Cargando…
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...
Autores principales: | , , , , , |
---|---|
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 |
_version_ | 1783330287541813248 |
---|---|
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. |
format | Online Article Text |
id | pubmed-5993807 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT mirdaiana inferringpopulationdynamicsofhiv1subtypecepidemicsineasternafricaandsouthernbrazilapplyingdifferentbayesianphylodynamicsapproaches AT graftiago inferringpopulationdynamicsofhiv1subtypecepidemicsineasternafricaandsouthernbrazilapplyingdifferentbayesianphylodynamicsapproaches AT estevesdematosalmeidasabrina inferringpopulationdynamicsofhiv1subtypecepidemicsineasternafricaandsouthernbrazilapplyingdifferentbayesianphylodynamicsapproaches AT pintoaguinaldoroberto inferringpopulationdynamicsofhiv1subtypecepidemicsineasternafricaandsouthernbrazilapplyingdifferentbayesianphylodynamicsapproaches AT delatorreedson inferringpopulationdynamicsofhiv1subtypecepidemicsineasternafricaandsouthernbrazilapplyingdifferentbayesianphylodynamicsapproaches AT bellogonzalo inferringpopulationdynamicsofhiv1subtypecepidemicsineasternafricaandsouthernbrazilapplyingdifferentbayesianphylodynamicsapproaches |