Public Health, Charleston, West Virginia
| | - Senad Handanagic
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Vicki Hogan
- West Virginia Department of Health & Human Resources, West Virginia Bureau for Public Health, Charleston, West Virginia
| | - Meg Watson
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Scott Eubank
- West Virginia Department of Health & Human Resources, West Virginia Bureau for Public Health, Charleston, West Virginia
| | - Carolyn Wright
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Antoine Thompson
- Division of STD Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Elizabeth DiNenno
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Robyn Neblett Fanfair
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia; U.S. Public Health Service Commissioned Corps, Atlanta, Georgia
| | - Alison Ridpath
- Division of STD Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Alexandra M Oster
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia; U.S. Public Health Service Commissioned Corps, Atlanta, Georgia
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Oster AM, Lyss SB, McClung RP, Watson M, Panneer N, Hernandez AL, Buchacz K, Robilotto SE, Curran KG, Hassan R, Ocfemia MCB, Linley L, Perez SM, Phillip SA, France AM. HIV Cluster and Outbreak Detection and Response: The Science and Experience. Am J Prev Med 2021; 61:S130-S142. [PMID: 34686282 DOI: 10.1016/j.amepre.2021.05.029] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 04/28/2021] [Accepted: 05/06/2021] [Indexed: 11/30/2022]
Abstract
The Respond pillar of the Ending the HIV Epidemic in the U.S. initiative, which consists of activities also known as cluster and outbreak detection and response, offers a framework to guide tailored implementation of proven HIV prevention strategies where transmission is occurring most rapidly. Cluster and outbreak response involves understanding the networks in which rapid transmission is occurring; linking people in the network to essential services; and identifying and addressing gaps in programs and services such as testing, HIV and other medical care, pre-exposure prophylaxis, and syringe services programs. This article reviews the experience gained through 30 HIV cluster and outbreak responses in North America during 2000-2020 to describe approaches for implementing these core response strategies. Numerous jurisdictions that have implemented these response strategies have demonstrated success in improving outcomes related to HIV care and viral suppression, testing, use of prevention services, and reductions in transmission or new diagnoses. Efforts to address important gaps in service delivery revealed by cluster and outbreak detection and response can strengthen prevention efforts broadly through multidisciplinary, multisector collaboration. In this way, the Respond pillar embodies the collaborative, data-guided approach that is critical to the overall success of the Ending the HIV Epidemic in the U.S. initiative.
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Affiliation(s)
- Alexandra M Oster
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia; U.S. Public Health Service, Atlanta, Georgia.
| | - Sheryl B Lyss
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia; U.S. Public Health Service, Atlanta, Georgia
| | - R Paul McClung
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia; U.S. Public Health Service, Atlanta, Georgia
| | - Meg Watson
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Nivedha Panneer
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Angela L Hernandez
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Kate Buchacz
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Susan E Robilotto
- Division of State HIV/AIDS Programs, HIV/AIDS Bureau, Health Resources and Services Administration, Rockville, Maryland
| | - Kathryn G Curran
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Rashida Hassan
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - M Cheryl Bañez Ocfemia
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Laurie Linley
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Stephen M Perez
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia; U.S. Public Health Service, Atlanta, Georgia
| | - Stanley A Phillip
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Anne Marie France
- Division of HIV Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention, Atlanta, Georgia; U.S. Public Health Service, Atlanta, Georgia
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Mazrouee S, Little SJ, Wertheim JO. Incorporating metadata in HIV transmission network reconstruction: A machine learning feasibility assessment. PLoS Comput Biol 2021; 17:e1009336. [PMID: 34550966 PMCID: PMC8457453 DOI: 10.1371/journal.pcbi.1009336] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 08/09/2021] [Indexed: 12/30/2022] Open
Abstract
HIV molecular epidemiology estimates the transmission patterns from clustering genetically similar viruses. The process involves connecting genetically similar genotyped viral sequences in the network implying epidemiological transmissions. This technique relies on genotype data which is collected only from HIV diagnosed and in-care populations and leaves many persons with HIV (PWH) who have no access to consistent care out of the tracking process. We use machine learning algorithms to learn the non-linear correlation patterns between patient metadata and transmissions between HIV-positive cases. This enables us to expand the transmission network reconstruction beyond the molecular network. We employed multiple commonly used supervised classification algorithms to analyze the San Diego Primary Infection Resource Consortium (PIRC) cohort dataset, consisting of genotypes and nearly 80 additional non-genetic features. First, we trained classification models to determine genetically unrelated individuals from related ones. Our results show that random forest and decision tree achieved over 80% in accuracy, precision, recall, and F1-score by only using a subset of meta-features including age, birth sex, sexual orientation, race, transmission category, estimated date of infection, and first viral load date besides genetic data. Additionally, both algorithms achieved approximately 80% sensitivity and specificity. The Area Under Curve (AUC) is reported 97% and 94% for random forest and decision tree classifiers respectively. Next, we extended the models to identify clusters of similar viral sequences. Support vector machine demonstrated one order of magnitude improvement in accuracy of assigning the sequences to the correct cluster compared to dummy uniform random classifier. These results confirm that metadata carries important information about the dynamics of HIV transmission as embedded in transmission clusters. Hence, novel computational approaches are needed to apply the non-trivial knowledge collected from inter-individual genetic information to metadata from PWH in order to expand the estimated transmissions. We note that feature extraction alone will not be effective in identifying patterns of transmission and will result in random clustering of the data, but its utilization in conjunction with genetic data and the right algorithm can contribute to the expansion of the reconstructed network beyond individuals with genetic data.
