Sharing and inappropriate discarding of syringes and drug use equipment can lead to transmission of bloodborne pathogens and decreased sense of community safety. To reduce these risks, interventions such as syringe drop boxes, are implemented. However, little consideration has been made of the social and spatial networks of the injection drug use (IDU) populations in the placement of these drop boxes. A sample of IDU was obtained through respondent driven sampling in Winnipeg, Canada in 2009. Characteristics of the sample and distribution of these characteristics through the social network were assessed. A spatial network was constructed which focused on the connections between IDU and specific geographic locations. Measures of centrality were calculated using Pajek and the geographic network was mapped using ArcGIS. Analysis of the social network revealed variation among network components in demographic and drug use characteristics. Spatial analysis revealed geographic clustering, quantified through network centrality measures. There was congruence between locations of high degree and current drop box placement in Winnipeg. This research illustrates the benefit of combining IDU social network and spatial data to inform evidence-based municipal policies and programs.

Sharing and inappropriate discarding of syringes and drug use equipment can lead to transmission of bloodborne pathogens and decreased sense of community safety. To reduce these risks, interventions such as syringe drop boxes, are implemented. However, little consideration has been made of the social and spatial networks of the injection drug use (IDU) populations in the placement of these drop boxes. A sample of IDU was obtained through respondent driven sampling in Winnipeg, Canada in 2009. Characteristics of the sample and distribution of these characteristics through the social network were assessed. A spatial network was constructed which focused on the connections between IDU and specific geographic locations. Measures of centrality were calculated using Pajek and the geographic network was mapped using ArcGIS. Analysis of the social network revealed variation among network components in demographic and drug use characteristics. Spatial analysis revealed geographic clustering, quantified through network centrality measures. There was congruence between locations of high degree and current drop box placement in Winnipeg. This research illustrates the benefit of combining IDU social network and spatial data to inform evidence-based municipal policies and programs.