Acceso abierto

Modelling the road network riskiness for motorcycle transport: The use of accident probability and accessibility to emergency medical service


Cite

Aftyka, A., Rybojad, B., & Rudnicka-Drozak, E. (2014). Are there any differences in medical emergency team interventions between rural and urban areas? A single-centre cohort study. Australian Journal of Rural Health, 22(5), 223–228. https://doi.org/10.1111/ajr.12108 Search in Google Scholar

Alanazy, A. R. M., Wark, S., Fraser, J., & Nagle, A. (2019). Factors impacting patient outcomes associated with use of emergency medical services operating in urban versus rural areas: A systematic review. International journal of environmental research and public health, 16(10), 1728. https://doi.org/10.3390/ijerph16101728 Search in Google Scholar

Al-Shaqsi, S. (2010). Models of international emergency medical service (EMS) systems. Oman medical journal, 25(4), 320. https://doi.org/10.5001/omj.2010.92 Search in Google Scholar

Amorim, M., Ferreira, S., & Couto, A. (2017). Road safety and the urban emergency medical service (uEMS): Strategy station location. Journal of Transport & Health, 6, 60–72. https://doi.org/10.1016/j.jth.2017.04.005 Search in Google Scholar

Andersson, A. K., & Chapman, L. (2011). The impact of climate change on winter road maintenance and traffic accidents in West Midlands, UK. Accident Analysis & Prevention, 43(1), 284–289. https://doi.org/10.1016/j.aap.2010.08.025 Search in Google Scholar

Azimian, A., Pyrialakou, V. D., Lavrenz, S., & Wen, S. (2021). Exploring the effects of area-level factors on traffic crash frequency by severity using multivariate space-time models. Analytic Methods in Accident Research, 31(100163). https://doi.org/10.1016/j.amar.2021.100163 Search in Google Scholar

Bahouth, G., Graygo, J., Digges, K., Schulman, C., & Baur, P. (2014). The benefits and tradeoffs for varied high-severity injury risk thresholds for advanced automatic crash notification systems. Traffic injury prevention, 15(1), 134–140. https://doi.org/10.1080/15389588.2014.936011 Search in Google Scholar

Bastida, J. L., Aguilar, P. S., & González, B. D. (2004). The economic costs of traffic accidents in Spain. Journal of Trauma and Acute Care Surgery, 56(4), 883–889. https://doi.org/10.1097/01.TA.0000069207.43004.A5 Search in Google Scholar

Bíl, M., Andrášik, R., & Janoška, Z. (2013). Identification of hazardous road locations of traffic accidents by means of kernel density estimation and cluster significance evaluation. Accident Analysis & Prevention, 55, 265–273. https://doi.org/10.1016/j.aap.2013.03.003 Search in Google Scholar

Bíl, M., Andrášik, R., & Sedoník, J. (2019). A detailed spatiotemporal analysis of traffic crash hotspots. Applied Geography, 107, 82–90. https://doi.org/10.1016/j.apgeog.2019.04.008 Search in Google Scholar

Byrne, J. P., Mann, N. C., Dai, M., Mason, S. A., Karanicolas, P., Rizoli, S., & Nathens, A. B. (2019). Association between emergency medical service response time and motor vehicle crash mortality in the United States. JAMA surgery, 154(4), 286–293. https://doi.org/10.1001/jamasurg.2018.5097 Search in Google Scholar

Cater, C. I. (2017). Tourism on two wheels: Patterns of motorcycle leisure in Wales. Tourism Management, 61, 180–189. https://doi.org/10.1016/j.tourman.2017.02.007 Search in Google Scholar

Clark, D. E., & Cushing, B. M. (2002). Predicted effect of automatic crash notification on traffic mortality. Accident Analysis & Prevention, 34(4), 507–513. https://doi.org/10.1016/S0001-4575(01)00048-3 Search in Google Scholar

