Towards an Integrated Global Transport and Health Assessment Tool (TIGTHAT) Globally, how people and goods move is important for urban health. Transport causes ill-health through road traffic injuries, noise, and air pollution, but is an opportunity for benefiting health through active travel. Although there are good examples, problems of poor safety, pollution, and environments unconducive to walking and cycling are common in many lower and middle income cities (LMICs).  These cities are often changing fast, many are growing rapidly, and motorbike and then car use is increasing. The problem and the opportunity are large.  A number of studies have used computer based models to estimate the health impacts of more active travel in high income Western countries. However, we are aware of only three studies in LMICs (Delhi, Sao Paulo and Kuala Lumpur), all involving the applicants.  The high income studies found more walking and cycling and fewer cars could bring large health benefits. However, our work shows things are more complicated in LMICs.  For example, how much people benefit from increasing their physical activity depends how active they are to start with. It also depends on how polluted the air is, because pedestrians and cyclists breath in faster. Road injuries numbers may go up or down as pedestrians and cyclists are at higher risk than drivers, but fewer cars may make the roads safer.  One way to support decision makers is to provide tools that help them to compare the health impacts of their choices. The challenge is to be both practically useful and scientifically accurate.  In this project we lay the basis for creating a model that can be readily applied to cities around the world. A key challenge is data comparability and quality. Our international team of health and transport researchers in the UK, India, Brazil, USA, and Peru will assess what data are available and work to develop rules for drawing the best conclusions from it.  We will build a model for two Indian cities (Bengaluru and Visakhapatnam) and do further work with the models we have recently created for Sao Paulo and Delhi. Running the model will not just produce new results but we also use statistical techniques to work out where getting better data is most valuable e.g. do our results change more if we have better information on injuries or on walking.  To estimate health impacts we need scenarios about how travel might change. We will do this in two ways. Firstly asking what would happen if people were as likely to walk, cycle (including electric-assist bikes) a trip of a given distance as people are in more active cities. Secondly, we will look at how more compact cities might affect how people travel.  We will look at the data available in a further four Latin America and sub-Saharan African cities in depth to model them in the future. We will also look across a wide range of settings to see what data is available on how people travel and useful it is for modelling.  We will use a computer programme to get information from Google Street View for different cities and use it to estimate the mix of traffic across the city. We will see if we can use this data to predict how much time people spend travelling by each mode, and using other data about the city how active people are in total.  The project team has worked previously on using a range of data to estimate the number of road traffic victims by mode in different countries. We will now apply this approach to the urban level and work with estimating the kind of data we need for the health impact model.  For calculating air pollution risk we will develop a simple method for estimating the contribution of transport to AP using global databases and we will compare this against more detailed analysis in cities for which we have better data.   In summary this project lays the foundation for a scientifically robust webtool that can help policy makers tackle a major determinant of population health. The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.