Integrating Spatial-Temporal Risk Factors for an Ambulance Allocation Strategy: A Case Study in Bangkok

Pakinai Chaicharoenwut; Jarotwan Koiwanit; Pannapa Changpetch; Sirisuda Buatongkue; Chumpol Yuangyai

doi:10.1051/matecconf/201819201038

All issues

Volume 192 (2018)

MATEC Web Conf., 192 (2018) 01038

References

Open Access

Issue		MATEC Web Conf. Volume 192, 2018 The 4^th International Conference on Engineering, Applied Sciences and Technology (ICEAST 2018) “Exploring Innovative Solutions for Smart Society”


Article Number		01038
Number of page(s)		4
Section		Track 1: Industrial Engineering, Materials and Manufacturing
DOI		https://doi.org/10.1051/matecconf/201819201038
Published online		14 August 2018

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Li X, Zhao Z, Zhu X, Wyatt T (2011) Covering models and optimization techniques for emergency response facility location and planning: A review. Math Methods Oper Res 74:281–310. doi: 10.1007/s00186-011-0363-4 [CrossRef] [Google Scholar]
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Steiger E, de Albuquerque JP, Zipf A (2015) An advanced systematic literature review on spatiotemporal analyses of Twitter data. Trans GIS 19:809–834. doi: 10.1111/tgis.12132 [CrossRef] [Google Scholar]

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[1] Lim CS, Mamat R, Braunl T (2011) Impact of ambulance dispatch policies on performance of emergency medical services. IEEE Trans Intell Transp Syst 12:624–632. doi: 10.1109/TITS.2010.2101063 [CrossRef] [Google Scholar]

[2] De Maio VJ, Stiell IG, Wells GA, Spaite DW (2003) Optimal defibrillation response intervals for maximum out-of-hospital cardiac arrest survival rates. Ann Emerg Med 42:242–250. doi: 10.1067/mem.2003.266 [CrossRef] [Google Scholar]

[3] Toregas, C., et al., The location of emergency service facilities. Operations research, 1971. 19(6): p. 1363-1373. [CrossRef] [Google Scholar]

[4] Church, R. and C. ReVelle. The maximal covering location problem. in Papers of the Regional Science Association. 1974. Springer. [Google Scholar]

[5] Farahani RZ, Asgari N, Heidari N, et al. (2012) Covering problems in facility location: A review. Comput Ind Eng 62:368–407. doi: 10.1016/j.cie.2011.08.020 [CrossRef] [Google Scholar]

[6] Nilsang S, Yuangyai C, Janjarassuk, U, Cheng CY, Locating an ambulance base by using social media: A case study in Bangkok. Annals of Operations. Research In process of public. [Google Scholar]

[7] Li X, Zhao Z, Zhu X, Wyatt T (2011) Covering models and optimization techniques for emergency response facility location and planning: A review. Math Methods Oper Res 74:281–310. doi: 10.1007/s00186-011-0363-4 [CrossRef] [Google Scholar]

[8] Ratanavaraha V, Suangka S (2014) Impacts of accident severity factors and loss values of crashes on expressways in Thailand. IATSS Res 37:130–136. doi: 10.1016/j.iatssr.2013.07.001 [CrossRef] [Google Scholar]

[9] Peacock PJ, Peacock JL (2006) Emergency call work-load, deprivation and population density: An investigation into ambulance services across England. J Public Health (Bangkok) 28:111–115. doi: 10.1093/pubmed/fdi079 [CrossRef] [Google Scholar]

[10] Laylavi F, Rajabifard A, Kalantari M (2017) Event relatedness assessment of Twitter messages for emergency response. Inf Process Manag 53:266–280. doi: 10.1016/j.ipm.2016.09.002 [CrossRef] [Google Scholar]

[11] Steiger E, de Albuquerque JP, Zipf A (2015) An advanced systematic literature review on spatiotemporal analyses of Twitter data. Trans GIS 19:809–834. doi: 10.1111/tgis.12132 [CrossRef] [Google Scholar]