A collaborative approach to advancing research and training in Public Health Data Science—challenges, opportunities, and lessons learnt

The unprecedented availability of increasingly complex, voluminous, and multi-dimensional data as well as the emergence of data science as an evolving field provide ideal opportunities to address the multi-faceted public health challenges faced by low and middle income countries (LMIC), especially those in sub-Saharan Africa. However, there is a severe lack of well-trained data scientists and home-grown educational programs to enable context-specific training. The lack of human capacity and resources for public health data analysis as well as the dire need to use modern technology for better understanding and possible intervention cannot be dealt with currently available educational programs and computing infrastructure, demanding a great deal of collaboration and investments within Africa and with the Global North This paper describes processes undertaken to establish sustainable research training programs and to train a new generation of data scientists with knowledge, mentoring, professional skills, and research immersion. The goal is to position them for rigorous, biomedically grounded and ethically conscious Public Health Data Science practice with a focus on Ethiopia and Kenya. The programs are realized through partnership among Columbia University (CU, USA), Addis Ababa University (AAU, Ethiopia), and the University of Nairobi (UoN, Kenya). In this paper, we describe the collaborative project named "<i>Advancing Public Health Research in Eastern Africa through Data Science Training (APHREA-DST)"</i> delving on its conceptualization, implementation framework and activities undertaken. We adopted both qualitative and quantitative approaches to understand the needs of the stakeholders for such educational and training programs. Through harmonized online surveys and stakeholder engagements via focus group discussions in Ethiopia and Kenya, a curriculum was developed for a masters degree program in Public Health Data Science (PHDS). Moreover, the engagement with local projects in both countries as well as active collaboration with other data science related projects in Africa under DSI-Africa consortium benefited the project to start the M. Sc. program successfully. So far, the launching of the graduate program in both countries and the two-cycle experience sharing program done at Columbia University as well as the numerous MoUs signed between partners for data sharing and internships are the major successes of the project. In this paper, we discuss in detail the challenges faced as well as the existing opportunities and lessons learnt this far in implementing this tripartite collaborative teaching and research project.