Brown'ın doğrusal üstel düzleştirme yöntemiyle COVİD-19 vaka sayılarının tahmin edilmesi: 15, 30 ve 60 günlük tahminlerle büyüme eğilimlerinin karşılaştırılması

Abstract

Amaç: Bu çalışmanın amacı, Türkiye, Almanya, Brezilya, Birleşik Arap Emirlikleri (BAE) ve Birleşik Krallık'ın günlük verilerini kullanarak ideal tahmin yöntemleri ile 15, 30 ve 60 günlük COVİD-19 vaka sayılarını tahmin etmektir. Gereç ve Yöntemler: Verilere Our World in Data COVİD-19 veri setinden ulaşılmıştır. 19 Şubat 2022 tarihine kadar 15, 30 ve 60 günlük dönemler için kümülatif vaka sayıları tahmin edilmiştir. Tahmin için en yaygın kullanılan yöntemler açıklayıcı teknikler ve zaman serisi algoritmalarıdır. Beş ülke için üstel düzleştirme yöntemi (Brown'ın doğrusal trendi) kullanılmıştır. Bulgular: Analizler, beş ülkenin benzer bir salgın eğrisi izlediğini gösterdi. Türkiye, Brezilya, Almanya, Birleşik Krallık ve BAE için 60 günlük tahminlerde 19 Şubat'a kadar sırasıyla 10322701, 22434809, 9552781, 16937127 ve 767819 toplam vakanın olacağı tahmin edildi. Türkiye, Brezilya, Almanya, İngiltere ve BAE için 30 günlük tahminlerde sırasıyla 12809393, 28752324, 12655999, 18857395 ve 905537, 15 günlük tahminlerde ise sırasıyla 13635838, 29678270, 14241248, 20006207 ve 885958 toplam vaka sayısına ulaşılacağı tahmin edilmiştir. Sonuç: Uygun yöntemler ile yapılan kısa süreli tahminler, pandemiyi kontrol altına almak gerekli müdahaleleri planlamaya, ayrılan sağlık personeli ve yoğun bakım üniteleri gibi sağlık kaynaklarının yeterli olup olmadığını görmeye yardımcı olacaktır.

Keywords

• COVİD-19
• Pandemi
• Tahmin yöntemleri
• Üstel düzleştirme yöntemeleri
• Brown

Forecasting for the number of the COVID-19 cases with Brown's linear exponential smoothing method: Comparison of the growth trends with 15 days, 30 and 60 days forecasts

Abstract

Aim: The aim of this study was to estimate the number of the COVID-19 cases for the 15, 30 and 60-days with the ideal forecasting analysis methods by using the daily data of the Turkey, Germany, Brazil, United Arab Emirates and United Kingdom. Material and Methods: The data were reached from the Our World in Data COVID-19 dataset. The forecasts for the cumulative cases for 15, 30, and 60 days periods to 19 February 2022 were made. The most commonly used methods for forecasting are explanatory techniques and time series algorithms. The exponential smoothing method (Brown’s linear trend) was used for the five countries. Results: The analyses showed that five countries have followed a similar epidemic curve. For 60-day forecasts, it was estimated respectively that 10322701, 22434809, 9552781, 16937127, and 767819 total cases would be in Turkey, Brazil, Germany, the UK, and The UAE until February 19. For 30-day forecasts, it was estimated respectively that 12809393, 28752324, 12655999, 18857395, and 905537 total cases would be in Turkey, Brazil, Germany, the UK, and The UAE until February 19. For 15-day forecasts, it was estimated respectively that 13635838, 29678270, 14241248, 20006207, and 885958 total cases would be in Turkey, Brazil, Germany, the UK, and The UAE until February 19. Conclusion: The short-time forecasting methods will help to plan the necessary interventions to control the pandemic, and to see whether health resources such as allocated health personnel and intensive care units are sufficient.

Keywords

• COVID-19
• Pandemic
• Forecasting methods
• Exponential smoothing method
• Brown’s linear trend

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