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

开发数据科学解决方案以减轻非洲气候变化对健康的影响：HE2AT 中心

• 批准号: 10314149
• 负责人: Matthew Francis Chersich
• 金额: $ 130万
• 依托单位: WITS HEALTH CONSORTIUM (PTY), LTD
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-15 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10314149
• 关键词: Address; Adopted; Africa; Africa South of the Sahara; African; Air; Basic Science; Behavioral; Behavioral Sciences; Biometry; Birth Weight; Centers for Disease Control and Prevention (U.S.); Characteristics; Climate; Climatology; Clinical; Clinical Medicine; Collaborations; Communities; Computers; Dangerousness; Data; Data Analyses; Data Science; Data Scientist; Data Sources; Development; Disease; Ecosystem; Elements; Environmental Exposure; Environmental Health; Event; Future; General Population; Geography; Goals; Government; Health; Health Sciences; Heat Waves; Housing; Individual; Industrialization; Industry; Influentials; Institution; Ivory Coast; Knowledge; Link; Low income; Machine Learning; Morbidity - disease rate; Outcome; Output; Participant; Pilot Projects; Planets; Policies; Pre-Eclampsia; Pregnant Women; Premature Birth; Preparation; Public Health; Research; Research Activity; Research Priority; Research Project Grants; Resources; Risk; Risk Factors; Scientist; Series; Social Sciences; Software Design; South Africa; Specificity; System; Techniques; Technology; Temperature; Testing; Time; Training; Training Support; United States; Universities; Vertebral column; Vulnerable Populations; Weather; Work; base; built environment; burden of illness; career; climate change; climate data; climate impact; cohort; complex data; computer science; data ecosystem; data management; data repository; data reuse; digital; doctoral student; extreme heat; global temperature; hazard; health data; high risk; high risk population; innovation; interest; machine learning algorithm; maternal outcome; mortality; neonatal outcome; neonate; programs; prospective; response; risk prediction; social; statistics; urban area; urban setting

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.

HE2AT中心整体-项目摘要/摘要 世界气候正在迅速变化，全球气温自 工业革命，到2040年，气温可能进一步上升0.5摄氏度。热浪和不断上升的气温 对健康的重大影响，特别是对低收入弱势群体的影响，虽然没有得到充分认识 设置。非洲热能与健康跨学科中心(HE2AT中心)的总体目标是 开发创新的解决方案，以减轻非洲气候变化对健康的影响。的财团 学术和非学术合作伙伴来自撒哈拉以南非洲和美国， 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 科学家们。该中心将系统地发展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，以及两个现有高度集中的地理空间数据 补充数据平台(IBM-PAIES和开普敦大学)。在五年内，我们将 实施两个研究项目和10-12个试点项目，全部由 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表征热暴露的临床结果 孕妇和新生儿。我们将重复使用来自队列和孕妇试验的数据，并 自2000年以来，在撒哈拉以南非洲地区进行了一次新生儿调查。来自系统识别的数据 研究将整合到来自数据储存库和数据所有者的个人参与者数据平台中。 然后，分析高温暴露与结局(早产、出生体重和早产)之间的关系。 子痫)将提供与高温相关的疾病负担的量化信息。最后，综合所有调查结果，我们将 试点区级气候变化指标，这是首个此类指标。第二个项目评估了 在科特省阿比让使用地理空间和热害分析的脆弱城市环境中与热有关的发病率 科特迪瓦和南非约翰内斯堡。这个项目使用了更复杂的数据和数据源 例如，环境和地形，以评估热健康影响，以及这些影响在城市中的变化情况 地理位置。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 根据他们的个性化风险，向人们提供关于他们的热健康疾病预测风险的信息 简档，由考虑到天气条件的机器学习算法确定，个人 特征、地理位置和其他驱动风险的因素。这些系统是热浪的中心要素。 应对措施，允许为高温事件做好充分准备，这对弱势群体尤其重要 和工业。我们将与DS-I非洲联盟的其他枢纽和部分成员密切合作，支持 他们需要将气候数据纳入他们的研究活动，反之亦然。