Dr Ernest Boakye-Dankwa
- Position: Research Fellow in Epidemiology
- Areas of expertise: Advanced Causal Inference Techniques; Target trial emulation; Pharmaco-epidemiology; Latent Variable Modelling; Statistics; Complex Observational Study Design Concept; Self-controlled Case-Series
- Email: E.BoakyeDankwa@leeds.ac.uk
- Location: LIDA | Level 11 Worsley Building
- Website: ORCID
Profile
Dr Ernest Boakye-Dankwa is a Research Fellow in Cardiovascular Epidemiology at the University of Leeds, with appointments in the Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) and the Leeds Institute for Data Analytics (LIDA). Working with Dr Marlous Hall, his research focuses on cardiovascular disease, multimorbidity phenotypes, and patient outcomes. He applies advanced epidemiological and statistical methods to large-scale electronic health record data to investigate disease patterns, trajectories, and outcomes, generating robust real-world evidence to inform clinical practice, healthcare policy, and population health.
His research centres on the application of real-world healthcare data, advanced causal inference approaches and latent variable modelling to address complex clinical and public health challenges. His work seeks to improve understanding of disease burden, treatment effectiveness and health outcomes using real-world healthcare data.
Dr Boakye-Dankwa has a multidisciplinary background in epidemiology, statistics and mathematics. Prior to joining the University of Leeds, he worked as a Postdoc within Data Science and Advanced Analytics function of BioPharmaceuticals R&D at AstraZeneca, Cambridge, UK. His work applied advanced analytical methods to real-world data to evaluate eligibility criteria in severe asthma randomised controlled trials and support evidence generation for healthcare decision-making.
Dr Boakye-Dankwa completed his PhD at the Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia, where his research focused on epidemiology and the influence of neighbourhood built- and social-environments on walking behaviours among older adults. Using latent class analysis and advanced regression techniques, he examined how latent classes of destinations within a walking distance from home related with walking patterns in older adults living in Brisbane, Australia and Hong Kong, China.
Qualifications
- PhD in Epidemiology, Australian Catholic University, Melbourne, Australia
- MPH in Epidemiology, University of Massachusetts, Lowell, Massachusetts, USA
- MSc in Statistics, University of Idaho, Moscow, Idaho, USA
- BSc (Hons) in Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Research groups and institutes
- Leeds Institute of Cardiovascular and Metabolic Medicine