Using HIV Networks to Inform Real Time Prevention Interventions

To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission. HIV-1 pol sequence data were analyzed to infer the local transmission network. We analyzed HIV-1 pol sequence data to infer a partial local transmission...

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Published inPloS one Vol. 9; no. 6; p. e98443
Main Authors Little, Susan J., Kosakovsky Pond, Sergei L., Anderson, Christy M., Young, Jason A., Wertheim, Joel O., Mehta, Sanjay R., May, Susanne, Smith, Davey M.
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 05.06.2014
Public Library of Science (PLoS)
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Abstract To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission. HIV-1 pol sequence data were analyzed to infer the local transmission network. We analyzed HIV-1 pol sequence data to infer a partial local transmission network among 478 recently HIV-1 infected persons and 170 of their sexual and social contacts in San Diego, California. A transmission network score (TNS) was developed to estimate the risk of HIV transmission from a newly diagnosed individual to a new partner and target prevention interventions. HIV-1 pol sequences from 339 individuals (52.3%) were highly similar to sequences from at least one other participant (i.e., clustered). A high TNS (top 25%) was significantly correlated with baseline risk behaviors (number of unique sexual partners and insertive unprotected anal intercourse (p = 0.014 and p = 0.0455, respectively) and predicted risk of transmission (p<0.0001). Retrospective analysis of antiretroviral therapy (ART) use, and simulations of ART targeted to individuals with the highest TNS, showed significantly reduced network level HIV transmission (p<0.05). Sequence data from an HIV-1 screening program focused on recently infected persons and their social and sexual contacts enabled the characterization of a highly connected transmission network. The network-based risk score (TNS) was highly correlated with transmission risk behaviors and outcomes, and can be used identify and target effective prevention interventions, like ART, to those at a greater risk for HIV-1 transmission.
AbstractList Objective To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission. Design HIV-1 pol sequence data were analyzed to infer the local transmission network. Methods We analyzed HIV-1 pol sequence data to infer a partial local transmission network among 478 recently HIV-1 infected persons and 170 of their sexual and social contacts in San Diego, California. A transmission network score (TNS) was developed to estimate the risk of HIV transmission from a newly diagnosed individual to a new partner and target prevention interventions. Results HIV-1 pol sequences from 339 individuals (52.3%) were highly similar to sequences from at least one other participant (i.e., clustered). A high TNS (top 25%) was significantly correlated with baseline risk behaviors (number of unique sexual partners and insertive unprotected anal intercourse (p = 0.014 and p = 0.0455, respectively) and predicted risk of transmission (p<0.0001). Retrospective analysis of antiretroviral therapy (ART) use, and simulations of ART targeted to individuals with the highest TNS, showed significantly reduced network level HIV transmission (p<0.05). Conclusions Sequence data from an HIV-1 screening program focused on recently infected persons and their social and sexual contacts enabled the characterization of a highly connected transmission network. The network-based risk score (TNS) was highly correlated with transmission risk behaviors and outcomes, and can be used identify and target effective prevention interventions, like ART, to those at a greater risk for HIV-1 transmission.
To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission.OBJECTIVETo reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission.HIV-1 pol sequence data were analyzed to infer the local transmission network.DESIGNHIV-1 pol sequence data were analyzed to infer the local transmission network.We analyzed HIV-1 pol sequence data to infer a partial local transmission network among 478 recently HIV-1 infected persons and 170 of their sexual and social contacts in San Diego, California. A transmission network score (TNS) was developed to estimate the risk of HIV transmission from a newly diagnosed individual to a new partner and target prevention interventions.METHODSWe analyzed HIV-1 pol sequence data to infer a partial local transmission network among 478 recently HIV-1 infected persons and 170 of their sexual and social contacts in San Diego, California. A transmission network score (TNS) was developed to estimate the risk of HIV transmission from a newly diagnosed individual to a new partner and target prevention interventions.HIV-1 pol sequences from 339 individuals (52.3%) were highly similar to sequences from at least one other participant (i.e., clustered). A high TNS (top 25%) was significantly correlated with baseline risk behaviors (number of unique sexual partners and insertive unprotected anal intercourse (p = 0.014 and p = 0.0455, respectively) and predicted risk of transmission (p<0.0001). Retrospective analysis of antiretroviral therapy (ART) use, and simulations of ART targeted to individuals with the highest TNS, showed significantly reduced network level HIV transmission (p<0.05).RESULTSHIV-1 pol sequences from 339 individuals (52.3%) were highly similar to sequences from at least one other participant (i.e., clustered). A high TNS (top 25%) was significantly correlated with baseline risk behaviors (number of unique sexual partners and insertive unprotected anal intercourse (p = 0.014 and p = 0.0455, respectively) and predicted risk of transmission (p<0.0001). Retrospective analysis of antiretroviral therapy (ART) use, and simulations of ART targeted to individuals with the highest TNS, showed significantly reduced network level HIV transmission (p<0.05).Sequence data from an HIV-1 screening program focused on recently infected persons and their social and sexual contacts enabled the characterization of a highly connected transmission network. The network-based risk score (TNS) was highly correlated with transmission risk behaviors and outcomes, and can be used identify and target effective prevention interventions, like ART, to those at a greater risk for HIV-1 transmission.CONCLUSIONSSequence data from an HIV-1 screening program focused on recently infected persons and their social and sexual contacts enabled the characterization of a highly connected transmission network. The network-based risk score (TNS) was highly correlated with transmission risk behaviors and outcomes, and can be used identify and target effective prevention interventions, like ART, to those at a greater risk for HIV-1 transmission.
