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Multicenter Study
. 2009 Jan 14;23(2):225-32.
doi: 10.1097/QAD.0b013e32831d2a81.

A public health model for the molecular surveillance of HIV transmission in San Diego, California

Affiliations
Multicenter Study

A public health model for the molecular surveillance of HIV transmission in San Diego, California

Davey M Smith et al. AIDS. .

Abstract

Background: Current public health efforts often use molecular technologies to identify and contain communicable disease networks, but not for HIV. Here, we investigate how molecular epidemiology can be used to identify highly related HIV networks within a population and how voluntary contact tracing of sexual partners can be used to selectively target these networks.

Methods: We evaluated the use of HIV-1 pol sequences obtained from participants of a community-recruited cohort (n = 268) and a primary infection research cohort (n = 369) to define highly related transmission clusters and the use of contact tracing to link other individuals (n = 36) within these clusters. The presence of transmitted drug resistance was interpreted from the pol sequences (Calibrated Population Resistance v3.0).

Results: Phylogenetic clustering was conservatively defined when the genetic distance between any two pol sequences was less than 1%, which identified 34 distinct transmission clusters within the combined community-recruited and primary infection research cohorts containing 160 individuals. Although sequences from the epidemiologically linked partners represented approximately 5% of the total sequences, they clustered with 60% of the sequences that clustered from the combined cohorts (odds ratio 21.7; P < or = 0.01). Major resistance to at least one class of antiretroviral medication was found in 19% of clustering sequences.

Conclusion: Phylogenetic methods can be used to identify individuals who are within highly related transmission groups, and contact tracing of epidemiologically linked partners of recently infected individuals can be used to link into previously defined transmission groups. These methods could be used to implement selectively targeted prevention interventions.

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Figures

Figure 1
Figure 1
A: Sequences from epidemiologically-linked partners that fell within clusters previously defined from the combined FCP and San Diego County cohorts (n=29) B: Sequences from the combined FCP and San Diego County cohorts that clustered together and with sequences from epidemiologically-linked partners (n=96) C: Sequences that clustered within the combined FCP and San Diego County cohorts (n=160)

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