Ridesharing and motor vehicle crashes: a spatial ecological case-crossover study of trip-level data.
Ridesharing and motor vehicle crashes: a spatial ecological case-crossover study of trip-level data.
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DOI：
10.1136/injuryprev-2020-043644
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发表时间：
2021-04
期刊：
影响因子：
--
通讯作者：
Humphreys DK
中科院分区：
文献类型：
--
作者：
Morrison CN;Mehranbod C;Kwizera M;Rundle AG;Keyes KM;Humphreys DK
自2010年开始运营以来，拼车服务(例如Uber、Lyft)已在全球范围内促成了超过110亿次出行，但拼车对机动车伤害事故的影响在很大程度上是未知的。这一空间生态案例交叉使用了2017年和2018年纽约市(NYC)高度空间和时间分辨率的出行级别拼车数据和事故级别伤害撞车数据。分析的时空单位是被划分为几个小时的纽约市出租车区多边形。对于每个出租车区域小时，我们计算了拼车出行起点和拼车出行目的地的计数。病例单位为发生任何机动车伤害事故的出租车区小时数，匹配的对照单位为病例单位前一周(−168h)和病例单元后一周(+168h)的同一出租车区。条件Logistic回归模型估计了发生撞车事故的几率(分为所有受伤撞车、驾车者受伤撞车、行人受伤撞车、自行车受伤撞车)相对于拼车出行计数。控制出租车出行的模型和其他理论上相关的协变量(例如，降雨量、假期)。在一个出租车专用区内每增加100次搭乘，与对照的出租车专用区相比，发生任何伤害事故的几率增加4.6%(OR=1.046；95%CI：1.032，1.060)。检测到了驾车者受伤和行人受伤撞车事故的关联，但没有检测到自行车受伤撞车事故。使用旅行目的地作为利益暴露的分析结果实质上是相似的。共乘增加了机动车碰撞造成的伤害负担，特别是在出行节点发生的驾车者和行人受伤碰撞。
Ridesharing services (e.g., Uber, Lyft) have facilitated over 11 billion trips worldwide since operations began in 2010, but the impacts of ridesharing on motor vehicle injury crashes are largely unknown. This spatial ecological case-cross over used highly spatially and temporally resolved trip-level rideshare data and incident-level injury crash data for New York City (NYC) for 2017 and 2018. The space-time units of analysis were NYC taxi zone polygons partitioned into hours. For each taxi zone-hour we calculated counts of rideshare trip origins and rideshare trip destinations. Case units were taxi zone-hours in which any motor vehicle injury crash occurred, and matched control units were the same taxi zone from one week before (−168 hours) and one week after (+168 hours) the case unit. Conditional logistic regression models estimated the odds of observing a crash (separated into all injury crashes, motorist injury crashes, pedestrian injury crashes, cyclist injury crashes) relative to rideshare trip counts. Models controlled for taxi trips and other theoretically relevant covariates (e.g., precipitation, holidays). Each additional 100 rideshare trips originating within a taxi zone-hour was associated with 4.6% increased odds of observing any injury crash compared to the control taxi zone-hours (OR=1.046; 95%CI:1.032,1.060). Associations were detected for motorist injury and pedestrian injury crashes, but not cyclist injury crashes. Findings were substantively similar for analyses conducted using trip destinations as the exposure of interest. Ridesharing contributes to increased injury burden due to motor vehicle crashes, particularly for motorist and pedestrian injury crashes at trip nodes.
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