Evidence map›Paper›PMID 26629540›Full record

ArticleEBioMedicine2015

HIV Transmission Networks in the San Diego-Tijuana Border Region.

Sanjay R Mehta, Joel O Wertheim, Kimberly C Brouwer, Karla D Wagner, Antoine Chaillon, Steffanie Strathdee, Thomas L Patterson, Maria G Rangel, Mlenka Vargas, Ben Murrell and 3 more

Abstract read
In one paragraph

Article in EBioMedicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  14. Dynamics and Dispersal of Local Human Immunodeficiency Virus Epidemics Within San Diego and Across the San Diego-Tijuana Border.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Sanjay R MehtaDivision of Infectious Diseases, University of California San Diego, #8208 200 W. Arbor St. San Diego, CA 92103, United States ; Division of Infectious Diseases, San Diego Veterans Affairs Medical Center, 3350 La Jolla Village Drive, San Diego, CA 92161, United States.
Joel O WertheimDivision of Infectious Diseases, University of California San Diego, #8208 200 W. Arbor St. San Diego, CA 92103, United States.
Kimberly C BrouwerDivision of Global Public Health, University of California San Diego, #0507, La Jolla, CA 92093, United States.
Karla D WagnerSchool of Community Health Sciences, University of Nevada Reno, Lombardi Building, 203, MS 0274, Reno, NV 89557, United States.
Antoine ChaillonDivision of Infectious Diseases, University of California San Diego, #8208 200 W. Arbor St. San Diego, CA 92103, United States.
Steffanie StrathdeeDivision of Global Public Health, University of California San Diego, #0507, La Jolla, CA 92093, United States.
Thomas L PattersonDepartment of Psychiatry, University of California San Diego #0680, La Jolla, CA 92093, United States.
Maria G RangelEl Colegio de la Frontera Norte, San Antonio del Mar, Baja California, Mexico.
Mlenka VargasDivision of Infectious Diseases, University of California San Diego, #8208 200 W. Arbor St. San Diego, CA 92103, United States.
Ben MurrellDivision of Infectious Diseases, University of California San Diego, #8208 200 W. Arbor St. San Diego, CA 92103, United States.
Richard GarfeinDivision of Global Public Health, University of California San Diego, #0507, La Jolla, CA 92093, United States.
Susan J LittleDivision of Infectious Diseases, University of California San Diego, #8208 200 W. Arbor St. San Diego, CA 92103, United States.
Davey M SmithDivision of Infectious Diseases, University of California San Diego, #8208 200 W. Arbor St. San Diego, CA 92103, United States ; Division of Infectious Diseases, San Diego Veterans Affairs Medical Center, 3350 La Jolla Village Drive, San Diego, CA 92161, United States.

