Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling

Melidoniotis Evangelos; Sifaki-Pistolla Dimitra; Chatzea Vasiliki-Eirini; Tzanakis Nikolaos

doi:doi:10.11648/j.sjph.s.2015030301.17

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Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling

Melidoniotis Evangelos, Sifaki-Pistolla Dimitra, Chatzea Vasiliki-Eirini, Tzanakis Nikolaos

Published in Science Journal of Public Health (Volume 3, Issue 3-1)

Received: 26 March 2015 Accepted: 26 March 2015 Published: 11 April 2015

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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.

Published in	Science Journal of Public Health (Volume 3, Issue 3-1) This article belongs to the Special Issue Spatial Analysis and Mathematics in Health Research, During Times of Global Socio-Economic Instability
DOI	10.11648/j.sjph.s.2015030301.17
Page(s)	35-41
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Fatal Road Accidents, Spatio-Temporal Analysis, High Risk Areas, Interpolation Model, GIS

References

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APA Style

Melidoniotis Evangelos, Sifaki-Pistolla Dimitra, Chatzea Vasiliki-Eirini, Tzanakis Nikolaos. (2015). Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling. Science Journal of Public Health, 3(3-1), 35-41. https://doi.org/10.11648/j.sjph.s.2015030301.17

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ACS Style

Melidoniotis Evangelos; Sifaki-Pistolla Dimitra; Chatzea Vasiliki-Eirini; Tzanakis Nikolaos. Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling. Sci. J. Public Health 2015, 3(3-1), 35-41. doi: 10.11648/j.sjph.s.2015030301.17

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AMA Style

Melidoniotis Evangelos, Sifaki-Pistolla Dimitra, Chatzea Vasiliki-Eirini, Tzanakis Nikolaos. Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling. Sci J Public Health. 2015;3(3-1):35-41. doi: 10.11648/j.sjph.s.2015030301.17

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@article{10.11648/j.sjph.s.2015030301.17,
  author = {Melidoniotis Evangelos and Sifaki-Pistolla Dimitra and Chatzea Vasiliki-Eirini and Tzanakis Nikolaos},
  title = {Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling},
  journal = {Science Journal of Public Health},
  volume = {3},
  number = {3-1},
  pages = {35-41},
  doi = {10.11648/j.sjph.s.2015030301.17},
  url = {https://doi.org/10.11648/j.sjph.s.2015030301.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjph.s.2015030301.17},
  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.},
 year = {2015}
}

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TY  - JOUR
T1  - Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling
AU  - Melidoniotis Evangelos
AU  - Sifaki-Pistolla Dimitra
AU  - Chatzea Vasiliki-Eirini
AU  - Tzanakis Nikolaos
Y1  - 2015/04/11
PY  - 2015
N1  - https://doi.org/10.11648/j.sjph.s.2015030301.17
DO  - 10.11648/j.sjph.s.2015030301.17
T2  - Science Journal of Public Health
JF  - Science Journal of Public Health
JO  - Science Journal of Public Health
SP  - 35
EP  - 41
PB  - Science Publishing Group
SN  - 2328-7950
UR  - https://doi.org/10.11648/j.sjph.s.2015030301.17
AB  - 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.
VL  - 3
IS  - 3-1
ER  -

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Author Information

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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Melidoniotis Evangelos, Sifaki-Pistolla Dimitra, Chatzea Vasiliki-Eirini, Tzanakis Nikolaos. (2015). Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling. Science Journal of Public Health, 3(3-1), 35-41. https://doi.org/10.11648/j.sjph.s.2015030301.17

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ACS Style

Melidoniotis Evangelos; Sifaki-Pistolla Dimitra; Chatzea Vasiliki-Eirini; Tzanakis Nikolaos. Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling. Sci. J. Public Health 2015, 3(3-1), 35-41. doi: 10.11648/j.sjph.s.2015030301.17

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AMA Style

Melidoniotis Evangelos, Sifaki-Pistolla Dimitra, Chatzea Vasiliki-Eirini, Tzanakis Nikolaos. Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling. Sci J Public Health. 2015;3(3-1):35-41. doi: 10.11648/j.sjph.s.2015030301.17

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@article{10.11648/j.sjph.s.2015030301.17,
  author = {Melidoniotis Evangelos and Sifaki-Pistolla Dimitra and Chatzea Vasiliki-Eirini and Tzanakis Nikolaos},
  title = {Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling},
  journal = {Science Journal of Public Health},
  volume = {3},
  number = {3-1},
  pages = {35-41},
  doi = {10.11648/j.sjph.s.2015030301.17},
  url = {https://doi.org/10.11648/j.sjph.s.2015030301.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjph.s.2015030301.17},
  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.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Monitoring Fatal Road Accidents, Using Spatio-Temporal Statistics and GIS Modeling
AU  - Melidoniotis Evangelos
AU  - Sifaki-Pistolla Dimitra
AU  - Chatzea Vasiliki-Eirini
AU  - Tzanakis Nikolaos
Y1  - 2015/04/11
PY  - 2015
N1  - https://doi.org/10.11648/j.sjph.s.2015030301.17
DO  - 10.11648/j.sjph.s.2015030301.17
T2  - Science Journal of Public Health
JF  - Science Journal of Public Health
JO  - Science Journal of Public Health
SP  - 35
EP  - 41
PB  - Science Publishing Group
SN  - 2328-7950
UR  - https://doi.org/10.11648/j.sjph.s.2015030301.17
AB  - 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.
VL  - 3
IS  - 3-1
ER  -

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