An Econometric Analysis to Explore the Temporal Variability of the Factors Affecting Crash Severity Due to COVID-19
DOI: 10.3390/su16031233
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Summary
This study investigates the temporal variability of factors influencing crash severity in Virginia, USA, from 2018 to 2023, specifically examining the impact of the COVID-19 pandemic and associated stay-at-home orders. The research addresses a gap in existing literature, which largely focused on the early stages of the pandemic, by providing a longitudinal analysis that covers pre-pandemic, lockdown, and post-pandemic periods. The primary motivation is to understand how drastic shifts in traffic volume and driver behavior during the pandemic altered road safety dynamics, particularly regarding the severity of injuries despite overall reductions in crash frequency. The authors utilized crash data sourced from the Virginia Department of Transportation, encompassing over 128,000 crash records across six years. The dataset was stratified into distinct periods: pre-pandemic (2018–2019), the specific stay-at-home order period (March–June 2020), and post-lockdown phases (2021–2023). Crash severity was categorized using the KABCO scale into three groups: property damage only (PDO), minor injury, and severe injury (fatal or incapacitating). The study employed multilevel ordinal logistic regression (M-OLR) to account for spatial heterogeneity across Virginia’s 23 planning districts. The model evaluated various predictors, including driver behaviors (speeding, alcohol, distraction), vulnerable road user involvement, roadway characteristics, weather conditions, and temporal factors. The results indicate that while total crash numbers dropped significantly in 2020 due to reduced travel, the proportion of severe injuries increased from approximately 5.5% in 2018–2019 to 6.88% in 2020. This elevated severity rate persisted in subsequent years, remaining higher than pre-pandemic levels through 2023. The analysis revealed that less congested roads during the pandemic correlated with riskier driving behaviors, notably an increase in speed violations. Additionally, the study highlighted heightened risks for vulnerable road users, such as pedestrians, cyclists, and motorcyclists, whose crashes became more severe due to changes in transportation habits. Environmental and roadway features, such as adverse weather and traffic signals, remained consistent determinants of crash outcomes throughout the study period. The findings underscore that the reduction in traffic volume did not equate to improved road safety outcomes in terms of injury severity. Instead, the pandemic induced behavioral changes, particularly increased speeding, which exacerbated the consequences of crashes. The study concludes that road safety strategies must be adaptive to societal shifts and evolving driver behaviors. It emphasizes the critical role of individual mental states and behaviors in traffic safety management, advocating for holistic approaches that address these dynamic factors to ensure safety in a post-pandemic landscape. These insights provide actionable guidance for policymakers and urban planners to develop resilient safety protocols.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-19 |
| archive | success | openalex | — | — | 5 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-20 |
| chunk | success | chunk | — | — | 1 | 2026-06-20 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-20 |
| promote | success | — | — | — | 1 | 2026-06-19 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-20 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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- Empirical Findings: crash risk outcomes