TY - JOUR
T1 - Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis
AU - PANGEA Consortium and Rakai Health Sciences Program
AU - Ratmann, Oliver
AU - Grabowski, M. Kate
AU - Hall, Matthew
AU - Golubchik, Tanya
AU - Wymant, Chris
AU - Abeler-Dörner, Lucie
AU - Bonsall, David
AU - Hoppe, Anne
AU - Brown, Andrew Leigh
AU - de Oliveira, Tulio
AU - Gall, Astrid
AU - Kellam, Paul
AU - Pillay, Deenan
AU - Kagaayi, Joseph
AU - Kigozi, Godfrey
AU - Quinn, Thomas C
AU - Wawer, Maria J.
AU - Laeyendecker, Oliver B.
AU - Serwadda, David
AU - Gray, Ronald H
AU - Fraser, Christophe
AU - Ayles, Helen
AU - Bowden, Rory
AU - Calvez, Vincent
AU - Cohen, Myron
AU - Dennis, Ann
AU - Essex, Max
AU - Fidler, Sarah
AU - Frampton, Daniel
AU - Hayes, Richard
AU - Herbeck, Joshua T.
AU - Kaleebu, Pontiano
AU - Kityo, Cissy
AU - Lingappa, Jairam
AU - Novitsky, Vladimir
AU - Paton, Nick
AU - Rambaut, Andrew
AU - Seeley, Janet
AU - Ssemwanga, Deogratius
AU - Tanser, Frank
AU - Nakigozi, Gertrude
AU - Ssekubugu, Robert
AU - Nalugoda, Fred
AU - Lutalo, Tom
AU - Galiwango, Ronald
AU - Aaron, Aaron A.
AU - Reynolds, Steven James
AU - Chang, Larry W.
AU - Redd, Andrew
AU - Kennedy, Caitlin E.
N1 - Publisher Copyright:
© 2019, The Author(s).
PY - 2019/12/1
Y1 - 2019/12/1
N2 - 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.
AB - 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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U2 - 10.1038/s41467-019-09139-4
DO - 10.1038/s41467-019-09139-4
M3 - Article
C2 - 30926780
AN - SCOPUS:85063743809
SN - 2041-1723
VL - 10
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 1411
ER -