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We present statistical techniques for analyzing global positioning system(GPS) data in order to understand, communicate about, and prevent patterns ofviolence. In this pilot study, participants in Nairobi, Kenya were asked torate their safety at several locations, with the goal of predicting safety andlearning important patterns. These approaches are meant to help articulatedifferences in experiences, fostering a discussion that will help communitiesidentify issues and policymakers develop safer communities. A generalizedlinear mixed model incorporating spatial information taken from existing mapsof Kibera showed significant predictors of perceived lack of safety includedbeing alone and time of day; in debrief interviews, participants describedfeeling unsafe in spaces with hiding places, disease carrying animals, anddangerous individuals. This pilot study demonstrates promise for detectingspatial patterns of violence, which appear to be confirmed by actual rates ofmeasured violence at schools. Several factors relevant to community buildingconsistently predict perceived safety and emerge in participants' qualitativedescriptions, telling a cohesive story about perceived safety and empoweringcommunication to community stakeholders.

Understanding the spatial burden of gender-based violence: Modelling patterns of violence in Nairobi, Kenya through geospatial information