ArticleViruses2022
Characterization of HIV-1 Transmission Clusters Inferred from the Brazilian Nationwide Genotyping Service Database.
Article in Viruses, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Nationwide Molecular Epidemiology of HIV-1 in Uruguay (2007-2021): Lineage Diversity, BF1 Recombinant Complexity and Epidemiological Patterns.Journal of the International AIDS Society · 2026Article
- South-to-Southeast Expansion of HIV-1 Subtype C in Brazil.Journal of medical virology · 2025Article
- Dynamics of clustering rates in the Rhode Island HIV-1 epidemic.AIDS (London, England) · 2025Article
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5 authors.
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Abstract
The study of HIV-1 transmission networks inferred from viral genetic data can be used to clarify important factors about the dynamics of HIV-1 transmission, such as network growth rate and demographic composition. In Brazil, HIV transmission has been stable since the early 2000s and the study of transmission clusters can provide valuable data to understand the drivers of virus spread. In this work, we analyzed a nation-wide database of approximately 53,000 HIV-1 nucleotide pol sequences sampled from genotyped patients from 2008-2017. Phylogenetic trees were reconstructed for the HIV-1 subtypes B, C and F1 in Brazil and transmission clusters were inferred by applying genetic distances thresholds of 1.5%, 3.0% and 4.5%, as well as high (>0.9) cluster statistical support. An odds ratio test revealed that young men (15-24 years) and individuals with more years of education presented higher odds to cluster. The assortativity coefficient revealed that individuals with similar demographic features tended to cluster together, with emphasis on features, such as place of residence and age. We also observed that assortativity weakens as the genetic distance threshold increases. Our results indicate that the phylogenetic clusters identified here are likely representative of the contact networks that shape HIV transmission, and this is a valuable tool even in sites with low sampling density, such as Brazil.
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