I am an applied mathematician/ statistician with a particular interest in the use of large observational datasets to better understand how we can improve outcomes for children with chronic conditions, reduce health inequalities in outcomes and ensure that children’s futures are as unlimited by their condition as possible.
A lot of my current work focusses on trying to understand how we can improve outcomes for people with cystic fibrosis (CF) and reduce health inequalities in CF. I work with national CF patient registries as well as population linked electronic health care records. I am a member of the UK CF EpiNet and a co-investigator on a study looking at pregnancy in CF: CF PROSPER - Cystic Fibrosis Pregnancy Related Outcome data to Support PERsonal choices.
My background is in Biomathematics which I studied at the University of Greifswald (Germany) and Massy University Palmerston North (New Zealand) followed by a PhD in Mathematical Biology at the University of Dundee. I then wanted to move more towards data science and statistics which led me first to a postdoctoral position in pharmacokinetic and drug combination modelling at Cranfield University (2013-2014) before I joined Lancaster University for a postdoc in biostatistics (2014-2019). During my time at Lancaster I worked across a range of projects applying different statistical methods including methods for longitudinal data analysis, spatial statistics and causal inference, to answer questions in tropical disease epidemiology, neurology, musculoskeletal science and public health. During this time, I developed my interest in child public health which led me to taking up a lectureship in the Department for Public Health and Policy at the University of Liverpool in October 2019.