Safety-in-numbers: An updated meta-analysis of estimates.
Accident; analysis and prevention
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Elvik, R., & Goel, R. (2019). Safety-in-numbers: An updated meta-analysis of estimates.. Accident; analysis and prevention, 129 136-147. https://doi.org/10.1016/j.aap.2019.05.019
ABSTRACT Safety-in-numbers denotes the tendency for the number of accidents to increase less than in proportion to traffic volume. This paper updates a meta-analysis of estimates of safety-in-numbers published in 2017 (Elvik and Bjørnskau, Safety Science, 92, 274-282). Nearly all studies find safety-in-numbers, but the numerical estimates vary considerably. As virtually all studies are cross-sectional, it is not possible to determine if safety-in-numbers represents a causal relationship. Meta-regression analysis was performed to identify factors which may explain the large heterogeneity of estimates of safety-in-numbers. It was found that safety-in-numbers tends to be stronger for pedestrians than for cyclists, and stronger at the macro-level (e.g. citywide) than at the micro-level (e.g. in junctions). Recent studies find a stronger tendency towards safety-in-numbers than older studies. Key words: Safety-in-numbers; meta-analysis; meta-regression; cyclists; pedestrians
Humans, Models, Statistical, Probability, Risk Assessment, Regression Analysis, Cross-Sectional Studies, Safety, Accidents, Traffic, Automobile Driving, Bicycling, Pedestrians
RE is supported by METAHIT, an MRC Methodology Panel project (MR/ P02663X/1). RG is supported by TIGTHAT, an MRC Global Challenges Project (MR/P024408/1).
Medical Research Council (MR/P02663X/1)
External DOI: https://doi.org/10.1016/j.aap.2019.05.019
This record's URL: https://www.repository.cam.ac.uk/handle/1810/293179
Attribution-NonCommercial-NoDerivatives 4.0 International
Licence URL: https://creativecommons.org/licenses/by-nc-nd/4.0/