All models are wrong, but not for everyone equally. Many infectious diseases disproportionately affect certain population sub-groups, such as ethnic minorities, Indigenous Peoples, and people living with high levels of socioeconomic deprivation. However, mathematical models of infectious diseases often ignore these variables and lump people into the same model compartment.
The aim of this project is to develop and apply new models that are capable of capturing and predicting differences in disease dynamics and impact amongst these different groups. The project will use a combination of deterministic and stochastic dynamical modelling techniques with methods for estimating model parameters from New Zealand’s detailed health and socioeconomic data.
The new models will help disentangle the relative contributions of differences in infection rates and differences in risk of clinically severe disease following infection. This will help inform public health interventions to reduce health inequities, and to ensure a more equitable response to future pandemic threats.
The project has an interdisciplinary team of infectious disease modellers and social epidemiologists. Funding for two PhD student scholarships has been awarded by the prestigious Royal Society of New Zealand Marsden Fund.
Supervisors
Primary Supervisor: Michael Plank
Key qualifications and skills
Undergraduate degree in mathematics, statistics or closely related subject, ideally with previous experience of modelling infectious disease dynamics.
Does the project come with funding
Yes: Marsden-funded PhD scholarship
Final date for receiving applications
Ongoing
How to apply
To apply for this position, please submit the following documents to Prof. Michael Plank at michael.plank@canterbury.ac.nz: a cover letter indicating your research interests (max. 1 page); a curriculum vitae; full academic transcripts; contact details of two referees; publications and thesis (if available).
Keywords
epidemiological models; infectious disease dynamics; mathematical modelling; public health; social determinants of health
