Developing data science solutions to mitigate the health impacts of climate change in Africa: the HE2AT Center

HE2AT 中心整体 - 项目摘要/摘要 世界气候正在迅速变化，自2017年以来全球气温已上升超过1°C 工业革命，到 2040 年，气温可能进一步上升 0.5°C。热浪和气温上升已经 尽管未得到充分重视，但仍对健康产生重大影响，特别是对低收入弱势群体 设置。非洲热与健康跨学科中心（HE2AT 中心）的总体目标是 开发创新解决方案以减轻非洲气候变化对健康的影响。该财团 学术和非学术合作伙伴来自撒哈拉以南非洲各地和美国， 并组成一个跨学科小组，包括热生理学家、生物医学和气候内容专家， 公共卫生从业者、社会行为科学家以及统计学家以及计算机和数据 科学家。该中心将系统地开发一个包含生物医学数据的数据生态系统，与 天气、空气质量和其他环境数据，以及两个现有高度相关的其他地理空间数据 互补数据平台（IBM-PAIRS 和开普敦大学）。五年内我们将 实施两个研究项目和 10-12 个试点项目，所有项目均得到简化和支持 管理、数据管理和分析以及培训和参与核心。第一个项目将 实施创新的数据科学方法来描述热暴露的临床结果 孕妇和新生儿。我们将重复使用来自孕妇和孕妇的队列和试验的数据 自 2000 年以来在撒哈拉以南非洲地区开展的新生儿研究。数据来自系统识别的 研究将被整合到来自数据存储库和数据所有者的个人参与者数据平台中。 然后，分析热暴露与结局（早产、出生体重和预产期）之间的关系。 子痫）将有助于量化与热相关的疾病负担。最后，将所有发现综合起来，我们将 试点地区级气候变化指标，这在同类指标中尚属首次。第二个项目评估了 利用科特迪瓦阿比让的地理空间和热危害分析，了解脆弱城市环境中与热相关的发病率 科特迪瓦和南非约翰内斯堡。该项目使用了更复杂的数据和构建的数据源 例如，环境和地形，以评估高温对健康的影响，以及这些影响在城市中的差异 地理。活动将为早期预警系统的开发提供信息，包括一个数字应用程序， 根据人们的个性化风险，向他们提供有关热健康疾病预测风险的信息 配置文件，由机器学习算法确定，该算法考虑了天气条件、个人情况 特征、地理位置和其他导致风险的因素。这些系统是热浪的核心要素 应对措施，为高温事件做好充分准备，这对于弱势群体尤其重要 和工业。我们将与 DS-I 非洲联盟的其他中心和部分机构密切合作，支持 他们将气候数据纳入其研究活动，反之亦然。

HE2AT Center Overall - Project summary/abstract The world's climate is changing rapidly, with global temperatures having risen more than 1°C since the industrial revolution, and a further 0.5°C increase is likely by 2040. Heat waves and rising temperatures have major, though underappreciated, health implications, particularly for vulnerable populations in low-income settings. The overarching objective of the Heat and Health African Transdisciplinary Center (HE2AT Center) is to develop innovative solutions to mitigate the health impacts of climate change in Africa. The consortium of academic and non-academic partners is drawn from across sub-Saharan Africa and from the United States, and constitutes a transdisciplinary group, including heat physiologists, biomedical and climate content experts, public health practitioners, social-behavioral scientists as well as statisticians, and computer and data scientists. The Center will systematically develop a data ecosystem containing biomedical data, integrated with weather, air quality and other environmental data, and other geospatial data within two existing highly- complementary data platforms (IBM-PAIRS and the University of Cape Town). Over five years we will implement two Research Projects and 10-12 Pilot Projects, all streamlined and supported by the Administration, Data Management and Analysis, and Training and Engagement Cores. The first Project will implement an innovative data science approach to characterize the clinical outcomes of heat exposure in pregnant women and neonates. We will reuse data from cohorts and trials among pregnant women and neonates conducted across sub-Saharan Africa since the year 2000. Data from systematically identified studies will be integrated in an Individual Participant Data platform from data repositories and data owners. Then, analyses of relationships between heat exposure and outcomes (preterm birth, birth weight and pre- eclampsia) will inform quantification of heat-related disease burden. Finally, taking all findings together, we will pilot a district-level climate change indicator, the first of its kind. The second Project assesses the burden of heat-related morbidity in vulnerable urban settings using geospatial and heat hazard analyses in Abidjan, Cote d'Ivoire and Johannesburg, South Africa. This Project uses more complex data and data sources on the built environment and topography, for example, to assess heat-health impacts, and how these vary across urban geographies. Activities will inform development of an Early Warning System, including a digital App that delivers information to people on their forecasted risks of heat-health disease, based on their individualized risk profile, as determined by a machine learning algorithm which takes into account weather conditions, individual characteristics, geolocation and other factors that drive risk. These systems are a central element in heatwave responses, allow for adequate preparations for heat events, which is especially important for vulnerable groups and industry. We will collaborate closely with other Hubs and parts of the DS-I Africa consortium, supporting them to incorporate climate data within their research activities, and vice versa.