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Social Network Structure and HIV Infection Among Injecting Drug Users in Lithuania: Gatekeepers as Bridges of Infection

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Abstract

The aim of the study was to assess—while controlling for individual risk characteristics—how certain social network structural characteristics (degree, eigenvector, and betweenness centrality) are related to HIV infections. Injecting drug users (N = 299) in Vilnius, Lithuania were recruited using incentivized chain referral sampling for a cross-sectional study. Sociometric social links were established between participants, and UCINET was used to calculate network measures. HIV prevalence was 10 %, and all except two knew they were infected. Of the five variables that remained significant in the final multivariate model, one showed temporal cumulative infection risk (more years since first drug injecting), three reflected informed altruism (always using condoms, less distributive syringe sharing and having not more than one sex partner), and one pointed to the importance of social network structure (betweenness centrality, indicating bridge populations). Loess regression indicates that betweenness may have the highest impact on HIV prevalence (about 60 vs. 20 % estimated HIV prevalence for the highest betweenness centrality values vs. highest age values). This analysis contributes to existing evidence showing both potential informed altruism (or maybe social desirability bias) in connection with HIV infection, and a link between HIV infection risk and the role of bridges within the social network of injecting drug user populations. These findings suggest the importance of harm reduction activities, including confidential testing and counseling, and of social network interventions.

Resumen

El objetivo del estudio fue evaluar—controlando por las características individuales de riesgo—como ciertas características estructurales de la red social se relacionan con la infección por el VIH. La prevalencia del VIH era del 10 %, y todos excepto dos sabían que estaban infectados. De las cinco variables que permanecieron significativas en el modelo multivariado final, uno mostró riesgo de infección acumulada temporal (más años desde la primera drogas inyectables), tres refleja el altruismo informado (usando siempre condones, distribuir menos jeringas y tener más de una pareja sexual), y uno señaló la importancia de la estructura de red social (centralidad betweenness, lo que indica poblaciones puente). Regresión Loess indica que betweenness puede tener el mayor impacto en la prevalencia del VIH (alrededor del 60 frente a 20 % la prevalencia del VIH estimada para los más altos valores de centralidad betweenness contra los valores de mayor edad). Este análisis contribuye a la evidencia existente de altruismo informado (o tal de deseabilidad social) en relación con la infección por el VIH, y un vínculo entre el riesgo de infección por el VIH y el papel de los puentes en la red social de las poblaciones de consumidores de drogas. Estos hallazgos sugieren la importancia de las actividades de reducción de daños, incluyendo pruebas confidenciales y el asesoramiento, y de intervenciones de redes sociales.

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References

  1. Pilon R, Leonard L, Kim J, et al. Transmission patterns of HIV and hepatitis C virus among networks of people who inject drugs. PLoS One. 2011;6:e22245.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  2. Adimora AA, Schoenbach VJ, Doherty IA. HIV and African Americans in the southern United States: sexual networks and social context. Sex Transm Dis. 2006;33:S39–45.

    Article  PubMed  Google Scholar 

  3. Howard DL, Latkin CA. A bridge over troubled waters: factors associated with non-injection drug users having injection drug-using sex partners. J Acquir Immune Defic Syndr. 2006;42:325–30.

    Article  PubMed  Google Scholar 

  4. Young AM, Jonas AB, Mullins UL, Halgin DS, Havens JR. Network structure and the risk for HIV transmission among rural drug users. AIDS Behav. 2013;17(7):2341–51.

    Article  CAS  PubMed  Google Scholar 

  5. Friedman SR, Neaigus A, Jose B, et al. Sociometric risk networks and risk for HIV infection. Am J Public Health. 1997;87:1289–96.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  6. Hanneman RA, Riddle M. Introduction to social network methods. Riverside: University of California, Riverside; 2005.

    Google Scholar 

  7. Gyarmathy VA, Neaigus A, Li N, et al. Liquid drugs and high dead space syringes may keep HIV and HCV prevalence high - a comparison of Hungary and Lithuania. Eur Addict Res. 2010;16:220–8.

    Article  PubMed Central  PubMed  Google Scholar 

  8. Gyarmathy VA, Neaigus A. The effect of personal network exposure on injecting equipment sharing among Hungarian IDUs. Connections. 2006;15:29–42.

    Google Scholar 

  9. Borgatti SP, Everett MG, Freeman LC. Ucinet for Windows: Software for Social Network Analysis. Harvard: Analytic Technologies; 2002.

    Google Scholar 

  10. Cleveland WS, Devlin SJ. Locally weighted regression: an approach to regression analysis by local fitting. J Am Stat Assoc. 1988;83:596–610.

    Article  Google Scholar 

  11. Wikipedia. Local regression. http://en.wikipedia.org/wiki/Local_regression. 2014.

  12. Neaigus A. Gyarmathy VA, Zhao M, Miller M, Friedman SR, and Des Jarlais DC. Sexual and other noninjection risks for HBV and HCV seroconversions among noninjecting heroin users. J Infect Dis. 2007;195:1052–61.

    Article  PubMed  Google Scholar 

  13. de Vos AS, van der Helm JJ, Matser A, Prins M, Kretzschmar ME. Decline in incidence of HIV and hepatitis C virus infection among injecting drug users in Amsterdam; evidence for harm reduction? Addiction. 2013;108(6):1070–81.

    Article  PubMed  Google Scholar 

  14. Rhodes T and Hedrich D. Harm reduction: evidence, impacts and challenges. Office for Official Publications of the European Communities, 2010.

  15. Des Jarlais DC, Perlis T, Arasteh K, et al. “Informed altruism” and “partner restriction” in the reduction of HIV infection in injecting drug users entering detoxification treatment in New York City, 1990-2001. J Acquir Immune Defic Syndr. 2004;35:158–66.

    Article  PubMed  Google Scholar 

  16. Latkin C, Donnell D, Liu TY, Davey-Rothwell M, Celentano D, Metzger D. The dynamic relationship between social norms and behaviors: the results of an HIV prevention network intervention for injection drug users. Addiction. 2013;108(5):934–43.

    Article  PubMed  Google Scholar 

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Acknowledgments

This research was supported by National Institute on Drug Abuse grant number 1R01DA016555-02-S (Network Oriented HIV Prevention Pilot Intervention among Injection Drug Users in Vilnius, Lithuania, PI: Carl Latkin).

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The authors declare no conflict of interest.

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Correspondence to V. Anna Gyarmathy.

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Gyarmathy, V.A., Caplinskiene, I., Caplinskas, S. et al. Social Network Structure and HIV Infection Among Injecting Drug Users in Lithuania: Gatekeepers as Bridges of Infection. AIDS Behav 18, 505–510 (2014). https://doi.org/10.1007/s10461-014-0702-6

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