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

Accid Anal Prev. 2019 Aug:129:136-147. doi: 10.1016/j.aap.2019.05.019. Epub 2019 May 28.

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.

Keywords: Cyclists; Meta-analysis; Meta-regression; Pedestrians; Safety-in-numbers.

Publication types

  • Meta-Analysis

MeSH terms

  • Accidents, Traffic / statistics & numerical data*
  • Automobile Driving / statistics & numerical data*
  • Bicycling / statistics & numerical data*
  • Cross-Sectional Studies
  • Humans
  • Models, Statistical
  • Pedestrians / statistics & numerical data*
  • Probability
  • Regression Analysis
  • Risk Assessment
  • Safety