Violent event-related fatality patterns in Ethiopia: a Bayesian spatiotemporal perspective
Osafu Augustine Egbon, Asrat Mekonnen Belachew, Ezra Gayawan, and Francisco Louzada

TL;DR
This study applies a Bayesian spatiotemporal model to analyze violent event-related fatalities in Ethiopia from 1997 to 2022, revealing regional patterns and a decline in fatalities over time, aiding policy decisions.
Contribution
It introduces a novel Bayesian spatiotemporal statistical method to map and analyze violence-related fatalities across Ethiopian regions.
Findings
Nine regions have high probabilities (>0.6) of fatality occurrence.
Five regions exceed a 0.7 probability threshold for fatalities.
The probability of more than 20 deaths per event decreased from 0.401 in 2020 to 0.148 in 2022.
Abstract
Fatalities resulting from violence in armed conflict have long been a significant public health issue in Ethiopia. Despite the severity of this problem, more comprehensive quantitative scientific studies need to be conducted to elucidate the sequence and dynamics of these occurrences. In response, this study introduces a spatio-temporal statistical method designed to uncover the patterns of fatalities associated with violent events in Ethiopia. The research employs a two-part zero-inflated Bayesian generalized additive mixed model, which integrates a spatio-temporal component to map the fatality patterns across Ethiopian regions. The dataset utilized originates from the Armed Conflict Location and Event Data Project, covering fatality counts related to violent events from 1997 to 2022. The analysis revealed that nine out of thirteen administrative regions exhibited a probability greater…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsHealth and Conflict Studies · Data-Driven Disease Surveillance · Intimate Partner and Family Violence
