The size, composition, and spatial distribution of both people and households have a substantial impact on the demand for and development and delivery of infrastructure required to support the population. Infrastructure encompasses a wide range of domains including energy, transport, and water, each of which has its own set of spatial catchments at differing scales. Demographic projections are required to assess potential future demand; however, official projections are usually not provided at a high level of spatial resolution required for infrastructure planning. Furthermore, generating bespoke demographic projections, often incorporating a range of scenarios of possible future demographic change is a specialist, resource intensive job and as such is often missing from infrastructure development projects. In this paper we make the case that such demographic projections should be at the heart of infrastructure planning and present a set of open‐source models which can be used to undertake this demographic projection work, thus providing the tools needed to fill the identified gap. We make use of a case study for the United Kingdom to exemplify how a range of scenarios can be assessed using our model.

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This note provides an overview of the provisional results from a dynamic microsimulation model called MINOS which assesses the impact on an individual's mental health (measured as SF-12 Mental Component Score) that result because of changes to household disposable income. There are five pathways that link household disposable income to mental heath (housing quality, neighbourhood safety, nutritional quality, tobacco use, and loneliness). We estimate change in SF-12 under three different scenarios: an uplift to the living wage for low earning employees; an uplift to child benefit, applied universally as £25 per child translated to household disposable income; and the impact that the new energy price `cap' will have on household disposable income. As well as the change in SF-12 MCS at the whole population level, we present the change in the sub-populations impacted by each policy experiment and assess the spatial distribution of each policy in the city of Glasgow, Scotland. We find that raising disposable income through the living wage and child benefit uplift scenarios have a modest positive impact on overall mental health and a larger impact in the intervention groups. The impact of increased energy prices has the effect of reducing household disposable income, and so has a negative impact on overall mental health. This note represents work in progress: further detailed methodology, reproducible code and latest results can be accessed via the project github page at https://github.com/Leeds-MRG/Minos.