General characteristics of the reviewed studies.

IntroductionMathematical modelling is a commonly utilised tool to predict the impact of policy on health outcomes globally. Given the persistently high levels of maternal and perinatal morbidity and mortality in sub-Saharan Africa, mathematical modelling is a potentially valuable tool to guide strategic planning for health and improve outcomes.MethodsThe aim of this scoping review was to explore the characteristics of mathematical models and modelling studies evaluating the impact of maternal and/or perinatal healthcare interventions or services on health-related outcomes in the region. A search across three databases was conducted on 2nd November 2023 which returned 8660 potentially relevant studies, from which 60 were included in the final review. Characteristics of these studies, the interventions which were evaluated, the models utilised, and the analyses conducted were extracted and summarised.ResultsFindings suggest that the popularity of modelling within this field is increasing over time with most studies published after 2015 and that population-based, deterministic, linear models were most frequently utilised, with the Lives Saved Tool being applied in over half of the reviewed studies (n = 34, 57%). Much less frequently (n = 6) models utilising system-thinking approaches, such as individual-based modelling or systems dynamics modelling, were developed and applied. Models were most applied to estimate the impact of interventions or services on maternal mortality (n = 34, 57%) or neonatal mortality outcomes (n = 39, 65%) with maternal morbidity (n = 4, 7%) and neonatal morbidity (n = 6, 10%) outcomes and stillbirth reported on much less often (n = 14, 23%).DiscussionGoing forward, given that healthcare delivery systems have long been identified as complex adaptive systems, modellers may consider the advantages of applying systems-thinking approaches to evaluate the impact of maternal and perinatal health policy. Such approaches allow for a more realistic and explicit representation of the systems- and individual- level factors which impact the effectiveness of interventions delivered within health systems.

引言：数学建模是全球范围内预测政策对健康结局影响的常用工具。鉴于撒哈拉以南非洲地区孕产妇和围产期发病率与死亡率持续处于高位，数学建模或可成为指导卫生战略规划、改善健康结局的极具价值的工具。
方法：本范围综述（scoping review）旨在探讨评估撒哈拉以南非洲地区孕产妇和/或围产期医疗干预措施或服务对健康相关结局影响的数学模型及建模研究的特征。研究于2023年11月2日检索了3个数据库，共检索到8660篇潜在相关研究，最终纳入60篇进行综述。研究人员提取并总结了纳入研究的特征、所评估的干预措施、所采用的模型以及所开展的分析内容。
结果：研究结果显示，该领域的建模研究热度随时间推移持续攀升，多数研究发表于2015年之后；其中基于人群的确定性线性模型最为常用，拯救生命工具（Lives Saved Tool）在超过半数的纳入综述研究中得到应用（n=34，占比57%）。采用系统思维方法（system-thinking approaches）的模型，如个体为基础的建模（individual-based modelling）或系统动力学建模（systems dynamics modelling），其开发与应用则相对较少（n=6）。模型最常被用于评估干预措施或服务对孕产妇死亡率（n=34，占比57%）或新生儿死亡率结局（n=39，占比65%）的影响，而孕产妇发病率（n=4，占比7%）、新生儿发病率（n=6，占比10%）结局以及死胎的相关报道则相对较少（n=14，占比23%）。
讨论：鉴于医疗服务系统长期以来被认定为复杂自适应系统（complex adaptive systems），未来建模研究者或可考虑采用系统思维方法，以评估孕产妇和围产期卫生政策的影响。此类方法能够更真实且清晰地展现影响卫生系统内所实施干预措施有效性的系统层面与个体层面因素。