The analysis of risk assessment for the transmission of COVID-19 by using PROMETHEE and ELECTRE methods

Abstract

Multi-Criteria Decision Making (MCDM) methods help researchers in solving many prob-lems in terms of numerical analysis. However, MCDM methods have not been very popular in the health sector. In this study, five ones of Turkey’s most intense and highly populated cities were selected and the risk of the spread of Covid-19 disease was evaluated on the basis of seven criteria. The PROMETHEE and the ELECTRE methods were conducted to rank the cities in terms of the spread of Covid-19. The PROMETHEE method correctly ranked the most risky city as Istanbul, but ELECTRE ranked Istanbul the second most risky. The results of the meth-ods are compared with real data. PROMETHEE gave more convenient results than ELECTRE. Also, this paper offers a new field of study to the literature.

Keywords

• Multi Criteria Decision Making
• ELECTRE
• PROMETHEE
• Disease
• COVID-19

References

1. REFERENCES
2. [1] Castro AF. Capital budgeting in health organiza-tions: Application of the multicriteria method pro-methee V1. Fuzzy Econ Rev 2002;7:93.
3. [2] Hatami-Marbini A, Tavana M. An extension of the Electre I method for group decision-making under a fuzzy environment. Omega 2011;39:373−386. [CrossRef]
4. [3] Ozcan T, Celebi N, Esnaf S. Comparative analysis of multi-criteria decision making methodologies and implementation of a warehouse location selection problem. Expert Syst Appl 2011;38:9773−9779. [CrossRef]
5. [4] Khandan M, Maghsoudipour M, Vosoughi S. Ranking of working shift groups in an Iranian petro-chemical company using ELECTRE method based on safety climate assessment results. J Chin Inst Ind Eng 2011;28:537−542. [CrossRef]
6. [5] Sánchez-Lozano JM, Antunes CH, García-Cascales MS, Dias LC. GIS-based photovoltaic solar farms site selection using ELECTRE-TRI: Evaluating the case for Torre Pacheco, Murcia, Southeast of Spain. Renew Energ 2014;66:478−494. [CrossRef]
7. [6] Sánchez-Lozano J, García-Cascales M, Lamata M. Comparative TOPSIS-ELECTRE TRI methods for optimal sites for photovoltaic solar farms. Case study in Spain. J Clean Prod 2016;127:387−398. [CrossRef]
8. [7] Seddiki M, Anouche K, Bennadji A, Boateng P. A multi-criteria group decision-making method for the thermal renovation of masonry buildings: The case of Algeria. Energ Build 2016;129:471−483. [CrossRef]

