Modelling the population to improve infrastructure and policy

Crowd of people

Transport, housing, water, and digital communications are all infrastructure systems and services that are instrumental to the fabric of modern society. To work effectively, urban infrastructure projects rely on complex, detailed planning, which is being made smarter and more efficient by the pioneering work of Dr Nik Lomax.

These multifaceted services rely on complex networks of systems to support them. This means sophisticated analytical insight is needed for planners and policymakers to make the most effective decisions about their investment.

Using the advanced data science technique ‘spatial microsimulation,’ Dr Lomax is giving government agencies, businesses, and policymakers new insight into how the population will grow and develop – and the outcomes play a crucial role in shaping future society. The National Infrastructure Commission is one of several high-profile organisations to apply Dr Lomax’s research in assessing the transport capacity of UK cities.

The research has been made possible through the University of Oxford-led MISTRAL programme, which provides models and evidence to inform the analysis, planning and design of resilient national, regional and local infrastructures. Dr Lomax’s expertise in delivering highly detailed projections of population growth is a key part of the project.

The population estimates produced by Dr Lomax’ team, using the model PopNation, are at the level of individual households. Their projections have proved invaluable to businesses and governmental agencies investing in the transformation of water, wastewater, energy, and transport infrastructure.

MISTRAL combines expertise from multiple disciplines to investigate the performance of infrastructure under a wide range of possible future scenarios. The project is delivered by the UK Infrastructure Transitions Research Consortium (ITRC), and brings together seven UK universities. 

Demographic forecasting

Demographic forecasting techniques are being refined through the Synthetic Population Estimation and Scenario Projection Model (SPENSER) project, a methodology developed by Dr Lomax as part of his Turing Fellowship. It is designed to help key planners and decision-makers to identify where future service demand might be.

The method is significant because, for the first time, it enabled data to be represented at highly refined level of detail. It involves combining existing datasets and surveys, such as the UK Census or Health Survey for England, to represent individuals in a way that is dynamic and precise.

“Dynamic spatial microsimulation enables us to stitch together different datasets to build a representation of anonymised individuals at a granular level of detail. We combine this data with methods that use random sampling techniques to form a ‘synthetic’ population,” said Dr Lomax.

“Then, we run an exhaustive representation through a bespoke model which we have developed, to carry out a series of highly complex calculations. The results enable us to determine the probability of different outcomes in society. This might be, for example, to estimate the demand for health care provision or for pensions. It allows us to offer insight into how different policies might impact on that demand in the future.”

Dr Lomax’ team have supplied their results to key stakeholders in the form of interactive visualisations, such as maps and plots. Presenting the insights in this user-friendly format means that a variety of different people, including businesses and policymakers, can use the information easily.

The results enable us to determine the probability of different outcomes in society... and to offer insight into how different policies might impact on that demand in the future.

Dr Nik Lomax, Centre for Spatial Analysis and Policy

Health modelling

Dr Lomax’s research is helping to combat pressing health inequalities through Systems Science in Public Health and Economic Research (SIPHER), a major investment by the UK Prevention Research Partnership (UKPRP). Dr Lomax and colleagues, who are steering the project, aim to tackle poor health in society by working towards a ‘health-in-all policy’ approach, linking together key health and non-health policy domains. Areas covered range from issues related to adverse child experiences, through to housing and economic growth.

By understanding the impact of interventions in policy, decision-makers are able to reform the workings of organisations across welfare, housing, education and employment sectors. Projections and scenarios supplied by Dr Lomax and colleagues are facilitating this change.

“Currently, much research in these areas is disparate from the health outcomes. The aim of SIPHER is to pioneer a joined up approach to examine potential causal links,” explained Dr Lomax. “Understanding the context of these transitions can help to model what might happen to people with similar demographic attributes in the future.”

SHIPHER is using spatial microsimulation models and a rich collection of data from surveys and the project’s partners, which are the Greater Manchester Combined Authority, Sheffield City Council, and the Scottish Government.

Collaborative research

Collaboration and interdisciplinary working is central to the research community within the Centre for Spatial Analysis and Policy (CSAP), which is part of the School of Geography, and more widely at the University of Leeds. Dr Lomax is part of the CSAP team, which also carries out research within Leeds Institute for Data Analytics (LIDA), a major powerhouse for research, engagement and business. His work sits broadly under the ‘urban analytics’ umbrella, with collaborations accross both LIDA and the Alan Turing Institute.

Through the Economic and Social Research Council (ESRC)-funded Consumer Data Research Centre (CDRC), which aims to make consumer data available for research use, Dr Lomax is undertaking research into using novel datasets, including understanding household mobility and predicting property and rental prices.

Contact us

If you would like to discuss this area of research in more detail, please contact Dr Nik Lomax.