Time series model for forecasting the number of COVID-19 cases in Turkey
Yıl: 2021 Cilt: 19 Sayı: 2 Sayfa Aralığı: 140 - 145 Metin Dili: İngilizce DOI: 10.20518/tjph.809201 İndeks Tarihi: 29-07-2022
Time series model for forecasting the number of COVID-19 cases in Turkey
Öz: Objective: Coronavirus disease 2019 (COVID-19) had an unprecedented effect on bothnations and health systems. Time series modeling using Auto-Regressive IntegratedMoving Averages (ARIMA) models have been used to forecast variables extensively instatistics and econometrics. We aimed to predict the total number of cases for COVID19using ARIMA models of time-series analysis in Turkey. Methods: We used timeseries analysis to build an ARIMA model of the total number of cases from March 11,2020 to August 24, 2020 and used the model to predict cases in the following 14 days,from August 25, 2020 to September 7, 2020. Hyndman and Khandakar algorithm wasused to select components of ARIMA models. Percentage error was used to evaluateforecasting accuracy. Results: During the model building period, 259692 cases werediagnosed and during 14 days of validation period additional 21817 new cases wereadded. ARIMA model with (p,d,q) components of (4, 2, 0) was used for forecasting.The mean percentage error of forecast was 0.20% and forecast accuracy was highestin the two weeks of forecasting. Conclusion: ARIMA models can be used to forecastthe total number of cases of COVID-19 patients for the upcoming two weeks in Turkey.
Anahtar Kelime: Türkiye’de görülen COVID-19 olgu sayılarının tahmininde zaman serisi modelinin kullanılması
Öz: Amaç: Koronavirüs hastalığı 2019’un (Covid-19) hem ülkeler hem de sağlık sistemleri üzerinde beklenmedik bir etkisi olmuştur. Otoregresif Entegre Hareketli Ortalama (Auto-Regressive Integrated Moving Averages) (ARIMA) modellerini kullanarak yapılan zaman serisi modellemesi, istatistik ve ekonometride değişkenleri kapsamlı şekilde tahminde kullanılmaktadır. Zaman serisi analizinin ARIMA modellerini kullanarak, Türkiyede Covid-19 için toplam olgu sayısını tahmin etmeyi amaçladık. Yöntem: 11 Mart 2020’den 24 Ağustos 2020’ye kadar olan toplam olgu sayısının bir ARIMA modelini oluşturmak için zaman serisi analizini kullandık ve 25 Ağustos 2020’den 7 Eylül 2020’ye kadar takip eden 14 gündeki vakaları tahmin etmek için bu modelden yararlandık. ARIMA modellerinin bileşenlerinin seçiminde Hyndman ve Khandakar algoritması kullanıldık. Öngörme doğruluğunu değerlendirmek için yüzde hata kullanıldı. Bulgular: Model oluşturma döneminde 259.692 olgu teşhis edildi ve 14 günlük doğrulama süresi boyunca ek 21.817 olgu vaka eklendi. Öngörü için (4, 2, 0) bileşenli (p, d, q) bileşenli ARIMA modeli kullanıldı. Ortalama tahmin hatası % 0.20 olarak bulundu ve tahmin doğruluğu tahminin iki haftalık döneminde en yüksekti. Sonuç: ARIMA modelleri, Türkiye’de önümüzdeki iki hafta boyunca Covid-19 hastalarının toplam olgu sayısını tahmin etmek için kullanılabilir.
Anahtar Kelime: Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
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| APA | Akay S, Akay H (2021). Time series model for forecasting the number of COVID-19 cases in Turkey. , 140 - 145. 10.20518/tjph.809201 |
| Chicago | Akay Serhat,Akay Huriye Time series model for forecasting the number of COVID-19 cases in Turkey. (2021): 140 - 145. 10.20518/tjph.809201 |
| MLA | Akay Serhat,Akay Huriye Time series model for forecasting the number of COVID-19 cases in Turkey. , 2021, ss.140 - 145. 10.20518/tjph.809201 |
| AMA | Akay S,Akay H Time series model for forecasting the number of COVID-19 cases in Turkey. . 2021; 140 - 145. 10.20518/tjph.809201 |
| Vancouver | Akay S,Akay H Time series model for forecasting the number of COVID-19 cases in Turkey. . 2021; 140 - 145. 10.20518/tjph.809201 |
| IEEE | Akay S,Akay H "Time series model for forecasting the number of COVID-19 cases in Turkey." , ss.140 - 145, 2021. 10.20518/tjph.809201 |
| ISNAD | Akay, Serhat - Akay, Huriye. "Time series model for forecasting the number of COVID-19 cases in Turkey". (2021), 140-145. https://doi.org/10.20518/tjph.809201 |
| APA | Akay S, Akay H (2021). Time series model for forecasting the number of COVID-19 cases in Turkey. Türkiye Halk Sağlığı Dergisi, 19(2), 140 - 145. 10.20518/tjph.809201 |
| Chicago | Akay Serhat,Akay Huriye Time series model for forecasting the number of COVID-19 cases in Turkey. Türkiye Halk Sağlığı Dergisi 19, no.2 (2021): 140 - 145. 10.20518/tjph.809201 |
| MLA | Akay Serhat,Akay Huriye Time series model for forecasting the number of COVID-19 cases in Turkey. Türkiye Halk Sağlığı Dergisi, vol.19, no.2, 2021, ss.140 - 145. 10.20518/tjph.809201 |
| AMA | Akay S,Akay H Time series model for forecasting the number of COVID-19 cases in Turkey. Türkiye Halk Sağlığı Dergisi. 2021; 19(2): 140 - 145. 10.20518/tjph.809201 |
| Vancouver | Akay S,Akay H Time series model for forecasting the number of COVID-19 cases in Turkey. Türkiye Halk Sağlığı Dergisi. 2021; 19(2): 140 - 145. 10.20518/tjph.809201 |
| IEEE | Akay S,Akay H "Time series model for forecasting the number of COVID-19 cases in Turkey." Türkiye Halk Sağlığı Dergisi, 19, ss.140 - 145, 2021. 10.20518/tjph.809201 |
| ISNAD | Akay, Serhat - Akay, Huriye. "Time series model for forecasting the number of COVID-19 cases in Turkey". Türkiye Halk Sağlığı Dergisi 19/2 (2021), 140-145. https://doi.org/10.20518/tjph.809201 |
