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印度道路交通死亡率建模。

Modelling of road traffic fatalities in India.

机构信息

MRC Epidemiology Unit, University of Cambridge, UK.

出版信息

Accid Anal Prev. 2018 Mar;112:105-115. doi: 10.1016/j.aap.2017.12.019.

DOI:10.1016/j.aap.2017.12.019
PMID:29329015
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5792624/
Abstract

Passenger modes in India include walking, cycling, buses, trains, intermediate public transport modes (IPT) such as three-wheeled auto rickshaws or tuk-tuks, motorised two-wheelers (2W) as well as cars. However, epidemiological studies of traffic crashes in India have been limited in their approach to account for the exposure of these road users. In 2011, for the first time, census in India reported travel distance and mode of travel for workers. A Poisson-lognormal mixture regression model is developed at the state level to explore the relationship of road deaths of all the road users with commute travel distance by different on-road modes. The model controlled for diesel consumption (proxy for freight traffic), length of national highways, proportion of population in urban areas, and built-up population density. The results show that walking, cycling and, interestingly, IPT are associated with lower risk of road deaths, while 2W, car and bus are associated with higher risk. Promotion of IPT has twofold benefits of increasing safety as well as providing a sustainable mode of transport. The mode shift scenarios show that, for similar mode shift across the states, the resulting trends in road deaths are highly dependent on the baseline mode shares. The most worrying trend is the steep growth of death burden resulting from mode shift of walking and cycling to 2W. While the paper illustrates a limited set of mode shift scenarios involving two modes at a time, the model can be applied to assess safety impacts resulting from a more complex set of scenarios.

摘要

印度的乘客出行方式包括步行、骑自行车、乘坐公共汽车、火车、中间公共交通方式(如三轮自动人力车或嘟嘟车)、机动两轮车(2W)以及汽车。然而,印度交通事故的流行病学研究在考虑这些道路使用者的暴露情况方面受到限制。2011 年,印度人口普查首次报告了工人的出行距离和出行方式。在州一级开发了泊松-对数正态混合回归模型,以探索所有道路使用者的道路死亡与不同道路出行方式的通勤出行距离之间的关系。该模型控制了柴油消耗(货运交通代理)、国家高速公路长度、城市地区人口比例和建成区人口密度。结果表明,步行、骑自行车和有趣的是中间公共交通方式与较低的道路死亡风险相关,而 2W、汽车和公共汽车与较高的风险相关。推广中间公共交通方式具有提高安全性和提供可持续交通方式的双重好处。模式转移情景表明,对于各州之间类似的模式转移,道路死亡的趋势高度依赖于基线模式份额。最令人担忧的趋势是,由于步行和骑自行车向 2W 的模式转移,导致死亡负担急剧增加。虽然本文说明了涉及两个模式的有限模式转移情景,但该模型可用于评估更复杂情景下的安全影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be67/5792624/1a926fffd7b3/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be67/5792624/411aa4b0a45a/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be67/5792624/d4f13a89c564/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be67/5792624/1a926fffd7b3/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be67/5792624/411aa4b0a45a/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be67/5792624/d4f13a89c564/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be67/5792624/1a926fffd7b3/gr3.jpg

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Correlates of fatality risk of vulnerable road users in Delhi.德里弱势道路使用者死亡风险的相关因素。
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