Pandemic hospital site selection: a GIS-based MCDM approach employing Pythagorean fuzzy sets.

Aslı Çalış Boyacı, Aziz Şişman
Author Information
  1. Aslı Çalış Boyacı: Department of Industrial Engineering, Ondokuz Mayıs University, 55139, Samsun, Turkey. asli.calis@omu.edu.tr. ORCID
  2. Aziz Şişman: Department of Geomatics Engineering, Ondokuz Mayıs University, 55139, Samsun, Turkey. ORCID

Abstract

COVID-19 poses many challenges for hospitals around the world. Each country attempts to solve the problems in its hospitals using different methods. In Turkey, two pandemic hospitals were built in İstanbul, the most crowded province. In addition, some hospitals were designated as pandemic hospitals. This study focuses on the methods used for site selection for a pandemic hospital in Atakum, a district of Samsun City, Turkey. As a solution to the problem, initially, spatial analysis was performed using GIS to produce maps based on seven criteria obtained from the insight of an expert team. Analytic hierarchy process (AHP) augmented by interval-valued Pythagorean fuzzy numbers (PFNs) was then used to determine weights for the criteria. Distance to transportation network was the most important criterion influencing the selection process and the least significant one was the distance to fire stations. Based on the criteria weights, and five rules specified by the expert team, 13 suitable locations for a pandemic hospital were determined using GIS. The technique for order preference by similarity to ideal solution (TOPSIS) method was used to determine the final ranking of 13 alternative locations (A1-A13). A10 was identified as the most appropriate site and A11 as the least appropriate site for a pandemic hospital. Finally, sensitivity analysis was performed to investigate how changes in weight values of the criteria affect the ranking of the alternatives.

