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Injection drug network characteristics as a predictor of injection behaviour
Social network characteristics of people who inject drugs (PWID) have previously been flagged as potential risk factors for HCV transmission such as increased injection frequency. To understand the role of the injecting network on injection frequency, we investigated how changes in an injecting netw...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6518653/ https://www.ncbi.nlm.nih.gov/pubmed/31063105 http://dx.doi.org/10.1017/S095026881900061X |
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author | Spelman, Tim Sacks-Davis, Rachel Dietze, Paul Higgs, Peter Hellard, Margaret |
author_facet | Spelman, Tim Sacks-Davis, Rachel Dietze, Paul Higgs, Peter Hellard, Margaret |
author_sort | Spelman, Tim |
collection | PubMed |
description | Social network characteristics of people who inject drugs (PWID) have previously been flagged as potential risk factors for HCV transmission such as increased injection frequency. To understand the role of the injecting network on injection frequency, we investigated how changes in an injecting network over time can modulate injecting risk behaviour. PWID were sourced from the Networks 2 Study, a longitudinal cohort study of PWID recruited from illicit drug street markets across Melbourne, Australia. Network-related correlates of injection frequency and the change in frequency over time were analysed using adjusted Cox Proportional Hazards and Generalised Estimating Equations modelling. Two-hundred and eighteen PWID followed up for a mean (s.d.) of 2.8 (1.7) years were included in the analysis. A greater number of injecting partners, network closeness centrality and eigenvector centrality over time were associated with an increased rate of infection frequency. Every additional injection drug partner was associated with an increase in monthly injection frequency. Similarly, increased network connectivity and centrality over time was also associated with an increase in injection frequency. This study observed that baseline network measures of connectivity and centrality may be associated with changes in injection frequency and, by extension, may predict subsequent HCV transmission risk. Longitudinal changes in network position were observed to correlate with changes in injection frequency, with PWID who migrate from the densely-connected network centre out to the less-connected periphery were associated with a decreased rate of injection frequency. |
format | Online Article Text |
id | pubmed-6518653 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-65186532019-06-04 Injection drug network characteristics as a predictor of injection behaviour Spelman, Tim Sacks-Davis, Rachel Dietze, Paul Higgs, Peter Hellard, Margaret Epidemiol Infect Original Paper Social network characteristics of people who inject drugs (PWID) have previously been flagged as potential risk factors for HCV transmission such as increased injection frequency. To understand the role of the injecting network on injection frequency, we investigated how changes in an injecting network over time can modulate injecting risk behaviour. PWID were sourced from the Networks 2 Study, a longitudinal cohort study of PWID recruited from illicit drug street markets across Melbourne, Australia. Network-related correlates of injection frequency and the change in frequency over time were analysed using adjusted Cox Proportional Hazards and Generalised Estimating Equations modelling. Two-hundred and eighteen PWID followed up for a mean (s.d.) of 2.8 (1.7) years were included in the analysis. A greater number of injecting partners, network closeness centrality and eigenvector centrality over time were associated with an increased rate of infection frequency. Every additional injection drug partner was associated with an increase in monthly injection frequency. Similarly, increased network connectivity and centrality over time was also associated with an increase in injection frequency. This study observed that baseline network measures of connectivity and centrality may be associated with changes in injection frequency and, by extension, may predict subsequent HCV transmission risk. Longitudinal changes in network position were observed to correlate with changes in injection frequency, with PWID who migrate from the densely-connected network centre out to the less-connected periphery were associated with a decreased rate of injection frequency. Cambridge University Press 2019-04-05 /pmc/articles/PMC6518653/ /pubmed/31063105 http://dx.doi.org/10.1017/S095026881900061X Text en © The Author(s) 2019 http://creativecommons.org/licenses/by/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Paper Spelman, Tim Sacks-Davis, Rachel Dietze, Paul Higgs, Peter Hellard, Margaret Injection drug network characteristics as a predictor of injection behaviour |
title | Injection drug network characteristics as a predictor of injection behaviour |
title_full | Injection drug network characteristics as a predictor of injection behaviour |
title_fullStr | Injection drug network characteristics as a predictor of injection behaviour |
title_full_unstemmed | Injection drug network characteristics as a predictor of injection behaviour |
title_short | Injection drug network characteristics as a predictor of injection behaviour |
title_sort | injection drug network characteristics as a predictor of injection behaviour |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6518653/ https://www.ncbi.nlm.nih.gov/pubmed/31063105 http://dx.doi.org/10.1017/S095026881900061X |
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