Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling
Science Journal of Public Health
Volume 3, Issue 3-1, May 2015, Pages: 35-41
Received: Mar. 26, 2015; Accepted: Mar. 26, 2015; Published: Apr. 11, 2015
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Authors
Melidoniotis Evangelos, Department of Anaesthesiology, University Hospital of Heraklion, University of Crete, Iraklion, Greece
Sifaki-Pistolla Dimitra, Epidemiology researcher, Faculty of Medicine, University of Crete, Iraklion, Greece
Chatzea Vasiliki-Eirini, Welfare Management, Faculty of Medicine, University of Crete, Iraklion, Greece
Tzanakis Nikolaos, Associate Professor of Epidemiology, Faculty of Medicine, University of Crete, Iraklion, Greece
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Abstract
Background: Purpose of this study is to monitor the fatal road accidents (FRA) in the Region of Crete, Greece and capture their dynamics in time and space using the Geographical Information System (GIS) technology. It aims to record the FRA spatially from 2001 to 2012, predict their spatio-temporal variance, estimate the number of FRA that should be expected the next years per region and identify the high risk areas. Methods: It is a spatio-temporal study using data from the National Emergency Center’s database. The SPSS 20 and the Arc map 10 were used for the analysis. Spatio-temporal models were applied; specifically, geographical descriptive, Geary’s C, co-kriging interpolation and the Geographical Weighted regression model. Results: According to the Geary’s C, FRA follow a clustered pattern in Crete, whilst they are not randomly occurred (Geary’s C= 0.42; 95%CI= 0.029-0.873; pvalue<0.001). There was a total of 1,039 FRA cases that presented heterogeneous distribution on the island, gathering within the standard distance and ellipse. Time related factors and age were found to be significant to the risk for FRA (pvalue<0.001), [summer months: ExpB=3.43, 95%CI=1.726-5.027 and the night hours: ExpB=2.43; 1.304-4.487]. High risk areas were identified and the expected number of unrecorded FRA was found to vary from 0.0001 to 5.5 cases per 50km2. Conclusions: The present study inserts, for the first time in the Greek bibliography, a new way of monitoring and capturing the FRA dynamics and highlights the use of the GIS technology and dynamic modeling.
Keywords
Fatal Road Accidents, Spatio-Temporal Analysis, High Risk Areas, Interpolation Model, GIS
To cite this article
Melidoniotis Evangelos, Sifaki-Pistolla Dimitra, Chatzea Vasiliki-Eirini, Tzanakis Nikolaos, Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling, Science Journal of Public Health. Special Issue: Spatial Analysis and Mathematics in Health Research, During Times of Global Socio-Economic Instability. Vol. 3, No. 3-1, 2015, pp. 35-41. doi: 10.11648/j.sjph.s.2015030301.17
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