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Open Access Research article

Demographic, risk behaviour and personal network variables associated with prevalent hepatitis C, hepatitis B, and HIV infection in injection drug users in Winnipeg, Canada

John L Wylie123*, Lena Shah2 and Ann M Jolly45

Author Affiliations

1 Department of Medical Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada

2 Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada

3 Cadham Provincial Laboratory, Manitoba Health, Winnipeg, Manitoba, Canada

4 The Centre for Infectious Disease Prevention and Control, Population and Public Health Branch, Health Canada, Ottawa, Ontario, Canada

5 Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada

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BMC Public Health 2006, 6:229  doi:10.1186/1471-2458-6-229

Published: 13 September 2006

Abstract

Background

Previous studies have used social network variables to improve our understanding of HIV transmission. Similar analytic approaches have not been undertaken for hepatitis C (HCV) or B (HBV), nor used to conduct comparative studies on these pathogens within a single setting.

Methods

A cross-sectional survey consisting of a questionnaire and blood sample was conducted on injection drug users in Winnipeg between December 2003 and September 2004. Logistic regression analyses were used to correlate respondent and personal network data with HCV, HBV and HIV prevalence.

Results

At the multivariate level, pathogen prevalence was correlated with both respondent and IDU risk network variables. Pathogen transmission was associated with several distinct types of high-risk networks formed around specific venues (shooting galleries, hotels) or within users who are linked by their drug use preferences. Smaller, isolated pockets of IDUs also appear to exist within the larger population where behavioural patterns pose a lesser risk, unless or until, a given pathogen enters those networks.

Conclusion

The findings suggest that consideration of both respondent and personal network variables can assist in understanding the transmission patterns of HCV, HBV, and HIV. It is important to assess these effects for multiple pathogens within one setting as the associations identified and the direction of those associations can differ between pathogens.