Modeling spatial segregation and travel cost influences on utilitarian walking: Towards policy intervention

Abstract

We develop an agent-based model of utilitarian walking and use the model to explore spatial and socioeconomic factors affecting adult utilitarian walking and how travel costs as well as various educational interventions aimed at changing attitudes can alter the prevalence of walking and income differentials in walking. The model is validated against US national data. We contrast realistic and extreme parameter values in our model and test effects of changing these parameters across various segregation and pricing scenarios while allowing for interactions between travel choice and place and for behavioral feedbacks. Results suggest that in addition to income differences in the perceived cost of time, the concentration of mixed land use (differential density of residences and businesses) are important determinants of income differences in walking (high income walk less), whereas safety from crime and income segregation on their own do not have large influences on income differences in walking. We also show the difficulty in altering walking behaviors for higher income groups who are insensitive to price and how adding to the cost of driving could increase the income differential in walking particularly in the context of segregation by income and land use. We show that strategies to decrease positive attitudes towards driving can interact synergistically with shifting cost structures to favor walking in increasing the percent of walking trips. Agent-based models, with their ability to capture dynamic processes and incorporate empirical data, are powerful tools to explore the influence on health behavior from multiple factors and test policy interventions.

The Impact of Neighborhoods on CV Risk

“…Ultimately a series of complementary approaches including observational studies like the MESA Neighborhood Study, policy evaluations, and simulation modeling will be necessary to identify effective neighborhood interventions to improve cardiovascular health. [102]…”

A dynamic framework on travel mode choice focusing on utilitarian walking based on the integration of current knowledge

“…Dynamic processes and causal relationships could be explicitly implemented in an ABM to test hypotheses, make predictions, or explore policy interventions 130,131 . For example, an ABM has been developed to examine the influence of spatial segregation and travel cost influences on utilitarian walking 132 . In this model, travel mode choice is based on a utility function that incorporates travel cost and attitude towards each travel mode.…”

Social Determinants of Population Health: A Systems Sciences Approach

“…In this model, we observed an equally slight reduction in the annual prevalence of violent victimization from implementing either hot-spot policing for 10 years or increasing CBT by 100% for 30 years; however, the joint implementation of hot-spot policing and a 50% increase in CBT resulted in a similar reduction in just five years. Our observation that interventions can work synergistically to obtain optimum improvement in population health has been replicated across several similar studies that have employed systems science methods [57, 46, 33, 47, 59]. Because the development, implementation, and long-term evaluation of community health interventions can be costly, ABMs have provided a particularly attractive opportunity to sequentially evaluate several competing interventions to determine those most likely to provide population health benefits.…”

“…Yang and colleagues employed an ABM to simulate several structural interventions that could target the walking behaviors of both school-aged children [30, 31] and adults [32, 33]. Interventions ranged from improving traffic safety [30, 31] to reducing residential segregation [33]. These simulations showed that the impact of the interventions depended on the changes in behavior it produced in the local social network.…”