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Which OECD Countries Are Advantageous in Fight Against COVID-19?

Yıl 2021, Cilt: 37 Sayı: 1, 137 - 148, 28.04.2021

Öz

COVID-19 outbreak has changed daily lives deeply, has fallen economies into recession, and has put social life and public health under unprecedented pressure. In this study, it is aimed to evaluate OECD countries in combating COVID-19 and to develop strategies for preventing or controlling a similar epidemic in the future. To this end, MCDM methods are used to evaluate the countries according to the criteria which are number of confirmed cases per one million population, number of recovered patients per one million population, number of deaths per one million population, number of doctors per 1000 population, number of nurses per 1000 population, number of hospital beds per 1000 population, and health spending share. SWARA method is employed to determine the criteria weights. Countries are ranked using TOPSIS, COPRAS, and ARAS methods according to the weights obtained by SWARA. Borda Count Data Fusion technique is used for integrated ranking.

Kaynakça

  • [1] World Health Organization (WHO). 2020a. Novel Coronavirus(2019-nCoV): Situation Report, 11.
  • [2] Türkiye Bilimler Akademisi (TÜBA). 2020. COVID-19 Pandemi Değerlendirme Raporu, Ankara.
  • [3] World Health Organization (WHO), 2020b. COVID-19 Strategy Update, 14 April 2020.
  • [4] Albahri, O. S., Al-Obaidi, J. R., Zaidan, A. A., Albahri, A. S., Zaidan, B. B., Salih, M. M., Qays, A., Dawood, K. A., Mohammed, R. T., Abdulkareem, K. H., Aleesa, A. M., Alamoodi, A. H., Chyad, M. A., Zulkifli, C. Z. 2020. Helping doctors hasten COVID-19 treatment: Towards a rescue framework for the transfusion of best convalescent plasma to the most critical patients based on biological requirements via ml and novel MCDM methods. Comput. Meth. Prog. Bio., 196, 105617.
  • [5] Yang, Z., Li, X., Garg, H., Qi, M. 2020. Decision support algorithm for selecting an antivirus mask over COVID-19 pandemic under spherical normal fuzzy environment. Int. J. Environ. Res. Public Health, 17, 3407.
  • [6] Ren, Z., Liao, H., Liu, Y. 2020. Generalized Z-numbers with hesitant fuzzy linguistic information and its application to medicine selection for the patients with mild symptoms of the COVID-19. Comput. Ind. Eng., 145, 106517.
  • [7] Maqbool, A., Khan, N. Z. 2020. Analyzing barriers for implementation of public health and social measures to prevent the transmission of COVID-19 disease using DEMATEL method. Diabetes Metab. Syndr., 14, 887-892.
  • [8] Sangiorgio, V., Parisi, F. 2020. A multicriteria approach for risk assessment of Covid-19 in urban district Lockdown. Saf. Sci., 130,104862.
  • [9] Majumder, P., Biswas, P., Majumder, S. 2020. Application of new TOPSIS approach to identify the most significant risk factor and continuous monitoring of death of COVID-19. Electron. J. Gen. Med., 17(6), em234.
  • [10] Mardani, A., Saraji, M. K., Mishra, A. R., Rani, P. 2020. A novel extended approach under hesitant fuzzy sets to design a framework for assessing the key challenges of digital health interventions adoption during the COVID-19 outbreak. Appl. Soft Comput., 96, 106613.
  • [11] Shah, S. A. A., Longsheng, C., Solangi, Y.A., Ahmad, M., Ali, S. Energy trilemma based prioritization of waste-to-energy technologies: Implications for post-COVID-19 green economic recovery in Pakistan. Journal of Cleaner Production, In Press.
  • [12] Wu, W., Xu, Z. 2020. Hybrid TODIM method with crisp number and probability linguistic term set for urban epidemic situation evaluation. Complexity, 1-11.
  • [13] Sayan, M., Sarigul Yildirim, F., Sanlidag, T., Uzun, B., Uzun Ozsahin, D., Ozsahin, I. 2020. Capacity evaluation of diagnostic tests for COVID-19 using multicriteria decision-making techniques. Computational and Mathematical Methods in Medicine, 1-8.
  • [14] Grida, M., Mohamed, R., Zaied, A. N. H. 2020. Evaluate the impact of COVID-19 prevention policies on supply chain aspects under uncertainty. Transportation Research Interdisciplinary Perspectives, 8,100240.
  • [15] Samanlioglu, F., Kaya, B. E. 2020. Evaluation of the COVID-19 pandemic intervention strategies with hesitant F-AHP. Journal of Healthcare Engineering, 1-11.
  • [16] Chai, J., Xian, S., Lu, S. 2020. Z‐uncertain probabilistic linguistic variables and its application in emergency decision making for treatment of COVID‐19 patients. Int. J. Intell. Syst., 1-41.
  • [17] Keršulienė, V., Zavadskas, E. K., Turskis, Z. 2010. Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243–258.
  • [18] Stanujkic, D., Karabasevic, D., Zavadskas, E. K. 2015. A Framework for the selection of a packaging design based on the SWARA method. Inzinerine Ekonomika-Engineering Economics 26(2), 181–187.
  • [19] Chen, S. J., Hwang, C. L. 1992. Fuzzy Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag, Berlin.
  • [20] Hwang, C. L., Yoon, K. 1981. Multiple Attribute Decision Making. Lecture Notes in Economics and Mathematical Systems. Springer-Verlag, Berlin.
  • [21] Opricovic, S., Tzeng, G. H. 2004. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. Eur. J. Oper. Res., 156, 445-455. [22] Zavadskas, E. K., Kaklauskas, A., Sarka, V. 1994. The new method of multicriteria complex proportional assessment of projects. Technological and Economic Development of Economy, 1(3),131-139.
  • [23] Zavadskas, E. K., Kaklauskas, A. 1996. Systemotechnical evaluation of buildings (Pastatų sistemotechninis įvertinimas). Vilnius: Tech. 280. (in Lithuanian).
  • [24] Zavadskas, E. K., Kaklauskas, A., Turskis, Z., Tamošaitienė, J. 2008. Selection of the Effective Dwelling House Walls by Applying Attributes Values Determined at Intervals. Journal of Civil Engineering and Management, 14(2), 85-93.
  • [25] Kaklauskas, A., Zavadskas, E.K., Naimavicienė, J., Krutinis, M., Plakys, V. Venskus, D.,2010. Model for a complex analysis of intelligent built environment. Autom. Constr., 19, 326-340.
  • [26] Kildienė, S., Kaklauskas, A. Zavadskas E.K. 2011. COPRAS based comparative analysis of the European country management capabilities within the construction sector in the time of crisis. J. Bus. Econ. Manag., 12(2), 417-434.
  • [27] Chatterjee, P., Athawale V. W., Chakraborty, S. 2011. Materials selection using complex proportional assessment and evaluation of mixed data methods. Mater. Des., 32, 851-860.
  • [28] Zavadskas, E. K., Turskis, Z. 2010. A new Additive Ratio Assessment (ARAS) method in multicriteria decision-making. Technol. Econ. Dev. Econ., 16, 159-172.
  • [29] Borda, J. C. 1784. Mémoire sur les élections au scrutin. Histoire de l’Académie royale des sciences, Paris.
  • [30] Lamboray, C. 2007. A comparison between the prudent order and the ranking obtained with Borda’s, Copeland’s, Slater’s and Kemeny’s rules. Math. Soc. Sci., 54, 1-16.
  • [31] Lansdowne, Z. F., Woodward, B. S. 1996. Applying the Borda ranking method. Air Force Journal of Logistics, 20(2), 27-29.
  • [32] Ömürbek, N., Urmak Akçakaya, E. D. 2018. Analysis of the aviation companies on the FORBES 2000 list with the ENTROPY, MAUT, COPRAS and SAW methods. Suleyman Demirel University the Journal of Faculty of Economics and Administrative Sciences, 23(1), 257-278.
  • [33] ISC, 2020. https://maps.isc.gov.ir/covid19/#/world, Retrieved 2020, June 25.
  • [34] OECD. 2019. Health at a Glance 2019: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/4dd50c09-en.

