Global and local health impact assessment of transport: methods for prioritising model development
Transport is a major determinant of population health.  Adverse health impacts are greatest in lower and middle income cities. Research and policy models are being used to predict how changes in travel patterns and related exposures (e.g. physical activity, air pollution, and road traffic danger) might influence health outcomes (e.g. injuries, heart disease, some cancers and diabetes). However, current methods are not able to produce reliable or comparable results for the questions researchers and policy makers are asking. Results are needed for settings with limited data. Methods are needed to integrate with the separate discipline of transport modelling. There is a need to develop the next generation of transport and health impact models and tools that are academically robust and practically useful. 
I will develop the next generation of models through the following objectives: 
1. To develop methods and computer programs that allow researchers to compare health impact models and data. By collating and comparing models across many settings and scenario I will identify the circumstances in which variation in model structure and parameters makes an important difference to model results. This information will be used to create and test models for new settings and problems.
2. To integrate health impact modelling methods with the models used by transport researchers. This will make health impacts visible to transport planners. I will  investigate the added value that land use/transport models can bring to health impact modelling from improved spatial and temporal detail and following households’ residential location over time. 
3. To use the methods from (1) and findings from (1) and (2) to develop a global city-level model and tool that utilises the best data available in any setting to create comparable exposure and disease estimates. This will transform the opportunities for modelling health impacts of transport policies and scenarios across the world.