Keywords

References

Adalı EA, Tuş A (2021) Hospital site selection with distance-based multi-criteria decision-making methods. Int J Healthc Manag 14(2):534–544
Ak MF, Gul M (2019) AHP–TOPSIS integration extended with Pythagorean fuzzy sets for information security risk analysis. Complex Intell Syst 5:113–126
Alban A, Chick SE, Dongelmans DA, Vlaar APJ, Sent D (2020) ICU capacity management during the COVID-19 pandemic using a process simulation. Intensive Care Med 46:1624–1626
Artz M (2014) What is GIS? https://gisandscience.com/2014/05/27/what-is-gis/ (Retrieved 10 February 2021)
Aslan MF, Unlersen MF, Sabanci K, Durdu A (2021) CNN-based transfer learning–BiLSTM network: A novel approach for COVID-19 infection detection. Appl Soft Comput 98:106912
Aydin N, Seker S (2021) Determining the location of isolation hospitals for COVID-19 via Delphi-based MCDM method. Int J Intell Syst 36:3011–3034
Bakioglu G, Atahan AO (2021) AHP integrated TOPSIS and VIKOR methods with Pythagorean fuzzy sets to prioritize risks in self-driving vehicles. Appl Soft Comput 99:106948
Bragazzi NL, Mansour M, Bonsignore A, Ciliberti R (2020) The role of hospital and community pharmacists in the management of COVID-19: towards an expanded definition of the roles, responsibilities, and duties of the pharmacist. Pharmacy 8(3):2–15
Çalık A (2020) A novel Pythagorean fuzzy AHP and fuzzy TOPSIS methodology for green supplier selection in the Industry 4.0 era. Soft Comput 25:2253–2265. https://doi.org/10.1007/s00500-020-05294-9 [DOI: 10.1007/s00500-020-05294-9]
Çalış Boyacı A, Şişman A, Sarıcaoğlu K (2021) Site selection for waste vegetable oil and waste battery collection boxes: a GIS-based hybrid hesitant fuzzy decision-making approach. Environ Sci Pollut Res 28:17431–17444
Çetinkaya C, Özceylan E, Erbaş M, Kabak M (2016) GIS-based fuzzy MCDA approach for siting refugee camp: A case study for southeastern Turkey. Int J Disaster Risk Reduct 18:218–231
Chatterjee D, Mukherjee B (2013) Potential hospital location selection using AHP: A study in rural India. Int J Comput Appl 71(17):1–7
Dell’Ovo M, Capolongo S, Oppio A (2018) Combining spatial analysis with MCDA for the siting of healthcare facilities. Land Use Policy 76:634–644
Eghtesadifard M, Afkhami P, Bazyar A (2020) An integrated approach to the selection of municipal solid waste landfills through GIS, K-Means and multi-criteria decision analysis. Environ Res 185:109348
Garg H (2018) Some methods for strategic decision-making problems with immediate probabilities in Pythagorean fuzzy environment. Int J Intell Syst 33(4):687–712
Gul M (2020) Application of Pythagorean fuzzy AHP and VIKOR methods in occupational health and safety risk assessment: the case of a gun and rifle barrel external surface oxidation and colouring unit. Int J Occup Saf Ergon 26(4):705–718
Hashemkhani Zolfani S, Yazdani M, Ebadi Torkayesh A, Derakhti A (2020) Application of a gray-based decision support framework for location selection of a temporary hospital during COVID-19 pandemic. Symmetry 12:886
Hwang CL, Yoon K (1981) Multiple attribute decision making. Lecture notes in economics and mathematical systems. Springer-Verlag, Berlin
Ilbahar E, Karaşan A, Cebi S, Kahraman C (2018) A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Saf Sci 103:124–136
Ivanov D, Dolgui A (2021) OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications. Int J Prod Econ 232:107921
Jozaghi A, Alizadeh B, Hatami M, Flood I, Khorrami M, Khodaei N, Tousi EG (2018) A comparative study of the AHP and TOPSIS techniques for dam site selection using GIS: A case study of Sistan and Baluchestan province, Iran. Geosciences 8(12):494–517
Kaveh M, Kaveh M, Mesgari MS, Paland RS (2020) Multiple criteria decision-making for hospital location-allocation based on improved genetic algorithm. Appl Geomatics 12:291–306
Li Y, Zobel CW (2020) Exploring supply chain network resilience in the presence of the ripple effect. Int J Prod Econ 228:107693
Luo C, Ju Y, Santibanez-Gonzalez EDR, Dong P, Wang A (2020) The waste-to-energy incineration plant site selection based on hesitant fuzzy linguistic Best-Worst method ANP and double parameters TOPSIS approach: A case study in China. Energy 211:118564
Ministry of Health. Pandemic Hospitals (2020) https://hasta.saglik.gov.tr/Eklenti/36907/0/pandemi-hastaneleripdf.pdf . (Retrieved 2 January 2021)
Mousavi-Nasab SH, Sotoudeh-Anvari A (2017) A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Mater Des 121:237–253
Nsaif QA, Khaleel SM, Khateeb AH (2020) Integration of GIS and remote sensing technique for hospital site selection in Baquba district. J Eng Sci Technol 15(3):1492–1505
Opricovic S, Tzeng GH (2004) Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. Eur J Oper Res 156:445–455
Otay I, Jaller M (2020) A novel Pythagorean fuzzy AHP and TOPSIS method for the wind power farm location selection problem. J Intell Fuzzy Syst 38(1):835–852
