Fatality arising from violent events is a critical public health problem in Africa. Although numerous studies on crime and violent events have been conducted, adequate attention has not been given to the distribution of fatalities arising from these events. This study unraveled the spatio-temporal pattern of fatality from violent events in Western and Central Africa. A two-component spatio-temporal zero-inflated model on a continuous spatial domain within a Bayesian framework was adopted. The stochastic partial differential equation was used to quantify the continuous pattern and make projections in unsampled regions. Fatality data from 1997 to 2021 was obtained from the Armed Conflict Location and Event Data Project (ACLED). Findings from the result revealed a spatial and temporal divide in the prevalence of fatality in the study region. Between the years 1997 and 2010, fatality from violence was most prevalent in Central Africa, whereas in more recent years, it was most prevalent in Western Africa. The posterior predictive probabilities of fatality occurrence due to violent events in Nigeria and Cameroon were highest and above 0.6, and the probability of more than one death per violent event is highest in Angola and Chad with probability 0.2. On violent event type, findings showed that suicide bombs had the highest likelihood of fatality occurrence whereas the event of violent non-state actors overtaking territory had the highest impact on the likelihood of multiple fatality counts. Among the armed actors who participated in violent events, armed religious groups were linked to the highest likelihood of fatality occurrence whereas Military forces were linked to the highest likelihood of multiple fatality counts per event. The finding also revealed that there is a higher likelihood of multiple fatalities in the Winter temperate season. These findings could be used for planning and policy design geared towards mitigating fatality and providing a guide towards resource distribution to support the affected communities.

中文翻译：

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西非和中非暴力相关死亡的贝叶斯时空统计模型

暴力事件造成的死亡是非洲的一个严重的公共卫生问题。尽管对犯罪和暴力事件进行了大量研究，但尚未对这些事件造成的死亡人数分布给予足够的关注。这项研究揭示了西非和中非暴力事件死亡的时空模式。采用贝叶斯框架内连续空间域上的二分量时空零膨胀模型。随机偏微分方程用于量化连续模式并在未采样区域进行预测。 1997 年至 2021 年的死亡数据来自武装冲突地点和事件数据项目 (ACLED)。结果发现，研究区域的死亡率存在空间和时间差异。 1997 年至 2010 年间，暴力造成的死亡在中部非洲最为普遍，而近年来，暴力死亡在西非最为普遍。尼日利亚和喀麦隆因暴力事件导致死亡的后验预测概率最高，均在 0.6 以上；安哥拉和乍得每次暴力事件导致 1 人以上死亡的概率最高，为 0.2。在暴力事件类型方面，调查结果显示，自杀式炸弹造成死亡的可能性最高，而暴力非国家行为者占领领土的事件对多人死亡的可能性影响最大。在参与暴力事件的武装行为者中，武装宗教团体与发生死亡的可能性最高有关，而军队与每次事件造成多人死亡的可能性最高有关。研究结果还表明，温带冬季发生多人死亡的可能性更高。这些发现可用于旨在减少死亡的规划和政策设计，并为支持受影响社区的资源分配提供指导。