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Genetic Cluster Analysis for HIV Prevention
Authors:Mary Kate Grabowski  Joshua T. Herbeck  Art F. Y. Poon
Affiliation:1.Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health,Rakai Health Sciences Program,Baltimore,USA;2.International Clinical Research Center, Department of Global Health,University of Washington,Seattle,USA;3.Department of Pathology and Laboratory Medicine,Western University,London,Canada
Abstract:

Purpose of Review

This review summarizes the use of genetic similarity clusters to understand HIV transmission and inform prevention efforts.

Recent Findings

Recent emphases include the development of real-time cluster identification in order to interrupt transmission chains, the use of clusters to estimate rates of transmission along the HIV care cascade, and the extension of cluster analyses to understand transmission in the generalized epidemics of sub-Saharan Africa. Importantly, this recent empirical work has been accompanied by theoretical work that elucidates the processes that underlie HIV genetic similarity clusters; multiple studies suggest that clusters are not necessarily enriched with individuals with high transmission rates, but rather can reflect variation in sampling times within a population, with individuals sampled early in infection more likely to cluster.

Summary

Analyses of genetic similarity clusters have great promise to inform HIV epidemiology and prevention. Future emphases should include the collection of additional sequence data from underrepresented populations, such as those in sub-Saharan Africa, and further development and evaluation of clustering methods.
Keywords:
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