To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission. HIV-1 pol sequence data were analyzed to infer the local transmission network. We analyzed HIV-1 pol sequence data to infer a partial local transmission network among 478 recently HIV-1 infected persons and 170 of their sexual and social contacts in San Diego, California. A transmission network score (TNS) was developed to estimate the risk of HIV transmission from a newly diagnosed individual to a new partner and target prevention interventions. HIV-1 pol sequences from 339 individuals (52.3%) were highly similar to sequences from at least one other participant (i.e., clustered). A high TNS (top 25%) was significantly correlated with baseline risk behaviors (number of unique sexual partners and insertive unprotected anal intercourse (p = 0.014 and p = 0.0455, respectively) and predicted risk of transmission (p<0.0001). Retrospective analysis of antiretroviral therapy (ART) use, and simulations of ART targeted to individuals with the highest TNS, showed significantly reduced network level HIV transmission (p<0.05). Sequence data from an HIV-1 screening program focused on recently infected persons and their social and sexual contacts enabled the characterization of a highly connected transmission network. The network-based risk score (TNS) was highly correlated with transmission risk behaviors and outcomes, and can be used identify and target effective prevention interventions, like ART, to those at a greater risk for HIV-1 transmission.
Objective To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission. Design HIV-1 pol sequence data were analyzed to infer the local transmission network. Methods We analyzed HIV-1 pol sequence data to infer a partial local transmission network among 478 recently HIV-1 infected persons and 170 of their sexual and social contacts in San Diego, California. A transmission network score (TNS) was developed to estimate the risk of HIV transmission from a newly diagnosed individual to a new partner and target prevention interventions. Results HIV-1 pol sequences from 339 individuals (52.3%) were highly similar to sequences from at least one other participant (i.e., clustered). A high TNS (top 25%) was significantly correlated with baseline risk behaviors (number of unique sexual partners and insertive unprotected anal intercourse (p = 0.014 and p = 0.0455, respectively) and predicted risk of transmission (p<0.0001). Retrospective analysis of antiretroviral therapy (ART) use, and simulations of ART targeted to individuals with the highest TNS, showed significantly reduced network level HIV transmission (p<0.05). Conclusions Sequence data from an HIV-1 screening program focused on recently infected persons and their social and sexual contacts enabled the characterization of a highly connected transmission network. The network-based risk score (TNS) was highly correlated with transmission risk behaviors and outcomes, and can be used identify and target effective prevention interventions, like ART, to those at a greater risk for HIV-1 transmission.
To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission. HIV-1 pol sequence data were analyzed to infer the local transmission network. We analyzed HIV-1 pol sequence data to infer a partial local transmission network among 478 recently HIV-1 infected persons and 170 of their sexual and social contacts in San Diego, California. A transmission network score (TNS) was developed to estimate the risk of HIV transmission from a newly diagnosed individual to a new partner and target prevention interventions. HIV-1 pol sequences from 339 individuals (52.3%) were highly similar to sequences from at least one other participant (i.e., clustered). A high TNS (top 25%) was significantly correlated with baseline risk behaviors (number of unique sexual partners and insertive unprotected anal intercourse (p = 0.014 and p = 0.0455, respectively) and predicted risk of transmission (p<0.0001). Retrospective analysis of antiretroviral therapy (ART) use, and simulations of ART targeted to individuals with the highest TNS, showed significantly reduced network level HIV transmission (p<0.05). Sequence data from an HIV-1 screening program focused on recently infected persons and their social and sexual contacts enabled the characterization of a highly connected transmission network. The network-based risk score (TNS) was highly correlated with transmission risk behaviors and outcomes, and can be used identify and target effective prevention interventions, like ART, to those at a greater risk for HIV-1 transmission.
