A space-time multivariate Bayesian model to analyse road traffic accidents by severity
Author(s)
Boulieri, A
Liverani, S
de Hoogh, K
Blangiardo, M
Type
Journal Article
Abstract
his paper investigates the dependencies between severity levels of
road traffic accidents, accounting at the same time for spatial and temporal cor-
relations. The study analyses road traffic accidents data at ward level in England
over the period 2005-2013. We include in our model multivariate spatially struc-
tured and unstructured effects to capture the respective dependencies between
severities, within a Bayesian hierarchical formulation. We also include a tempo-
ral component to capture the time effects and we carry out an extensive model
comparison. The results show important associations in both spatially structured
and unstructured effects between severities, while a downward temporal trend is
observed for low and high severity levels. Maps of posterior accident rates indi-
cate elevated risk within big cities for accidents of low severity and in suburban
areas in the north and on the southern coast of England for accidents of high
2
Boulieri
et al.
severity. Posterior probability of extreme rates is used to suggest the presence
of hot spots in a public health perspective.
road traffic accidents, accounting at the same time for spatial and temporal cor-
relations. The study analyses road traffic accidents data at ward level in England
over the period 2005-2013. We include in our model multivariate spatially struc-
tured and unstructured effects to capture the respective dependencies between
severities, within a Bayesian hierarchical formulation. We also include a tempo-
ral component to capture the time effects and we carry out an extensive model
comparison. The results show important associations in both spatially structured
and unstructured effects between severities, while a downward temporal trend is
observed for low and high severity levels. Maps of posterior accident rates indi-
cate elevated risk within big cities for accidents of low severity and in suburban
areas in the north and on the southern coast of England for accidents of high
2
Boulieri
et al.
severity. Posterior probability of extreme rates is used to suggest the presence
of hot spots in a public health perspective.
Date Issued
2016-01-27
Date Acceptance
2015-10-11
Citation
Journal of the Royal Statistical Society. Series A. Statistics in Society, 2016, 180 (1), pp.119-139
ISSN
0964-1998
Publisher
Wiley
Start Page
119
End Page
139
Journal / Book Title
Journal of the Royal Statistical Society. Series A. Statistics in Society
Volume
180
Issue
1
Copyright Statement
© 2016 The Authors Journal of the Royal Statistical Society: Series A (Statistics in Society) Published by John Wiley & Sons Ltd on behalf of the Royal Statistical Society. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Sponsor
National Institute for Health Research
Grant Number
MET 11/13 Elliott
Subjects
Social Sciences
Science & Technology
Physical Sciences
Social Sciences, Mathematical Methods
Statistics & Probability
Mathematical Methods In Social Sciences
Mathematics
Bayesian hierarchical models
Multivariate modelling
Probability maps
Road traffic accidents
Space-time correlation
USE REGRESSION-MODELS
SMALL-AREA ESTIMATION
GEOMETRIC DESIGN
SPATIAL-ANALYSIS
CRASH COUNTS
DISEASE RISK
EXPOSURE
RATES
RANKING
POISSON
0104 Statistics
1403 Econometrics
Publication Status
Published