Which OECD Countries Are Advantageous in Fight Against COVID-19?

Yıl 2021, Cilt: 37 Sayı: 1, 137 - 148, 28.04.2021

Öz

COVID-19 salgını günlük hayatı derinden değiştirmiş, ekonomileri durgunluğa sürüklemiş, sosyal hayatı ve halk sağlığını benzeri görülmemiş bir baskı altına almıştır. Bu çalışmada, COVID-19 ile mücadelede OECD ülkelerinin değerlendirilmesi ve gelecekte benzer bir salgının önlenmesi veya kontrol altına alınması için stratejilerin geliştirilmesi amaçlanmaktadır. Bu amaçla, ÇKKV yöntemleri kullanılarak OECD ülkeleri, bir milyon nüfus başına doğrulanmış vaka sayısı, bir milyon nüfus başına iyileşen hasta sayısı, bir milyon nüfus başına ölüm sayısı, bin kişiye düşen hekim sayısı, bin kişiye düşen hemşire sayısı, bin kişiye düşen hastane yatağı sayısı ve sağlık harcamalarının GSYİH içindeki payı kriterlerine göre değerlendirilmektedir. Kriterlerin ağırlıklarını belirlemek için SWARA yöntemi kullanılmaktadır. SWARA ile elde edilen ağırlıklar doğrultusunda ülkeler TOPSIS, COPRAS ve ARAS yöntemleri ile sıralanmaktadır. Bütünleşik sıralama için bir veri birleştirme tekniği olan Borda Sayım yöntemi kullanılmaktadır.

