Spatial Assessment of Road Traffic Injuries in the Greater Toronto Area (GTA): Spatial Analysis Framework

Eric de Noronha Vaz, Sina Tehranchi () and Michael Cusimano ()
Additional contact information
Sina Tehranchi: Ryerson University, Postal: Department of Geography and Environmental Studies Ryerson University, Toronto, ON, Canada, http://www.ryerson.ca/
Michael Cusimano: University of Toronto, Postal: Department of Neurosurgery, University of Toronto,, St. Michael’s Hospital, Toronto, ON, Canada, http://www.utoronto.ca/

Journal of Tourism, Sustainability and Well-being, 2017, vol. 5, issue 1, 37-55

Abstract: This research presents a Geographic Information Systems (GIS) and spatial analysis approach based on the global spatial autocorrelation of road traffic injuries for identifying spatial patterns. A locational spatial autocorrelation was also used for identifying traffic injury at spatial level. Data for this research study were acquired from Canadian Institute for Health Information (CIHI) based on 2004 and 2011. Moran’s I statistics were used to examine spatial patterns of road traffic injuries in the Greater Toronto Area (GTA). An assessment of Getis-Ord Gi* statistic was followed as to identify hot spots and cold spots within the study area. The results revealed that Peel and Durham have the highest collision rate for other motor vehicle with motor vehicle. Geographic weighted regression (GWR) technique was conducted to test the relationships between the dependent variable, number of road traffic injury incidents and independent variables such as number of seniors, low education, unemployed, vulnerable groups, people smoking and drinking, urban density and average median income. The result of this model suggested that number of seniors and low education have a very strong correlation with the number of road traffic injury incidents.

Keywords: Spatial Analysis; Geographic Information Systems; Injury Analytics; Traffic Injuries; Geographically Weighted Regression (search for similar items in EconPapers)
JEL-codes: C31 I10 I18 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.cieo.pt/journal/J_1_2017/article4.pdf Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ris:jspord:0930

Access Statistics for this article

Journal of Tourism, Sustainability and Well-being is currently edited by Patrícia Pinto

More articles in Journal of Tourism, Sustainability and Well-being from Cinturs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve University of Algarve, Faculty of Economics, Campus de Gambelas, 8005-139 Faro, Portugal, Coordinator of the Centre: Prof. Patrícia Pinto, E-mail: pvalle@ualg.pt. Contact information at EDIRC.
Bibliographic data for series maintained by Silvia Fernandes ().