Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-27T05:30:49.971Z Has data issue: false hasContentIssue false

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: [email protected]).

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.

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

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