Clark, D. E., Qian, J., Sihler, K. C., Hallagan, L. D., & Betensky, R. A. (2012). The distribution of survival times after injury. World journal of surgery, 36(7), 1562–1570. https://doi.org/10.1007/s00268-012-1549-5 Search in Google Scholar

Clark, D. E., Winchell, R. J., & Betensky, R. A. (2013). Estimating the effect of emergency care on early survival after traffic crashes. Accident Analysis & Prevention, 60, 141–147. https://doi.org/10.1016/j.aap.2013.08.019 Search in Google Scholar

Di Stasi, L. L., Contreras, D., Cándido, A., Cañas, J. J., & Catena, A. (2011). Behavioral and eye-movement measures to track improvements in driving skills of vulnerable road users: First-time motorcycle riders. Transportation research part F: traffic psychology and behaviour, 14(1), 26–35. https://doi.org/10.1016/j.trf.2010.09.003 Search in Google Scholar

Dolejš, M., Purchard, J., & Javorčák, A. (2020). Generating a spatial coverage plan for the emergency medical service on a regional scale: Empirical versus random forest modelling approach. Journal of Transport Geography, 89(102889). https://doi.org/10.1016/j.jtrangeo.2020.102889 Search in Google Scholar

Dvořák J., & Mrkvička T. (2021). Graphical tests of independence for general distributions. Computational statistics. https://doi.org/10.1007/s00180-021-01134-y Search in Google Scholar

Enayati, S., Mayorga, M. E., Rajagopalan, H. K., & Saydam, C. (2018). Real-time ambulance redeployment approach to improve service coverage with fair and restricted workload for EMS providers. Omega,79, 67–80. https://doi.org/10.1016/j.omega.2017.08.001 Search in Google Scholar

Gonzalez, R. P., Cummings, G. R., Phelan, H. A., Mulekar, M. S., & Rodning, C. B. (2009). Does increased emergency medical services prehospital time affect patient mortality in rural motor vehicle crashes? A statewide analysis. The American journal of surgery, 197(1), 30–34. https://doi.org/10.1016/j.amjsurg.2007.11.018 Search in Google Scholar

Gutierrez-Osorio, C., & Pedraza, C. (2020). Modern data sources and techniques for analysis and forecast of road accidents: A review. Journal of traffic and transportation engineering (English edition), 7(4), 432–446. https://doi.org/10.1016/j.jtte.2020.05.002 Search in Google Scholar

Hashtarkhani, S., Kiani, B., Bergquist, R., Bagheri, N., Vafaeinejad, R., & Tara, M. (2020). An age-integrated approach to improve measurement of potential spatial accessibility to emergency medical services for urban areas. The International journal of health planning and management, 35(3), 788–798. https://doi.org/10.1002/hpm.2960 Search in Google Scholar

Harmsen, A. M. K., Giannakopoulos, G. F., Moerbeek, P. R., Jansma, E. P., Bonjer, H. J., & Bloemers, F. W. (2015). The influence of prehospital time on trauma patients outcome: a systematic review. Injury, 46(4), 602–609. https://doi.org/10.1016/j.injury.2015.01.008 Search in Google Scholar

He, Z., Qin, X., Xie, Y., & Guo, J. (2018). Service location optimization model for improving rural emergency medical services. Transportation Research Record, 2672(32), 83–93. https://doi.org/10.1177/0361198118791363 Search in Google Scholar

He, Z., Qin, X., Renger, R., & Souvannasacd, E. (2019). Using spatial regression methods to evaluate rural emergency medical services (EMS). The American Journal of Emergency Medicine, 37(9), 1633–1642. https://doi.org/10.1016/j.ajem.2018.11.029 Search in Google Scholar

Iamtrakul, P., Tanaboriboon, Y., & Hokao, K. (2003). Analysis of motorcycle accidents in developing countries: a case study of Khon Kaen, Thailand. Journal of the Eastern Asia Society for Transportation Studies, 5, 147–162. Search in Google Scholar