Audience Academic
Author Wertheim, Joel O.
Kosakovsky Pond, Sergei L.
Young, Jason A.
Little, Susan J.
May, Susanne
Smith, Davey M.
Anderson, Christy M.
Mehta, Sanjay R.
AuthorAffiliation 1 Department of Medicine, University of California, San Diego, La Jolla, California, United States of America
2 Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
University of British Columbia, Canada
3 Veterans Affairs San Diego Healthcare System, San Diego, California, United States of America
AuthorAffiliation_xml – name: 3 Veterans Affairs San Diego Healthcare System, San Diego, California, United States of America
– name: 1 Department of Medicine, University of California, San Diego, La Jolla, California, United States of America
– name: 2 Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
– name: University of British Columbia, Canada
Author_xml – sequence: 1
  givenname: Susan J.
  surname: Little
  fullname: Little, Susan J.
– sequence: 2
  givenname: Sergei L.
  surname: Kosakovsky Pond
  fullname: Kosakovsky Pond, Sergei L.
– sequence: 3
  givenname: Christy M.
  surname: Anderson
  fullname: Anderson, Christy M.
– sequence: 4
  givenname: Jason A.
  surname: Young
  fullname: Young, Jason A.
– sequence: 5
  givenname: Joel O.
  surname: Wertheim
  fullname: Wertheim, Joel O.
– sequence: 6
  givenname: Sanjay R.
  surname: Mehta
  fullname: Mehta, Sanjay R.
– sequence: 7
  givenname: Susanne
  surname: May
  fullname: May, Susanne
– sequence: 8
  givenname: Davey M.
  surname: Smith
  fullname: Smith, Davey M.
BackLink https://www.ncbi.nlm.nih.gov/pubmed/24901437$$D View this record in MEDLINE/PubMed
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Copyright COPYRIGHT 2014 Public Library of Science
2014. This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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– notice: 2014. This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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Conceived and designed the experiments: SJL SLKP DMS. Performed the experiments: SJL DMS. Analyzed the data: SLKP SM JOW JAY CMA SJL DMS. Contributed reagents/materials/analysis tools: CMA JAY JOW. Wrote the paper: SJL SLKP SRM DMS.
Competing Interests: Dr. Pond served as a consultant for Monogram Biosciences and Genprobe. Dr. Smith reported receiving grant funding from ViiV Healthcare and having served as a consultant for Genprobe and Testing Talent Services. No other competing interest disclosures were reported. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials
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Snippet To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission. HIV-1 pol...
Objective To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission....
To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission. HIV-1 pol...
To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission.OBJECTIVETo...
To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission.HIV-1 pol...
Objective To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission....
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StartPage e98443
SubjectTerms Adult
Analysis
Antiretroviral agents
Antiretroviral drugs
Antiretroviral therapy
Biology and Life Sciences
California
Cluster Analysis
Data processing
Disease transmission
Drug resistance
Epidemics
Female
Health risks
HIV
HIV Infections - diagnosis
HIV Infections - prevention & control
HIV Infections - transmission
HIV tests
HIV-1 - genetics
Human immunodeficiency virus
Humans
Male
Mass Screening
Medicine and health sciences
Middle Aged
pol Gene Products, Human Immunodeficiency Virus - genetics
Population Surveillance
Prevention
Risk
Risk taking
Sequence Analysis, DNA
Sexual Behavior
Sexual Partners
Sexually transmitted diseases
STD
Target recognition
Young Adult
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Title Using HIV Networks to Inform Real Time Prevention Interventions
URI https://www.ncbi.nlm.nih.gov/pubmed/24901437
https://www.proquest.com/docview/1532986997
https://www.proquest.com/docview/1534101022
https://pubmed.ncbi.nlm.nih.gov/PMC4047027
https://doaj.org/article/73ac2e8b86284b9192a34e14599f9433
http://dx.doi.org/10.1371/journal.pone.0098443
Volume 9
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