In a world plagued by infectious pathogens, biomathematics is used to predict the course of deadly epidemics, such as measles, ebola, influenza and even the zombie virus. In doing this, scientists are able to learn more about the pathogen, and test a variety of ways in which deaths can be averted.
What Students will do
In this project, students will independently explore the dynamics of an epidemic. They will identify relevant biological factors affecting disease transmission and progression to inform the development of a model using excel. This model will be developed under the supervision of the project mentor, Michaela, and will be used to test hypotheses relating to the prevention of disease transmission.
Please note - Students will be asked to submit a proposed hypothesis devised from the guidelines on Openlearning by Sunday, 15 December 2019. This will allow Michaela to asses them against available data sets. Students will receive feedback in early January if modification is needed. Hypotheses will be confirmed at the January Summer School.
- Advanced Mathematics (calculus-based course)
Areas of Student Interest
- Medical research
- Public health care
- Health policy
- Translating research into policy
- Computational biology
Lead Academic: Dr Christopher Angstmann - Senior Lecturer, School of Mathematics and Statistics
Much of Christopher's research could broadly be placed in the categories of complex dynamical systems and stochastic modelling. Christopher has been involved in both the development of applied mathematics as well as the application of mathematics to real world phenomena. One aspect of his work has focused on using stochastic processes to incorporate fractional derivative in to partial differential equation, and ordinary differential equation, based models. This has lead to Christopher developing models for anomalous diffusion as well as fractional order compartment models. Christopher has applied this work in a number of different areas in both physics and biology, and has an interest in fractional calculus, finance, and pattern formation.
PhD Student: Michaela Hall
Michaela is currently a PhD student at the School of Mathematics and Statistics (UNSW), currently holds as position as a Modelling Specialist with Cancer Council NSW and is a student mentor with the Australian Mathematical Sciences Institute (AMSI). She has a master’s degree in Applied Mathematics from the UNSW, and a bachelor’s degree in Advanced Mathematics from Macquarie University. Michaela’s interests are grounded in epidemiology and modelling infectious diseases. Her current research involves modelling the impact of HIV prevention and treatment in countries with high burden of disease.