LOJİSTİK BÜYÜME VE ÜSTEL BÜYÜME MODELLERİ İLE TÜRKİYE’DE COVID-19 MODELLEMESİ

Abstract

Lojistik Büyüme ve Üstel Büyüme modelleri çeşitli durumlarda kullanılabilen matematiksel birer fonksiyondur. Üstel Büyüme modelleri, durdurulamaz bir enfeksiyon büyümesini ifade ederek salgınların başlangıç dönemleri için bu büyümeye yeterli bir yaklaşım sağlayabilen bir yöntem iken Lojistik Büyüme modelleri, başlangıç döneminde büyümenin arttığı daha sonra maksimuma yaklaştıkça azalan büyümenin modellenmesinde karşımıza çıkan bir yöntemdir. Enfeksiyon salgınlarının büyümesinde, bu maksimum sınır dünyadaki toplam insan sayısı olacaktır, çünkü herkes hasta olduğunda büyüme mutlaka azalacaktır. Bu sebeple, son zamanlarda büyük bir hızla tüm dünyayı etkileyen COVID-19 salgın verilerinin modellenmesinde de bu yöntemler sıklıkla kullanılmaktadır. Bu çalışmada amaç, Türkiye’de 11 Mart 2020 – 19 Mayıs 2020 tarihleri arasında ortaya çıkan ve onaylanmış COVID-19 vakalarının toplam sayılarına ilişkin büyümeyi tanımlayan bir matematiksel model oluşturmaktır. Bu bağlamda, belirtilen tarihlerde Türkiye’de ortaya çıkan COVID-19 toplam vaka sayılarını kullanarak Lojistik Büyüme, Lojistik ve Üstel Büyüme modelleri oluşturulmuştur. Ayrıca, oluşturulan bu modeller ile vaka sayılarının seyrini öngörme yeteneğini de gözlemlemek hedeflenmiştir. Modelleme çalışmasına ilişkin çözümlemeler Python programlama dilinde yer alan bazı fonksiyonlar ile gerçekleştirilerek çıkan sonuçlar yorumlanmıştır.

Keywords

• Lojistik Büyüme Modeli,Üstel Büyüme Modeli,Lojistik Model,COVID-19,Türkiye

MODELLING COVID-19 IN TURKEY WITH LOGISTIC GROWTH MODEL AND EXPONENTIAL GROWTH MODEL

Abstract

Exponential Growth Model is a method that can provide an adequate approach to this growth for the beginning periods of outbreaks by expressing an unstoppable infection growth, while Logistics Growth Model is a method that appears in the modeling of the growth that decreases as the growth increases in the initial period and then approaches the maximum. In the growth of infectious outbreaks, this maximum limit will be the total number of people in the world, because growth will certainly decrease when everyone is ill. For this reason, it is also frequently used in the modeling of COVID-19 data, which has recently affected the whole world with great speed. The purpose of this study is to create a statistical model that describes the growth in total number of COVID-19 confirmed cases which occurred the dates between March 11 and May 19, 2020 in Turkey. In this context, Logistic Growth and Exponential Growth models were created to analyze the total number of COVID-19 confirmed cases between the dates mentioned above. In addition to these models, another model called as Logistic Model, which is similar to the Logistics Growth Model and is used frequently in modeling population growth, is also used. With these models, it is also aimed to observe the ability to predict the course of the number of cases. Analyzes related to the modeling study were carried out using some functions in the Python programming language and the results were interpreted.

Keywords

• Logistic Growth Model,Exponential Growth Model,Logistic Model,COVID-19 Turkey

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