title: Contribution of Epidemiological Predictors in Unraveling the Phylogeographic History of HIV-1 Subtype C in Brazil.
abstract: The phylogeographic history of the Brazilian HIV-1 subtype C (HIV-1C) epidemic is still unclear. Previous studies have mainly focused on the capital cities of Brazilian federal states, and the fact that HIV-1C infections increase at a higher rate than subtype B infections in Brazil calls for a better understanding of the process of spatial spread. A comprehensive sequence data set sampled across 22 Brazilian locations was assembled and analyzed. A Bayesian phylogeographic generalized linear model approach was used to reconstruct the spatiotemporal history of HIV-1C in Brazil, considering several potential explanatory predictors of the viral diffusion process. Analyses were performed on several subsampled data sets in order to mitigate potential sample biases. We reveal a central role for the city of Porto Alegre, the capital of the southernmost state, in the Brazilian HIV-1C epidemic (HIV-1C_BR), and the northward expansion of HIV-1C_BR could be linked to source populations with higher HIV-1 burdens and larger proportions of HIV-1C infections. The results presented here bring new insights to the continuing discussion about the HIV-1C epidemic in Brazil and raise an alternative hypothesis for its spatiotemporal history. The current work also highlights how sampling bias can confound phylogeographic analyses and demonstrates the importance of incorporating external information to protect against this.
  
  
  OBJECTIVE
  Subtype C is responsible for the largest HIV infection burden worldwide, but our understanding of its transmission dynamics remains incomplete. Brazil witnessed a relatively recent introduction of HIV-1C compared to HIV-1B, but it swiftly spread throughout the south, where it now circulates as the dominant variant. The northward spread has been comparatively slow, and HIV-1B still prevails in that region. While epidemiological data and viral genetic analyses have both independently shed light on the dynamics of spread in isolation, their combination has not yet been explored. Here, we complement publically available sequences and new genetic data from 13 cities with epidemiological data to reconstruct the history of HIV-1C spread in Brazil. The combined approach results in more robust reconstructions and can protect against sampling bias. We found evidence for an alternative view of the HIV-1C spatiotemporal history in Brazil that, contrary to previous explanations, integrates seamlessly with other observational data.
authors.affiliation: Laboratório de Imunologia Aplicada, Departamento de Microbiologia, Imunologia e Parasitologia, Universidade Federal de Santa Catarina, Florianópolis, SC, Brazil Centro de Desenvolvimento Científico e Tecnológico, Fundação Estadual de Produção e Pesquisa em Saúde, Porto Alegre, RS, Brazil akograf@gmail.com.
authors.forename: Tiago
authors.initials: T
authors.lastname: Gräf
authors.affiliation: Department of Microbiology and Immunology, Rega Institute, KU Leuven-University of Leuven, Leuven, Belgium.
authors.forename: Bram
authors.initials: B
authors.lastname: Vrancken
authors.affiliation: Centro de Desenvolvimento Científico e Tecnológico, Fundação Estadual de Produção e Pesquisa em Saúde, Porto Alegre, RS, Brazil Departamento de Ciências da Saúde, Uniritter Laureate International Universities, Porto Alegre, RS, Brazil Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
authors.forename: Dennis
authors.initials: D
authors.lastname: Maletich Junqueira
authors.affiliation: Centro de Desenvolvimento Científico e Tecnológico, Fundação Estadual de Produção e Pesquisa em Saúde, Porto Alegre, RS, Brazil Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
authors.forename: Rúbia Marília
authors.initials: RM
authors.lastname: de Medeiros
authors.affiliation: Departments of Biomathematics and Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, California, USA Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, California, USA.
authors.forename: Marc A
authors.initials: MA
authors.lastname: Suchard
authors.affiliation: Department of Microbiology and Immunology, Rega Institute, KU Leuven-University of Leuven, Leuven, Belgium.
authors.forename: Philippe
authors.initials: P
authors.lastname: Lemey
authors.affiliation: Centro de Desenvolvimento Científico e Tecnológico, Fundação Estadual de Produção e Pesquisa em Saúde, Porto Alegre, RS, Brazil Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
authors.forename: Sabrina
authors.initials: S
authors.lastname: Esteves de Matos Almeida
authors.affiliation: Laboratório de Imunologia Aplicada, Departamento de Microbiologia, Imunologia e Parasitologia, Universidade Federal de Santa Catarina, Florianópolis, SC, Brazil.
authors.forename: Aguinaldo Roberto
authors.initials: AR
authors.lastname: Pinto
mesh_terms: D001938:Brazil / Q000453:epidemiology; D005260:Female; D015658:HIV Infections / Q000453:epidemiology* / Q000235:genetics*; D015497:HIV-1 / Q000235:genetics*; D006801:Humans; D008297:Male; D010802:Phylogeny; D058974:Phylogeography