Bridging Gaps in the ELSI of Data Science Health Research in Nigeria (BridgELSI)

弥合尼日利亚数据科学健康研究ELSI的差距（BridgELSI） 项目摘要 数据科学有望影响撒哈拉以南非洲的科学研究，创新，发现和医疗保健 (SSA)由于手机和电脑等基础设施的快速发展， 比如人工智能。这些方法和资源为跨越式发展提供了巨大机会 目前的研究，公共卫生和临床护理在非洲通过利用数据科学，以解决巨大的负担， 传染性和非传染性疾病在撒哈拉以南非洲。 然而，尽管有这些承诺，人们对道德、法律的和社会影响仍有很大的担忧 （ELSI）在SSA的数据科学研究。这些问题产生于使用常规和非常规的 数据;在数据科学中生成、操作、存储、共享和利用数据的方法;局限性 在这些情况下的当前知情同意模式以及法律的监督新策略的机会 在尼日利亚的数据科学研究ELSI中。 在尼日利亚生物伦理学和研究中心（CBR）与华盛顿的乔治之间的这个合作项目中， 华盛顿大学和马里兰州医学院（UMSOM），我们将评估当前的法律的 和框架及其执行情况，并利用这些文书和框架， 治理框架，以支持尼日利亚的数据科学健康研究。我们还将实施混合 前瞻性地评估数据科学家的知识、态度和实践（KAP）的研究方法， 在尼日利亚，为当前和新兴的ELSI数据科学研究提供伦理委员会。鉴于数据的新奇 在尼日利亚，我们将实施一般和具体的，短期和中期的数据伦理培训 尼日利亚数据科学研究人员的科学研究，并为成员介绍数据科学 伦理委员会审查数据科学研究项目。

Bridging Gaps in the ELSI of Data Science Health Research in Nigeria (BridgELSI) Project Summary Data science is poised to impact scientific research, innovation, discovery and healthcare in sub-Saharan Africa (SSA) because of the rapid growth of infrastructure such as cell phones and computers, and the availability of technologies like Artificial Intelligence. These methods and resources present huge opportunities to leapfrog current research, public health and clinical care in Africa by utilizing data science to address the huge burden of communicable and non-communicable diseases in SSA. Despite these promises however, there are substantial concerns about the ethical, legal and social implications (ELSI) of data science research in SSA. These concerns arise from the use of conventional and unconventional data; the methods for generating, manipulating, storing, sharing and utilizing data in data science; the limitations of current informed consent models in these scenarios and opportunities for novel strategies for legal oversight of the ELSI of data science research in Nigeria. In this collaborative project between the Center for Bioethics and Research (CBR), Nigeria, George Washington University, DC and University of Maryland School of Medicine (UMSOM), we will evaluate current legal instruments, guidelines and frameworks, and their implementation, and use these to develop new and innovative governance frameworks to support data science health research in Nigeria. We will also implement mixed research methods to prospectively evaluate the knowledge, attitude and practices (KAP) of data scientists and ethics committees to current and emerging ELSI of data science research in Nigeria. Given the novelty of data science in Nigeria, we will implement general and specific, short and medium-term training in ethics of data science research in Nigeria for data science researchers and an introduction to data science for members of ethics committees reviewing data science research projects.