Will HIV Vaccination Reshape HIV Risk Behavior Networks? A Social Network Analysis of Drug Users' Anticipated Risk Compensation
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Mendeley | Further Information

{"title"=>"Will HIV vaccination reshape HIV risk behavior networks? A social network analysis of drug users' anticipated risk compensation", "type"=>"journal", "authors"=>[{"first_name"=>"April M.", "last_name"=>"Young", "scopus_author_id"=>"36492578500"}, {"first_name"=>"Daniel S.", "last_name"=>"Halgin", "scopus_author_id"=>"51561384100"}, {"first_name"=>"Ralph J.", "last_name"=>"DiClemente", "scopus_author_id"=>"7005292881"}, {"first_name"=>"Claire E.", "last_name"=>"Sterk", "scopus_author_id"=>"7005035862"}, {"first_name"=>"Jennifer R.", "last_name"=>"Havens", "scopus_author_id"=>"24457742300"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"373460249", "sgr"=>"84903776198", "issn"=>"19326203", "pmid"=>"24992659", "scopus"=>"2-s2.0-84903776198", "doi"=>"10.1371/journal.pone.0101047", "isbn"=>"0889-2229"}, "id"=>"6f7425be-660b-358b-8404-46762b897e8f", "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. [ABSTRACT FROM AUTHOR]", "link"=>"http://www.mendeley.com/research/hiv-vaccination-reshape-hiv-risk-behavior-networks-social-network-analysis-drug-users-anticipated-ri", "reader_count"=>28, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>3, "Researcher"=>4, "Student > Ph. D. Student"=>5, "Student > Postgraduate"=>1, "Student > Master"=>8, "Other"=>1, "Student > Bachelor"=>1, "Lecturer"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>3, "Researcher"=>4, "Student > Ph. D. Student"=>5, "Student > Postgraduate"=>1, "Student > Master"=>8, "Other"=>1, "Student > Bachelor"=>1, "Lecturer"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Environmental Science"=>1, "Nursing and Health Professions"=>2, "Mathematics"=>1, "Medicine and Dentistry"=>9, "Arts and Humanities"=>1, "Business, Management and Accounting"=>2, "Physics and Astronomy"=>1, "Psychology"=>3, "Social Sciences"=>4, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>9}, "Social Sciences"=>{"Social Sciences"=>4}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>3}, "Computer Science"=>{"Computer Science"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>2}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>3}, "Environmental Science"=>{"Environmental Science"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"Spain"=>1}, "group_count"=>1}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1579680"], "description"=>"<p>Nodes are sized by degree centrality (i.e. number of partners).</p>", "links"=>[], "tags"=>["immunology", "Vaccination and immunization", "vaccines", "Clinical immunology", "immunity", "microbiology", "Medical microbiology", "Microbial pathogens", "Viral pathogens", "Immunodeficiency viruses", "hiv", "epidemiology", "HIV epidemiology", "Infectious disease epidemiology", "Social epidemiology", "health care", "Health care policy", "Health risk analysis", "Infectious diseases", "Viral diseases", "Public and occupational health", "Behavioral and social aspects of health", "research design", "Clinical research design", "injection-related", "networks", "respondents", "named"], "article_id"=>1093005, "categories"=>["Biological Sciences"], "users"=>["April M. Young", "Daniel S. Halgin", "Ralph J. DiClemente", "Claire E. Sterk", "Jennifer R. Havens"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0101047.g002", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sexual_and_injection_related_risk_networks_of_respondents_and_named_alters_/1093005", "title"=>"Sexual and injection-related risk networks of respondents and named alters.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-07-03 02:58:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1579701"], "description"=>"<p><b>Bold</b> indicates responses consistent with intent to engage in risk compensation.</p>a<p>Percentages are based on the total number of participants reporting at least one sexual (n = 353) or equipment-sharing relationship (n = 45). Of note, 31 people reported a relationship with someone with whom they had sex <i>and</i> shared injection equipment. The total number of respondents is greater than 367 because each respondent could give a different response for each named alter.</p>b<p>Percentages for rows corresponding to changes in condom use and equipment sharing are based on the total number of sexual (n = 511) and equipment-sharing relationships (n = 68), respectively.</p>c<p>Number of respondents and dyads in which no change was reported under <i>all</i> three vaccination scenarios.</p>", "links"=>[], "tags"=>["immunology", "Vaccination and immunization", "vaccines", "Clinical immunology", "immunity", "microbiology", "Medical microbiology", "Microbial pathogens", "Viral pathogens", "Immunodeficiency viruses", "hiv", "epidemiology", "HIV epidemiology", "Infectious disease epidemiology", "Social epidemiology", "health care", "Health care policy", "Health risk analysis", "Infectious diseases", "Viral diseases", "Public and occupational health", "Behavioral and social aspects of health", "research design", "Clinical research design", "injection-related", "vaccination"], "article_id"=>1093018, "categories"=>["Biological Sciences"], "users"=>["April M. Young", "Daniel S. Halgin", "Ralph J. DiClemente", "Claire E. Sterk", "Jennifer R. Havens"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0101047.t001", "stats"=>{"downloads"=>2, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Intent_to_engage_in_sexual_and_injection_related_risk_compensation_in_three_HIV_vaccination_scenarios_/1093018", "title"=>"Intent to engage in sexual and injection-related risk compensation in three HIV vaccination scenarios.