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JOURNAL OF INTELLIGENT SYSTEMS WITH APPLICATIONS
J Intel Syst App
E-ISSN: 2667-6893

Forecasting Model to Predict the Spreading of the COVID-19 Outbreak in Turkey

Türkiye'de COVID-19 Salgınının Yayılımını Öngörmek İçin Tahmin Modeli

How to cite: Bereketoğlu C, Özcan N, Kıran TR, Yola ML. Forecasting model to predict the spreading of the covid-19 outbreak in turkey. Journal of Intelligent Systems with Applications 2021; 4(2): 95-102.

Full Text: PDF, in English.

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Title: Forecasting Model to Predict the Spreading of the COVID-19 Outbreak in Turkey

Abstract: This study aimed to forecast the future of the COVID-19 outbreak parameters such as spreading, case fatality, and case recovery values based on the publicly available epidemiological data for Turkey. We first performed different forecasting methods including Facebook’s Prophet, ARIMA and Decision Tree. Based on the metrics of MAPE and MAE, Facebook’s Prophet has the most effective forecasting model. Then, using Facebook’s Prophet, we generated a forecast model for the evolution of the outbreak in Turkey fifteen-days-ahead. Based on the reported confirmed cases, the simulations suggest that the total number of infected people could reach 4328083 (with lower and upper bounds of 3854261 and 4888611, respectively) by April 23, 2021. Simulation forecast shows that death toll could reach 35656 with lower and upper bounds of 34806 and 36246, respectively. Besides, our findings suggest that although more than 86.38% growth in recovered cases might be possible, the future active cases will also significantly increase compared to the current active cases. This time series analysis indicates an increase trend of the COVID-19 outbreak in Turkey in the near future. Altogether, the present study highlights the importance of an efficient data-driven forecast model analysis for the simulation of the pandemic transmission and hence for further implementation of essential interventions for COVID-19 outbreak.

Keywords: COVID-19; forecasting, Facebook’s Prophet, Turkish population, intervention


Başlık: Türkiye'de COVID-19 Salgınının Yayılımını Öngörmek İçin Tahmin Modeli

Özet: Bu çalışma, Türkiye için kamuya açık epidemiyolojik verilere dayanarak COVID-19 salgını yayılımı, ölüm oranı ve iyileşme verileri gibi parametlerinin geleceğini tahmin etmeyi amaçlamıştır. İlk olarak Facebook’s Prophet, ARIMA ve Decision Tree gibi farklı tahmin yöntemlerini uyguladık. MAPE ve MAE ölçümlerine dayalı olarak, Facebook’s Prophet en etkili tahmin modeli çıkmıştır. Daha sonra, Facebook’s Prophet kullanarak, salgının Türkiye'deki gelişimi için on beş gün öncesinden bir tahmin modeli oluşturduk. Bildirilen doğrulanmış vakalara dayanarak, simülasyonlar, enfekte olmuş kişilerin toplam sayısının 23 Nisan 2021'e kadar 4328083'e (sırasıyla 3854261 ve 4888611 alt ve üst sınırlar ile) ulaşabileceğini göstermektedir. Simülasyon tahmini, ölü sayısının sırasıyla 34806 ve 36246 alt ve üst sınırlar olmak üzere 35656'ya ulaşabileceğini göstermektedir. Ayrıca bulgularımız, iyileşen vaka oranın %86.38'i aşabileceğini, ancak gelecekteki aktif vakaların mevcut aktif vakalara göre önemli ölçüde artabileceğini de göstermektedir. Bu zaman serisi analizi, yakın gelecekte Türkiye'deki COVID-19 salgınının artış eğiliminde olduğunu göstermektedir. Genel olarak bu çalışma, pandemik yayılmanın simülasyonu ve dolayısıyla COVID-19 salgını için temel müdahalelerin daha ileri düzeyde uygulanması için verimli bir veriye dayalı tahmin modeli analizinin önemini vurgulamaktadır.

Anahtar kelimeler: COVID-19; tahmin; Facebook's prophet; Türk popülasyonu; müdahale


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