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Cities Research Seminar Series: Health Impacts of a Shift To Walking and Cycling: Methods, Models and Direction of Travel

In this talk I will introduce methods and results from studies modelling the health impacts of a mode shift to walking and cycling. I will discuss the direction of the science, indicating what we can be confident about and where are the greatest uncertainties and gaps in the evidence. The vast majority of studies have focused on a limited range of high income settings, yet the few results from LMICs show impacts could differ outside these settings. In the TIGTHAT project we will be laying the foundations for a globally applicable model. Key to the success of this endeavour will be developing methods for producing comparable and robust results using diverse data and indicating the extent of uncertainty.


Speaker: Dr. James Woodcock

Dr. James Woodcock leads the Public Health Modelling Programme at the Centre for Diet and Activity Research (CEDAR). He is the head investigator on the Propensity to Cycle Tool (www.pct.bike) and is a lead on the development of the ITHIM tool. In addition, James also spearheads the TIGTHAT project that aims to lay the scientific foundations of a health impact assessment tool that can be readily applied to a wide variety of urban settings in Low or Middle Income Countries to estimate health impacts of transport choices.

In this talk James introduced methods and results from studies modelling the health impacts of a mode shift to walking and cycling. He discussed the direction of the science, indicating what we can be confident about and where the greatest uncertainties and gaps in the evidence. The vast majority of studies have focused on a limited range of high income settings, yet the few results from LMICs show impacts could differ outside these settings. In the TIGTHAT project we will be laying the foundations for a globally applicable model. Key to the success of this endeavor will be developing methods for producing comparable and robust results using diverse data and indicating the extent of uncertainty.

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