Epidemiological Modelling

We apply cutting-edge research methodologies to project the burden of disease across time, space and demographic groups, including predicting the likely future trajectory of diseases.

Our Unit has been built on communicable disease modelling, with major research themes currently including tuberculosis, HIV and emerging infections (including Ebola). However, we are actively looking to expand our activities in non-communicable and demographic modelling. Specific methodologies employed by the Unit include calculus, linear algebra, software engineering, health economics, statistics, epidemiology and Bayesian inference.

Within the School, we are closely linked to Biostatistics, CCRET and Infectious Diseases Epidemiology, with extensive overlap in both the methodology and content of the research of these Units. Active external collaborations include James Cook University, Melbourne Sexual Health Centre, the Global Fund to Fight AIDS, TB and Malaria, RMIT and IBM.

Head of Unit

Dr James Trauer

Contact: james.trauer@monash.edu

Research Aims

Our overall aim is to develop epidemiological models to relate non-communicable and communicable disease risk factors to disease onset and its subsequent course and impact. The research is intended to inform:

  1. patient understanding of the relationship between modifiable risk factors and disease outcome
  2. clinical practice, and in particular GPs' understanding of this relationship and their ability to use this understanding in helping their patients to modify their lifestyles and associated risk factors
  3. health policy development, both by assisting health policy makers to devise optimal health promotion and disease prevention strategies and by providing lobby and advocate groups and interested individuals with relevant, evidence-based information on risk factors and disease outcomes
  4. disease forecasting methods, for both communicable and non-communicable diseases
  5. translation and incorporation of cutting-edge data analytical methods into decision support tools

Associated Staff

Professor Allen Cheng
Professor Andrew Forbes
Professor Danny Liew
Professor Dianna Magliano
Associate Professor Lei Zhang

Research Fellows

Dr Andrea Curtis
Dr Ella Zomer

PhD students

Neal Smith
Richard Ofori-Asenso
Phil Kiely