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Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis

To prevent new infections with human immunodeficiency virus type 1 (HIV-1) in sub-Saharan Africa, UNAIDS recommends targeting interventions to populations that are at high risk of acquiring and passing on the virus. Yet it is often unclear who and where these ‘source’ populations are. Here we demons...

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Autores principales: Ratmann, Oliver, Grabowski, M. Kate, Hall, Matthew, Golubchik, Tanya, Wymant, Chris, Abeler-Dörner, Lucie, Bonsall, David, Hoppe, Anne, Brown, Andrew Leigh, de Oliveira, Tulio, Gall, Astrid, Kellam, Paul, Pillay, Deenan, Kagaayi, Joseph, Kigozi, Godfrey, Quinn, Thomas C., Wawer, Maria J., Laeyendecker, Oliver, Serwadda, David, Gray, Ronald H., Fraser, Christophe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6441045/
https://www.ncbi.nlm.nih.gov/pubmed/30926780
http://dx.doi.org/10.1038/s41467-019-09139-4
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author Ratmann, Oliver
Grabowski, M. Kate
Hall, Matthew
Golubchik, Tanya
Wymant, Chris
Abeler-Dörner, Lucie
Bonsall, David
Hoppe, Anne
Brown, Andrew Leigh
de Oliveira, Tulio
Gall, Astrid
Kellam, Paul
Pillay, Deenan
Kagaayi, Joseph
Kigozi, Godfrey
Quinn, Thomas C.
Wawer, Maria J.
Laeyendecker, Oliver
Serwadda, David
Gray, Ronald H.
Fraser, Christophe
author_facet Ratmann, Oliver
Grabowski, M. Kate
Hall, Matthew
Golubchik, Tanya
Wymant, Chris
Abeler-Dörner, Lucie
Bonsall, David
Hoppe, Anne
Brown, Andrew Leigh
de Oliveira, Tulio
Gall, Astrid
Kellam, Paul
Pillay, Deenan
Kagaayi, Joseph
Kigozi, Godfrey
Quinn, Thomas C.
Wawer, Maria J.
Laeyendecker, Oliver
Serwadda, David
Gray, Ronald H.
Fraser, Christophe
author_sort Ratmann, Oliver
collection PubMed
description To prevent new infections with human immunodeficiency virus type 1 (HIV-1) in sub-Saharan Africa, UNAIDS recommends targeting interventions to populations that are at high risk of acquiring and passing on the virus. Yet it is often unclear who and where these ‘source’ populations are. Here we demonstrate how viral deep-sequencing can be used to reconstruct HIV-1 transmission networks and to infer the direction of transmission in these networks. We are able to deep-sequence virus from a large population-based sample of infected individuals in Rakai District, Uganda, reconstruct partial transmission networks, and infer the direction of transmission within them at an estimated error rate of 16.3% [8.8–28.3%]. With this error rate, deep-sequence phylogenetics cannot be used against individuals in legal contexts, but is sufficiently low for population-level inferences into the sources of epidemic spread. The technique presents new opportunities for characterizing source populations and for targeting of HIV-1 prevention interventions in Africa.
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spelling pubmed-64410452019-04-01 Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis Ratmann, Oliver Grabowski, M. Kate Hall, Matthew Golubchik, Tanya Wymant, Chris Abeler-Dörner, Lucie Bonsall, David Hoppe, Anne Brown, Andrew Leigh de Oliveira, Tulio Gall, Astrid Kellam, Paul Pillay, Deenan Kagaayi, Joseph Kigozi, Godfrey Quinn, Thomas C. Wawer, Maria J. Laeyendecker, Oliver Serwadda, David Gray, Ronald H. Fraser, Christophe Nat Commun Article To prevent new infections with human immunodeficiency virus type 1 (HIV-1) in sub-Saharan Africa, UNAIDS recommends targeting interventions to populations that are at high risk of acquiring and passing on the virus. Yet it is often unclear who and where these ‘source’ populations are. Here we demonstrate how viral deep-sequencing can be used to reconstruct HIV-1 transmission networks and to infer the direction of transmission in these networks. We are able to deep-sequence virus from a large population-based sample of infected individuals in Rakai District, Uganda, reconstruct partial transmission networks, and infer the direction of transmission within them at an estimated error rate of 16.3% [8.8–28.3%]. With this error rate, deep-sequence phylogenetics cannot be used against individuals in legal contexts, but is sufficiently low for population-level inferences into the sources of epidemic spread. The technique presents new opportunities for characterizing source populations and for targeting of HIV-1 prevention interventions in Africa. Nature Publishing Group UK 2019-03-29 /pmc/articles/PMC6441045/ /pubmed/30926780 http://dx.doi.org/10.1038/s41467-019-09139-4 Text en © The Author(s) 2019 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
Ratmann, Oliver
Grabowski, M. Kate
Hall, Matthew
Golubchik, Tanya
Wymant, Chris
Abeler-Dörner, Lucie
Bonsall, David
Hoppe, Anne
Brown, Andrew Leigh
de Oliveira, Tulio
Gall, Astrid
Kellam, Paul
Pillay, Deenan
Kagaayi, Joseph
Kigozi, Godfrey
Quinn, Thomas C.
Wawer, Maria J.
Laeyendecker, Oliver
Serwadda, David
Gray, Ronald H.
Fraser, Christophe
Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis
title Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis
title_full Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis
title_fullStr Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis
title_full_unstemmed Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis
title_short Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis
title_sort inferring hiv-1 transmission networks and sources of epidemic spread in africa with deep-sequence phylogenetic analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6441045/
https://www.ncbi.nlm.nih.gov/pubmed/30926780
http://dx.doi.org/10.1038/s41467-019-09139-4
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