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HIV-1 Phylodynamics to Detect and Characterize Active Transmission Clusters in North Carolina.

BACKGROUND
HIV-1 phylodynamics can be used to monitor epidemic trends and help target prevention through identification and characterization of transmission clusters.


METHODS
We analyzed HIV-1 pol sequences sampled in North Carolina from 1997-2014. Putative clusters were identified using maximum-likelihood trees and dated using Bayesian Markov Chain Monte Carlo inference. Active clusters were defined as clusters including internal nodes 2009-2014. Effective reproductive numbers (Re) were estimated using birth-death models for large clusters that expanded ≥2-fold from 2009-2014.


RESULTS
Of 14,921 persons, 7,508 (50%) sequences were identified in 2,264 clusters. Only 288 (13%) clusters were active from 2009-2014; 37 were large (10-36 members). Compared to smaller clusters, large clusters were increasingly populated by men and younger persons; however, nearly 60% included ≥1 women. Clusters with ≥3 members demonstrated assortative mixing by gender, age, and sample region. Of 15 large clusters with ≥2-fold expansion, nearly all had Re ~1 by 2014.


CONCLUSIONS
Phylodynamics revealed transmission cluster expansion in this densely sampled region and allowed estimates of Re to monitor active clusters, showing the propensity for steady, onward propagation. Associations with clustering and cluster characteristics vary by cluster size. Harnessing sequence-derived epidemiologic parameters within routine surveillance could allow refined monitoring of local sub-epidemics.