Jiang, F., Yuen, K. K. R., & Lee, E. W. M. (2020). Analysis of motorcycle accidents using association rule mining-based framework with parameter optimization and GIS technology. Journal of safety research, 75, 292–309. https://doi.org/10.1016/j.jsr.2020.09.004 Search in Google Scholar

Jung, S., Xiao, Q., & Yoon, Y. (2013). Evaluation of motorcycle safety strategies using the severity of injuries. Accident Analysis & Prevention, 59, 357–364. https://doi.org/10.1016/j.aap.2013.06.030 Search in Google Scholar

Kashani, A. T., Rabieyan, R., & & Besharati, M. M. (2014). A data mining approach to investigate the factors influencing the crash severity of motorcycle pillion passengers. Journal of safety research, 51, 93–98. https://doi.org/10.1016/j.jsr.2014.09.004 Search in Google Scholar

Kingham, S., Sabel, C. E., & Bartie, P. (2011). The impact of the ‘school run’ on road traffic accidents: A spatio-temporal analysis. Journal of Transport Geography, 19(4), 705–711. https://doi.org/10.1016/j.jtrangeo.2010.08.011 Search in Google Scholar

Klapka, P., Kraft, S., & Halás, M. (2020). Network based definition of functional regions: A graph theory approach for spatial distribution of traffic flows. Journal of Transport Geography, 88, 102855. https://doi.org/10.1016/j.jtrangeo.2020.102855 Search in Google Scholar

Kmet, L., & Macarthur, C. (2006). Urban–rural differences in motor vehicle crash fatality and hospitalization rates among children and youth. Accident Analysis & Prevention, 38(1), 122–127. https://doi.org/10.1016/j.aap.2005.07.007 Search in Google Scholar

Kononen, D. W., Flannagan, C. A., & Wang, S. C. (2011). Identification and validation of a logistic regression model for predicting serious injuries associated with motor vehicle crashes. Accident Analysis & Prevention, 43(1), 112–122. https://doi.org/10.1016/j.aap.2010.07.018 Search in Google Scholar

Kraft, S., Marada, M., Petříček, J., Blažek, V., & Mrkvička, T. (2022). Identification of motorcycle accidents hotspots in the Czech Republic and their conditional factors: The use of KDE+ and two-step cluster analysis. The Geographical Journal, 188(3), 444–458. https://doi.org/10.1111/geoj.12446 Search in Google Scholar

Lahausse, J. A., Fildes, B. N., Page, Y., & Fitzharris, M. P. (2008). The potential for automatic crash notification systems to reduce road fatalities. Annals of Advances in Automotive Medicine/Annual Scientific Conference, Vol. 52, p. 85. Search in Google Scholar

Li, M. D., Doong, J. L., Chang, K. K., Lu, T. H., & Jeng, M. C. (2008). Differences in urban and rural accident characteristics and medical service utilization for traffic fatalities in less-motorized societies. Journal of safety research, 39(6), 623-630. https://doi.org/10.1016/j.jsr.2008.10.008 Search in Google Scholar

Liu, H. H., Chen, A. Y., Dai, C. Y., & Sun, W. Z. (2014). Physical infrastructure assessment for emergency medical response. Journal of Computing in Civil Engineering, 29(3), 04014044. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000395 Search in Google Scholar

McCoy, C. E., Menchine, M., Sampson, S., Anderson, C., & Kahn, C. (2013). Emergency medical services out-of-hospital scene and transport times and their association with mortality in trauma patients presenting to an urban Level I trauma center. Annals of emergency medicine, 61(2), 167–174. https://doi.org/10.1016/j.annemergmed.2012.08.026 Search in Google Scholar

