Influencing transport-health interactions through incentivised mode switch using new data and models

IF 3.2 3区 工程技术 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Gillian Harrison, Yuanxuan Yang, Keiran Suchak, Susan M. Grant-Muller, Simon Shepherd, Frances C. Hodgson
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引用次数: 0

Abstract

Introduction

In this study we present a ‘proof-of-concept’ model using novel model integration and new forms of data that addresses the research question, How does incentivising a change in travel mode to reduce personal car use impact health? We focus on simple transport-health interactions between switching between car and bus: the exposure to activity and pollution linked to these modes and how these changes effect health status, which in turn influences the mode choice.

Methods

We identify a basic causal loop diagram of key conceptual feedback between mode choice and health status (related to exposure to activity and pollution). From this we build a simple system dynamics stock and flow simulation model, with data input from spatial micro-simulation synthetic populations derived from ‘track and trace’ data as the output from an agent-based model. We then analyse scenarios of mode shift incentivised by bus fare reduction and bus frequency increase.

Results

In the tested scenarios of this novel modelling approach, we identify that a reduction in bus fare or increase in bus frequency could incentivise a shift from car to bus which would result in a small decrease in relative risk of all causes mortality. Reducing bus fare in particular could provide both health and financial benefits for the most deprived communities.

Conclusions

This modelling approach presented in this data is a promising new method for the study of complex transport-health interactions. From our prototype model we have identified the impacts of mode shift on health status through exposure to pollution and activity, using unique feedbacks that are unaccounted for in conventional models.

利用新数据和模型,通过激励性交通模式转换影响交通与健康之间的相互作用
导言在本研究中,我们提出了一个 "概念验证 "模型,利用新颖的模型集成和新形式的数据来解决研究问题:鼓励改变出行方式以减少个人汽车使用对健康有何影响?我们将重点放在汽车和公交车之间简单的交通-健康相互作用上:与这些模式相关的活动和污染暴露,以及这些变化如何影响健康状况,而健康状况又反过来影响模式选择。在此基础上,我们建立了一个简单的系统动力学存量和流量模拟模型,数据输入来自空间微观模拟合成人口,这些合成人口来自基于代理的模型输出的 "跟踪和追踪 "数据。然后,我们分析了通过降低公共汽车票价和增加公共汽车班次来激励模式转变的情景。结果 在这种新颖建模方法的测试情景中,我们发现降低公共汽车票价或增加公共汽车班次可以激励人们从汽车转向公共汽车,从而使所有原因导致的死亡的相对风险略有下降。降低公交车票价尤其可以为最贫困的社区带来健康和经济效益。通过我们的原型模型,我们利用传统模型未考虑到的独特反馈,确定了模式转换通过暴露于污染和活动对健康状况的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.10
自引率
11.10%
发文量
196
审稿时长
69 days
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