Spatial Modelling of Emergency Service Response Times

TL;DR

This paper develops a spatial survival analysis model to better understand emergency response times, revealing the impact of station closures and highlighting areas needing improved fire service coverage.

Contribution

It introduces a sophisticated spatial survival model with harmonic regression and shared frailties for analyzing emergency response times, improving upon previous descriptive methods.

Findings

Response times vary with time-of-day and location.

Station closures may negatively affect response times in specific areas.

The model provides insights for optimizing fire service deployment.

Abstract

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.