Pioneering computer model measures health impact of green transport

Cycling19 September 2012

By Simon Hadlington

A pioneering computer model developed by a UK researcher enables transport planners to measure how greener transport strategies impact on people's health. The Integrated Transport and Health Impact Model, developed at the Centre for Diet and Activity Research (CEDAR) in Cambridge, will help in the development of healthier transport policies.

It has been recognised for some time that moves to combat climate change, such as cleaner power generation and a reduction in road traffic, can have positive effects on the health of populations. However, quantifying and modelling these effects has until now received little attention.

Dr James Woodcock, a senior research associate at CEDAR which is co-funded by the ESRC, developed the ITHM model as a way of predicting how different patterns of transport use impact on health.

"Climate change mitigation strategies can affect health in a number of ways," says Dr Woodcock. "We found that these effects can be quite large for transport. If people drive less and walk or cycle more, for example, there will be benefits in terms of people becoming more physically active, but there might more injuries from collisions involving road vehicles.

"We found that the benefits from physical activity were consistently larger than the effect on injuries, and that injuries can be reduced if people travel less far and speeds are kept down."

The model is first populated with data from a range of sources, such as government road and travel surveys. This includes information such as the volume and type of traffic on different road networks and how travel varies by age and gender.

It is then possible to present the model with different policies or scenarios. This can give estimations of the benefits from actual policies such as the hire bike scheme in London, or predict the consequences of hypothetical scenarios, such as how much health outcomes would change if people in England travelled like the Dutch.

"From these inputs we can see how changes in transport patterns can result in different levels of activity from cycling or walking, reduced air pollution and any changes in injury or fatality rates," says Dr Woodcock.

These changes in behaviour across different categories of the population, in terms of age and gender, for example, can then be related to potential effects on health, such as heart disease, stroke, diabetes, dementia, asthma and certain cancers."

Dr Woodcock adds, "Modelling the health impacts from climate change mitigation has shown that one should not just think about the costs of reducing emissions. If we choose the right policies there can be substantial co-benefits too."

ITHIM has also grabbed the interest of public health experts in California. Dr Neil Maizlish, of the California Department of Public Health, has adapted the model to the San Francisco Bay region. "In addition to estimating health co-benefits of active transport scenarios for the Bay Area, I developed a method using existing cost-of-illness data to monetise the health co-benefits," Dr Maizlish says. "I am also examining ways to apply ITHIM to smaller geographical areas to assess the health impacts. This has applications to assess specific development projects or differential health co-benefits or harms of socially disadvantaged populations."

Dr Maizlish believes that tools such as ITHIM will be "extremely important" in planning transport strategies in the future. "Transportation modellers and epidemiologists I have worked with say that ITHIM fills an unmet business need by providing a means to estimate the health co-benefits of active transport. They say that it is methodologically appealing by complementing their transportation demand models and by having a firm conceptual – epidemiological – foundation."