Understanding the underlying causes of maternal death across all regions of the world is essential to inform policies and resource allocation to reduce the mortality burden. However, in many countries of the world there exists very little data on the causes of maternal death, and data that do exist do not capture the entire population of risk. In this paper we present a Bayesian hierarchical multinomial model to estimate maternal cause of death distributions globally, regionally and for all countries worldwide. The framework combines data from various sources to inform estimates, including data from civil registration and vital systems, smaller-scale surveys and studies, and high-quality data from confidential enquiries and surveillance systems. The framework accounts of varying data quality and coverage, and allows for situations where one or more causes of death are missing. We illustrate the results of the model on three case study countries that have different data availability situations.

翻译：了解世界各区域孕产妇死亡的根本原因,对于为减少死亡负担提供政策和资源分配信息至关重要,然而,在世界上许多国家,关于孕产妇死亡原因的数据很少,而现有的数据不能涵盖所有风险人口。在本文件中,我们提出了一个巴伊西亚等级多民族模型,用以估计全球、区域和全世界所有国家的孕产妇死亡原因分布情况。框架综合了各种来源的数据,以提供估计数,包括民事登记和生命系统的数据、小规模调查和研究以及保密查询和监测系统的高质量数据。数据质量和覆盖范围各不相同,并允许出现一个或多个死亡原因缺失的情况。我们介绍了三个有不同数据提供情况的案例研究国家的模式结果。