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Distinct rates and patterns of spread of the major HIV-1 subtypes in Central and East Africa
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Autores
Faria, Nuno R.
Vidal, Nicole
Lourenco, José
Raghwani, Jayna
Sigaloff, Kim C. E.
Tatem, Andy J.
van de Vijver, David A. M.
Pineda-Peña, Andrea-Clemencia
Rose, Rebecca
Wallis, Carole L.
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Fecha
2019
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Public Library of Science
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Abstract
Since the ignition of the HIV-1 group M pandemic in the beginning of the 20th century, group M lineages have spread heterogeneously throughout the world. Subtype C spread rapidly through sub-Saharan Africa and is currently the dominant HIV lineage worldwide. Yet the epidemiological and evolutionary circumstances that contributed to its epidemiological expansion remain poorly understood. Here, we analyse 346 novel pol sequences from the DRC to compare the evolutionary dynamics of the main HIV-1 lineages, subtypes A1, C and D. Our results place the origins of subtype C in the 1950s in Mbuji-Mayi, the mining city of southern DRC, while subtypes A1 and D emerged in the capital city of Kinshasa, and subtypes H and J in the less accessible port city of Matadi. Following a 15-year period of local transmission in southern DRC, we find that subtype C spread at least three-fold faster than other subtypes circulating in Central and East Africa. In conclusion, our results shed light on the origins of HIV-1 main lineages and suggest that socio-historical rather than evolutionary factors may have determined the epidemiological fate of subtype C in sub-Saharan Africa. © 2019 Faria et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
Virus RNA , Antiretroviral therapy , Antiviral resistance , Article , Bayes theorem , Biogeography , Bioinformatics , Correlation analysis , Gene sequence , Genetic analysis , Genetic recombination , Geographic distribution , Human , Human immunodeficiency virus 1 infection , Major clinical study , Markov chain , Maximum likelihood method , Molecular clock , Molecular epidemiology , Nested polymerase chain reaction , Phylogeny , Phylogeography , Population growth , RNA sequence , Sequence alignment , Seroprevalence , Virus isolation , Africa , Central Africa , Genetics , Human immunodeficiency virus 1 , Human immunodeficiency virus infection , Virology , Africa , Africa , HIV Infections , HIV-1 , Humans
