160 Using Hotspot Analysis to Detect Spatial & Time Trends for Pedestrian Traffic Accident Fatalities in Miami-Dade County, Florida: 2011 – 2015

Tuesday, June 6, 2017: 3:30 PM-4:00 PM
Eagle, Boise Centre
Anthony Llau , Florida Department of Health in Miami-Dade County, Miami, FL

BACKGROUND:  According to the Florida Department of Highway Safety and Motor Vehicles (FDSMV), pedestrian traffic accident fatalities in Miami-Dade County has steadily increased in recent years. During 2015, there were 93 fatal pedestrian traffic accidents in Miami-Dade County, representing an increase of 27% since 2011. Although previous research has generally focused on either vehicle or pedestrian characteristics, few analyses have examined the spatial-temporal relationship. Therefore, in order to examine potential space-time patterns of fatal pedestrian traffic accidents, a hotspot analysis was conducted using GIS.

METHODS: Data was retrieved from the National Highway Traffic Safety Administration’s (NHTSA) Fatal Analysis Reporting System (FARS), a national database containing all fatal traffic crashes within the U.S. and its territories. Fatal pedestrian traffic accidents occurring in Miami-Dade County during 2011 - 2015 were included for analysis. Traffic crash dates and geographical coordinates were extracted using SAS (version 9.4). Spatial and time trends were analyzed on biannual intervals using ARCGIS Desktop’s (version 10.3.1) Emerging Hot Spot Analysis tool. The distance interval was set at two miles in order to compare spatial trends by neighborhood. 

RESULTS: There were 370 fatal pedestrian traffic accidents in Miami-Dade County during the five-year period, with the greatest number of crashes occurring in 2015. The Emerging Hotspot Analysis tool detected sporadic spatial-temporal clustering of high crash incidence in several areas within central Miami-Dade County, particularly within the Allapattah, Brownsville, Wynwood, Downtown, and Little Havana neighborhoods. Moreover, these neighborhoods did not experience clustering of low crash counts (i.e. cold-spots) during the five-year period. No other spatial-temporal patterns were observed outside of the central Miami-Dade County area.

CONCLUSIONS: Spatial-temporal analysis using GIS identified clustering of high fatal pedestrian traffic crash incidents in several neighborhoods within Central Miami-Dade County. This area has previously been identified as having the highest unsheltered homeless population within the county according to the Miami-Dade Homeless Trust. Homeless persons have previously been known to be at greater risk for pedestrian fatalities compared to other residents. In addition, these areas are readily accessible to forms of fixed-route public transportation including Miami-Dade Transit Metrorail (heavy rail), Metromover (automated people mover), and Metrobus (fixed route bus). Therefore, accessing these modes of transportation has the potential to result in a greater number of trips by foot. Pedestrian traffic accidents can be reduced by improving visibility for pedestrians and drivers, adding refuge islands, improved street lighting, and crossing streets at designated crosswalks or intersections.