Journals / Journal of Biotechnology and Strategic Health Research / 2021 / Cilt: 5 - Sayı: 3

Ranking OECD Countries By Using COVID-19 And Health Policy Variables With Fuzzy AHP And Multimoora Methods

OECD Ülkelerinin COVID-19 ve Sağlık Politikaları Değişkenlerine göre Bulanık AHP ve MULTIMOORA Yöntemi İle Değerlendirilmesi

Pages
185–193
Publication Date
2021-12-31
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

According to the results of performance rankings by MULTIMOORA, New Zealand was located in the first and Belgium in the last place while Turkey has been the eighteenth.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Aim: The aim of this study is to compare performance rankings of OECD countries with the MULTIMOORA method by using the health policy responses and various variables related to COVID-19.
📊
Key Findings & Data:Material and Method: Study includes cross-sectional data of 37 OECD countries.
💡
Conclusion & Impact:According to the results of performance rankings by MULTIMOORA, New Zealand was located in the first and Belgium in the last place while Turkey has been the eighteenth.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Analitik Hiyerarşi Süreci · COVID-19 · MULTIMOORA

Abstract

Aim: The aim of this study is to compare performance rankings of OECD countries with the MULTIMOORA method by using the health policy responses and various variables related to COVID-19. Material and Method: Study includes cross-sectional data of 37 OECD countries. Data regarding eleven variables about the current population health status in these countries are collected from open reliable sources. CO- VID-19 health policy responses of the countries recorded in the OECD database were scored and weighted scores computed by using Fuzzy AHP method. The performance rankings of OECD countries were determined by the MULTIMOORA method with use of all variables. Results: Among the policy responses highest ranking score was computed for “mobilizing and protecting health workers” and the lowest score for “increasing access to mental health services” (0,172 and 0,042 points respectively). According to the results of performance rankings by MULTIMOORA, New Zealand was located in the first and Belgium in the last place while Turkey has been the eighteenth. Conclusion: Study findings can be concluded as the COVID-19 performance of the Eastern countries is better than the Western developed countries with the exceptions of Iceland and Czechia. However, it is difficult to draw justifying conclusions about the success or failure of a country in managing the pandemic due to the complex interactions between various variables and the cross-sectional nature of the study data.

Özet

Amaç: Çalışmanın amacı, OECD ülkelerinin COVID-19 için izlediği sağlık politikaları ve diğer ilişkili değişkenlere göre performansının MULTIMOORA yöntemi ile analizidir. Materyal ve Metod: Çalışmada 37 OECD ülkesinin verileri kesitsel olarak incelenmiştir. Ülkelerinin COVID-19 dönemi performansını değerlendirilmesi için 11 değişken belirlenmiştir. Bu dönemde, ülkelerin belirlediği dokuz sağlık politikasının Bulanık AHP yöntemi ile ağırlıkları hesaplanarak ülkeler için sağlık politikası skoru belirlenmiştir. Ardından, MULTIMOORA ile ülkelerin COVID-19 ilişkili performansları analiz edilmiştir. Bulgular: Ülkelerin dokuz COVID-19 ilişkili sağlık politikaları sıralandığında, 0,172 ile en yüksek puan “Sağlık çalışanlarını harekete geçirmek ve korumak”, 0,042 en düşük puan ile “Akıl sağlığı hizmetlerine erişimi arttırmak” bulunuştur. MULTIMOORA ile yapılan COVID-19 pandemi yönetimi analizine göre ise, Yeni Zelanda en yüksek, Belçika en düşük, Türkiye ise on sekizinci sırada performansa sahip ülkeler olarak bulunmuştur. Sonuç: Çalışma bulgularına göre, İzlanda ve Çek Cumhuriyeti hariç, doğu bölgesinde yer alan ülkelerin performansının batı bölgesinde yer alan gelişmiş ülkelerden daha iyi olduğu anlaşılmaktadır. Ancak araştırmanın kesitsel yönteminin yanı sıra, değişkenlerin kendi arasındaki etkileşimleri nedeniyle, ülkelerin pandemiyi yönetmedeki başarı veya başarı- sızlığı hakkında iddialı sonuçlar çıkarmak doğru değildir.

🔖

Cite This Article

HAYRAN, O., YIGIT, P. (2021). Ranking OECD Countries By Using COVID-19 And Health Policy Variables With Fuzzy AHP And Multimoora Methods. Journal of Biotechnology and Strategic Health Research, Cilt: 5 - Sayı: 3, 185–193. https://ajindex.com/articles/774401

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (12)

  1. Li Q, Guan X, Wu P, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med. 2020
  2. 382(13):1199-1207. doi:10.1056/NEJMoa2001316 2. WHO. “The world is not prepared for a pandemic,.” WHO. Published 2020. https://www.who.int/news/item/01-10-2020-the-best-time-to-prevent-the-next-pandemic-is-now-countries-join-voices-for-better-emergency-preparedness 3. Yamey G, Schäferhoff M, Aars OK, et al. Financing of international collective action for epidemic and pandemic preparedness. Lancet Glob Heal. 2017
  3. 5(8):e742-e744. doi:10.1016/S2214-109X(17)30203-6 4. Organisation for Economic Co-operation and Development. Strengthening health systems during a pandemic: The role of development finance. Tackling Coronavirus (COVID-19). 2020
  4. (June):1-24. 5. Kilbourne ED. Influenza pandemics of the 20th century. Emerg Infect Dis. 2006
  5. 12(1):9-14. doi:10.3201/eid1201.051254 6. Farmer P. Social Inequalities and Emerging Infectious Diseases. Emerg Infect Dis. 1996
  6. 2(4):259-269. doi:10.3201/eid0204.960402 7. Bavel JJV, Baicker K, Boggio PS, et al. Using social and behavioural science to support COVID-19 pandemic response. Nat Hum Behav. 2020
  7. 4(5):460-471. doi:10.1038/s41562-020-0884-z 8. Bandayrel K, Lapinsky S, Christian M. Information technology systems for critical care triage and medical response during an influenza pandemic: a review of current systems. Disaster Med Public Health Prep. 2013
  8. 7(3):287-291. doi:10.1001/dmp.2011.45 9. Chew C, Eysenbach G. Pandemics in the age of Twitter: Content analysis of tweets during the 2009 H1N1 outbreak. PLoS One. 2010
  9. 5(11):1-13. doi:10.1371/journal.pone.0014118 10. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020
  10. 395(10223):497-506. 11. Timeline of WHO’s response to COVID-19. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/interactive-timeline 12. Walker PGT, Whittaker C, Watson OJ, et al. The impact of COVID-19 and strategies for mitigation and suppression in low- And middle-income countries. Science (80- ). 2020
  11. 369(6502):413-422. doi:10.1126/science.abc0035 13. Kayı İ, Sakarya S. Policy Analysis of Suppression and Mitigation Strategies in the Management of an Outbreak Through the Example of COVID-19 Pandemic. Infect Dis Clin Microbiol. 2020
  12. 2(1):30-41. doi:10.36519/idcm.2020.0009 14. Hsiang S, Allen D, Annan-Phan S, et al. The effect of large-scale anti-contagion policies on the COVID-19 pandemi