  We present statistical techniques for analyzing global positioning system
(GPS) data in order to understand, communicate about, and prevent patterns of
violence. In this pilot study, participants in Nairobi, Kenya were asked to
rate their safety at several locations, with the goal of predicting safety and
learning important patterns. These approaches are meant to help articulate
differences in experiences, fostering a discussion that will help communities
identify issues and policymakers develop safer communities. A generalized
linear mixed model incorporating spatial information taken from existing maps
of Kibera showed significant predictors of perceived lack of safety included
being alone and time of day; in debrief interviews, participants described
feeling unsafe in spaces with hiding places, disease carrying animals, and
dangerous individuals. This pilot study demonstrates promise for detecting
spatial patterns of violence, which appear to be confirmed by actual rates of
measured violence at schools. Several factors relevant to community building
consistently predict perceived safety and emerge in participants' qualitative
descriptions, telling a cohesive story about perceived safety and empowering
communication to community stakeholders.
