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On the Evaluation of the Ambulance Capacity of the Asian Side of Istanbul in the Case of a Serious Earthquake

Published online by Cambridge University Press:  27 October 2020

Aysun Pınarbaşı
Affiliation:
Department of Industrial Engineering, Eastern Mediterranean University, Famagusta, North Cyprus
Tareq Babaqi*
Affiliation:
Department of Industrial Engineering, Eastern Mediterranean University, Famagusta, North Cyprus
Béla Vizvári
Affiliation:
Department of Industrial Engineering, Eastern Mediterranean University, Famagusta, North Cyprus
*
Correspondence and reprint requests to Tareq Babaqi, Department of Industrial Engineering, Eastern Mediterranean University, Famagusta, North Cyprus via Mersin 10, Turkey (e-mail: tareq.babaqi@cc.emu.edu.tr).

Abstract

Objectives:

The purpose of this study is to analyze a strategy for the assignment and transportation of injured patients to hospital to decrease the demand on transportation, in both predisaster and postdisaster periods, on the Anatolian side of Istanbul.

Methods:

Two approaches are used in this study: a Voronoi diagram, and a heuristic approach to the problem of scheduling. A Voronoi diagram is used to divide the city into 74 regions, where each hospital has a certain region of responsibility. The transportation strategy of 1 hospital is modeled by minimizing the makespan (ie, the maximal completion time) and the work-in-process, which are used as different objectives in scheduling theory.

Results:

The total waiting time of 100 injured people was minimized to 13,036 min when a total of 3 vehicles was used in the studied region, on the Asian side of Istanbul. The transportation capacity and total operating capacity of the hospitals should be approximately equal.

Conclusions:

The people of Istanbul will be in a safer position if the suggested measures are implemented. This is an important consideration, as Istanbul is situated in a region where serious earthquakes are possible at any moment.

Type
Original Research
Copyright
© 2020 Society for Disaster Medicine and Public Health, Inc.

