Mapping maternal mortality rate via spatial zero-inflated models for count data: A case study of facility-based maternal deaths from Mozambique

Maternal mortality remains very high in Mozambique, with estimates from 2015 showing a maternal mortality ratio of 489 deaths per 100,000 live births, even though the rates tend to decrease since 1990. Pregnancy related hemorrhage, gestational hypertension and diseases such as malaria and HIV/AIDS are amongst the leading causes of maternal death in Mozambique, and a significant number of these deaths occur within health facilities. Often, the analysis of data on maternal mortality involves the use of counts of maternal deaths as outcome variable. Previously we showed that a class of hierarchical zero-inflated models were very successful in dealing with overdispersion and clustered counts when analyzing data on maternal deaths and related risk factors within health facilities in Mozambique. This paper aims at providing additional insights over previous analyses and presents an extension of such models to account for spatial variation in a disease mapping framework of facility-based maternal mortality in Mozambique.莫桑比克的孕产妇死亡率（maternal mortality）仍处于较高水平，据2015年估算数据，其孕产妇死亡率比值（maternal mortality ratio）为每10万活产489例死亡，尽管自1990年以来该比率已呈下降趋势。妊娠出血（pregnancy-related hemorrhage）、妊娠高血压（gestational hypertension）以及疟疾、艾滋病（HIV/AIDS）等疾病是莫桑比克孕产妇死亡的主要诱因，且有相当比例的死亡案例发生在医疗卫生机构内。通常而言，孕产妇死亡率相关数据分析会将孕产妇死亡人数作为结局变量（outcome variable）开展建模分析。此前我们的研究表明，在分析莫桑比克医疗卫生机构内的孕产妇死亡及相关危险因素数据时，一类分层零膨胀模型（hierarchical zero-inflated models）能够有效处理过度离散（overdispersion）与聚集性计数数据（clustered counts）的问题。本研究旨在为既往相关分析提供补充见解，并针对莫桑比克基于医疗卫生机构的孕产妇死亡率疾病制图框架（disease mapping framework），提出上述模型的扩展版本以纳入空间变异（spatial variation）因素。