Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches
Main Author: | |
---|---|
Publication Date: | 2018 |
Other Authors: | , , , , |
Format: | Article |
Language: | eng |
Source: | Repositório Institucional da FIOCRUZ (ARCA) |
DOI: | 10.1038/s41598-018-26824-4 |
Download full: | https://arca.fiocruz.br/handle/icict/29323 |
Summary: | Produção científica do Laboratório de Aids e Imunologia Molecular. |
id |
CRUZ_917950f01d7c1e6d879d7af6b10f64f5 |
---|---|
oai_identifier_str |
oai:arca.fiocruz.br:icict/29323 |
network_acronym_str |
CRUZ |
network_name_str |
Repositório Institucional da FIOCRUZ (ARCA) |
repository_id_str |
2135 |
spelling |
Mir, DaianaGräf, TiagoAlmeida, Sabrina Esteves de MatosPinto, Aguinaldo RobertoDelatorre, EdsonBello, Gonzalo2018-10-04T12:18:34Z2018-10-04T12:18:34Z2018MIR, Daiana et al. Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches. Scientific Reports, v. 8, n. 8778, p. 1-10, 8 June 2018.2045-2322https://arca.fiocruz.br/handle/icict/2932310.1038/s41598-018-26824-42045-2322Produção científica do Laboratório de Aids e Imunologia Molecular.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de AIDS e Imunologia Molecular. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Centro de Ciências da Saúde. Instituto de Biologia. Departamento de Genética. Rio de Janeiro, RJ, Brasil / University of KwaZulu-Natal. College of Health Sciences. KwaZulu-Natal Research Innovation and Sequencing Platform. Durban, South Africa.Fundação Estadual de Produção e Pesquisa em Saúde. Centro de Desenvolvimento Científico e Tecnológico. Porto Alegre, RS, Brasil / Universidade Federal do Rio Grande do Sul. Programa de Pós-Graduação em Genética e Biologia Molecular. Porto Alegre, RS, Brasil / Universidade Feevale. Instituto de Ciências da Saúde. Novo Hamburgo, RS, Brasil.Universidade Federal de Santa Catarina. Departamento de Microbiologia, Imunologia e Parasitologia. Laboratório de Imunologia Aplicada. Florianópolis, SC, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de AIDS e Imunologia Molecular. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de AIDS e Imunologia Molecular. Rio de Janeiro, RJ, Brasil.The subtype C Eastern Africa clade (CEA), 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 CEA 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 CEA 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 CEA sub-epidemics in Burundi/Rwanda and Tanzania (Re < 1) and a recent growth for Southern Brazil (Re > 1); whereas coalescent models infer an epidemic stabilization. To the contrary, the BSKG model captured a decline of Ethiopian CEA 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.engNature ResearchSubtipo C do HIV-1Abordagens filodinâmicas bayesianasSul do BrasilÁfrica OrientalDinâmicas populacionaisEpidemiasHIV-1 subtype CEastern AfricaSouthern BrazilBayesian phylodynamic approachesPopulation dynamicsEpidemics03 Saúde e Bem-EstarInferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approachesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZTHUMBNAILcapa_Daiana_Mir_etal_IOC_2018.jpegcapa_Daiana_Mir_etal_IOC_2018.jpegCapaimage/jpeg2543532https://arca.fiocruz.br/bitstreams/f84e69ea-6178-4aef-ab0a-9fc3e3a5df2d/download9acb3f015e11bd9485b9be4752535853MD54falseAnonymousREADedsondelatorre_gonzalobello_etal_IOC_2018.pdf.jpgedsondelatorre_gonzalobello_etal_IOC_2018.pdf.jpgGenerated Thumbnailimage/jpeg6669https://arca.fiocruz.br/bitstreams/0c5edc98-727d-406e-b250-02ef7aac004b/download24fcb844b97187cc0c5b312abdc0622aMD57falseAnonymousREADLICENSElicense.txtlicense.txttext/plain; charset=utf-82991https://arca.fiocruz.br/bitstreams/efb03901-8963-4e12-a148-9e11688f8149/download5a560609d32a3863062d77ff32785d58MD51falseAnonymousREADORIGINALedsondelatorre_gonzalobello_etal_IOC_2018.pdfedsondelatorre_gonzalobello_etal_IOC_2018.pdfapplication/pdf2469298https://arca.fiocruz.br/bitstreams/8fbc0673-d7da-453b-97aa-53d029baeba9/download698241db98456db2f54313282ec989adMD52trueAnonymousREADTEXTedsondelatorre_gonzalobello_etal_IOC_2018.pdf.txtedsondelatorre_gonzalobello_etal_IOC_2018.pdf.txtExtracted texttext/plain54120https://arca.fiocruz.br/bitstreams/04f66d89-9dd0-4e13-897b-7a82f85375c9/downloadb7e5c5d470bbde8e2e497666017a8459MD56falseAnonymousREADicict/293232025-07-30 01:16:58.965open.accessoai:arca.fiocruz.br:icict/29323https://arca.fiocruz.brRepositório InstitucionalPUBhttps://www.arca.fiocruz.br/oai/requestrepositorio.arca@fiocruz.bropendoar:21352025-07-30T04:16:58Repositório Institucional da FIOCRUZ (ARCA) - Fundação Oswaldo Cruz (FIOCRUZ)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 |