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Affiliation(s)
- Sepideh Mazrouee
- Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California San Diego, San Diego, California, United States
| | - Susan J. Little
- Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California San Diego, San Diego, California, United States
| | - Joel O. Wertheim
- Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California San Diego, San Diego, California, United States
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Wilbourn B, Saafir-Callaway B, Jair K, Wertheim JO, Laeyendeker O, Jordan JA, Kharfen M, Castel A. Characterization of HIV Risk Behaviors and Clusters Using HIV-Transmission Cluster Engine Among a Cohort of Persons Living with HIV in Washington, DC. AIDS Res Hum Retroviruses 2021; 37:706-715. [PMID: 34157853 PMCID: PMC8501467 DOI: 10.1089/aid.2021.0031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Molecular epidemiology (ME) is one tool used to end the HIV epidemic in the United States. We combined clinical and behavioral data with HIV sequence data to identify any overlap in clusters generated from different sequence datasets; to characterize HIV transmission clusters; and to identify correlates of clustering among people living with HIV (PLWH) in Washington, District of Columbia (DC). First, Sanger sequences from DC Cohort participants, a longitudinal HIV study, were combined with next-generation sequences (NGS) from participants in a ME substudy to identify clusters. Next, demographic and self-reported behavioral data from ME substudy participants were used to identify risks of secondary transmission. Finally, we combined NGS from ME substudy participants with Sanger sequences in the DC Molecular HIV Surveillance database to identify clusters. Cluster analyses used HIV-Transmission Cluster Engine to identify linked pairs of sequences (defined as distance ≤1.5%). Twenty-eight clusters of ≥3 sequences (size range: 3-12) representing 108 (3%) participants were identified. None of the five largest clusters (size range: 5-12) included newly diagnosed PLWH. Thirty-four percent of ME substudy participants (n = 213) reported condomless sex during their last sexual encounter and 14% reported a Syphilis diagnosis in the past year. Seven transmission clusters (size range: 2-19) were identified in the final analysis, each containing at least one ME substudy participant. Substudy participants in clusters from the third analysis were present in clusters from the first analysis. Combining HIV sequence, clinical and behavioral data provided insights into HIV transmission that may not be identified using traditional epidemiological methods alone. Specifically, the sexual risk behaviors and STI diagnoses reported in the substudy survey may not have been disclosed during Partner Services activities and the survey data complemented clinical data to fully characterize transmission clusters. These findings can be used to enhance local efforts to interrupt transmission and avert new infections.
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Affiliation(s)
- Brittany Wilbourn
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia, USA
| | - Brittani Saafir-Callaway
- HIV/AIDS, Hepatitis, STD and TB Administration, DC Health, Washington, District of Columbia, USA
| | - Kamwing Jair
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia, USA
| | - Joel O. Wertheim
- Department of Medicine, University of California San Diego, LA Jolla, California, USA
| | - Oliver Laeyendeker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, Maryland, USA
| | - Jeanne A. Jordan
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia, USA
| | - Michael Kharfen
- HIV/AIDS, Hepatitis, STD and TB Administration, DC Health, Washington, District of Columbia, USA
| | - Amanda Castel
- Department of Epidemiology, Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia, USA
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