Inflammation and Immunity Driver Programme

My Journey into Health Data Science

9 November 2023: Dobgima Mofor recounts the series of events that led him to pursue a career in health data research.

Portrait image of Dobgima Mofor standing next to a banner at the opening ceremony for the HDR UK Health Data Science Black Internship Programme 2023
Dobgima at the opening ceremony for the 2023 the HDR UK Health Data Science Black Internship Programme.

Growing up in Cameroon and excelling in the sciences, I like most of my peers had eyes set on a career in engineering or medicine. I wanted to help address the ever-increasing health challenges of my immediate society.

From attending a primary school right next to the University of Buea (or UB as it is fondly called - known for its research projects targeted towards eliminating tropical diseases), to gaining admission into Sacred Heart College Mankon Bamenda (one of the country’s prestigious and renowned secondary schools), I had the opportunity to observe and learn from some of the world’s finest STEM teachers and practitioners. Although my fondness for literature made me consider a future in the Arts, I eventually registered for all sciences in my A-level exams where I particularly excelled in the quantitative modules. Challenged by the limited opportunities for pursuing a traditional health career, I sought to get into research. Inspired by exciting projects aimed at eliminating Neglected Tropical Diseases, I enrolled for a BSc in Microbiology and Parasitology at the University of Buea where I was introduced to scientific research by internationally acclaimed academics.

My undergraduate and internship experiences made me aware of the knowledge gaps in the health system and motivated me to seek further education. To understand better how inferential statistical methods could generate evidence to influence policy, I returned to UB for a Master’s in Epidemiology and Control of Infectious Diseases. Unfortunately, the raging sociopolitical conflict in this part of the country meant significant disruptions to the course. However, being grounded in core mathematical concepts integral to statistical sciences like Epidemiology, I was able to study independently, supplementing my class work with resources from online courses. A two-month seminar with the International Network for Research and Development (INSEARCH) focused on R for Epidemiology ignited my curiosity around programming in healthcare and its benefits, particularly in a local context where data quality was a major challenge. I stayed on as a volunteer for INSEARCH, assisting other participants to complete the same program.

Having gained good programming experience, I was excited by the research prospects of Data Science for evidence generation through novel statistical and machine learning techniques. This led me to the MSc. Health Data Science program at Swansea University.

Landscape image of Dobgima Mofor sitting outside a on a bench.

Studying and living in a new environment is always challenging, as was applying engineering principles to epidemiological concepts on unfamiliar health conditions, all with the pressures of an academic setting. Thankfully, prior experience and theoretical knowledge enabled me adapt quickly. Modules on Analysis of Linked Health Data nicely complemented my knowledge of epidemiological concepts and gave me further insights into evidence-generation techniques. To improve my writing skills and gain research experience unique to the UK, I worked as a grant writing intern with the National Center for Population Health and Wellbeing. Seeking to augment my analytic skillset further, I applied for the HDRUK Black internship and got onto the HDRUK Inflammation and Immunity Driver Program hosted by Queen’s University Belfast.

This internship improved my understanding of data analysis and inferential statistical techniques. Warmly hosted and mentored by Dr John Busby and Dr Charlene Redmond, I learned to improve my analysis and automate results into more optimal research outputs. It was quite insightful discussing the findings from our work investigating ethnic differences in asthma characteristics across a large multi-ethnic cohort with peers and researchers within the Driver program. In addition to analysis in R, the internship also allowed collaboration with other interns on the Python-based technical challenge, with our group ultimately winning the Amazon-sponsored prize for our model predicting A & E outcomes using machine learning models. Thus far, it has been an exciting journey in research development that I hope to continue. For one who originally envisioned a career in engineering or medicine, I have certainly found the best of both worlds in Health Data Science. Working in the Driver program has been quite beneficial in my pursuit of a research career, and I look forward to applying the techniques and knowledge gained at the next opportunity.

Useful links

View Dobgima's LinkedIn profile

Read Dr John Busby's programme profile

Visit Dr Charlene Redmond's profile page

Page publication date: 9/11/2023