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Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches

The subtype C Eastern Africa clade (C(EA)), a particularly successful HIV-1 subtype C lineage, has seeded several sub-epidemics in Eastern African countries and Southern Brazil during the 1960s and 1970s. Here, we characterized the past population dynamics of the major C(EA) sub-epidemics in Eastern...

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Autores principales: Mir, Daiana, Gräf, Tiago, Esteves de Matos Almeida, Sabrina, Pinto, Aguinaldo Roberto, Delatorre, Edson, Bello, Gonzalo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993807/
https://www.ncbi.nlm.nih.gov/pubmed/29884822
http://dx.doi.org/10.1038/s41598-018-26824-4
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author Mir, Daiana
Gräf, Tiago
Esteves de Matos Almeida, Sabrina
Pinto, Aguinaldo Roberto
Delatorre, Edson
Bello, Gonzalo
author_facet Mir, Daiana
Gräf, Tiago
Esteves de Matos Almeida, Sabrina
Pinto, Aguinaldo Roberto
Delatorre, Edson
Bello, Gonzalo
author_sort Mir, Daiana
collection PubMed
description The subtype C Eastern Africa clade (C(EA)), a particularly successful HIV-1 subtype C lineage, has seeded several sub-epidemics in Eastern African countries and Southern Brazil during the 1960s and 1970s. Here, we characterized the past population dynamics of the major C(EA) sub-epidemics in Eastern Africa and Brazil by using Bayesian phylodynamic approaches based on coalescent and birth-death models. All phylodynamic models support similar epidemic dynamics and exponential growth rates until roughly the mid-1980s for all the C(EA) sub-epidemics. Divergent growth patterns, however, were supported afterwards. The Bayesian skygrid coalescent model (BSKG) and the birth-death skyline model (BDSKY) supported longer exponential growth phases than the Bayesian skyline coalescent model (BSKL). The BDSKY model uncovers patterns of a recent decline for the C(EA) sub-epidemics in Burundi/Rwanda and Tanzania (R(e) < 1) and a recent growth for Southern Brazil (R(e) > 1); whereas coalescent models infer an epidemic stabilization. To the contrary, the BSKG model captured a decline of Ethiopian C(EA) sub-epidemic between the mid-1990s and mid-2000s that was not uncovered by the BDSKY model. These results underscore that the joint use of different phylodynamic approaches may yield complementary insights into the past HIV population dynamics.
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spelling pubmed-59938072018-06-21 Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches Mir, Daiana Gräf, Tiago Esteves de Matos Almeida, Sabrina Pinto, Aguinaldo Roberto Delatorre, Edson Bello, Gonzalo Sci Rep Article The subtype C Eastern Africa clade (C(EA)), a particularly successful HIV-1 subtype C lineage, has seeded several sub-epidemics in Eastern African countries and Southern Brazil during the 1960s and 1970s. Here, we characterized the past population dynamics of the major C(EA) sub-epidemics in Eastern Africa and Brazil by using Bayesian phylodynamic approaches based on coalescent and birth-death models. All phylodynamic models support similar epidemic dynamics and exponential growth rates until roughly the mid-1980s for all the C(EA) sub-epidemics. Divergent growth patterns, however, were supported afterwards. The Bayesian skygrid coalescent model (BSKG) and the birth-death skyline model (BDSKY) supported longer exponential growth phases than the Bayesian skyline coalescent model (BSKL). The BDSKY model uncovers patterns of a recent decline for the C(EA) sub-epidemics in Burundi/Rwanda and Tanzania (R(e) < 1) and a recent growth for Southern Brazil (R(e) > 1); whereas coalescent models infer an epidemic stabilization. To the contrary, the BSKG model captured a decline of Ethiopian C(EA) sub-epidemic between the mid-1990s and mid-2000s that was not uncovered by the BDSKY model. These results underscore that the joint use of different phylodynamic approaches may yield complementary insights into the past HIV population dynamics. Nature Publishing Group UK 2018-06-08 /pmc/articles/PMC5993807/ /pubmed/29884822 http://dx.doi.org/10.1038/s41598-018-26824-4 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Mir, Daiana
Gräf, Tiago
Esteves de Matos Almeida, Sabrina
Pinto, Aguinaldo Roberto
Delatorre, Edson
Bello, Gonzalo
Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches
title Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches
title_full Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches
title_fullStr Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches
title_full_unstemmed Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches
title_short Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches
title_sort inferring population dynamics of hiv-1 subtype c epidemics in eastern africa and southern brazil applying different bayesian phylodynamics approaches
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993807/
https://www.ncbi.nlm.nih.gov/pubmed/29884822
http://dx.doi.org/10.1038/s41598-018-26824-4
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