title: Will HIV vaccination reshape HIV risk behavior networks? A social network analysis of drug users' anticipated risk compensation.
abstract: BACKGROUND
  An HIV vaccine could substantially impact the epidemic. However, risk compensation (RC), or post-vaccination increase in risk behavior, could present a major challenge. The methodology used in previous studies of risk compensation has been almost exclusively individual-level in focus, and has not explored how increased risk behavior could affect the connectivity of risk networks. This study examined the impact of anticipated HIV vaccine-related RC on the structure of high-risk drug users' sexual and injection risk network.
  
  
  METHODS
  A sample of 433 rural drug users in the US provided data on their risk relationships (i.e., those involving recent unprotected sex and/or injection equipment sharing). Dyad-specific data were collected on likelihood of increasing/initiating risk behavior if they, their partner, or they and their partner received an HIV vaccine. Using these data and social network analysis, a "post-vaccination network" was constructed and compared to the current network on measures relevant to HIV transmission, including network size, cohesiveness (e.g., diameter, component structure, density), and centrality.
  
  
  RESULTS
  Participants reported 488 risk relationships. Few reported an intention to decrease condom use or increase equipment sharing (4% and 1%, respectively). RC intent was reported in 30 existing risk relationships and vaccination was anticipated to elicit the formation of five new relationships. RC resulted in a 5% increase in risk network size (n = 142 to n = 149) and a significant increase in network density. The initiation of risk relationships resulted in the connection of otherwise disconnected network components, with the largest doubling in size from five to ten.
  
  
  CONCLUSIONS
  This study demonstrates a new methodological approach to studying RC and reveals that behavior change following HIV vaccination could potentially impact risk network connectivity. These data will be valuable in parameterizing future network models that can determine if network-level change precipitated by RC would appreciably impact the vaccine's population-level effectiveness.
authors.affiliation: Department of Epidemiology, University of Kentucky, Lexington, Kentucky, United States of America; Center on Drug and Alcohol Research, University of Kentucky, Lexington, Kentucky, United States of America.
authors.forename: April M
authors.initials: AM
authors.lastname: Young
authors.affiliation: LINKS Center for Social Network Analysis, Gatton College of Business and Economics, University of Kentucky, Lexington, Kentucky, United States of America.
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Halgin
authors.affiliation: Department of Behavioral Sciences and Health Education, Emory University, Atlanta, Georgia, United States of America.
authors.forename: Ralph J
authors.initials: RJ
authors.lastname: DiClemente
authors.affiliation: Department of Behavioral Sciences and Health Education, Emory University, Atlanta, Georgia, United States of America.
authors.forename: Claire E
authors.initials: CE
authors.lastname: Sterk
authors.affiliation: Center on Drug and Alcohol Research, University of Kentucky, Lexington, Kentucky, United States of America.
authors.forename: Jennifer R
authors.initials: JR
authors.lastname: Havens
mesh_terms: D016915:AIDS Vaccines / Q000627:therapeutic use; D000328:Adult; D000368:Aged; D055030:Drug Users / Q000523:psychology; D005260:Female; D015658:HIV Infections / Q000453:epidemiology* / Q000517:prevention & control; D006801:Humans; D008875:Middle Aged; D012309:Risk-Taking; D012944:Social Support; D055815:Young Adult
chemical_list: D016915:AIDS Vaccines