9. [8] Nassereddine M, Eskandari H. An integrated MCDM approach to evaluate public transportation systems in Tehran. Transp Res Part Policy Pract 2017;106:427−439. [CrossRef]
10. [9] Mousavi M, Gitinavard H, Mousavi S. A soft comput-ing based-modified ELECTRE model for renewable energy policy selection with unknown information. Renew Sustain Energ Rev 2017;68:774−787. [CrossRef]
11. [10] Kumar P, Singh RK, Kharab K. A comparative anal-ysis of operational performance of Cellular Mobile Telephone Service Providers in the Delhi working area using an approach of fuzzy ELECTRE. Appl Soft Comput 2017;59:438−447. [CrossRef]
12. [11] Govindan K, Kadziński M, Sivakumar R. Application of a novel PROMETHEE-based method for con-struction of a group compromise ranking to pri-oritization of green suppliers in food supply chain. Omega 2017;71:129−145. [CrossRef]
13. [12] Lopes APF, Muñoz MM, Alarcón-Urbistondo P. Regional tourism competitiveness using the PROMETHEE approach. Ann Tour Res 2018;73:1−13. [CrossRef]
14. [13] Haddad M, Sanders D. Selection of discrete multi-ple criteria decision making methods in the pres-ence of risk and uncertainty. Oper Res Perspect 2018;5:357−370. [CrossRef]
15. [14] Ostovare M, Shahraki MR. Evaluation of hotel websites using the multicriteria analysis of PROMETHEE and GAIA: Evidence from the five-star hotels of Mashhad. Tour Manag Perspect 2019;30:107−116. [CrossRef]
16. [15] De Souza Barbosa A, Shayani RA, de Oliveira MAG. A multi-criteria decision analysis method for regu-latory evaluation of electricity distribution service quality. Util Policy 2018;53:38−48. [CrossRef]
17. [16] Ezbakhe F, Pérez-Foguet A. Decision analysis for sustainable development: The case of renewable energy planning under uncertainty. Eur J Oper Res 2021;291:601−613. [CrossRef]
18. [17] Thokala P, Duenas A. Multiple criteria decision anal-ysis for health technology assessment. Value Health 2012;15:1172−1181. [CrossRef]
19. [18] Hatami-Marbini A, Tavana M, Moradi M, Kangi F. A fuzzy group Electre method for safety and health assessment in hazardous waste recycling facilities. Saf Sci 2013;51:414−426. [CrossRef]
20. [19] Amaral TM, Costa AP. Improving decision-mak-ing and management of hospital resources: An application of the PROMETHEE II method in an Emergency Department. Oper Res Health Care 2014;3:1−6. [CrossRef]
21. [20] Mishra SS, Muduli K, Dash M, Yadav DK. PROMETHEE-based analysis of hcwm challenges in healthcare sector of Odisha. In: Satapathy SC, Bhateja V, Das S, editors. Smart Computing and Informatics. Berlin: Springer; 2018. pp. 163−70. [CrossRef]
22. [21] Silva Ad, Gurgel Júnior GD, Falk JA, Pedroso MDM. Maternal and child patient safety: a multiple crite-ria analysis of the decisionmaking preferences of nurse managers. Rev Bras Saúde Materno Infant 2018;18:577−591. [CrossRef]
23. [22] Jamshidiantehrani M, Ahmadzadeh A, Rahimisadr M, Abdolmohammadi M. Identifying and priori-tizing the factors affecting the agility of the supply chain of pharmaceutical company using multi-cri-teria decision-making methods in COVID-19 pan-demic. Sys Rev Pharm 2020;11:371−381.
24. [23] Ghorui N, Ghosh A, Mondal SP, Bajuri MY, Ahmadian A, Salahshour S, et al. Identification of dominant risk factor involved in spread of COVID-19 using hesitant fuzzy MCDM methodology. Results Phys 2021;21:103811. [CrossRef]
25. [24] Benayoun R, Roy B, Sussman B. ELECTRE: Une méthode pour guider le choix en présence de points de vue multiples. Note de travail. 1966;49:2−120.
26. [25] Brans J-P, Vincke P, Mareschal B. How to select and how to rank projects: The PROMETHEE method. Eur J Oper Res 1986;24:228−238. [CrossRef]
27. [26] Senkayas H, Hekimoglu H. Application of PROMETHEE method for multiple criteria supplier selection problem. J Product 2013;2:63−80.
28. [27] Aabed K, Lashin MM. An analytical study of the fac-tors that influence COVID-19 spread. Saudi J Biol Sci 2021;28:1177−1195. [CrossRef]
29. [28] Cao W, Chen C, Li M, Nie R, Lu Q, Song D, et al. Important factors affecting COVID-19 transmis-sion and fatality in metropolises. Public Health 2021;190:e21. [CrossRef]
30. [29] TUIK. Address Based Population Registration System [Press release]. http://www.tuik.gov.tr/PreTablo.do?alt_id=1059 Last Accessed Date: 12.03.2021.
31. [30] Bhadra A, Mukherjee A, Sarkar K. Impact of popula-tion density on Covid-19 infected and mortality rate in India. Model Earth Syst Environ 2021;7:623−629. [CrossRef]
32. [31] Contini D, Costabile F. Does air pollution influence COVID-19 outbreaks?. 2020;11:377. [CrossRef]
33. [32] Visual Promethee Academic. Visual PROMETHEE 1.4 Academic Edition.: http://www.promethee-gaia. net/software.html Last Accessed Date: 10.04.2023
34. [33] TC Ministry of Health. The weekly status report of the Ministry of Health. Available at: https://covid19.saglik.gov.tr/Eklenti/39229/0/covid-19-haftalik- durum-raporu---43pdf.pdf?_tag1=70F-7CD89B8F7191D8FAD3ACF29EF550190C31B61 Accessed on April 8, 2023.