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Existing methods are typically spatiotemporally aggregate and cannot offer insight into the mechanisms of behavioural change. Emerging methods from transport modelling could support health analyses by incorporating more advanced behavioural theory and capturing movements with high spatial and temporal precision. This dissertation explores how transport modelling can evolve to support health applications. Travel demand modelling methods are enhanced to simulate plausible week-long itineraries to better capture habitual behaviour. Methods from health impact modelling are incorporated into an agent-based transport simulation to capture exposures and impacts as agents carry out their itineraries. Micro-environmental spatial data are incorporated into a network database to capture street-level determinants of walking and cycling. Using this enhanced database, methods are developed for incorporating street-level environment sensitivities into mode choice and accessibility. 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Emerging methods from transport modelling could support health analyses by incorporating more advanced behavioural theory and capturing movements with high spatial and temporal precision. This dissertation explores how transport modelling can evolve to support health applications. Travel demand modelling methods are enhanced to simulate plausible week-long itineraries to better capture habitual behaviour. Methods from health impact modelling are incorporated into an agent-based transport simulation to capture exposures and impacts as agents carry out their itineraries. Micro-environmental spatial data are incorporated into a network database to capture street-level determinants of walking and cycling. Using this enhanced database, methods are developed for incorporating street-level environment sensitivities into mode choice and accessibility. 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