The use of emergency medical services (EMS) data to map violence: A case study in Nairobi, Kenya
DOI:
https://doi.org/10.23917/forgeo.v39i1.7199Keywords:
Violence, Emergency Medical Services (EMS), Kenya, Spatial RegressionAbstract
This study investigates the use of emergency medical services (EMS) data as an alternative source for map-ping and understanding violence in Nairobi, Kenya. Given that many crimes go unreported, relying solely on police data can create an incomplete picture of violence hotspots. Using social disorganisation theory as a theoretical framework, this study uses EMS data from fifteen hospitals across three Nairobi sub-counties to map violence and analyse its spatial patterns. A spatial regression model was employed to assess the influ-ence of five social disorganisation variables—unemployment, education, gender, residential mobility and youth demographics—on violence rates, disaggregated by gender. The findings suggest that unemployment is positively correlated with violence, particularly among females, while a higher percentage of youth is un-expectedly associated with lower violence rates. The study demonstrates the value of EMS data for crime mapping in contexts with high levels of unreported crime and offers insights into the spatial distribution of violence in Nairobi, advancing understanding of alternative crime data sources in African urban settings. This approach highlights the utility of EMS data for informing more targeted violence prevention strategies in regions where traditional crime data are limited.
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