Kaynakça

  • [1] World Health Organization (WHO). 2020a. Novel Coronavirus(2019-nCoV): Situation Report, 11.
  • [2] Türkiye Bilimler Akademisi (TÜBA). 2020. COVID-19 Pandemi Değerlendirme Raporu, Ankara.
  • [3] World Health Organization (WHO), 2020b. COVID-19 Strategy Update, 14 April 2020.
  • [4] Albahri, O. S., Al-Obaidi, J. R., Zaidan, A. A., Albahri, A. S., Zaidan, B. B., Salih, M. M., Qays, A., Dawood, K. A., Mohammed, R. T., Abdulkareem, K. H., Aleesa, A. M., Alamoodi, A. H., Chyad, M. A., Zulkifli, C. Z. 2020. Helping doctors hasten COVID-19 treatment: Towards a rescue framework for the transfusion of best convalescent plasma to the most critical patients based on biological requirements via ml and novel MCDM methods. Comput. Meth. Prog. Bio., 196, 105617.
  • [5] Yang, Z., Li, X., Garg, H., Qi, M. 2020. Decision support algorithm for selecting an antivirus mask over COVID-19 pandemic under spherical normal fuzzy environment. Int. J. Environ. Res. Public Health, 17, 3407.
  • [6] Ren, Z., Liao, H., Liu, Y. 2020. Generalized Z-numbers with hesitant fuzzy linguistic information and its application to medicine selection for the patients with mild symptoms of the COVID-19. Comput. Ind. Eng., 145, 106517.
  • [7] Maqbool, A., Khan, N. Z. 2020. Analyzing barriers for implementation of public health and social measures to prevent the transmission of COVID-19 disease using DEMATEL method. Diabetes Metab. Syndr., 14, 887-892.
  • [8] Sangiorgio, V., Parisi, F. 2020. A multicriteria approach for risk assessment of Covid-19 in urban district Lockdown. Saf. Sci., 130,104862.
  • [9] Majumder, P., Biswas, P., Majumder, S. 2020. Application of new TOPSIS approach to identify the most significant risk factor and continuous monitoring of death of COVID-19. Electron. J. Gen. Med., 17(6), em234.
  • [10] Mardani, A., Saraji, M. K., Mishra, A. R., Rani, P. 2020. A novel extended approach under hesitant fuzzy sets to design a framework for assessing the key challenges of digital health interventions adoption during the COVID-19 outbreak. Appl. Soft Comput., 96, 106613.
  • [11] Shah, S. A. A., Longsheng, C., Solangi, Y.A., Ahmad, M., Ali, S. Energy trilemma based prioritization of waste-to-energy technologies: Implications for post-COVID-19 green economic recovery in Pakistan. Journal of Cleaner Production, In Press.
  • [12] Wu, W., Xu, Z. 2020. Hybrid TODIM method with crisp number and probability linguistic term set for urban epidemic situation evaluation. Complexity, 1-11.
  • [13] Sayan, M., Sarigul Yildirim, F., Sanlidag, T., Uzun, B., Uzun Ozsahin, D., Ozsahin, I. 2020. Capacity evaluation of diagnostic tests for COVID-19 using multicriteria decision-making techniques. Computational and Mathematical Methods in Medicine, 1-8.
  • [14] Grida, M., Mohamed, R., Zaied, A. N. H. 2020. Evaluate the impact of COVID-19 prevention policies on supply chain aspects under uncertainty. Transportation Research Interdisciplinary Perspectives, 8,100240.
  • [15] Samanlioglu, F., Kaya, B. E. 2020. Evaluation of the COVID-19 pandemic intervention strategies with hesitant F-AHP. Journal of Healthcare Engineering, 1-11.
  • [16] Chai, J., Xian, S., Lu, S. 2020. Z‐uncertain probabilistic linguistic variables and its application in emergency decision making for treatment of COVID‐19 patients. Int. J. Intell. Syst., 1-41.
  • [17] Keršulienė, V., Zavadskas, E. K., Turskis, Z. 2010. Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243–258.
  • [18] Stanujkic, D., Karabasevic, D., Zavadskas, E. K. 2015. A Framework for the selection of a packaging design based on the SWARA method. Inzinerine Ekonomika-Engineering Economics 26(2), 181–187.
  • [19] Chen, S. J., Hwang, C. L. 1992. Fuzzy Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag, Berlin.
  • [20] Hwang, C. L., Yoon, K. 1981. Multiple Attribute Decision Making. Lecture Notes in Economics and Mathematical Systems. Springer-Verlag, Berlin.
  • [21] Opricovic, S., Tzeng, G. H. 2004. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. Eur. J. Oper. Res., 156, 445-455. [22] Zavadskas, E. K., Kaklauskas, A., Sarka, V. 1994. The new method of multicriteria complex proportional assessment of projects. Technological and Economic Development of Economy, 1(3),131-139.
  • [23] Zavadskas, E. K., Kaklauskas, A. 1996. Systemotechnical evaluation of buildings (Pastatų sistemotechninis įvertinimas). Vilnius: Tech. 280. (in Lithuanian).
  • [24] Zavadskas, E. K., Kaklauskas, A., Turskis, Z., Tamošaitienė, J. 2008. Selection of the Effective Dwelling House Walls by Applying Attributes Values Determined at Intervals. Journal of Civil Engineering and Management, 14(2), 85-93.
  • [25] Kaklauskas, A., Zavadskas, E.K., Naimavicienė, J., Krutinis, M., Plakys, V. Venskus, D.,2010. Model for a complex analysis of intelligent built environment. Autom. Constr., 19, 326-340.
  • [26] Kildienė, S., Kaklauskas, A. Zavadskas E.K. 2011. COPRAS based comparative analysis of the European country management capabilities within the construction sector in the time of crisis. J. Bus. Econ. Manag., 12(2), 417-434.
  • [27] Chatterjee, P., Athawale V. W., Chakraborty, S. 2011. Materials selection using complex proportional assessment and evaluation of mixed data methods. Mater. Des., 32, 851-860.
  • [28] Zavadskas, E. K., Turskis, Z. 2010. A new Additive Ratio Assessment (ARAS) method in multicriteria decision-making. Technol. Econ. Dev. Econ., 16, 159-172.
  • [29] Borda, J. C. 1784. Mémoire sur les élections au scrutin. Histoire de l’Académie royale des sciences, Paris.
  • [30] Lamboray, C. 2007. A comparison between the prudent order and the ranking obtained with Borda’s, Copeland’s, Slater’s and Kemeny’s rules. Math. Soc. Sci., 54, 1-16.
  • [31] Lansdowne, Z. F., Woodward, B. S. 1996. Applying the Borda ranking method. Air Force Journal of Logistics, 20(2), 27-29.
  • [32] Ömürbek, N., Urmak Akçakaya, E. D. 2018. Analysis of the aviation companies on the FORBES 2000 list with the ENTROPY, MAUT, COPRAS and SAW methods. Suleyman Demirel University the Journal of Faculty of Economics and Administrative Sciences, 23(1), 257-278.
  • [33] ISC, 2020. https://maps.isc.gov.ir/covid19/#/world, Retrieved 2020, June 25.
  • [34] OECD. 2019. Health at a Glance 2019: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/4dd50c09-en.
Toplam 33 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makale
Yazarlar

