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Geospatial Analysis of Severe Road Traffic Accidents in
Singapore
Dr Wee Choon Peng Jeremy
• Injury is a significant cause of mortality and morbidity. In 2012, Road Traffic Accidents (RTAs) are the 9th leading cause of death worldwide and is projected to be the 7th leading cause of death by the year 2030 (1)
• Our goal is to investigate which areas in Singapore have a statistical significantly higher incidence of RTAs resulting in severe Tier 1 injuries, which is defined as an Injury Severity Score (ISS) of more than 15 (2), and develop a spatio-temporal model describing the patterns of RTAs in Singapore in order to identify potential hotspots
• Through this we hope to decrease the incidence of RTAs and provide better care and treatment for the victims.
• Singapore is one of the smallest but most densely populated countries in the world. (3)
Introduction
Materials and Methods
• Data from 1st January 2013 till 31st December 2013 was obtained from the National Trauma Registry (NTR) (4)
• The coordinates where severe RTAs occurred weregeomapped onto the Singapore base map via ArcGIS (5)
• Spatial statistical techniques were used to identify hotspotsvia the Getis-Ord-Gi* algorithm (6)
• The incident data was aggregated using the Integrate function within the Collect Events tool. This generated an icount field which was a collection of weighted points rather than individual incidence points.
• The Spatial Autocorrelation tool was used to create a graph of z scores at each distance and the peak was used as the distance band that reflected maximum spatial correlation for the hotspot analysis. Each of these hotspots were studied to identify if any particular road had 2 or more RTAs.
Materials and Methods
Hotspot
GiZscore
GiZscore P value
X-Coord
Y-Coord
ICOUNT
Type
1
3.551755
0.000383
103.846185
1.319478
21
Motor vehicle driver
1
3.551755
0.000383
103.857135
1.322414
21
Motorbike rider
1
3.551755
0.000383
103.849087
1.332516
21
Pedestrian
1
3.551755
0.000383
103.836995
1.335397
21
Cyclist vs vehicle
1
3.551755
0.000383
103.852287
1.339127
21
Cyclist not vs vehicle
1
3.551755
0.000383
103.862183
1.317196
21
Pedestrian
1
3.551755
0.000383
103.850284
1.336231
21
Pedestrian
1
3.551755
0.000383
103.855445
1.318128
21
Motorbike rider
1
3.551755
0.000383
103.855432
1.313609
21
Cyclist vs vehicle
Hotspot
GiZscore
GiZscore P value
X-Coord
Y-Coord
ICOUNT
Type
1
3.551755
0.000383
103.862260
1.335376
21
Motorbike rider
1
3.551755
0.000383
103.865455
1.324500
21
Pedestrian
1
3.551755
0.000383
103.860629
1.318330
21
Motorbike rider
1
3.551755
0.000383
103.840249
1.329616
21
Motorbike rider
1
3.551755
0.000383
103.843256
1.319650
21
Motor vehicle driver
1
3.551755
0.000383
103.852465
1.338096
21
Others
1
3.551755
0.000383
103.862421
1.331386
21
Motor vehicle back passenger
1
3.551755
0.000383
103.867039
1.327954
21
Cyclist not vs vehicle
1
3.551755
0.000383
103.852951
1.329453
21
Motorbike rider
1
3.551755
0.000383
103.849369
1.341727
21
Pedestrian
1
3.551755
0.000383
103.863435
1.322233
21
Motor vehicle back passenger
2
3.206358
0.001344
103.873563
1.362289
5
Pedestrian
2
3.206358
0.001344
103.874529
1.354622
5
Pedestrian
2
3.206358
0.001344
103.864295
1.353857
5
Motorbike rider
2
3.206358
0.001344
103.858053
1.339891
5
Cyclist vs vehicle
2
3.206358
0.001344
103.870716
1.339496
5
Pedestrian
2
3.206358
0.001344
103.867822
1.355351
5
Motorbike rider
3
3.059226
0.002219
103.870812
1.313187
13
Pedestrian
3
3.059226
0.002219
103.881872
1.315021
13
Cyclist vs vehicle
3
3.059226
0.002219
103.882038
1.315906
13
Motorbike rider
3
3.059226
0.002219
103.876767
1.313682
13
Motorbike rider
3
3.059226
0.002219
103.873650
1.310907
13
Pedestrian
3
3.059226
0.002219
103.878822
1.304350
13
Pedestrian
3
3.059226
0.002219
103.878856
1.318340
13
Motor vehicle driver
3
3.059226
0.002219
103.875782
1.320256
13
Motor vehicle driver
3
3.059226
0.002219
103.879852
1.312667
13
Pedestrian
3
3.059226
0.002219
103.872719
1.314650
13
Pedestrian
3
3.059226
0.002219
103.882115
1.313020
13
Pedestrian
3
3.059226
0.002219
103.885303
1.2979850
13
Motorbike rider
3
3.059226
0.002219
103.883025
1.3027450
13
Pedestrian
4
2.616189
0.008892
