or direct observations. The number of overdose events in the SIF (nfODSIF) was compiled from the facility’s comprehensive on-site surveillance database. This system was the source of data for an earlier analysis of SIF overdose patterns and has already been described in detail [15]. Briefly, all new clients must register at the SIF using a pseudonymous identifier and basic information (i.e., gender and age). All activities in the SIF, including the type and amount of substances injected, the characteristics of overdose events and the interventions taken in response, are entered into the database and associated with the client’s identifier. For this analysis, we accessed a dataset from the SIF with all pseudonymous identifiers stripped. In order to limit our analysis to on-site overdose events that might conceivably resulted in a death, we restricted our definition of a potentially-fatal overdose event as any that required the provision of naloxone, a 911 call and/or an ambulance. The ratio of fatal to non-fatal overdoses in the DTES was estimated using data from various official or peer-reviewed sources. The incidence of fatal overdose (fODDTES) was calculated using counts of drug-induced deaths in the Downtown Eastside published annually by the British Columbia Vital Statistics Agency [36-44]. As these totals included deaths from drug overdose as well as suicide by drug poisoning and adverse events from medications, we multiplied the counts by 75%, the approximate proportion of deaths from drug overdoses [44]. The number of person-years at risk was calculated using estimates of the size of the IDU population in the DTES in two recent capture-recapture studies [29,30]. The local incidence of non- fatal overdose (nfODDTES) was estimated from a review of cross- sectional and longitudinal surveys of active IDU in both domestic and international settings [3,5,14,23,24,31,45–52]. Both rates were expressed per 1,000 person years. A small amount of data was missing and its value was imputed. Counts of drug-induced deaths in the DTES were unavailable for 2007 and 2008. Thus, the median number of fatal overdoses per annum between 1997 and 2006 was used for both 2007 and 2008. For 2008, we multiplied this number by the proportion of the year included in our study period. We accounted for the uncertainty in some model parameters in two ways. First, we performed a Monte Carlo simulation for each year of the study period and the entire study period. By permitting the mean, variability and distribution for each model value to be References 1. (2007) Unintentional poisoning deaths-United States, 1999–2004. MMWR: Morbidity and mortality weekly report 56: 93–96. 2. Degenhardt L, Roxburgh A, Barker B (2005) Underlying causes of cocaine, amphetamine and opioid related deaths in Australia. Journal of clinical forensic medicine 12: 187–195. 3. Fischer B, Brissette S, Brochu S, Bruneau J, el-Guebaly N, et al. 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Second, owing to the wide range of non-fatal overdose rates cited in the literature, we conducted a sensitivity analysis by repeating the Monte Carlo simulation three times, using different plausible values for the local non-fatal overdose rate: 50 per 1,000 person years, reflecting the lowest value observed in a local cohort of IDU [24]; 200 per 1,000 person years, the median value observed in a local cohort of IDU [14]; and 300 per 1,000 person years, the largest external estimate observed [31]. In a subanalyses, we calculated estimates of the number of non- fatal overdoses in the DTES for each year in the study period as well as the entire study period. These estimates are the product of the number of fatal overdoses defined in the model multiplied by the non-fatal to fatal overdose ratio. As above, we performed Monte Carlo simulations using three different non-fatal overdose rates to calculate three point estimates with 95% CI. 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