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国际卫生突发事件的数据挑战:从十个国际 COVID-19 驱动项目中吸取的教训。

Data challenges for international health emergencies: lessons learned from ten international COVID-19 driver projects.

机构信息

Health Data Research UK, London, UK.

Department of Global Health, Milken Institute School of Public Health, George Washington University, Washington, DC, USA.

出版信息

Lancet Digit Health. 2024 May;6(5):e354-e366. doi: 10.1016/S2589-7500(24)00028-1.

Abstract

The COVID-19 pandemic highlighted the importance of international data sharing and access to improve health outcomes for all. The International COVID-19 Data Alliance (ICODA) programme enabled 12 exemplar or driver projects to use existing health-related data to address major research questions relating to the pandemic, and developed data science approaches that helped each research team to overcome challenges, accelerate the data research cycle, and produce rapid insights and outputs. These approaches also sought to address inequity in data access and use, test approaches to ethical health data use, and make summary datasets and outputs accessible to a wider group of researchers. This Health Policy paper focuses on the challenges and lessons learned from ten of the ICODA driver projects, involving researchers from 19 countries and a range of health-related datasets. The ICODA programme reviewed the time taken for each project to complete stages of the health data research cycle and identified common challenges in areas such as data sharing agreements and data curation. Solutions included provision of standard data sharing templates, additional data curation expertise at an early stage, and a trusted research environment that facilitated data sharing across national boundaries and reduced risk. These approaches enabled the driver projects to rapidly produce research outputs, including publications, shared code, dashboards, and innovative resources, which can all be accessed and used by other research teams to address global health challenges.

摘要

新冠疫情凸显了国际数据共享和获取对于改善全人类健康结果的重要性。国际新冠疫情数据联盟(ICODA)项目使 12 个示范或驱动项目能够利用现有的与健康相关的数据来解决与疫情相关的重大研究问题,并开发出数据科学方法,帮助每个研究团队克服挑战、加速数据研究周期,并快速产生洞察和成果。这些方法还旨在解决数据获取和使用方面的不平等问题,测试伦理健康数据使用方法,并使更广泛的研究人员能够访问摘要数据集和成果。本卫生政策文件重点介绍了来自 19 个国家的研究人员参与的 10 个 ICODA 驱动项目所面临的挑战和经验教训,这些项目涉及各种与健康相关的数据集。ICODA 项目审查了每个项目完成健康数据研究周期各个阶段所花费的时间,并确定了在数据共享协议和数据管理等领域的共同挑战。解决方案包括提供标准的数据共享模板、在早期阶段增加数据管理专业知识,以及建立一个值得信赖的研究环境,促进跨国界的数据共享,降低风险。这些方法使驱动项目能够快速产生研究成果,包括出版物、共享代码、仪表板和创新资源,所有这些都可以被其他研究团队访问和使用,以应对全球健康挑战。

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