Aslı Çalış Boyacı

Yayımlanma Tarihi 28 Nisan 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 37 Sayı: 1

Kaynak Göster

APA Çalış Boyacı, A. (2021). Which OECD Countries Are Advantageous in Fight Against COVID-19?. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, 37(1), 137-148.
AMA Çalış Boyacı A. Which OECD Countries Are Advantageous in Fight Against COVID-19?. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi. Nisan 2021;37(1):137-148.
Chicago Çalış Boyacı, Aslı. “Which OECD Countries Are Advantageous in Fight Against COVID-19?”. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 37, sy. 1 (Nisan 2021): 137-48.
EndNote Çalış Boyacı A (01 Nisan 2021) Which OECD Countries Are Advantageous in Fight Against COVID-19?. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 37 1 137–148.
IEEE A. Çalış Boyacı, “Which OECD Countries Are Advantageous in Fight Against COVID-19?”, Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, c. 37, sy. 1, ss. 137–148, 2021.
ISNAD Çalış Boyacı, Aslı. “Which OECD Countries Are Advantageous in Fight Against COVID-19?”. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 37/1 (Nisan 2021), 137-148.
JAMA Çalış Boyacı A. Which OECD Countries Are Advantageous in Fight Against COVID-19?. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi. 2021;37:137–148.
MLA Çalış Boyacı, Aslı. “Which OECD Countries Are Advantageous in Fight Against COVID-19?”. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, c. 37, sy. 1, 2021, ss. 137-48.
Vancouver Çalış Boyacı A. Which OECD Countries Are Advantageous in Fight Against COVID-19?. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi. 2021;37(1):137-48.

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