Newgard, C. D., Fu, R., Bulger, E., Hedges, J. R., Mann, N. C., Wright, D. A., & Hansen, M. (2017). Evaluation of rural vs urban trauma patients served by 9-1-1 emergency medical services. JAMA surgery, 152(1), 11–18. https://doi.org/10.1001/jamasurg.2016.3329 Search in Google Scholar

Noland, R. B., & Quddus, M. A. (2004). A spatially disaggregate analysis of road casualties in England. Accident Analysis & Prevention, 36(6), 973–984. https://doi.org/10.1016/j.aap.2003.11.001 Search in Google Scholar

Nunn, S., & Newby, W. (2015). Landscapes of risk: The geography of fatal traffic collisions in Indiana, 2003 to 2011. The Professional Geographer, 67(2), 269–281. https://doi.org/10.1080/00330124.2014.935165 Search in Google Scholar

Pinch, P., & Reimer, S. (2012). Moto-mobilities: Geographies of the Motorcycle and Motorcyclists. Mobilities, 7(3), 439–457. https://doi.org/10.1080/17450101.2012.659466 Search in Google Scholar

Pileček, J., Chromý, P., & Jančák, V. (2013). Social Capital and Local Socioeconomic Development: The Case of Czech Peripheries. Tijdschrift voor economische en sociale geografie, 104(5), 604–620. https://doi.org/10.1111/tesg.12053 Search in Google Scholar

Plevin, R. E., Kaufman, R., Fraade-Blanar, L., & Bulger, E. M. (2017). Evaluating the potential benefits of advanced automatic crash notification. Prehospital and disaster medicine, 32(2), 156–164. https://doi.org/10.1017/S1049023X16001473 Search in Google Scholar

Rezapour, M., Molan, A. M., & Ksaibati, K. (2020). Analyzing injury severity of motorcycle at-fault crashes using machine learning techniques, decision tree and logistic regression models. International journal of transportation science and technology, 9(2), 89–99. https://doi.org/10.1016/j.ijtst.2019.10.002 Search in Google Scholar

Rodrigues, E. M., Villaveces, A., Sanhueza, A., & Escamilla-Cejudo, J. A. (2014). Trends in fatal motorcycle injuries in the Americas, 1998–2010. International journal of injury control and safety promotion, 21(2), 170–180. https://doi.org/10.1080/17457300.2013.792289 Search in Google Scholar

Rowden, P., Watson, B., Haworth, N., Lennon, A., Shaw, L., & Blackman, R. (2016). Motorcycle riders’ self-reported aggression when riding compared with car driving. Transportation research part F: traffic psychology and behaviour, 36, 92–103. https://doi.org/10.1016/j.trf.2015.11.006 Search in Google Scholar

Sánchez-Mangas, R., García-Ferrrer, A., De Juan, A., & Arroyo, A. M. (2010). The probability of death in road traffic accidents. How important is a quick medical response? Accident Analysis & Prevention, 42(4), 1048–1056. https://doi.org/10.1016/j.aap.2009.12.012 Search in Google Scholar

Salum, J. H., Kitali, A. E., Bwire, H., Sando, T., & Alluri, P. (2019). Severity of motorcycle crashes in Dar es Salaam, Tanzania. Traffic injury prevention, 20(2), 189–195. https://doi.org/10.1080/15389588.2018.1544706 Search in Google Scholar

Serre, T., Masson, C., Llari, M., Canu, B., Py, M., & Perrin, C. (2019). Airbag jacket for motorcyclists: evaluation of real effectiveness. In IRCOBI 2019, International Conference on the Biomechanics of Injury, (533–547). hal-02958978f Search in Google Scholar

Shahzad, M. (2020). Review of road accident analysis using GIS technique. International journal of injury control and safety promotion, 27(4), 472–481. https://doi.org/10.1080/17457300.2020.1811732 Search in Google Scholar

Shafabakhsh, G. A., Famili, A., & Bahadori, M. S. (2017). GIS-based spatial analysis of urban traffic accidents: Case study in Mashhad, Iran. Journal of traffic and transportation engineering (English edition), 4(3), 290–299. https://doi.org/10.1016/j.jtte.2017.05.005 Search in Google Scholar

