The economic assessment of health benefits of active transport

Purpose:This chapter addresses the economic assessment of health benefits of active transport and presents most recent valuation studies with an overview of progresses made towards the inclusion of health benefits in the cost-benefit analysis (CBA) of active transport. Methodology/approach: It is built upon the contracted study for the World Health Organization (WHO) on the economic appraisal of health benefits of walking and cycling investments at the city of Viana do Castelo, the former pilot study in Portugal for evaluating the health benefits of non-motorized transport using the WHO Health Economic Assessment Tool (HEAT). The relative risk values adopted in the HEAT for walking refer to adult population of the age group 20â 74 years and the assessment focus in on average physical activity/regular behaviour of groups of pedestrians and all-cause mortality health impacts. During the case study, it was developed and implemented a mobility survey which aimed to collect behavioural data before and after a street intervention in the historic centre. Findings: Most recent appraisal guidance of walking and cycling and health impact modelling studies reviewed confirm that further research is expected before a more comprehensive appraisal procedure can be adopted in Europe, able to integrate physical activity effects along with other health risks such as those related to road traffic injuries and exposure to air pollution. Social implications: The health benefits assessment of walking investments helped local decision-makers to progress towards sustainable mobility options in the city. Making the population aware of the potential health benefits of regular walking can encourage more people to uptake active transport as part of their daily activities. Originality/value: This study provides a useful review of the health benefits of active transport with a comprehensive analysis of valuation studies, presenting value-added information. It then reports a former assessment of the health effects of active transport in the Portuguese context (case study) using the state-of-the-art economic analysis tool (HEAT) of the World Health Organization which is believed to contribute to a paradigm shift in the transport policy and appraisal practice given the need of shaping future cities (and their citizens) for health through more investments in active transport.

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.