International Journal of Drug Policy - 2014

Volume 25 Issue 3 May 2014

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Page 17 of 153

518 A.N. Martinez et al. / International Journal of Drug Policy 25 (2014) 516–524 Fig. 1. Participant locations of sleeping, hanging out and using drugs (N = 2861). usually use drugs. Routes were not drawn for participants with more than one missing location. Calculation of activity space routes is made possible through the use of a San Francisco street network shapefile accessed from the public GIS portal through the City and County of San Francisco. After activity space routes were success- fully created in ArcGIS, we created two new variables: activity space distances and syringe exchange program accessibility. Activity space distances To calculate the distance between the locations where partici- pants sleep, where participants hang out, and where participants use drugs, we used the OD (origin-destination) Cost Matrix tool in the Network Analyst extension. The OD cost matrix finds and measures distance between points along a street network, rather than a straight-line, from multiple origins to multiple destinations. When configuring an OD cost matrix analysis, it is possible to spec- ify the number of destinations to find. We specified the point of origin as where participants sleep. The OD cost matrix calculated the shortest route distance, measured in units of miles, between where participants sleep, where they hang out, and where they use drugs. Distance of the entire activity space route The OD cost matrix analysis calculated the total distance of the activity space routes. Syringe program accessibility We used the 'points to lines' join feature in ArcGIS to identify if individual activity space routes intersect with location of SEPs. A

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