Funding

VirologyP30AI036214 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Maile Ann Young Karris · 1994 to 2026
$78.4M
STRUCTURAL NEUROIMAGING COREP30MH062512 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DAVID J MOORE · 2001 to 2026
$50.4M
Transmission ProbabilityP01AI074621 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI RICHMAN, DOUGLAS D · 2008 to 2012
$23.1M
Primary Infection Resource Consortium (PIRC)R24AI106039 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LITTLE, SUSAN JANET · 2013 to 2021
$23.1M
Southern California Primary Infection ProgramU01AI043638 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI RICHMAN, DOUGLAS D · 1998 to 2010
$21.3M
Impact of Drug Policy Reform on the HIV Risk Environment among IDUs in TijuanaR37DA019829 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI STRATHDEE, STEFFANIE A. · 2010 to 2019
$6.7M
Molecular Epidemiology for HIV Prevention for Drug Users and Other Risk Groups DP1DA034978 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SMITH, DAVID MITCHELL · 2012 to 2016
$4.1M
Intervention for Female Workers in MexicoR01MH065849 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PATTERSON, THOMAS L. · 2004 to 2008
$3.6M
Epidemiologic Study on Changing HIV Risks Among FSW-IDUs on the Mexico-US BorderR01DA023877 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI STRATHDEE, STEFFANIE A. · 2008 to 2012
$3.3M
Evolving HIV/STI risk environments of FSWs on the Mexico/U.S. BorderR01DA028692 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BROUWER, KIMBERLY C · 2010 to 2014
$3.2M
Drug tourism to Mexico: Impact of Mexicos new drug law on HIV-HCV-TB in US IDUsR01DA031074 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GARFEIN, RICHARD S · 2011 to 2015
$3.2M
Proyecto Parejas: HIV/STI Risks among FSWs and their Non-Commercial PartnersR01DA027772 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI STRATHDEE, STEFFANIE A. · 2009 to 2013
$3.1M
NIAID NIH HHS AI036214NIAID NIH HHS AI100665NIAID NIH HHS AI106039NIAID NIH HHS AI110181NIAID NIH HHS AI43638NIAID NIH HHS AI74621NIAID NIH HHS AI93163NIAID NIH HHS K01 AI110181NIAID NIH HHS K23 AI093163NIAID NIH HHS K24 AI100665NIAID NIH HHS P01 AI074621NIAID NIH HHS P30 AI036214NIAID NIH HHS R24 AI106039NIAID NIH HHS U01 AI043638NIDA NIH HHS DA019829NIDA NIH HHS DA023877NIDA NIH HHS DA027772NIDA NIH HHS DA028692NIDA NIH HHS DA029008NIDA NIH HHS DA031031NIDA NIH HHS DA031074NIDA NIH HHS DA034978NIDA NIH HHS DP1 DA034978NIDA NIH HHS K01 DA031031NIDA NIH HHS R01 DA019829NIDA NIH HHS R01 DA023877NIDA NIH HHS R01 DA027772NIDA NIH HHS R01 DA028692NIDA NIH HHS R01 DA029008NIDA NIH HHS R01 DA031074NIDA NIH HHS R37 DA019829NIMH NIH HHS MH065849NIMH NIH HHS R01 MH065849
6 · The paper itself

Abstract

backgroundHIV sequence data can be used to reconstruct local transmission networks. Along international borders, like the San Diego-Tijuana region, understanding the dynamics of HIV transmission across reported risks, racial/ethnic groups, and geography can help direct effective prevention efforts on both sides of the border.

methodsWe gathered sociodemographic, geographic, clinical, and viral sequence data from HIV infected individuals participating in ten studies in the San Diego-Tijuana border region. Phylogenetic and network analysis was performed to infer putative relationships between HIV sequences. Correlates of identified clusters were evaluated and spatiotemporal relationships were explored using Bayesian phylogeographic analysis.

findingsAfter quality filtering, 843 HIV sequences with associated demographic data and 263 background sequences from the region were analyzed, and 138 clusters were inferred (2-23 individuals). Overall, the rate of clustering did not differ by ethnicity, residence, or sex, but bisexuals were less likely to cluster than heterosexuals or men who have sex with men (p = 0.043), and individuals identifying as white (p ≤ 0.01) were more likely to cluster than other races. Clustering individuals were also 3.5 years younger than non-clustering individuals (p < 0.001). Although the sampled San Diego and Tijuana epidemics were phylogenetically compartmentalized, five clusters contained individuals residing on both sides of the border.

interpretationThis study sampled ~ 7% of HIV infected individuals in the border region, and although the sampled networks on each side of the border were largely separate, there was evidence of persistent bidirectional cross-border transmissions that linked risk groups, thus highlighting the importance of the border region as a "melting pot" of risk groups.

fundingNIH, VA, and Pendleton Foundation.

Indexed as

Emigration and ImmigrationHIV-1Population SurveillanceAdultBayes TheoremCaliforniaCluster AnalysisDrug Resistance, ViralFemaleGenome, ViralHIV InfectionsHumansMaleMexicoMiddle AgedMutationHIVInternational borderMexicoPhylogeographyTransmission network

Identifiers

PMID26629540
PMCPMC4634195

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.