Project: Optimal design of competitive mixture experiments
McVernon Group
Competitive mixture experiments consist of infecting a host (in this case, a ferret), with different proportions of virus subtypes with nominally differing fitness levels. The ferret is then co-housed with a susceptible (uninfected) ferret, and the abundance of the viral-subtypes is quantified in each host over time. The aim of these experiments is to determine the absolute and relative fitness levels of the subtypes, both in terms of their ability to replicate within the host, and transmit to a new host. To date, the proportions of competing-strains has been chosen uniformly, with equal numbers of ferrets infected with mixtures of 0:100, 20:80, 50:50, 80:20 and 100:0 percent. Virus-dynamics models (coupled systems of differential equations) are used to capture the within- and between-host dynamics observed in the data.
In this project, we will investigate models of the viral dynamics, and use these in conjunction with optimal design tools to establish the optimal setup for experiments of this type (with respect to, e.g., proportions of strains, time to introduce the susceptible host, etc.), for strains with different levels of fitness, and for differing experimental aims.
This project will be best suited to someone with strong coding skills, and studying a degree in mathematics or statistics eg MSc (Mathematics and Statistics) in applied mathematics, stochastic processes or statistics
Contact project supervisor for further
information and application enquiries
McVernon Group
13 vacancies

Professor Jodie McVernon is a physician with subspecialty qualifications in public health and vaccinology. She has extensive expertise in clinical vaccine trials, epidemiologic studies and mathematical modelling of infectious diseases, gained at the University of Oxford, Health Protection Agency London and the University of Melbourne. Her work focuses on the application of a range of cross-disciplinary methodological approaches, including mathematical and computational models, to synthesise insights from basic biology, epidemiological data and sociological research. These models advance understanding of the observed epidemiology of infectious diseases and inform understanding of optimal interventions for disease control.
McVernon Group Current Projects
-
Sample size determination for within-host animal studies of infection
PhD/MPhil, Master of Biomedical Science
-
Bias in vaccine effectiveness studies
-
Measuring the association between influenza presentations and invasive group A Streptococcus infections (iGAS)
Master of Biomedical Science
-
Buruli ulcers’ Most Wanted – Understanding the mosquito associated with the flesh-eating bacteria, Mycobacterium ulcerans.
Master of Biomedical Science
-
Exploring the association between hepatitis C and invasive group A streptococcus infections (iGAS)
Master of Biomedical Science
-
Invasive Streptococcus A – piecing together clinical, genomic and public health aspects of the puzzle
PhD/MPhil
-
Optimising use of existing and emerging SARS-CoV-2 diagnostics to support the public health response to COVID-19
PhD/MPhil
-
Modelling spatial and demographic heterogeneity of malaria transmission risk
PhD/MPhil, Master of Biomedical Science
-
Epidemiology of Scarlet Fever in Victoria
Master of Biomedical Science
-
Optimal design of competitive mixture experiments
PhD/MPhil, Master of Biomedical Science
-
Investigating the household risk of group A Streptococcus infection
Master of Biomedical Science
-
Understanding the impact of new testing for infectious diseases
PhD/MPhil, Master of Biomedical Science
-
Acute respiratory infection presentations and prescribing in primary care
Master of Biomedical Science