Rights statement: This is the peer reviewed version of the following article: Taylor, B. M. (2017), Spatial modelling of emergency service response times. J. R. Stat. Soc. A, 180: 433–453. doi:10.1111/rssa.12192 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/rssa.12192/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Spatial modelling of emergency service response times
AU - Taylor, Benjamin
N1 - This is the peer reviewed version of the following article: Taylor, B. M. (2017), Spatial modelling of emergency service response times. J. R. Stat. Soc. A, 180: 433–453. doi:10.1111/rssa.12192 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/rssa.12192/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
PY - 2017/2
Y1 - 2017/2
N2 - This article concerns the statistical modelling of emergency service response times. We apply advanced methods from spatial survival analysis to deliver inference for data collected by the London Fire Brigade on response times to reported dwelling fires. Existing approaches to the analysis of these data have been mainly descriptive; we describe and demonstrate the advantages of a more sophisticated approach. Our final parametric proportional hazards model includes harmonic regression terms to describe how response time varies with time-of-day and shared spatially correlated frailties on an auxiliary grid for computational efficiency.We investigate the short-term impact of fire station closures in 2014. Whilst the London Fire Brigade are working hard to keep response times down, our findings suggest there is a limit to what can be achieved logistically: the present article identifies areas around the now closed Belsize, Downham, Kingsland, Knightsbridge, Silvertown, Southwark, Wesminster and Woolwich fire stations in which there should perhaps be some concern as to the provision of fire services.
AB - This article concerns the statistical modelling of emergency service response times. We apply advanced methods from spatial survival analysis to deliver inference for data collected by the London Fire Brigade on response times to reported dwelling fires. Existing approaches to the analysis of these data have been mainly descriptive; we describe and demonstrate the advantages of a more sophisticated approach. Our final parametric proportional hazards model includes harmonic regression terms to describe how response time varies with time-of-day and shared spatially correlated frailties on an auxiliary grid for computational efficiency.We investigate the short-term impact of fire station closures in 2014. Whilst the London Fire Brigade are working hard to keep response times down, our findings suggest there is a limit to what can be achieved logistically: the present article identifies areas around the now closed Belsize, Downham, Kingsland, Knightsbridge, Silvertown, Southwark, Wesminster and Woolwich fire stations in which there should perhaps be some concern as to the provision of fire services.
KW - Emergency service response times
KW - Fire station closures
KW - London Fire Brigade
KW - Service provision
KW - Spatial survival
U2 - 10.1111/rssa.12192
DO - 10.1111/rssa.12192
M3 - Journal article
VL - 180
SP - 433
EP - 453
JO - Journal of the Royal Statistical Society: Series A Statistics in Society
JF - Journal of the Royal Statistical Society: Series A Statistics in Society
SN - 0964-1998
IS - 2
ER -