Safety-in-numbers: A systematic review and meta-analysis of evidence

Abstract

This paper presents a systematic review and meta-analysis of studies that have estimated the relationship between the number of accidents involving motor vehicles and cyclists or pedestrians and the volume of motor vehicles, cyclists and pedestrians. A key objective of most of these studies has been to determine if there is a safety-in-numbers effect. There is safety-in-numbers if the number of accidents increases less than proportionally to traffic volume (for motor vehicles, pedestrians and cyclists). All studies reviewed in the paper are multivariate accident prediction models, estimating regression coefficients that show how the number of accidents depends on the conflicting flows (pedestrians, cyclists, motor vehicles), as well as (in some of the models) other factors that influence the number of accidents. Meta-analysis of regression coefficients involves methodological problems, which require careful consideration of whether the coefficients are sufficiently comparable to be formally synthesised by means of standard techniques of meta-analysis. The comparability of regression coefficients was assessed. It was concluded that a formal synthesis of regression coefficients in studies of the safety-in-numbers effect is defensible. According to a random-effects inverse-variance meta-analysis, the summary estimates of the regression coefficients for traffic volume are 0.50 for motor vehicle volume, 0.43 for cycle volume and 0.51 for pedestrian volume. Estimates are highly consistent between studies. It is concluded that a safety-in-numbers effect exists. It is still not clear whether this effect is causal, nor, if causal, which mechanisms generate the effect.