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

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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.

Suggested Citation

  • Vaz, Eric & Tehranchi, Sina & Cusimano, Michael, 2017. "Spatial Assessment of Road Traffic Injuries in the Greater Toronto Area (GTA): Spatial Analysis Framework," Journal of Spatial and Organizational Dynamics, CIEO-Research Centre for Spatial and Organizational Dynamics, University of Algarve, vol. 5(1), pages 37-55.
  • Handle: RePEc:ris:jspord:0930
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    References listed on IDEAS

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    1. Marco Helbich & Wolfgang Brunauer & Eric Vaz & Peter Nijkamp, 2014. "Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria," Urban Studies, Urban Studies Journal Limited, vol. 51(2), pages 390-411, February.
    2. Vaz, Eric & Khaper, Monica, 2016. "New Resources For Smart Food Retail Mapping. A Gis And The Open Source Perspective," Journal of Spatial and Organizational Dynamics, CIEO-Research Centre for Spatial and Organizational Dynamics, University of Algarve, vol. 4(4), pages 305-313.
    3. repec:ris:cieodp:2013_020 is not listed on IDEAS
    4. repec:aph:ajpbhl:10.2105/ajph.2011.300528_6 is not listed on IDEAS
    5. Mackie, Peter, 2005. "The London congestion charge: A tentative economic appraisal. A comment on the paper by Prud'homme and Bocajero," Transport Policy, Elsevier, vol. 12(3), pages 288-290, May.
    6. Chisholm, Daniel & Naci, Huseyin & Hyder, Adnan Ali & Tran, Nhan T. & Peden, Margie, 2012. "Cost effectiveness of strategies to combat road traffic injuries in sub-Saharan Africa and South East Asia: mathematical modelling study," LSE Research Online Documents on Economics 55474, London School of Economics and Political Science, LSE Library.
    7. repec:aph:ajpbhl:2000:90:1:70-77_0 is not listed on IDEAS
    8. repec:aph:ajpbhl:2003:93:9:1541-1545_1 is not listed on IDEAS
    9. Vaz, Eric, 2013. "The Spatial Business Landscape of India," Journal of Spatial and Organizational Dynamics, CIEO-Research Centre for Spatial and Organizational Dynamics, University of Algarve, vol. 1(4), pages 241-253.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Spatial Analysis; Geographic Information Systems; Injury Analytics; Traffic Injuries; Geographically Weighted Regression;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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