dc.title.none.fl_str_mv |
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 |
spellingShingle |
Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches Mir, Daiana Subtipo C do HIV-1 Abordagens filodinâmicas bayesianas Sul do Brasil África Oriental Dinâmicas populacionais Epidemias HIV-1 subtype C Eastern Africa Southern Brazil Bayesian phylodynamic approaches Population dynamics Epidemics 03 Saúde e Bem-Estar |
title_short |
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_sort |
Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches |
author |
Mir, Daiana |
author_facet |
Mir, Daiana Gräf, Tiago Almeida, Sabrina Esteves de Matos Pinto, Aguinaldo Roberto Delatorre, Edson Bello, Gonzalo |
author_role |
author |
author2 |
Gräf, Tiago Almeida, Sabrina Esteves de Matos Pinto, Aguinaldo Roberto Delatorre, Edson Bello, Gonzalo |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Mir, Daiana Gräf, Tiago Almeida, Sabrina Esteves de Matos Pinto, Aguinaldo Roberto Delatorre, Edson Bello, Gonzalo |
dc.subject.other.none.fl_str_mv |
Subtipo C do HIV-1 Abordagens filodinâmicas bayesianas Sul do Brasil África Oriental Dinâmicas populacionais Epidemias |
topic |
Subtipo C do HIV-1 Abordagens filodinâmicas bayesianas Sul do Brasil África Oriental Dinâmicas populacionais Epidemias HIV-1 subtype C Eastern Africa Southern Brazil Bayesian phylodynamic approaches Population dynamics Epidemics 03 Saúde e Bem-Estar |
dc.subject.en.none.fl_str_mv |
HIV-1 subtype C Eastern Africa Southern Brazil Bayesian phylodynamic approaches Population dynamics Epidemics |
dc.subject.ods.none.fl_str_mv |
03 Saúde e Bem-Estar |
description |
Produção científica do Laboratório de Aids e Imunologia Molecular. |
publishDate |
2018 |
dc.date.accessioned.fl_str_mv |
2018-10-04T12:18:34Z |
dc.date.available.fl_str_mv |
2018-10-04T12:18:34Z |
dc.date.issued.fl_str_mv |
2018 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
MIR, Daiana et al. Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches. Scientific Reports, v. 8, n. 8778, p. 1-10, 8 June 2018. |
dc.identifier.uri.fl_str_mv |
https://arca.fiocruz.br/handle/icict/29323 |
dc.identifier.issn.none.fl_str_mv |
2045-2322 |
dc.identifier.doi.none.fl_str_mv |
10.1038/s41598-018-26824-4 |
dc.identifier.eissn.none.fl_str_mv |
2045-2322 |
identifier_str_mv |
MIR, Daiana et al. Inferring population dynamics of HIV-1 subtype C epidemics in Eastern Africa and Southern Brazil applying different Bayesian phylodynamics approaches. Scientific Reports, v. 8, n. 8778, p. 1-10, 8 June 2018. 2045-2322 10.1038/s41598-018-26824-4 |
url |
https://arca.fiocruz.br/handle/icict/29323 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Nature Research |
publisher.none.fl_str_mv |
Nature Research |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da FIOCRUZ (ARCA) instname:Fundação Oswaldo Cruz (FIOCRUZ) instacron:FIOCRUZ |
instname_str |
Fundação Oswaldo Cruz (FIOCRUZ) |
instacron_str |
FIOCRUZ |
institution |
FIOCRUZ |
reponame_str |
Repositório Institucional da FIOCRUZ (ARCA) |
collection |
Repositório Institucional da FIOCRUZ (ARCA) |
bitstream.url.fl_str_mv |
https://arca.fiocruz.br/bitstreams/f84e69ea-6178-4aef-ab0a-9fc3e3a5df2d/download https://arca.fiocruz.br/bitstreams/0c5edc98-727d-406e-b250-02ef7aac004b/download https://arca.fiocruz.br/bitstreams/efb03901-8963-4e12-a148-9e11688f8149/download https://arca.fiocruz.br/bitstreams/8fbc0673-d7da-453b-97aa-53d029baeba9/download https://arca.fiocruz.br/bitstreams/04f66d89-9dd0-4e13-897b-7a82f85375c9/download |
bitstream.checksum.fl_str_mv |
9acb3f015e11bd9485b9be4752535853 24fcb844b97187cc0c5b312abdc0622a 5a560609d32a3863062d77ff32785d58 698241db98456db2f54313282ec989ad b7e5c5d470bbde8e2e497666017a8459 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da FIOCRUZ (ARCA) - Fundação Oswaldo Cruz (FIOCRUZ) |
repository.mail.fl_str_mv |
repositorio.arca@fiocruz.br |
_version_ |
1839716359423918080 |