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-07-03 02:58:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1579675"], "description"=>"<p>Figure 1 displays a network of risk relationships among participants A, B, C and D. The corresponding adjacency matrixes are also presented. The values of the pre- and post-vaccination network ties represent frequency of HIV risk behavior, or the sum of three Likert scales on which participants rated the frequency of unprotected sex and frequency of needle and cooker sharing with the alter. Values in the risk compensation matrix represent the degree of behavior change anticipated to occur after HIV vaccination, with negative numbers representing a decrease in risk behavior, zeros representing no change, and positive numbers representing risk compensation. To construct the post-vaccination matrix, the risk compensation matrix was added to the pre-vaccination matrix. Also, Participant D reported that they would initiate a risk relationship with Participant B, so a tie was added and a one was entered in the corresponding cell of the post-vaccination matrix. Numbers in parentheses represent the symmetrized version of the network; the symmetrized version was used for analysis.</p>", "links"=>[], "tags"=>["immunology", "Vaccination and immunization", "vaccines", "Clinical immunology", "immunity", "microbiology", "Medical microbiology", "Microbial pathogens", "Viral pathogens", "Immunodeficiency viruses", "hiv", "epidemiology", "HIV epidemiology", "Infectious disease epidemiology", "Social epidemiology", "health care", "Health care policy", "Health risk analysis", "Infectious diseases", "Viral diseases", "Public and occupational health", "Behavioral and social aspects of health", "research design", "Clinical research design", "constructing", "pre-", "post-vaccination", "networks"], "article_id"=>1093000, "categories"=>["Biological Sciences"], "users"=>["April M. Young", "Daniel S. Halgin", "Ralph J. DiClemente", "Claire E. Sterk", "Jennifer R. Havens"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0101047.g001", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Illustration_of_procedure_for_constructing_pre_and_post_vaccination_risk_networks_for_comparison_/1093000", "title"=>"Illustration of procedure for constructing pre- and post-vaccination risk networks for comparison.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-07-03 02:58:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1579683"], "description"=>"<p>Number of sexual and injection relationships in the expansive network, with numbers in parentheses indicating the subset of relationships present in the sociometric network (i.e. confirmed ties). Relationships indicated in the shaded portions of the figure (e.g., unprotected sex and equipment sharing) comprise the expansive and sociometric pre-vaccination networks.</p>", "links"=>[], "tags"=>["immunology", "Vaccination and immunization", "vaccines", "Clinical immunology", "immunity", "microbiology", "Medical microbiology", "Microbial pathogens", "Viral pathogens", "Immunodeficiency viruses", "hiv", "epidemiology", "HIV epidemiology", "Infectious disease epidemiology", "Social epidemiology", "health care", "Health care policy", "Health risk analysis", "Infectious diseases", "Viral diseases", "Public and occupational health", "Behavioral and social aspects of health", "research design", "Clinical research design", "relationships", "expansive", "sociometric"], "article_id"=>1093008, "categories"=>["Biological Sciences"], "users"=>["April M. Young", "Daniel S. Halgin", "Ralph J. DiClemente", "Claire E. Sterk", "Jennifer R. Havens"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0101047.g003", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Risk_relationships_in_the_expansive_and_sociometric_networks_/1093008", "title"=>"Risk relationships in the expansive and sociometric networks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-07-03 02:58:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1579703"], "description"=>"<p>SD: standard deviation.</p>a<p>Excluding isolates.</p>b<p>Difference was no statistically significant (p = 0.356).</p>c<p>Difference was not statistically significant (p = 0.139).</p>d<p>Difference was statistically significant (p<0.001).</p>e<p>Difference was statistically significant (p = 0.019).</p>", "links"=>[], "tags"=>["immunology", "Vaccination and immunization", "vaccines", "Clinical immunology", "immunity", "microbiology", "Medical microbiology", "Microbial pathogens", "Viral pathogens", "Immunodeficiency viruses", "hiv", "epidemiology", "HIV epidemiology", "Infectious disease epidemiology", "Social epidemiology", "health care", "Health care policy", "Health risk analysis", "Infectious diseases", "Viral diseases", "Public and occupational health", "Behavioral and social aspects of health", "research design", "Clinical research design", "pre-", "post-vaccination"], "article_id"=>1093020, "categories"=>["Biological Sciences"], "users"=>["April M. Young", "Daniel S. Halgin", "Ralph J. DiClemente", "Claire E. Sterk", "Jennifer R. Havens"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0101047.t002", "stats"=>{"downloads"=>2, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_pre_and_post_vaccination_risk_networks_/1093020", "title"=>"Comparison of pre- and post-vaccination risk networks.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-07-03 02:58:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/1579699"], "description"=>"<p>Nodes are sized by degree centrality (i.e. number of partners). The figure does not include the 95 participants who did not someone with whom they shared equipment or had unprotected sex.</p>", "links"=>[], "tags"=>["immunology", "Vaccination and immunization", "vaccines", "Clinical immunology", "immunity", "microbiology", "Medical microbiology", "Microbial pathogens", "Viral pathogens", "Immunodeficiency viruses", "hiv", "epidemiology", "HIV epidemiology", "Infectious disease epidemiology", "Social epidemiology", "health care", "Health care policy", "Health risk analysis", "Infectious diseases", "Viral diseases", "Public and occupational health", "Behavioral and social aspects of health", "research design", "Clinical research design"], "article_id"=>1093016, "categories"=>["Biological Sciences"], "users"=>["April M. Young", "Daniel S. Halgin", "Ralph J. DiClemente", "Claire E. Sterk", "Jennifer R. Havens"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0101047.g004", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Risk_compensation_within_a_risk_network_of_rural_drug_users_/1093016", "title"=>"Risk compensation within a risk network of rural drug users.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-07-03 02:58:49"}

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