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

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.

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

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.

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Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi-Cover
  • ISSN: 1012-2354
  • Yayın Aralığı: Yılda 3 Sayı
  • Başlangıç: 1985
  • Yayıncı: Erciyes Üniversitesi