ArticleThe Journal of infectious diseases2020
Human Immunodeficiency Virus Type 1 Phylodynamics to Detect and Characterize Active Transmission Clusters in North Carolina.
Article in The Journal of infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Impact of Disclosing to Patients the Use of Antiretroviral Resistance Testing Results for Molecular HIV Surveillance: A Randomized Experiment in 2 National Surveys.JMIR public health and surveillance · 2025Article
- Dynamics of clustering rates in the Rhode Island HIV-1 epidemic.AIDS (London, England) · 2025Article
- Predictors of HIV Molecular Cluster Membership and Implications for Partner Services.AIDS research and human retroviruses · 2023Article
- Molecular Epidemiology of HIV-1 Subtype B Infection across Florida Reveals Few Large Superclusters with Metropolitan Origin.Microbiology spectrum · 2022Article
- Optimized phylogenetic clustering of HIV-1 sequence data for public health applications.PLoS computational biology · 2022Article
- Article
- Statewide Longitudinal Trends in Transmitted HIV-1 Drug Resistance in Rhode Island, USA.Open forum infectious diseases · 2022Article
- Exploring the Evolutionary History and Phylodynamics of Human Immunodeficiency Virus Type 1 Outbreak From Unnao, India Using Phylogenetic Approach.Frontiers in microbiology · 2022Article
- HIV Cluster and Outbreak Detection and Response: The Science and Experience.American journal of preventive medicine · 2021Review
- Independent epidemic patterns of HIV-1 CRF01_AE lineages driven by mobile population in Shenzhen, an immigrant city of China.Virus evolution · 2021Article
- Interplay Between Geography and HIV Transmission Clusters in Los Angeles County.Open forum infectious diseases · 2021Article
- The Relationship Between the Human Immunodeficiency Virus-1 Transmission Network and the HIV Care Continuum in Los Angeles County.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2020Article
- Incident infection in high-priority HIV molecular transmission clusters in the United States.AIDS (London, England) · 2020Article
- Molecular network-based intervention brings us closer to ending the HIV pandemic.Frontiers of medicine · 2020Review
- HIV Outbreak Control With Effective Access to Care and Harm Reduction in North Carolina, 2017-2018.American journal of public health · 2020Article
- Dynamics of HIV-1 Molecular Networks Reveal Effective Control of Large Transmission Clusters in an Area Affected by an Epidemic of Multiple HIV Subtypes.Frontiers in microbiology · 2020Article
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Abstract
backgroundHuman immunodeficiency virus type 1 (HIV-1) phylodynamics can be used to monitor epidemic trends and help target prevention through identification and characterization of transmission clusters.
methodsWe analyzed HIV-1 pol sequences sampled in North Carolina from 1997 to 2014. Putative clusters were identified using maximum-likelihood trees and dated using Bayesian Markov Chain Monte Carlo inference. Active clusters were defined as clusters including internal nodes from 2009 to 2014. Effective reproductive numbers (Re) were estimated using birth-death models for large clusters that expanded ≥2-fold from 2009 to 2014.
resultsOf 14 921 persons, 7508 (50%) sequences were identified in 2264 clusters. Only 288 (13%) clusters were active from 2009 to 2014; 37 were large (10-36 members). Compared to smaller clusters, large clusters were increasingly populated by men and younger persons; however, nearly 60% included ≥1 women. Clusters with ≥3 members demonstrated assortative mixing by sex, age, and sample region. Of 15 large clusters with ≥2-fold expansion, nearly all had Re approximately 1 by 2014.
conclusionsPhylodynamics revealed transmission cluster expansion in this densely sampled region and allowed estimates of Re to monitor active clusters, showing the propensity for steady, onward propagation. Associations with clustering and cluster characteristics vary by cluster size. Harnessing sequence-derived epidemiologic parameters within routine surveillance could allow refined monitoring of local subepidemics.
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