2017
DOI: 10.1093/ve/vex013
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Rising prevalence of non-B HIV-1 subtypes in North Carolina and evidence for local onward transmission

Abstract: HIV-1 diversity is increasing in North American and European cohorts which may have public health implications. However, little is known about non-B subtype diversity in the southern United States, despite the region being the epicenter of the nation’s epidemic. We characterized HIV-1 diversity and transmission clusters to identify the extent to which non-B strains are transmitted locally. We conducted cross-sectional analyses of HIV-1 partial pol sequences collected from 1997 to 2014 from adults accessing rou… Show more

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Cited by 18 publications
(15 citation statements)
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References 29 publications
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“…Similarly, the prevalence of non-B infections has increased from 5.9% in 2006 to 8.5% in 2013 in 7 US states (Colorado, Connecticut, Michigan, New York, South Carolina, Texas, and Washington) [ 44 ]. Lower rates, however, of non-B subtypes have been reported for other Southeastern US states like North Carolina [ 45 ], which is consistent with the national average prevalence of non-B subtypes (3.27%) estimated in 2011 [ 46 ].…”
Section: Discussionsupporting
confidence: 82%
“…Similarly, the prevalence of non-B infections has increased from 5.9% in 2006 to 8.5% in 2013 in 7 US states (Colorado, Connecticut, Michigan, New York, South Carolina, Texas, and Washington) [ 44 ]. Lower rates, however, of non-B subtypes have been reported for other Southeastern US states like North Carolina [ 45 ], which is consistent with the national average prevalence of non-B subtypes (3.27%) estimated in 2011 [ 46 ].…”
Section: Discussionsupporting
confidence: 82%
“…Putative clusters of subtype B sequences in the ML tree were confirmed using Bayesian Markov Chain Monte Carlo (MCMC) inference in BEAST, v. 1.8.2 [ 31 ]. Non-B subtypes were investigated in a separate analysis [ 32 ]. Sequences clustered in the initial ML tree were split into 40 alignments along cluster lines with <200 sequences per file to decrease computational time in BEAST.…”
Section: Methodsmentioning
confidence: 99%
“…Here, we demonstrate our approach by the application to the HIV-1 INSTIs. With the rollout of INSTIs in LMICs, an increasing introduction of non-B subtypes in highincome countries (26)(27)(28)(29), and the anticipated approval of additional INSTIs, this study addressed the need for an in-depth understanding of the dynamics underlying INSTI resistance development across HIV-1 subtypes. We derived an optimized genetic barrier score based on empirical substitution costs, which contrasts with previous approaches that used arbitrary costs differing from in vivo estimates (30).…”
mentioning
confidence: 99%