Pell JP, Sirel JM, Marsden AK, Ford I, Cobbe SM (2001) Effect of reducing ambulance response times on deaths from out of hospital cardiac arrest: cohort study. BMJ 322:1385–1388
Pons PT, Markovchick VJ (2002) Eight minutes or less: does the ambulance response time guideline impact trauma patient outcome? J Emerg Med 23(1):43–48
Rahimi F, Goli A, Rezaee R (2017) Hospital location-allocation in Shiraz using geographical information system (GIS). Shiraz E-Med J 18(8):e57572
Ramya S, Devadas V (2019) Integration of GIS, AHP and TOPSIS in evaluating suitable locations for industrial development: A case of Tehri Garhwal district, Uttarakhand, India. J Clean Prod 238:117872
Regulation of Investment Principles of Ministry of Health Hospitals (2003) https://planlamadb.saglik.gov.tr/Eklenti/3163/0/saglik-bakanligina-ait-hastanelerin yatirim-esaslarinin-belirlenmesine-dair-yonergepdf.pdf (Retrieved 3 February 2021)
Regulation of Spatial Planning (2014) https://www.mevzuat.gov.tr/mevzuat?MevzuatNo=19788&MevzuatTur=7&MevzuatTertip=5 (Retrieved 3 February 2021)
Rezayee M (2020) Hospital site selection in Iskandar Malaysia using GIS-multi criteria analysis. Int J Basic Sci Appl Comput 2(10):8–15
Rızvanoğlu O, Kaya S, Ulukavak M, Yeşilnacar Mİ (2020) Optimization of municipal solid waste collection and transportation routes, through linear programming and geographic information system: a case study from Şanlıurfa, Turkey. Environ Monit Assess 192(9). https://doi.org/10.1007/s10661-019-7975-1
Rostami-Tabar B, Rendon-Sanchez JF (2021) Forecasting COVID-19 daily cases using phone call data. Appl Soft Comput 100:106932
Şahin T, Ocak S, Top M (2019) Analytic hierarchy process for hospital site selection. Health Policy Technol 8:42–50
Sarkar B, Biswas A (2021) Pythagorean fuzzy AHP-TOPSIS integrated approach for transportation management through a new distance measure. Soft Comput 25:4073–4089. https://doi.org/10.1007/s00500-020-05433-2 [DOI: 10.1007/s00500-020-05433-2]
Sisman A (2013) Epidemiologic features and risk factors of Crimean–Congo hemorrhagic fever in Samsun province, Turkey. J Epidemiol 23(2):95–102
Soltani A, Marandi EZ (2011) Hospital site selection using two-stage fuzzy multi-criteria decision making process. J Urban Environ Eng 5(1):32–43
Soltani A, Inaloo RB, Rezaei M, Shaer F, Riyabi MA (2019) Spatial analysis and urban land use planning emphasising hospital site selection: a case study of Isfahan city. Bull Geogr Socio-Econ Ser 43:71–89
Terzi O, Sisman A, Canbaz S, Dündar C, Peksen Y (2013) A geographic information system-based analysis of ambulance station coverage area in Samsun, Turkey. Singap Med J 54(11):653–658
TSI. Turkish Statistical Institute (2020) https://biruni.tuik.gov.tr/medas/?kn=95&locale=tr (Retrieved 20 February 2021)
USGS (2021) Earth explorer. https://earthexplorer.usgs.gov (Retrieved 15 January 2021)
Vahidnia MH, Alesheikh AA, Alimohammadi A (2009) Hospital site selection using fuzzy AHP and its derivatives. J Environ Manag 90:3048–3056
World Health Organization (WHO) (2014) Hospital preparedness for epidemics. http://apps.who.int/iris/bitstream/handle/10665/151281/9;jsessionid=C7E947D70C7BDC6C6FA2D0C1D8F10487?sequence=1 . Accessed 20 Feb 2021
World Health Organization (WHO) (2020) COVID-19 Strategy Update. https://www.who.int/publications/i/item/covid-19-strategy-update---14-april-2020 . Accessed 25 Feb 2021
Yager RR (2014) Pythagorean membership grades in multicriteria decision making. IEEE Trans Fuzzy Syst 22(4):958–965
Yağma NM, Donkor AG, Gökler ME (2020) Management of hospitals during COVID-19 pandemic. Med Res Rep 3:155–161
Yal GP, Akgün H (2014) Landfill site selection utilizing TOPSIS methodology and clay liner geotechnical characterization: a case study for Ankara, Turkey. Bull Eng Geol Environ 73:369–388
Yildiz A, Ayyildiz E, Gümüş AT, Özkan C (2020) A modified balanced scorecard based hybrid Pythagorean fuzzy AHP-TOPSIS methodology for ATM site selection problem. Int J Inf Technol Decis Mak 19(2):365–384
Yılmaz ÖF, Özçelik G, Yeni FB (2021) Ensuring sustainability in the reverse supply chain in case of the ripple effect: A two-stage stochastic optimization model. J Clean Prod 282:124548
Yucesan M, Gul M (2020) Hospital service quality evaluation: an integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS. Soft Comput 24:3237–3255
Zègre-Hemsey J, Sommargren CE, Drew BJ (2011) Initial ECG acquisition within 10 minutes of arrival at the emergency department in persons with chest pain: time and gender differences. J Emerg Nurs 37(1):109–112
Zeng S, Chen J, Li X (2016) A hybrid method for Pythagorean fuzzy multiple-criteria decision making. Int J Inf Technol Decis Mak 15(2):403–422
Zhang X, Xu Z (2014) Extension of TOPSIS to multiple criteria decision making with Pythagorean fuzzy sets. Int J Intell Syst 29(12):1061–1078

MeSH Term

COVID-19
Geographic Information Systems
Hospitals
Humans
Mobile Health Units
Pandemics
Refuse Disposal
SARS-CoV-2
Turkey

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