Ülkelerin COVID-19 ve İlişkili Faktörlere göre Kümelenmesi ve Değerlendirilmesi: Kümeleme ve MULTIMOORA Analizleri

Öz

COVID-19 pandemi dönemi insanlığın yaşadığı en zor dönemlerden bir tanesidir. Pandeminin yayılımı ve etkisi bütün ülkeler için aynı deredecede olmamıştır. Ülkeler arasındaki bu farklılıkların incelenmesi politika yapıcılar için önem arzetmektedir. Bu çalışmanın amacı, ülkelerin pandemi ve ilişkili sosyoekonomik, hastalık ve sağlık risk faktörlerini kümelememek ve bir çok kriterli karar verme yöntemi olan MULTIMOORA (MOORA plus the full multiplicative form) yöntemi ile sıralanmaktır. Çalışmanın verileri, halka açık kaynaklardan elde edilmiş, 148 ülke için ve 13 değişkenden oluşmaktadır. Kümeleme analizi için K-Means algoritması kullanılmıştır. Optimal küme sayısı Silhoute Index kullanılarak altı olarak belirlenmiştir. Çoğunlukla gelişmiş ülkelerden oluşan küme birinci sırada yer almıştır. Bu kümedeki ülkeler en yüksek COVID-19 aşılama oranı, kişi başına düşen GSMH, sağlık harcamasının GSMH oranı, doğumda beklenen yaşam süresi, ve çevre performans indeksine, en düşük kronik hastalıklardan ölüm oranın sahiptir. Bunun yanında, Norveç, İzlanda ve Danimarka bu kümedeki en iyi performansa sahip ülkeler olarak bulunmuştur. Türkiye ise ikinci en iyi performansa sahip kümede yer almaktadır. COVID-19 değişkenleri (vaka sayısı, ölüm sayısı, aşılama sayısı) kişi başına düşen GSMH, çevresel performans indeksi ve doğumda beklenen yaşam süresi ile ilişkili bulunmuştur. Sonuç olarak, Politika yapıcılar ülke gruplarına yönelik ayrı ayrı COVİD-19 politikaları geliştirebilir ve ülkelerin öncelik sırasına göre pandemi konusunda yardımlar sağlanabilir.

Anahtar Kelimeler

• COVID-19
• kümeleme analizi
• K-means
• MULTIMOORA

Assessing and Clustering Countries Based on COVID-19 and Related Indicators: Clustering and MULTIMOORA Approaches

Öz

The COVID-19 pandemic has been one of humanity's most difficult times. The pandemic spread and impact were not at the same level for all countries. Investigation of the variation of the countries is crucial for policymakers. Therefore, the study proposed to cluster countries according to the number of COVID-19 cases, deaths, vaccinations and related socioeconomic, disease, and health risk factors and rank them by using MULTIMOORA (MOORA plus the full multiplicative form) in an integrated way. The data set consists of 148 countries and 13 indicators. K-Means algorithm was used to cluster countries. Optimal cluster was found as six according to Silhouette Index. The cluster consisted of mostly developed countries ranked as best perform cluster. It had the highest number of COVID-19 vaccinations, GDP per capita, share health expenditure in GDP, life expectancy, elderly population portion, and environmental performance index values, and the least mortality of chronic diseases. Moreover, Norway, Iceland, and Denmark were the best-performing countries in this cluster. In addition to this, Turkey was located in the second-ranked cluster. It was also determined that COVID-19 indicators (cases, deaths, and vaccinations) were related to GDP per capita, environmental index, and life expectancy. As a result, policymakers can develop pandemic policies for country groups separately, and assistance can be provided in this regard according to the priority order of the countries.

Anahtar Kelimeler

• COVID-19
• clustering analysis
• K-means
• MULTIMOORA

Kaynakça

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