Citation

Friedberg R, Sarnquist C, Nyairo G, Amuyunzu-Nyamongo M, Baiocchi M. arXiv 2020; arXiv:2002.06710v1.

Copyright

(Copyright © 2020, The author(s), Publisher Cornell University Library)

DOI

unavailable

PMID

unavailable

Abstract

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.

Keywords

Statistics - Applications