A public health model for the molecular surveillance of HIV transmission in San Diego, California
A public health model for the molecular surveillance of HIV transmission in San Diego, California
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.
225-232
Smith, D.M.
88dfac94-ed7d-438d-9581-3dce369e9882
May, S.
2e21009a-849a-4de9-b293-86fd033bf2a7
Tweeten, S.
daa18f27-cd83-4dfc-b444-f1bc2243edd5
Drumright, L.
15e7a63b-29ea-4084-bdbc-7258ab3a77b8
Pacold, M.E.
35a12b7c-849f-448e-8255-89fc1fb23b39
Kosakovsky Pond, S.L.
b80f6d16-0c4f-4577-9cbb-7e8f65a0c70d
Pesano, R.L.
2077c68f-474d-4458-93f1-13e6bd676a33
Lie, Y.S.
0b553c1c-c61a-4c19-be78-9724c5f1014e
Richman, D.D.
1d5f38e4-c778-4b0b-b542-9d1160e63041
Frost, S.D.W.
4664d117-e177-48d1-8951-030014c61f0e
Woelk, C.H.
4d3af0fd-658f-4626-b3b5-49a6192bcf7d
Little, S.J.
97d16cb1-b00a-40f8-9746-2300b5f7174d
14 January 2009
Smith, D.M.
88dfac94-ed7d-438d-9581-3dce369e9882
May, S.
2e21009a-849a-4de9-b293-86fd033bf2a7
Tweeten, S.
daa18f27-cd83-4dfc-b444-f1bc2243edd5
Drumright, L.
15e7a63b-29ea-4084-bdbc-7258ab3a77b8
Pacold, M.E.
35a12b7c-849f-448e-8255-89fc1fb23b39
Kosakovsky Pond, S.L.
b80f6d16-0c4f-4577-9cbb-7e8f65a0c70d
Pesano, R.L.
2077c68f-474d-4458-93f1-13e6bd676a33
Lie, Y.S.
0b553c1c-c61a-4c19-be78-9724c5f1014e
Richman, D.D.
1d5f38e4-c778-4b0b-b542-9d1160e63041
Frost, S.D.W.
4664d117-e177-48d1-8951-030014c61f0e
Woelk, C.H.
4d3af0fd-658f-4626-b3b5-49a6192bcf7d
Little, S.J.
97d16cb1-b00a-40f8-9746-2300b5f7174d
Smith, D.M., May, S., Tweeten, S., Drumright, L., Pacold, M.E., Kosakovsky Pond, S.L., Pesano, R.L., Lie, Y.S., Richman, D.D., Frost, S.D.W., Woelk, C.H. and Little, S.J.
(2009)
A public health model for the molecular surveillance of HIV transmission in San Diego, California.
AIDS, 23 (2), .
(doi:10.1097/QAD.0b013e32831d2a81).
(PMID:19098493)
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.
This record has no associated files available for download.
More information
Published date: 14 January 2009
Organisations:
Clinical & Experimental Sciences
Identifiers
Local EPrints ID: 352811
URI: http://eprints.soton.ac.uk/id/eprint/352811
PURE UUID: 35e3a4be-524d-4eb3-bb87-be034a57de87
Catalogue record
Date deposited: 21 May 2013 11:46
Last modified: 14 Mar 2024 13:56
Export record
Altmetrics
Contributors
Author:
D.M. Smith
Author:
S. May
Author:
S. Tweeten
Author:
L. Drumright
Author:
M.E. Pacold
Author:
S.L. Kosakovsky Pond
Author:
R.L. Pesano
Author:
Y.S. Lie
Author:
D.D. Richman
Author:
S.D.W. Frost
Author:
C.H. Woelk
Author:
S.J. Little
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics