How many HIV infections are prevented by Vancouver Canada's supervised injection facility?

Abstract Mathematical modelling analyses of drug injection-related HIV risk reduction interventions can provide policy makers, researchers, and others with important information that would be difficult to obtain through other means. The validity of the results of mathematical modelling analyses that rely on secondary data sources critically depends on the model(s) employed in the analyses and the parameter values used to populate the models. A recent article in the International Journal of Drug Policy by Andresen and Boyd (2010: 70–76) utilised four different mathematical models of injection-related HIV transmission to estimate the number of HIV infections prevented by Vancouver Canada's Insite supervised injection facility (SIF). The present article reviews and critiques the mathematical models utilised in the Andresen and Boyd article, then describes an alternative—and potentially more accurate—method for estimating the impact of the Insite SIF. This model indicates that the SIF prevents approximately 5–6 infections per year, with a plausible range of 4–8 prevented infections. These estimates are far smaller than suggested by Andresen and Boyd (19–57 prevented infections).