Quantitative Health Impact Assessment of Environmental Exposures Linked to Urban Transport and Land Use in Europe: State of Research and Research Agenda

In this article, we summarise recent developments, identify gaps, and propose a research agenda for quantitative health impact assessment (HIA) of environmental exposures linked to urban transport and land use. This is based on a workshop of 30 experts, complemented by targeted literature identified by participants to illustrate the state of research and practice gaps. The practice of quantitative HIA in urban transport and land use interventions covers a diverse range of methods, models, and frameworks. The selection of an appropriate model depends upon the use case, i.e., the research question, resources and expertise, and application. The plurality of models can be a strength if differences are explicit and their implications are understood. A major gap in most assessments and frameworks is the lack of equity consideration. This should be integrated into all stages of the HIA, considering exposures, susceptibility, disease burden, capacity to benefit, household budgets, responsibility for harm, and participation in the process. Scenarios of environmental exposures in urban transport and land use interventions are often overly simple, while the scenario design process of spatial planning is often opaque. Researchers should specify the involvement of stakeholders and the data, evidence, or behavioural model used to construct the scenario. Recent developments in exposure assessment (remote sensing and modelling) have increased the capacity to conduct HIAs for small geographies at scale. At the same time, advances in simulation have enabled the representation of behaviours at high spatial and temporal resolution. The combination can enable person-centric measures accounting for location, activities, and behaviours, with HIA proceeding ahead of epidemiology. Most HIAs still use Comparative Risk Assessment. This is suitable for estimating the disease burdens of environmental exposures, but more advanced longitudinal methods are better suited for studying interventions. Beyond health outcomes, well-being must be incorporated. The monetisation of health outcomes through welfare economics remains contentious. Representation of uncertainty is increasingly acknowledged. Value of Information methods can inform where new data collection would most efficiently reduce final result uncertainty. In the context of the climate crisis and related environmental limits, methods are needed that consider adaptation alongside mitigation and prevention and test robustness to an increasingly unstable future.