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References

REFERENCES

TurkStat. Turkish Statistical Institute, Transportation statistics. 2015; http://www.tuik.gov.tr/. Accessed September 10, 2020.Google Scholar
Karadoğan, BC. Estimating the Future Role and Success of the Istanbul Airport: A Regional Planning Perspective. 2019. Ankara, Turkey: Middle East Technical University.Google Scholar
Kalkan, E, Gülkan, P, Öztürk, NY, et al., Seismic hazard in the Istanbul metropolitan area: a preliminary re-evaluation. J Earthquake Eng. 2008;12(S2):151-164.CrossRefGoogle Scholar
Picozzi, M, Strollo, A, Parolai, S, et al., Site characterization by seismic noise in Istanbul, Turkey. Soil Dyn Earthquake Eng. 2009;29(3):469-482.CrossRefGoogle Scholar
Istambul Metropolitan Municipality. The Study on a Disaster Prevention/Mitigation Basic Plan in Istanbul Including Seismic Microzonation in the Republic of Turkey. 2002. https://www.preventionweb.net/publications/view/43027. Accessed September 10, 2020.Google Scholar
Naghii, MR. Public health impact and medical consequences of earthquakes. Rev Panam Salud Publica. 2005;18:216-221.CrossRefGoogle ScholarPubMed
World Health Organization, Disasters and Emergencies. Definitions Training Package. Addis Ababa; WHO/EHA PanAfrican Emergency Training Centre; 2002.Google Scholar
Karadag, CO, Hakan, AK. Ethical dilemmas in disaster medicine. Iran Red Crescent Med J. 2012;14(10):602-612.Google Scholar
World Medical Association. WMA Statement on Medical Ethics in the Event of Disasters. 2017. https://www.wma.net/policies-post/wma-statement-on-medical-ethics-in-the-event-of-disasters/. Accessed March 15, 2020.Google Scholar
Shavarani, SM, Golabi, M, Vizvari, B. Assignment of medical staff to operating rooms in disaster preparedness: a novel stochastic approach. IEEE Trans Eng Manag. 2019;67(3).Google Scholar
CAL-EMA. State of California Emergency Plan. https://www.sanjoseca.gov/DocumentCenter/View/47602. Accessed July 1, 2009.Google Scholar
Ansal, A, Özaydın, K, Edinçliler, A, et al. Earthquake Master Plan for Istanbul. Turkey: Metropolital Municipality of Istanbul, Planning and Construction Directorate, Geotechnical and Earthquake Investigation Department; 2003.Google Scholar
Jin, S, Jeong, S, Kim, J, et al. A logistics model for the transport of disaster victims with various injuries and survival probabilities. Ann Oper Res. 2014;230(1):17-33.CrossRefGoogle Scholar
Liu, Z, Yu, H, Sui, J, et al. A research on vehicle scheduling problem to rescue the victims from chemical and biological terrorist attacks. In: 2011 IEEE international conference on automation and logistics (ICAL). 2011.CrossRefGoogle Scholar
Amadini, R, Sefrioui, I, Mauro, J, et al. Fast post-disaster emergency vehicle scheduling. In: Distributed Computing and Artificial Intelligence. New York: Springer; 2013:219-226.CrossRefGoogle Scholar
Ozdamar, L. Planning Helicopter Logistics in Disaster Relief. Germany: OR Spectrum; 2011;33(3):655-672.CrossRefGoogle Scholar
Shavarani, SM, Vizvari, B. Post-disaster transportation of seriously injured people to hospitals. J Humanitarian Logist Supply Chain Management. 2018;8(2):227-251.CrossRefGoogle Scholar
Pinedo, M. Scheduling: Theory, Algorithms and Applications. Englewood Cliffs, NJ: Prentice-Hall; 1995.Google Scholar
Conway, R, Maxwell, W, McClain, JO, et al. The role of work-in-process inventory in serial production lines. Oper Res. 1988;36(2):229-241.CrossRefGoogle Scholar
Graham, RL. Bounds on multiprocessing timing anomalies. SIAM J Appl Math. 1969;17(2):416-429.CrossRefGoogle Scholar
Coffman, J, Edward, G, Garey, MR, et al. An application of bin-packing to multiprocessor scheduling. SIAM J Comput. 1978;7(1):1-17.CrossRefGoogle Scholar
Sevimoğlu, O. Assessment of major air pollution sources in efforts of long term air quality improvement in Istanbul. J Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2020;24(2):389-405.CrossRefGoogle Scholar
Saritas, E. New Researches New Ideas on Social Sciences. Victoria, Canada: Trafford Publishing; 2017.Google Scholar
Nufusu. İstanbul İlçeleri nüfusu. https://www.nufusu.com/ilceleri/istanbul-ilceleri-nufusu. Accessed September 24, 2018.Google Scholar
Erdik, M, Demircioglu, M, Sesetyan, K, et al. Earthquake hazard in Marmara region, Turkey. 2004;24(8):605-631.Google Scholar
Hubert-Ferrari, A, Armijo, R, King, G, et al. Morphology, displacement, and slip rates along the North Anatolian Fault, Turkey. 2002;107(B10):ETG 9-1-ETG 9-33.CrossRefGoogle Scholar
Alpar, B, Altınok, Y, Gazioğlu, C, et al. Tsunami hazard assessment in Istanbul. J Black Sea/Mediter Environ. 2003;9(1):3-29.Google Scholar
BDTIM. Türkiye ve tsunami riski. http://www.koeri.boun.edu.tr/sismo/2/tsunami/turkiye-ve-tsunami-riski/. Accessed April 28, 2017.Google Scholar
Yilmaz, BK, Karakuş, BY, Çevik, E, et al. Metropolde 112 Acil Sağlik Hizmeti. İstanbul Tıp Fakültesi Dergisi. 2014;77(3):37-40.CrossRefGoogle Scholar
Aurenhammer, F, Klein, R. Voronoi diagrams. Handb Comput Geom. 2000;5(10):201-290.CrossRefGoogle Scholar
ESRI. ArcGIS Desktop10.7. Redlands, CA: Environmental Systems Research Institute; 2017.Google Scholar
Sabti, ANH. Solution Approaches for Multı Objective Parallel Machine Scheduling Problems [dissertation]. Eskişehir, Turkey: Anadolu University; 2017.Google Scholar
Shmoys, DB, Wein, J, Williamson, DP. Scheduling parallel machines on-line. SIAM J Comput. 1995;24(6):1313-1331.CrossRefGoogle Scholar
Haupt, R. A survey of priority rule-based scheduling. OR Spektr. 1989;11(1):3-16.CrossRefGoogle Scholar
CBINSIGHTS. 38 Ways Drones Will Impact Society: From Fighting War to Forecasting Weather UAVs Change Everything. New York: CBINSIGHTS; 2019.Google Scholar