University of Glasgow

Work Package Lead: Professor Nik Lomax, University of Leeds

Theme: Computational Modelling

Objectives:

• Augment an existing synthetic population (digital twin) of Great Britain by combining data from diverse sources to incorporate relevant individual-level health and economic characteristics.

• Use machine learning approaches to improve the synthetic population’s accuracy

• Dynamically update the synthetic population to represent distributions arising from policy scenarios and demographic processes

Work Package Lead: Professor Vittal Katikireddi, University of Glasgow

Theme: Computational Modelling

Objectives:

• Estimate causal effects of prioritised economic determinants of health, disaggregating by population group where possible

• Produce meta-analyses of the causal effects of economic determinants of health on prioritised health outcomes

• Use estimates to parameterise the model developed in Dynamic modelling for policy appraisal work package.

Work Package Lead: Professor Matteo Richiardi, University of Essex

Theme: Computational Modelling

Objectives:

• By integrating and enhancing existing models, develop a dynamic policy simulation model that allows the health impacts of a wide range of economic policy options to be explored

• Evaluate the impact of specific policies prioritised by stakeholders and the public on population health and health inequalities.

This work package will build on three existing, complementary, open-source modelling infrastructures developed by programme members (all estimated and validated on Understanding Society data).

• UKMOD a tax-benefit model for the UK and its constituent nations. The current version allows estimation of every household’s income after real or hypothetical income and welfare benefit policies, by applying the UK’s complex tax and benefit rules to a representative population.

• SIMPATHS simulates individual life-course trajectories over the work, family and health domains.

• SIPHER MINOS considers multiple inter-dependent pathways by which income can affect health (e.g. via financial security, nutrition, neighbourhood quality), bringing essential granularity to consider health inequalities, because policies such as child benefit uplifts play out differently for different population groups and areas.

Work Package Lead: Professor Robin Purshouse, University of Sheffield

Theme: Computational Modelling

Objectives:

• Integrate existing models used in policy settings so they can be run alongside our work to provide additional insights and added utility

• Develop new model components that ensure lived experience perspectives on causal relationships between economic determinants of health and health outcomes are represented in our work, and included when estimating and reporting outcomes.

Work Package Leads: Julian Cox, Greater Manchester Combined Authority & Jo Winterbottom, University of Glasgow

Theme: Enhancing Policy Utility

Objectives:

• Understand partners’ changing policy priorities, choices and questions

• Map relevant local, devolved and UK policy levers

• Understand key influences on partners’ agendas

• Work with officers from across each partner to integrate our insights, tools and other outputs into policy processes.

This work package convenes the Policy Working Group and the Think Tank and Advocacy Working Group. It also has oversight of our Embedded Researchers.

Work Package Leads: Professor Kat Smith, University of Strathclyde & Dr Clementine Hill O’Connor, University of Glasgow

Theme: Enhancing Policy Utility

Objectives:

• To better understand the use and potential of computational modelling within a fragmented economic and health policy landscape

• To develop insights that enable us to enhance the policy utility and traction of our modelling outputs and our ability to provide persuasive evidence.

Work Package Lead: Dr Corinna Elsenbroich, University of Glasgow

Theme: Enhancing Policy Utility

Objectives:

• Increase capacity in computational modelling for public health across academic and policy audiences

• Increase levels of modelling literacy and critical engagement with models across scientific (including across the PHI-UK network), policy and Non-Governmental Organisations (NGOs) /advocacy organisations

• Support democratisation of modelling by providing novel, inclusive ways to engage with modelling through a range of multidimensional activities.

Work Package Leads: Professor Ellen Stewart, University of Glasgow & Dr Clementine Hill O’Connor, University of Glasgow

Theme: Democratising Modelling

Objectives:

• Work with community panels to co-create a socially robust account of ‘missing’ dimensions and experiences (inputs, outputs, variables and links between them) in existing policy models of economy-health relationships

• Use insights to inform activities in:
  • Dynamic modelling for policy appraisal -WP3
  • Developing alternative methods for integrating lived experience and existing policy models -WP4
  • Policy Engagement -WP5
  • Elicitation of Normative Social Preferences -WP9

• Co-develop creative options for narratives (textual, visual) to communicate missing dimensions alongside models

• Elicit novel ideas for system interventions.

Work Package Lead: Professor Aki Tsuchiya, University of Sheffield

Theme: Democratising Modelling

Objective:

• Elicit quantitative normative social preferences of the UK general public across selected policy goals via Discreet Choice Experiment surveys.

Work Package Leads: Professor Kat Smith & Dr Clementine Hill O’Connor, University of Glasgow

Theme: Democratising Modelling

Objectives:

• To provide insights on what makes economic determinants of health models, and the policy projections they produce, convincing and useful to diverse public and policy audiences

• To provide early, cross-sector assessment of the potential of our innovative, creative modelling tools for wide-ranging research and policy settings