ArticleThe Journal of infectious diseases2018
Growth of HIV-1 Molecular Transmission Clusters in New York City.
Article in The Journal of infectious diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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Who cites it
59 citing papers in PubMed.
- From giant components to communities: community-level insights for prioritizing interventions within large clusters of HIV-1 transmission networks.Infectious Disease Modelling · 2027Article
- HIV Transmission Dynamics in Greater Mexico City are Shaped by Dense Spatial Mixing.Research square · 2026Article
- HIV Transmission Dynamics in Greater Mexico City are Shaped by Dense Spatial Mixing.medRxiv : the preprint server for health sciences · 2026Article
- Article
- HIV molecular network in Mexico City (2021-2022): Understanding transmission dynamics through the role of newly diagnosed cases.HIV medicine · 2025Article
- Sequencing HIV Diagnostic Samples to Detect Genetic Clusters and Assess Sequence Coverage Gaps.Open forum infectious diseases · 2025Article
- Transmission dynamics of the 2022 mpox epidemic in New York City.Nature medicine · 2025Article
- Dynamics of clustering rates in the Rhode Island HIV-1 epidemic.AIDS (London, England) · 2025Article
- Molecular transmission network characteristics and high-risk transmission analysis of newly reported HIV-1 subjects in Nantong, China.Frontiers in immunology · 2025Article
- Molecular transmission network analysis of newly diagnosed HIV-1 infections in Ningbo from 2018-2022.Frontiers in microbiology · 2025Article
- Rapid circulation of HIV-1 CRF85_BC in Southwest China: its geographic origins and molecular transmission networks analysis.Frontiers in cellular and infection microbiology · 2025Article
- Prospective Evaluation of Routine Statewide Integration of Molecular Epidemiology and Contact Tracing to Disrupt Human Immunodeficiency Virus Transmission.Open forum infectious diseases · 2024Article
- Genomic epidemiology reveals 2022 mpox epidemic in New York City governed by heavy-tailed sexual contact networks.medRxiv : the preprint server for health sciences · 2024Article
- Exploring Dynamic Changes in HIV-1 Molecular Transmission Networks and Key Influencing Factors: Cross-Sectional Study.JMIR public health and surveillance · 2024Article
- DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction.PLoS computational biology · 2024Article
- HIV transmission and associated factors under the scale-up of HIV antiretroviral therapy: a population-based longitudinal molecular network study.Virology journal · 2023Article
- Article
- Modeling homophily in dynamic networks with application to HIV molecular surveillance.BMC infectious diseases · 2023Article
- Article
- The characteristics of HIV-1 subtype B on phylogenetic dynamic and molecular transmission network in Fuyang City, China, 2011 to 2019.Frontiers in public health · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Background: HIV-1 genetic sequences can be used to infer viral transmission history and dynamics. Throughout the United States, HIV-1 sequences from drug resistance testing are reported to local public health departments. Methods: We investigated whether inferred HIV transmission network dynamics can identify individuals and clusters of individuals most likely to give rise to future HIV cases in a surveillance setting. We used HIV-TRACE, a genetic distance-based clustering tool, to infer molecular transmission clusters from HIV-1 pro/RT sequences from 65736 people in the New York City surveillance registry. Logistic and LASSO regression analyses were used to identify correlates of clustering and cluster growth, respectively. We performed retrospective transmission network analyses to evaluate individual- and cluster-level prioritization schemes for identifying parts of the network most likely to give rise to new cases in the subsequent year. Results: Individual-level prioritization schemes predicted network growth better than random targeting. Across the 3600 inferred molecular transmission clusters, previous growth dynamics were superior predictors of future transmission cluster growth compared to individual-level prediction schemes. Cluster-level prioritization schemes considering previous cluster growth relative to cluster size further improved network growth predictions. Conclusions: Prevention efforts based on HIV molecular epidemiology may improve public health outcomes in a US surveillance setting.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.