Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
Dr. Bing Zhang Department of Statistics, University of Kentucky, Lexington, KY, United States.
Front Public Health. 2021 Oct 11;9:710961. doi: 10.3389/fpubh.2021.710961. eCollection 2021.
Technological advances now make it possible to generate diverse, complex and varying sizes of data in a wide range of applications from business to engineering to medicine. In the health sciences, in particular, data are being produced at an unprecedented rate across the full spectrum of scientific inquiry spanning basic biology, clinical medicine, public health and health care systems. Leveraging these data can accelerate scientific advances, health discovery and innovations. However, data are just the raw material required to generate new knowledge, not knowledge on its own, as a pile of bricks would not be mistaken for a building. In order to solve complex scientific problems, appropriate methods, tools and technologies must be integrated with domain knowledge expertise to generate and analyze big data. This integrated interdisciplinary approach is what has become to be widely known as data science. Although the discipline of data science has been rapidly evolving over the past couple of decades in resource-rich countries, the situation is bleak in resource-limited settings such as most countries in Africa primarily due to lack of well-trained data scientists. In this paper, we highlight a roadmap for building capacity in health data science in Africa to help spur health discovery and innovation, and propose a sustainable potential solution consisting of three key activities: a graduate-level training, faculty development, and stakeholder engagement. We also outline potential challenges and mitigating strategies.
技术进步使得在从商业到工程再到医学等广泛应用中生成多样化、复杂和不同大小的数据成为可能。在健康科学领域,特别是在跨越基础生物学、临床医学、公共卫生和医疗保健系统的整个科学研究领域,数据的产生速度以前所未有的速度增长。利用这些数据可以加速科学进步、健康发现和创新。然而,数据只是生成新知识所需的原材料,本身并不是知识,就像一堆砖头不会被误认为是建筑物一样。为了解决复杂的科学问题,必须将适当的方法、工具和技术与领域知识专业知识相结合,以生成和分析大数据。这种综合的跨学科方法就是广为人知的数据科学。尽管在资源丰富的国家,数据科学学科在过去几十年中迅速发展,但在资源有限的环境中,情况并不乐观,例如大多数非洲国家,主要是因为缺乏受过良好培训的数据科学家。在本文中,我们强调了在非洲建立健康数据科学能力的路线图,以帮助促进健康发现和创新,并提出了一个由三个关键活动组成的可持续潜在解决方案:研究生培训、教师发展和利益相关者参与。我们还概述了潜在的挑战和缓解策略。