Small area population projection: inputs to behavioural and demand models
UGI-IGU Centennial Congress, Paris, 18-22 June 2022.
Nik Lomax, The Alan Turing Institute, United Kingdom
Individual level population and household data at a fine spatial scale have utility in a wide range of applied contexts: they can be used as an input to spatial demand models, agent based models, disease models, and models of social systems or ‘digital twins’. Further incorporating a time element to produce projections adds another layer of utility, allowing for the modelling of counterfactual trade-offs for different future population size, composition and spatial distribution. However, data at this level of disaggregation are not routinely available and require a bespoke modelling solution.
This paper first describes an open-source modelling framework for producing these spatially detailed, individual level demographic projections. It then goes on to demonstrate, via a collection of case studies, the utility of these data as they are fed into other applied models of different systems. A land use model is used to examine the spatial distribution of population under different urban growth scenarios. A disease spread model is used to examine the impact of interventions on daily activity for COVID-19 transition. Finally the individual level data are used in an Agent Based model which is used to assess different transport development scenarios.
Users are able to download and adapt the demographic model for their own purposes and this talk outlines the open-source principles upon which the model is built. To date the model has delivered utility in the applied case studies outlined but it is also continuing to evolve. The talk will outline the current state of the model, supported by funding from the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence.
Keywords: demographic | projection | small area | individual | applied