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

Smith, Davey Ma,b; May, Susanne Jc; Tweeten, Samanthad; Drumright, Lydiaa; Pacold, Mary Ea; Pond, Sergei L Kosakovskya; Pesano, Rick Le; Lie, Yolanda Se; Richman, Douglas Da,b; Frost, Simon DWa; Woelk, Christopher Ha; Little, Susan Ja

doi: 10.1097/QAD.0b013e32831d2a81
Epidemiology and Social

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 ≤ 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.

aUniversity of California San Diego, La Jolla, USA

bVeterans Administration San Diego Healthcare System, San Diego, USA

cUniversity of Washington, Seattle, Washington, USA

dCounty of San Diego Department of Health and Human Services, San Diego, USA

eMonogram Biosciences Inc., South San Francisco, California, USA.

Received 31 July, 2008

Revised 17 September, 2008

Accepted 29 September, 2008

Correspondence to Davey M. Smith, MD, University of California, San Diego, 9500 Gilman Drive 0679, La Jolla, CA 92093-0679, USA. Tel: +1 858 552 4339; fax: +858 552 7445; e-mail: davey@ucsd.edu

© 2009 Lippincott Williams & Wilkins, Inc.