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Phylogeographic Assessment Reveals Geographic Sources of HIV-1 Dissemination Among Men Who Have Sex With Men in Kenya

Nduva, George M. LU ; Otieno, Frederick ; Kimani, Joshua ; McKinnon, Lyle R. ; Cholette, Francois ; Sandstrom, Paul ; Graham, Susan M. ; Price, Matt A. ; Smith, Adrian D. and Bailey, Robert C. , et al. (2022) In Frontiers in Microbiology 13.
Abstract

HIV-1 transmission dynamics involving men who have sex with men (MSM) in Africa are not well understood. We investigated the rates of HIV-1 transmission between MSM across three regions in Kenya: Coast, Nairobi, and Nyanza. We analyzed 372 HIV-1 partial pol sequences sampled during 2006–2019 from MSM in Coast (N = 178, 47.9%), Nairobi (N = 137, 36.8%), and Nyanza (N = 57, 15.3%) provinces in Kenya. Maximum-likelihood (ML) phylogenetics and Bayesian inference were used to determine HIV-1 clusters, evolutionary dynamics, and virus migration rates between geographic regions. HIV-1 sub-subtype A1 (72.0%) was most common followed by subtype D (11.0%), unique recombinant forms (8.9%), subtype C (5.9%), CRF 21A2D (0.8%), subtype G (0.8%), CRF... (More)

HIV-1 transmission dynamics involving men who have sex with men (MSM) in Africa are not well understood. We investigated the rates of HIV-1 transmission between MSM across three regions in Kenya: Coast, Nairobi, and Nyanza. We analyzed 372 HIV-1 partial pol sequences sampled during 2006–2019 from MSM in Coast (N = 178, 47.9%), Nairobi (N = 137, 36.8%), and Nyanza (N = 57, 15.3%) provinces in Kenya. Maximum-likelihood (ML) phylogenetics and Bayesian inference were used to determine HIV-1 clusters, evolutionary dynamics, and virus migration rates between geographic regions. HIV-1 sub-subtype A1 (72.0%) was most common followed by subtype D (11.0%), unique recombinant forms (8.9%), subtype C (5.9%), CRF 21A2D (0.8%), subtype G (0.8%), CRF 16A2D (0.3%), and subtype B (0.3%). Forty-six clusters (size range 2–20 sequences) were found—half (50.0%) of which had evidence of extensive HIV-1 mixing among different provinces. Data revealed an exponential increase in infections among MSM during the early-to-mid 2000s and stable or decreasing transmission dynamics in recent years (2017–2019). Phylogeographic inference showed significant (Bayes factor, BF > 3) HIV-1 dissemination from Coast to Nairobi and Nyanza provinces, and from Nairobi to Nyanza province. Strengthening HIV-1 prevention programs to MSM in geographic locations with higher HIV-1 prevalence among MSM (such as Coast and Nairobi) may reduce HIV-1 incidence among MSM in Kenya.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
HIV-1, Kenya, molecular epidemiology, MSM, phylogeographic
in
Frontiers in Microbiology
volume
13
article number
843330
publisher
Frontiers Media S. A.
external identifiers
  • pmid:35356525
  • scopus:85127329138
ISSN
1664-302X
DOI
10.3389/fmicb.2022.843330
language
English
LU publication?
yes
id
74b9eee9-a272-4b76-b3c7-95cd13520850
date added to LUP
2022-06-07 13:45:41
date last changed
2022-07-28 00:16:02
@article{74b9eee9-a272-4b76-b3c7-95cd13520850,
  abstract     = {{<p>HIV-1 transmission dynamics involving men who have sex with men (MSM) in Africa are not well understood. We investigated the rates of HIV-1 transmission between MSM across three regions in Kenya: Coast, Nairobi, and Nyanza. We analyzed 372 HIV-1 partial pol sequences sampled during 2006–2019 from MSM in Coast (N = 178, 47.9%), Nairobi (N = 137, 36.8%), and Nyanza (N = 57, 15.3%) provinces in Kenya. Maximum-likelihood (ML) phylogenetics and Bayesian inference were used to determine HIV-1 clusters, evolutionary dynamics, and virus migration rates between geographic regions. HIV-1 sub-subtype A1 (72.0%) was most common followed by subtype D (11.0%), unique recombinant forms (8.9%), subtype C (5.9%), CRF 21A2D (0.8%), subtype G (0.8%), CRF 16A2D (0.3%), and subtype B (0.3%). Forty-six clusters (size range 2–20 sequences) were found—half (50.0%) of which had evidence of extensive HIV-1 mixing among different provinces. Data revealed an exponential increase in infections among MSM during the early-to-mid 2000s and stable or decreasing transmission dynamics in recent years (2017–2019). Phylogeographic inference showed significant (Bayes factor, BF &gt; 3) HIV-1 dissemination from Coast to Nairobi and Nyanza provinces, and from Nairobi to Nyanza province. Strengthening HIV-1 prevention programs to MSM in geographic locations with higher HIV-1 prevalence among MSM (such as Coast and Nairobi) may reduce HIV-1 incidence among MSM in Kenya.</p>}},
  author       = {{Nduva, George M. and Otieno, Frederick and Kimani, Joshua and McKinnon, Lyle R. and Cholette, Francois and Sandstrom, Paul and Graham, Susan M. and Price, Matt A. and Smith, Adrian D. and Bailey, Robert C. and Hassan, Amin S. and Esbjörnsson, Joakim and Sanders, Eduard J.}},
  issn         = {{1664-302X}},
  keywords     = {{HIV-1; Kenya; molecular epidemiology; MSM; phylogeographic}},
  language     = {{eng}},
  publisher    = {{Frontiers Media S. A.}},
  series       = {{Frontiers in Microbiology}},
  title        = {{Phylogeographic Assessment Reveals Geographic Sources of HIV-1 Dissemination Among Men Who Have Sex With Men in Kenya}},
  url          = {{http://dx.doi.org/10.3389/fmicb.2022.843330}},
  doi          = {{10.3389/fmicb.2022.843330}},
  volume       = {{13}},
  year         = {{2022}},
}