103.905751
1.317317
7
Motorbike rider
4
2.616189
0.008892
103.906748
1.314030
7
Pedestrian
4
2.616189
0.008892
103.893508
1.301954
7
Motorbike rider
4
2.616189
0.008892
103.903667
1.305080
7
Motor vehicle driver
4
2.616189
0.008892
103.894158
1.314231
7
Motorbike rider
Hotspot
GiZscore
GiZscore P value
X-Coord
Y-Coord
ICOUNT
Type
4
2.616189
0.008892
103.898141
1.315381
7
Pedestrian
4
2.616189
0.008892
103.893769
1.317078
7
Pedestrian
5
2.440506
0.014667
103.851067
1.305219
12
Pedestrian
5
2.440506
0.014667
103.850777
1.292737
12
Pedestrian
5
2.440506
0.014667
103.844085
1.287272
12
Motorbike rider
5
2.440506
0.014667
103.854162
1.280845
12
Pedestrian
5
2.440506
0.014667
103.851077
1.282050
12
Pedestrian
5
2.440506
0.014667
103.850686
1.294459
12
Cyclist vs vehicle
5
2.440506
0.014667
103.849609
1.283834
12
Pedestrian
5
2.440506
0.014667
103.856932
1.301969
12
Cyclist vs vehicle
5
2.440506
0.014667
103.861996
1.290278
12
Motorbike rider
5
2.440506
0.014667
103.850074
1.303508
12
Pedestrian
5
2.440506
0.014667
103.860304
1.283993
12
Pedestrian
6
2.242448
0.024932
103.891862
1.323215
10
Motor vehicle back passenger
6
2.242448
0.024932
103.891250
1.330655
10
Motorbike rider
6
2.242448
0.024932
103.905668
1.334417
10
Pedestrian
6
2.242448
0.024932
103.910005
1.331132
10
Motorbike rider
6
2.242448
0.024932
103.886592
1.329888
10
Cyclist not vs vehicle
6
2.242448
0.024932
103.895955
1.338068
10
Motorbike rider
6
2.242448
0.024932
103.890079
1.326887
10
Cyclist vs vehicle
6
2.242448
0.024932
103.910159
1.327722
10
Motorbike rider
6
2.242448
0.024932
103.895469
1.323842
10
Motorbike rider
6
2.242448
0.024932
103.898881
1.343146
10
Motorbike rider
• RTAs injured a total of 18 047 people. Out of which there were 467 victims whose ISS were greater than 15 (Tier 1).
• There were 6 statistically significant hotspots
• The individual points were studied within each of the hotspots and the roads that had a relatively high incidence of events were identified (see attached table)
ResultsResults
Discussion• Tier 1 injured RTA victims tend to be young males and most
were motor cyclists and pedestrians
• Police enforcements of traffic laws at the hotspots can help
• Analysis of these hotspots can guide efforts to decrease the response time of the ambulances and transport times
• Despatch centres should be located near these hotspots and staffed adequately
• From the location of the hospitals in Singapore and their proximity to the hotspots, Tan Tock Seng Hospital and Changi General Hospital receive many of the Tier 1 RTA victims and they should receive adequate resource allocation
• Limitations: 1) Only Tier 1 were studied 2) hotspots are determined via distance and do not take into account of how the roads run 3) Data was about 88% complete
Discussion
• Coordinated efforts from multiple agencies are needed for
• Road safety• Prevention of RTAs, • Treatment and eventual rehabilitation of RTA
victims • Important agencies include
• Law Enforcement• Land/Road safety professionals• Prehospital EAS• Trauma Centres and Rehabilitation facilities
• Thus through the study of hotspots of incidences of traumatic events especially those resulting in severe injuries; multiple agencies can use this information to direct their efforts and resources.
ConclusionsConclusions1. Injuries and violence: the facts 2014. Geneva:
World Health Organization, 2014 9789241508018.
2. Baker SP, OʼNeill B, Haddon W, Long WB. The Injury Severity Score. The Journal of Trauma: Injury, Infection, and Critical Care. 1974;14(3):187-96.
3. The World Factbook 2016-17 Washington, DC: Central Intelligence Agency; 2016 [Available from: https://www.cia.gov/library/publications/the-world-factbook/geos/sn.html.
4. National Trauma Registry Annual Registry Report 2013. Health Promotion Board, Singapore, Office NRoD; 2014.
5. ESRI. ArcGIS Desktop. 10.4 ed: Environmental Systems Research Institute.
6. Getis A, Ord JK. The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis. 2010;24(3):189-206.
https://www.cia.gov/library/publications/the-world-factbook/geos/sn.html
Geospatial Analysis of Severe Road Traffic Accidents in SingaporeSlide Number 2Slide Number 3Slide Number 4Slide Number 5Slide Number 6