Shinar, D. (2012). Safety and mobility of vulnerable road users: pedestrians, bicyclists, and motorcyclists. Accident Analysis & Prevention, 44(1), 1–2. https://doi.org/10.1016/j.aap.2010.12.031 Search in Google Scholar

Swaroop, M., Straus, D. C., Agubuzu, O., Esposito, T. J., Schermer, C. R., & Crandall, M. L. (2013). Pre-hospital transport times and survival for hypotensive patients with penetrating thoracic trauma. Journal of emergencies, trauma, and shock, 6(1), 16. https://doi.org/10.4103/0974-2700.106320 Search in Google Scholar

Travis, L. L., Clark, D. E., Haskins, A. E., & Kilch, J. A. (2012). Mortality in rural locations after severe injuries from motor vehicle crashes. Journal of safety research, 43(5-6), 375–380. https://doi.org/10.1016/j.jsr.2012.10.004 Search in Google Scholar

Thollon, L., Godio, Y., Bidal, S., & Brunet, C. (2010). Evaluation of a new security system to reduce thoracic injuries in case of motorcycle accidents. International journal of crashworthiness, 15(2), 191–199. https://doi.org/10.1080/13588260903102062 Search in Google Scholar

Verner, R. (2008). Emergency Medical Service in the Czech Republic. Annals of Emergency Medicine, 51(4), 486. https://doi.org/10.1016/j.annemergmed.2008.01.318 Search in Google Scholar

Vlahogianni, E. I., Yannis, G., & Golias, J. C. (2012). Overview of critical risk factors in Power-Two-Wheeler safety. Accident Analysis & Prevention, 49, 12–22. https://doi.org/10.1016/j.aap.2012.04.009 Search in Google Scholar

Wilde, E. T. (2013). Do emergency medical system response times matter for health outcomes? Health economics, 22(7), 790–806. https://doi.org/10.1002/hec.2851 Search in Google Scholar

World Health Organization (2018). Global status report on road safety 2018: summary (No. WHO/NMH/NVI/18.20). World Health Organization. Search in Google Scholar

Wu, J., Subramanian, R., Craig, M., Starnes, M., & Longthorne, A. (2013). The effect of earlier or automatic collision notification on traffic mortality by survival analysis. Traffic injury prevention, 14(1), 50–57. https://doi.org/10.1080/15389588.2013.799279 Search in Google Scholar

Xia, T., Song, X., Zhang, H., Song, X., Kanasugi, H., & Shibasaki, R. (2019). Measuring spatio-temporal accessibility to emergency medical services through big GPS data. Health & place, 56, 53–62. https://doi.org/10.1016/j.healthplace.2019.01.012 Search in Google Scholar

Xie, K., Ozbay, K., & Yang, H. (2019). A multivariate spatial approach to model crash counts by injury severity. Accident Analysis & Prevention, 122, 189–198. https://doi.org/10.1016/j.aap.2018.10.009 Search in Google Scholar

Xiong, Q., Liu, Y., Xing, L., Wang, L., Ding, Y., & Liu, Y. (2022). Measuring spatio-temporal disparity of location-based accessibility to emergency medical services. Health & Place, 74, 102766. https://doi.org/10.1016/j.healthplace.2022.102766 Search in Google Scholar

Zhang, J., Hayashi, Y., & Frank, L. D. (2021). COVID-19 and transport: Findings from a world-wide expert survey. Transport Policy, 103, 68–85. https://doi.org/10.1016/j.tranpol.2021.01.011 Search in Google Scholar

eISSN:
2199-6202
Idioma:
Inglés
Calendario de la edición:
4 veces al año
Temas de la revista:
Business and Economics, Business Management, Industries, Environmental Management, Geosciences, Geography