CHaracterizing Effects of Air Quality In Maternal, Newborn and Child Health: The CHEAQI-MNCH Research Project

空气污染是造成全球疾病负担的主要因素，这是一个令人严重关切的问题。 随着撒哈拉以南非洲地区的空气质量显著和迅速恶化， 城镇化、工业化、人口增长加快。协同式联合 热浪和空气污染之间的关系预计会随着气候的变化而加剧， 这对低收入环境中弱势群体的健康构成了严重威胁。 研究表明母体和产前暴露于 环境污染和不良健康后果，突出表明有必要进一步 在非洲人口中进行调查，因为这种脆弱的亚群并不一致 调查过了。暴露在热应激和空气污染中的孕妇 更容易发生不良分娩后果，包括流产、死产、早产、 低出生体重和先兆子痫。制定适当的卫生部门应对措施和 适应性干预依赖于识别这些脆弱人群及其水平 对环境风险的担忧。贫穷、粮食和水不安全等社会经济因素； 获得医疗设施的机会有限，使这些社区的脆弱性永久化。 气温升高期间污染暴露的影响很难衡量 并且需要完善的数据科学和分析方法。目前糟糕的网络 测量空气质量的地面传感器，量化关联的零碎方法 有不良的健康后果，缺乏从证据到干预授权的转换 方法上的范式转变。解决对环境风险缺乏了解的问题 对撒哈拉以南非洲不断变化的流行病学的影响，拟议的研究项目 将致力于量化当前和未来空气污染对产妇和新生儿的影响 通过创新的数据科学方法，如机器学习，通过加速 低成本表征污染暴露数据，同时了解其与 与怀孕、分娩和早期生命有关的不良后果。在此基础上，我们将发展 帮助孕妇及其子女抵御风险的适应性干预措施 由于暴露在污染物中而强加的，并建立了对抗有害健康的高几率的韧性 结果。CHEAQI-MNCH项目将为新兴数据科学家提供一个机会 和非洲的研究人员参与、合作和开发可转让的技能，同时 为知识翻译和传播的大陆资源中心做出贡献 在气候和健康领域。

Air pollution is a leading contributor to the global disease burden, which is a crucial concern as the air quality across sub-Saharan Africa significantly and rapidly deteriorates with accelerated urbanization, industrialization, and population growth. The synergistic association between heat waves and air pollution is expected to exacerbate with the changing climate, which poses a crucial threat to the health of vulnerable populations in low-income settings. Studies which indicate associations between maternal and prenatal exposure to environmental pollution and adverse health outcomes, highlight the need for further investigation in African populations, as such vulnerable subpopulations are not consistently investigated. Pregnant women who are exposed to heat stress coupled with air pollution are more susceptible to adverse birth outcomes including; miscarriages, stillbirth, preterm birth, low birth weight, and preeclampsia. Developing appropriate health sector responses and adaptive interventions relies on identifying these vulnerable populations along with their level of environmental risk. Socio-economic factors such as poverty, food and water insecurity, and limited access to healthcare facilities perpetuate vulnerability among these communities. Impacts of pollution exposure over periods of increased temperatures are difficult to measure and require refined data science and analytical approaches. The current poor networks of ground sensors for measuring air quality, piecemeal approaches to quantifying associations with adverse health outcomes and dearth of translation from evidence to intervention warrants a paradigm shift in approach. To address the lack of understanding of the environmental risk impacts on the changing epidemiology in sub-Saharan Africa, the proposed research project will aim to quantify the current and future impacts of air pollution on maternal and neonatal health through innovative data science approaches such as machine learning, by accelerating low-cost characterization of pollution exposure data while understanding its associations with adverse outcomes related to pregnancy, childbirth and early life. Further to this we will develop adaptive interventions that will help pregnant women and their children counter the risk imposed by exposure to pollutants and build resilience against the high odds of adverse health outcomes. The CHEAQI-MNCH project will provide an opportunity for emerging data scientists and researchers in Africa to engage, collaborate and develop transferrable skills, while contributing to a continental resource center for knowledge translation and dissemination within the fields of climate and health.