Journal of safety research · 2026
How have the associations between crash risks and roadway, speed, and the built environment changed after COVID-19?
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Dong Xiaoxia, Guerra Erick, Wu Jasmine Siyu
Аннотация
INTRODUCTION: Several U.S. cities saw significant increases in traffic fatalities after the COVID-19 pandemic. What remains unclear is what factors are associated with the rise in traffic crash risks post-COVID, and how these associations are different from those pre-COVID. This inadequate understanding presents an obstacle to optimizing resource allocation and prioritizing safety enhancement strategies post-COVID.
METHOD: We used multilevel negative binomial logit models to examine the associations between motor-vehicle crashes and fatal crashes that occurred on roadways and at intersections in the Philadelphia region and a series of road configuration, speed, built environment, and socioeconomic factors. We compared these associations between pre-COVID (2017-2019) and post-COVID (2021-2023) periods to identify notable differences.
RESULTS: We found that roads and intersections in the study area became deadlier post-COVID amid an overall decline in total traffic crashes. Fast local roads and arterials had the most drastic increases in fatal crash risks post-COVID. COVID widened the disparity in fatal crashes between neighborhoods with higher and lower poverty rates.
CONCLUSIONS AND PRACTICAL APPLICATIONS: By comparing the relationship between crashes, roadway characteristics, socioeconomic conditions, and the built environment, our study enables targeted recommendations for roadway design, street network planning, and speed management to enhance safety post-COVID.
METHOD: We used multilevel negative binomial logit models to examine the associations between motor-vehicle crashes and fatal crashes that occurred on roadways and at intersections in the Philadelphia region and a series of road configuration, speed, built environment, and socioeconomic factors. We compared these associations between pre-COVID (2017-2019) and post-COVID (2021-2023) periods to identify notable differences.
RESULTS: We found that roads and intersections in the study area became deadlier post-COVID amid an overall decline in total traffic crashes. Fast local roads and arterials had the most drastic increases in fatal crash risks post-COVID. COVID widened the disparity in fatal crashes between neighborhoods with higher and lower poverty rates.
CONCLUSIONS AND PRACTICAL APPLICATIONS: By comparing the relationship between crashes, roadway characteristics, socioeconomic conditions, and the built environment, our study enables targeted recommendations for roadway design, street network planning, and speed management to enhance safety post-COVID.