Citation

Wee CPJ, He DX, Win W, Ong MEH. Singapore Med. J. 2020; ePub(ePub): ePub.

Affiliation

Health Services and Systems Research, Duke-NUS Medical School, Singapore.

Copyright

(Copyright © 2020, Singapore Medical Association)

DOI

10.11622/smedj.2020037

PMID

32211912

Abstract

INTRODUCTION: Injury is a significant cause of mortality and morbidity. We aimed to investigate which areas in Singapore have a significantly higher incidence of road traffic accidents (RTA) resulting in severe injuries (Tier 1), which is defined as an Injury Severity Score (ISS) greater than 15, and to develop a spatiotemporal model.

METHODS: Data was obtained from the National Trauma Registry. The RTA locations were geo-mapped onto the Singapore map, and spatial statistical techniques were used to identify hotspots with the Getis-Ord-Gi* algorithm.

RESULTS: From 1 January 2013 till 31 December 2014, there were 35,673 people who were injured as a result of RTAs and 976 Tier 1 RTA victims. A total of 920 people were included in the geospatial analysis. Another 56 were involved in RTAs that did not occur within Singapore or had missing location data and thus were not included. 745 (81.0%) were discharged alive, whereas 175 (19.0%) did not survive to discharge (median ISS 38.00, interquartile range 30.00-48.00). Most of the Tier 1 RTA victims were motorcycle riders (50.1%, n = 461), pedestrians (21.85%, n = 201) and cyclists (9.9%, n = 91). The majority were male and aged 20-40 years, and there was a peak occurrence at 0600-0759 hours. Nine hotspots were identified (p < 0.01).

CONCLUSION: Information from studying hotspots of RTAs, especially those resulting in severe injuries, can be used by multiple agencies to direct resources efficiently.

Language: en

Keywords

Singapore; geospatial analysis; trauma