With the advent of community policing, the notion of insecurity complexified. New dimensions such as the sense of safety, levels of incivilities, or the fear of crime joined the traditional crime rates to defined its larger perimeter. If, added one to another and often measured by crime victimization surveys, they account better for the notion of local public safety in its globality, the multiplication of indicators is a real challenge for interpretation and complicates comparative analyses and impact studies. We miss a single indicator summarizing the richer information. Advances in computing multidimensional indexes may change this. Inspired by studies of poverty, this paper shows how to compute an index measuring local insecurity while accounting for its complexity. It then formulates a series of synthetic indicators measuring the incidence of insecurity, its severity, rates of extreme insecurity, and “sensitive” neighborhoods. These indicators - and how they can be useful for defining local strategies of community policing - are illustrated with examples from cities in the Republic of Guinea and the Democratic Republic of Congo.
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