Population Interventions

Research Overview

The Population Interventions Unit (PI) aims:

To provide robust evidence on the health and cost impacts of population interventions, through causal inference and sophisticated simulation approaches from epidemiology, economics and data science.

To impact policy through the provision of high quality, timely and actionable evidence on how interventions change health, health inequalities, future health expenditure and working age economic productivity.

Stream One: Primary research the effects of interventions on population health

In Stream 1 we use existing data, preferably longitudinal, to estimate causal effects of interventions on health, using contemporary causal inference and natural experiment methods. For example, the impact of Health Star Rating (HSR) nutrition labels on both formulation of food and consumer purchasing.

The PI Unit welcomes collaboration opportunities with researchers interested in applying cutting-edge, contemporary causal inference methods in their work.

Knowledge sharing

Professor Blakely teaches short courses in contemporary epidemiological methods to equip the next generation of population health researchers and policy-makers with the right tools to answer pressing questions.

Step Two: Forecasting the health and economic gains of deploying an intervention for a population or a subpopulation over time

Our mission is to be able to quantify the impact of (virtually) any intervention on health, health inequalities, health expenditure and income-earning potential of the population.  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. We call this program of impact-driven research SHINE: Scalable Health Intervention Evaluation.  We aim to scale SHINE’s influence in three ways: out to include multi-country evaluations (e.g., Australia, NZ, SE Asian countries); down to quantity intervention impacts by sub-populations (e.g. health inequality impacts on Aboriginal and Torres Strait Islander populations); and up to examine packages of interventions (e.g., an education campaign and a new health app launched simultaneously).

    SHINE’s state-of-the-art forecasting toolkit

    Core components of SHINE include:

    SHINE-Infrastructure : Building and evolving next-generation simulation models and supporting tools such as.

  • Australia New Zealand Health Intervention League Table (ANZ-HILT): A world-first online interactive tool that allows users to compare 100s of interventions on their health gains (i.e. quality-adjusted life-years gained or disability-adjusted life-years averted), health systems costs and cost-effectiveness.
    • Who can use this, what expertise is required and perhaps a quick demo video so people can see what it looks like/how it works quickly
  • Health Intervention Impact Calculator (HIIC) : a freeonline webtool, about to be launched as a protype that will allow the user to input what they estimate will be the change in disease incidence rates by time into the future for a given intervention. The tool then outputs expected: gains in health adjusted life years, changes in health expenditure and gains in workforce income (i.e. productivity).  Future iterations of HIIC will allow the user to input changes in risk factors arising from an intervention (e.g. the percentage point change in tobacco consumption or BMI distribution), and run scenarios for multiple countries.
    • Who can use this, what expertise is required and perhaps a quick demo video so people can see what it looks like/how it works quickly
  • SHINE-Research : a suite of thematic programs of research that tackles ‘big issues’ (e.g. COVID-19, tobacco, housing and other interventions) that are either:

  • led by the Population Interventions Unit
  • undertaken collaboratively between the PI Unit and other researchers.
  • SHINE-Consulting : our consulting arm undertakes evaluations of the health gains (e.g. in health adjusted life years), health expenditure impacts, productivity gains among the working age population and cost effectiveness of – virtually – any population intervention. Potential clients are diverse, ranging across:

  • academic researchers wanting to sub-contract SHINE to undertake an evaluation of intervention(s)
  • policy makers wanting a range of interventions evaluated to inform decision making
  • NGOs and other parties wanting independent and robust estimates of the future health gains and cost impacts of population interventions.

Staff

Professor Tony Blakely, Unit Head, Epidemiologist, & Public Health Medicine Specialist

Dr Driss Ait Ouakrim, Research Fellow in Epidemiology

Dr Tim Wilson, Simulation Modelling and Software Engineering

Dr Shiva Raj Mishra, Research Fellow in Epidemiology And Intervention Modelling

Professor Vijaya Sundararajan, Clinical Epidemiologist

Mr Hassan Andrabi, Research Assistant in Simulation Modelling and Software Engineering

Dr Kirsti Hakala Assendelft, Research Assistant and Project Coordinator

Collaborators

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.

Funding

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)
  • Philanthropy