Aminat holds a BTech in Statistics from the Federal University of Technology, Akure (FUTA) and an MSc in Mathematical Biology, Ecology, and Medicine from Heriot-Watt University (HWU). During her time at HWU, she developed an interest in the applications of mathematics to biological systems. Recently, her interest became keen on the mathematical modelling of infectious diseases within the human host. She conducted a summer research project using an individual-based model to study antibiotic-resistant tuberculosis. In her spare time, she enjoys reading novels, watching football and TV shows, and funny videos of her little nieces and nephews.

Research project title:
Within-Host Individual-Based Model for Diabetic Tuberculosis Patients

Supervisor(s):
Ruth Bowness, Jane White

Project description:
For several decades, Tuberculosis (TB) has been preventable and curable. However, someone still dies from tuberculosis across the world every 15-20 seconds, and 50 percent of those deaths are children. In addition to this, patients with diabetes have a higher mortality rate when infected with TB and have an increased likelihood of TB relapse. This Ph.D. project aims to use individual-based modelling (or agent-based modelling) to develop a within-host model of TB infection within a human lung, building on previous models (Bowness et al. 2018) to focus on patients with type 2 diabetes. The goal would be to understand the differences in immune responses in these patients to TB infection and simulate improved treatment strategies. We will work with experimentalists, using laboratory data to calibrate the model, and clinicians who have access to clinical data to validate model findings. Specifically, this project will benefit from a collaboration with Dr. Muge Cevik (University of St Andrews/NHS Lothian), who is an expert on treating diabetic TB patients and is currently involved in a clinical trial in this area of research.

Bowness, R., Chaplain, M.A., Powathil, G.G. and Gillespie, S.H., 2018. Modelling the effects of bacterial cell state and spatial location on tuberculosis treatment: Insights from a hybrid multiscale cellular automaton model. Journal of theoretical biology, 446, pp.87-100.