Turkiye Klinikleri Journal of Medical Sciences

.: ORIGINAL RESEARCH
A Study on Determination of the Growth Models Using COVID-19 Cases Between March 17 and July 12 2020 in Turkey: Cross-sectional Study
Türkiye'de 17 Mart ile 12 Temmuz 2020 Arasında COVID-19 Vakaları Kullanılarak Büyüme Modellerinin Belirlenmesi Üzerine Bir Çalışma: Kesitsel Çalışma
Levent ÖZBEKa
aDepartment of Statistics, Ankara University Faculty of Sciences, Ankara, TURKEY
Turkiye Klinikleri J Med Sci. 2021;41(3):320-6
doi: 10.5336/medsci.2020-78094
Article Language: EN
Full Text
ABSTRACT
 Objective: We use the most frequently used growth functions in the literature for estimating Turkey's cumulative number of confirmed coronavirus disease-2019 (COVID-19) cases. We analyze Brody, Bertalanffy, Logistic, Generalized Logistic, Gompertz, Richards, Negative Exponential, Stevens, and Tanaka models for determining the appropriate model. Material and Methods: The number of cases of COVID-19 in Turkey between March 17, 2020 and July 12, 2020 were included in the study. The data used in the study were obtained from Johns Hopkins University. We used the most frequently used Non-linear growth models in the literature for estimating Turkey's cumulative number of confirmed COVID-19 cases. Matlab software was used to estimate the parameters in the models studied. non-linear least squares regression function is used in Matlab software. Results: According to the estimation results, the best fitting model is the Richards model in terms of both the mean squared error and R2 (coefficient of determination). Conclusion: We recommend to use the Richards model in modeling the cumulative COVID-19 cases. For estimating the future cases, it will be appropriate to use the Richards model. In addition, estimates of the number of daily cases obtained from the Richards model are not compatible with the actual number of daily cases. This may occur because estimations on these growth models can sometimes lead to erroneous results.

Keywords: Turkey; COVID-19; pandemic; growth function
ÖZET
 Amaç: Türkiye'nin teyit edilmiş koronavirüs hastalığı-2019 [coronavirus disease-2019 (COVID-19)] vakalarının kümülatif sayısını tahmin etmek amacıyla literatürde en sık kullanılan büyüme fonksiyonları göz önünde bulundurulmuştur. Bu çalışmada, literatürde mevcut olan toplam 9 model araştırılmıştır. Bu modeler; Brody, Bertalanffy, Lojistik, Genelleştirilmiş Lojistik, Gompertz, Richards, Negatif Üstel, Stevens ve Tanaka'dır. Bu modellerden hangisinin daha iyi olduğu tespit edilmeye çalışılmıştır. Gereç ve Yöntemler: Türkiye'de 17 Mart 2020 ve 12 Temmuz 2020 tarihleri arasında ortaya çıkan COVID-19 vaka sayıları çalışmaya dâhil edilmiştir. Çalışmada kullanılan veriler Johns Hopkins Üniversitesinden alınmıştır. Literatürde çok sık kullanılan lineer olmayan büyüme modellerinden bazıları ele alınmış ve hangi modelin Türkiye COVID-19 verilerine daha iyi uyum sağladığı araştırılmıştır. Ele alınan modellerdeki parametreleri tahmin etmek için Matlab yazılımı kullanılmıştır. Matlab yazılımında doğrusal olmayan en küçük kareler regresyonu fonksiyonu kullanılmıştır. Bulgular: Çalışmadaki tahmin sonucunda, toplam vaka sayılarını modellemede en iyi analizin Richards modeli tarafından, hem ortalama hata karesi hem de R2 (belirleme katsayısı) açısından yapıldığı görülmüştür. Sonuç: Richard modelinin kümülatif COVID-19 vaka sayısını modellemede kullanılması tavsiye edilmektedir. Gelecek sürecin tahmininde, Richard modeli kullanılarak tahminlerin yapılmasının uygun olacağı düşünülmektedir. Bununla birlikte, Richard modelinden elde edilen günlük vaka sayısı tahminleri gerçek günlük vaka sayısıyla uyumlu değildir. Bu büyüme modelleri üzerinde tahmin yapmanın bazen hatalı sonuçlara yol açabileceği düşünülmektedir.

Anahtar Kelimeler: Türkiye; COVID-19; pandemic; büyüme fonksiyonu
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