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Safety-in-numbers: An updated meta-analysis of estimates.

Accepted version
Peer-reviewed

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Type

Article

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Authors

Elvik, Rune 

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.

Description

Keywords

Cyclists, Meta-analysis, Meta-regression, Pedestrians, Safety-in-numbers, Accidents, Traffic, Automobile Driving, Bicycling, Cross-Sectional Studies, Humans, Models, Statistical, Pedestrians, Probability, Regression Analysis, Risk Assessment, Safety

Journal Title

Accid Anal Prev

Conference Name

Journal ISSN

0001-4575
1879-2057

Volume Title

129

Publisher

Elsevier BV
Sponsorship
Medical Research Council (MR/P024408/1)
Medical Research Council (MR/P02663X/1)
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).