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The purpose of this course run by the Centre for Epidemiology and Biostatistics, in association with The University of Adelaide, is to provide a systematic overview of epidemiological concepts and methods, building up from sources of error (confounding, information bias, selection bias) to bias analysis methods, then a range of contemporary methods. The course is premised on a counterfactual and potential outcomes approach to epidemiology.

This course has been taught in Australia by Professor Tony Blakely and Professor John Lynch for many years, and is highly regarded.


New dates will be announced in early 2023.

The Hone & Stirling Teaching Space,
Helen Mayo South Building,
The University of Adelaide,
1 Frome Rd, Adelaide
Hone & Stirling Teaching Space | Infrastructure | University of Adelaide

What does the course include?
  • An introduction to causal inference using contemporary approaches such as a potential approach model and directed acyclic graphs (DAGs).
  • A comprehensive overview of systematic error (confounding, selection and information biases).
  • An introduction to quantitative bias analysis methods to correct for systematic error in epidemiological studies. (Sometimes called sensitivity analyses.) Methods taught range from simple to probabilistic methods.
  • Quantitative bias analysis exercises using Excel spreadsheets. Understanding and applying bias analyses not only enables you to undertake your own analyses in the future, but also means you have a deeper understanding of systematic error.
  • Selected specific topics such as regression model building strategies, effect measure modification and interaction; direct and indirect effects (i.e. mediation analysis), propensity scores, instrument variables; null hypothesis significance testing and p values.

Who is this course designed for?

The course is designed for 2 target audiences:

  • PhD students, early career researchers, and advanced MPH students who wish to extend their knowledge to include some of the more advanced epidemiological ways of thinking and methods that have merged over the last decade.
  • More senior investigators who want an efficient “catch up” on some of the new thinking and methods being used in higher quality research publications

Course prerequisites

This course will assume knowledge of study design and analytical methods, the basic principles of systematic error (confounding, selection and information biases) and biostatistics up to multivariable regression. For example, successful completion of a Diploma or Masters of Public Health course in epidemiology and biostatistics (or similar) will usually provide the necessary basis to undertake this course. If you wish to discuss your suitability for this course, please contact:

Course outline


Day 1

  • Causal Concepts in Epidemiology
  • Potential Outcomes Approach (POA) to Causation
  • Directed Acyclic Graphs (DAGs)
  • Quantitative Bias Analysis (QBA)
  • Understanding Selection Bias – an application of DAGs
  • Selection Bias and QBA

Day 2

  • Understanding Confounding Bias
  • Some Alternative Approaches to Control Confounding
  • Confounding Bias QBA
  • Information Bias and QBA
  • G-Methods

Day 3

  • Probabilistic and Multiple Bias Analysis
  • Mediation analysis
  • Examples of application of G-Methods to assess population intervention impacts (e.g. marginal structural models, G-computation, targeted maximum likelihood estimation)
  • Simulation modelling of intervention effects into the future (e.g. tobacco, COVID-19 policy, housing policy), and the intersection of epidemiology and cost-effectiveness

Course leaders

Professor Tony Blakely

Professor Tony Blakely (MBChB, PhD) is an epidemiologist and public health medicine specialist, specialising in quantifying the health gains, costs, and economic effectiveness of public health interventions. Within three years of completing his PhD Tony was directing NZ Health Research Council (HRC) funded programs (the largest HRC funding scheme) and has done so continuously since. From 2010-19 he directed the HRC-funded Burden of Disease Epidemiology, Equity and Cost-Effectiveness Program (BODE³). This Program builds infrastructure (e.g. linked routine datasets) and capacity (e.g. epidemiological and economic decision modelling) to rapidly assess the health impact and cost effectiveness of a range of public health interventions. A strength of his research leadership is his ability to innovate and lead teams from multiple disciplines. The programs he leads are designed to maximize policy impact, including innovations such as interactive league tables that compare health gains and costs for 100s of Australasian interventions. In 2020, Tony was frequently sought by the media as an expert in COVID-19. In collaboration with colleagues, he provided modelling to Vic DHHS that underpinned the RoadMap. Tony is well known for his enthusiastic and engaging style of presentation and teaching.

Professor John Lynch

John Lynch is the Professor of Epidemiology and Public Health in the School of Public Health, at the University of Adelaide. He is also a Visiting Professor of Epidemiology in the School of Social and Community Medicine at the University of Bristol (UK). He has held academic positions at the University of Michigan (USA) and McGill University in Canada. John is an internationally recognised scholar in epidemiology and public health. He was one of the editors of the International Journal of Epidemiology from 2000 to 2016. His recent research involves early life interventions and he leads the NHMRC CRE, EMPOWER: Health systems, disadvantage and child well-being. He has over 350 academic publications that have attracted over 49,000 citations and a Google H index of 101. From 2014 to 2018 he received Thomson Reuters’/Clarivate “Highly Cited Researcher” status that places him in the top 1% of cited scientists internationally in his field. He currently serves on several international, national and local scientific advisory groups. He was an editor of the highly ranked International Journal of Epidemiology from 2005-16.

What do previous participants say about the course?

About 30 participants have completed the course each year since 2011, ranging from: recent students of a Diploma/Masters-level taught paper in epidemiology; to lecturers of the same; to senior epidemiologists. All participants would recommend the course to other colleagues, and at least three quarters rated the course 5 out of 5 on ‘content’ and ‘presentation’. Summary comments about the course included:

“This was by far the most useful short course I have ever done. It was an excellent summary of epidemiological advances. I would recommend it to anyone working in, or studying, epidemiology at a moderate to advanced level.” [Lecturer and convenor of Diploma/Masters-level epidemiology taught course.]

“I found the course highly useful in that it grounded what I had learnt in [Diploma/Masters course] and extended on this. Bits of the [Diploma/Masters course] were still a bit foggy; this course has definitely provided clarity. I also feel much better equipped to consider systematic error and how to address it.” [Recent student of Diploma/Masters-level epidemiology taught course.]

Fee Structure


Others - Early bird

(up to 31 July)

Others - Normal rates

(non-early bird)

3-day course




Further Enquiries:

E: epi-shortcourse@unimelb.edu.au

Dietary restrictions

Please email epi-shortcourse@unimelb.edu.au to let us know of any dietary restrictions (e.g. vegan, vegetarian, gluten free, dairy free, nut allergy).

Course Information

Key dates

New dates will be announced in early 2023


The Hone & Stirling Teaching Space,

Helen Mayo South Building,

The University of Adelaide,

1 Frome Rd, Adelaide

Entry requirements

This course will assume knowledge of study design and analytical methods, the basic principles of systematic error (confounding, selection and information biases) and biostatistics up to multivariable regression.