The Population Interventions Unit (PI) aims:
To provide robust evidence on the health and cost impacts of population interventions, through causal inference and simulation approaches from epidemiology, economics and data science.
Stream 1 of PI is the application of contemporary causal inference and natural experiment methods to quantify the effect of some exposure or intervention on health outcomes. For example, the impact of Health Star Rating (HSR) nutrition labels on both formulation of food and consumer purchasing. Professor Blakely also teaches 4-day short courses in contemporary epidemiological methods .
Stream 2 of PI is about estimating health gains at the population-level for an intervention when we already know much about exposure-outcome associations. We seldom systematically ask questions like: “when applied to the population, how much health gain will intervention X achieve compared to intervention Y? Over what time period? At what cost?” Answering these questions is vital to forecasting the impact of a range of interventions and optimising policy-making for best value-for-money. Our aim here is to develop a program of research called SHINE, standing for Scalable Health Intervention Evaluation. We aim to scale in three ways: out to include multi-country evaluations; down to quantity intervention impacts by sub-populations (e.g. health inequality impacts); and up to examine packages of interventions. Professor Blakely also teaches a 1-day short course on using epidemiological and economic methods for evaluating public health interventions. Projects within Stream 2 or SHINE include:
- Building next-generation simulation models (VIVARIUM) with the Institute of Health Metrics and Evaluation (home of the Global Burden of Disease Study) to allow more efficient and multi-country evaluations.
- A body of tobacco control evaluations, among other topics
- The collation of 100s of evaluations in the Australia New Zealand Health Interventions League Table (ANZ-HILT), a world-first online interactive tool that allows users to compare interventions in multiple countries on their health gains (i.e. quality-adjusted life-years gained or disability-adjusted life-years averted), health systems costs and cost-effectiveness.
PI sits on a platform of collaborations and data sharing.
Professor Tony Blakely, Unit Head, Epidemiologist, & Public Health Medicine Specialist
Professor Vijaya Sundararajan, Clinical Epidemiologist
Mr Hassan Andrabi, Research Assistant in Simulation Modelling and Software Engineering
Dr Driss Ait Ouakrim, Research Fellow in Epidemiology
Ms Ameera Katar, Research Assistant and Project Coordinator
Dr Tim Wilson, Simulation Modelling and Software Engineering
Dr Shiva Raj Mishra, Research Fellow in Epidemiology And Intervention Modelling
Dr Natalie Carvalho, Research Fellow in Health Economics
Mr Patrick Abraham, Research Assistant in Health Economics
PI is built on many Australasian and international collaborations. Key ones include:
- The Burden of Disease Epidemiology, Equity and Cost-Effectiveness Programme (BODE3) at the University of Otago, Wellington, NZ. (Prof Blakely directed this programme from 2010-19 and continues as a Co-Director.)
- The Dietary Interventions: Evidence & Translation (DIET) Programme at the University of Auckland, NZ.
- The Institute of health Metrics and Evaluation (home of the Global Burden of Disease Study), University of Washington – with whom PI is collaborating with building the next-generation VIVARIUM simulation model.
PI receives strategic funding by the University of Melbourne, and funding through its projects from:
- The Australian Institute of Health and Welfare (league tables)
- The Health Research Council of New Zealand (health star rating [HSR] and tobacco projects).
- National Health and Medical Research Council (NHMRC)
- VIVARIUM – next-generation proportional multi-state life-table simulation model
- Health Star Rating (HSR) label impact on food formulation and consumer purchasing
- Australia New Zealand Health Intervention League Table (ANZ-HILT)
- Tobacco intervention modelling
- Student Research Opportunities
Faculty Research Themes
School Research Themes
For further information about this research, please contact Unit Head Professor Tony Blakely
Department / Centre
Unit / Centre
MDHS Research library
Explore by researcher, school, project or topic.