Turkiye Klinikleri Journal of Biostatistics

.: ORIGINAL RESEARCH
COVID19Takip: Türkiye'de COVID-19 Salgınının Gerçek Zamanlı İzlenmesi için Web Arayüzü
COVID19Takip: A Real Time Web Interface for Tracking COVID-19 Outbreak in Turkey
Onur KARASOYa, Zeynep Filiz EREN DOĞUb
aMuğla Sıtkı Koçman Üniversitesi Mühendislik Fakültesi, Bilgi İşlem Daire Başkanlığı, Muğla, TÜRKİYE
bMuğla Sıtkı Koçman Üniversitesi Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Muğla, TÜRKİYE
Turkiye Klinikleri J Biostat. 2020;12(1):97-106
doi: 10.5336/biostatic.2020-75406
Article Language: TR
Full Text
ÖZET
 Amaç: Dünya Sağlık Örgütü tarafından pandemi olarak ilan edilen, 10 Nisan 2020 itibarıyla dünyada yaklaşık 100.000 ölen, 1.700.000 doğrulanan, Türkiye'de ise yaklaşık 1.000 ölen, 50.000 doğrulanan vakası bulunan COVID-19 salgınına ilişkin verileri, 'COVID19Takip' adlı arayüz ile anlaşılır şekilde sunmak ve Türkiye'ye özel günlük değişimi ve salgının seyrini modellemektir. Gereç ve Yöntemler: Arayüz, Johns Hopkins Üniversitesi resmî web sitesinde gerçek zamanlı derlenen verileri, bu verilerden oluşan web servisleri ve salgın ile ilgili ulusal haberleri anlık güncellemektedir. Açık kaynaklı R yazılımı kullanılarak, SIR modeli ve Otomatik Regresif Entegre Hareketli Ortalama (ARIMA) modeli ile Türkiye'ye ilişkin modelleme ve tahmin, T.C. Sağlık Bakanlığı tarafından günlük sunulan verilerle yenilenmektedir. Önerilen web aracını geliştirmek için ve Asp.NET MVC C# #, Ajax, Javascript ve R dilleri kullanılmıştır. Bulgular: Dünyada, Amerika Birleşik Devletleri, İspanya, İtalya'nın salgından en çok etkilenen ülkeler olduğu; salgını en iyi kontrol eden ülkelerin başında Japonya, Singapur ve Güney Kore'nin geldiği, Türkiye'nin ilk 4 haftalık süreç itibarıyla toplam vaka sayısı açısından İspanya'ya, ölen sayısı açısından ise Almanya'ya benzediği gözlenmektedir. Epidemik modelimize göre günlük vaka sayısının önümüzdeki günlerde de artarak devam etmesi ve salgının 20 Haziran 2020'den sonra azalması beklenmektedir. Sonuç: Türkiye'deki salgın hakkında bilgi almak isteyen tüm kullanıcılar için tasarlanmış olan COVID19Takip sistemi tanıtılmıştır. Arayüz ile, tüm dünya hakkında gerçek zamanlı bilgilere ulaşmak ve Türkiye'deki salgın durumunu öngörmek mümkündür. Bu arayüzün, günden güne artacak verilerle, salgına ilişkin erken tedbirler almak konusunda sağlık otoritelerine ve topluma faydalı olacağına inanıyoruz.

Anahtar Kelimeler: COVID-19; koronavirüs; pandemik; arayüz; SIR; ARIMA
ABSTRACT
 Objective: Declared as a pandemic by the World Health Organization, as of April 2; around 100.000 people, out of 1.700.000 confirmed cases out of the world have died because of COVID-19. In Turkey aroung 1.000 people have died out of 50.000 confirmed cases. In this study, we aim to introduce an interface, called 'COVID19Takip' to model the daily change and the epidemic trend in Turkey. Material and Methods: The interface updates the official data and web services, acquired from the website of the Johns Hopkins University in real time; along with the national news about this epidemic. SIR and Automatic Regressive Integrated Moving Average models are implemented in the open-source software, R; and the outputs are updated daily with as the Turkish Republic Ministry of Health reports mew cases. The web interface is built by using Asp. Net MVC C#, Ajax ve Javascript and R languages. Results: By 2020 April,10, USA, Spain and Italy are seem to have more cases, whereas the countries that best control the outbreak are Japan, Singapore, and South Korea. In the first four week period, Turkey's total case trend is similar to that observed in Spain and death toll is similar to that observed in Germany. The number of daily cases in Turkey is expected to increase in the upcoming days and drop as of June, 20 2020 based on our epidemic model. Conclusion: COVID19Takip is introduced, which is designed for users with various backgrounds, who want to get information about the outbreak in Turkey. With the interface, it is possible to access real-time information about the whole world and model-based forecasts for Turkey. We believe that this interface, with the data accummulated day by day, will be beneficial to health authorities and the society in taking early precautions regarding the epidemic.

Keywords: COVID-19; coronavirus; pandemic; graphical user interface; SIR; ARIMA
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