Turkiye Klinikleri Journal of Biostatistics

.: ORIGINAL RESEARCH
Türkiye'deki COVID-19 Hasta Sayılarının Üstel Düzgünleştirme Modeli Kullanılarak Tahmin Edilmesi
Estimation of COVID-19 Infections in Turkey by Using Exponential Smoothing Model
İhsan Erdem KAYRALa, Sencer BUZRULb
aKonya Gıda ve Tarım Üniversitesi Sosyal ve Beşeri Bilimler Fakültesi, Ekonomi Bölümü, Konya, TÜRKİYE
bKonya Gıda ve Tarım Üniversitesi Mühendislik ve Mimarlık Fakültesi, Gıda Mühendisliği Bölümü, Konya, TÜRKİYE
Turkiye Klinikleri J Biostat. 2021;13(1):112-9
doi: 10.5336/biostatic.2020-79501
Article Language: TR
Full Text
ÖZET
 Amaç: Bu çalışmanın amacı, 11.3.2020 ve 9.9.2020 tarihleri arasında Türkiye'deki koronavirüs hastalığı-2019 [coronavirus disease (COVID-19)] hasta sayılarını ve üstel düzgünleştirme modelini (exponential smoothing model) kullanılarak 2020 yılı sonuna kadar hasta sayılarının tahmin edilmesidir. Gereç ve Yöntemler: Türkiye Cumhuriyeti Sağlık Bakanlığının web sitesinden günlük olarak yayımladığı ve güncellediği COVID-19 hasta sayıları kullanılarak, üstel düzgünleştirme modelinin farklı versiyonları uygulanarak karşılaştırılmış, bu versiyonlardan en iyi uyum gösteren 2 adet model (toplamsal yöntem içeren model: Model 1 ve çarpımsal yöntem içeren model: Model 2) belirlendikten sonra bu modeller kullanılarak yakın gelecek tahminleri gerçekleştirilmiştir. Bulgular: Kullanılması önerilen ilk model (Model 1) için Türkiye'de 31 Ekim 2020 tarihi itibarıyla 374.842, 30 Kasım 2020 tarihi itibarıyla 427.672, 31 Aralık 2020 tarihi itibarıyla ise 482.263 hasta sayısına ulaşılacağı tahmin edilmiştir. İkinci model (Model 2) için ise aynı tarihler için sırasıyla 391.992, 472.782 ve 573.811 vaka sayılarına ulaşılacağı hesaplanmıştır. Kışın etkisiyle COVID-19 hasta sayılarının daha da artacağı göz önüne alındığında Model 2'nin daha gerçekçi sonuçlar ortaya koyduğu değerlendirilmiştir. Sonuç: Önümüzdeki süreçte, bu çalışmada önerilen modellerin uluslararası ölçekteki çalışmalarda hasta sayılarının tahmin edilmesinde de kullanılabileceği düşünülmektedir. Aynı zamanda, söz konusu modellerin sadece COVID-19 hasta sayılarını değil bu hastalığa bağlı ölüm sayılarının ve iyileşen hasta sayılarına ilişkin tahminlerin gerçekleştirilmesinde de kullanılabileceği değerlendirilmiştir.

Anahtar Kelimeler: Koronavirüs; modeller, istatistiksel; tahmin
ABSTRACT
 Objective: The aim of this study was to predict the number of patients infected with coronavirus disease (COVID-19) by the end of year 2020 by using the number of infections in Turkey between the dates 11.3.2020-9.9.2020 and exponential smoothing model. Material and Methods: Different versions of the exponential smoothing model were applied and compared by using the data published and upgraded on the web by the Turkish Republic Ministry of Health, and near future predictions were performed after the determination of two models (containing additive method model: Model 1 and containing multiplicative method model: Model 2) producing the best estimates. Results: The first proposed model (Model 1) estimated that there would be 374,842, 427,672 and 482,263 infected patients in Turkey by the date 31 October 2020, 30 November 2020, and 31 December 2020, respectively. For the same dates, it was calculated that there would be 391,992, 472,782, and 573,811 infected patients, respectively for the second model (Model 2). The model 2 was evaluated to produce more realistic results considering that the number of patients infected with COVID-19 will increase even more with the effect of winter. Conclusion: It was thought that the models proposed in this study could also be used to predict the number of infected patients in international studies in the upcoming period. At the same time, it was evaluated that these models not only for infections but could also be used to estimate the number of deaths and recoveries due to coronavirus disease 2019.

Keywords: Coronavirus; models, statistical; forecasting
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