Can the Google search engine be used to monitor and predict the spread of the Covid-19 pandemic in Turkey?

Year 2021, Volume: 14 Issue: 3, 520 - 531, 15.12.2021

Mürsel Tirgil Ercan Çulha Şenol Demirci

https://doi.org/10.26559/mersinsbd.842118

Abstract

Aim: The Covid-19 is the first pandemic encountered in the digital age, and it is thought that digital health solutions may play an important role in monitoring, managing this outbreak and conducting predictions about the pandemic. At this point, it is stated that online search engines such as Google, which produce real-time internet data, provide information about the behavior of individuals and is among the digital health solutions, can be used to predict and monitor the spread of the pandemic. Accordingly, this study was aimed to examine the availability of the Google search engine in predicting and monitoring the spread of the Covid-19 pandemic in Turkey. Method: Time lag relationship between the scores obtained from Google Trends for searches on Covid-19 symptoms via Google and the number of Covid-19 cases reported daily in Turkey was examined by Cross-Correlation analysis. Results: As a result of the study, it was determined that the highest interest in the keywords "cough", "high fever", "shortness of breath", "sore throat" and "nasal congestion", which are among the symptoms of Covid-19, occurred about 2-3 weeks before the daily number of Covid-19 cases peaked. It was determined that the correlation coefficients showed a positive relationship and the results were statistically significant. Conclusion: The keywords "cough", "high fever", "shortness of breath", "sore throat", and " nasal congestion", which have a higher correlation score compared to other keywords, can be used to predict and monitor the spread of the Covid-19 pandemic in Turkey.

Google arama motoru Türkiye’de Covid-19 salgınının yayılımının izlenmesinde ve tahmininde kullanılabilir mi?

Abstract

Amaç: Covid-19 salgını dijital çağda karşılaşılan ilk salgındır ve dijital sağlık çözümlerinin bu salgının izlenmesinde, yönetiminde ve salgına ilişkin tahminler yürütülmesinde önemli rol oynayabileceği düşünülmektedir. Bu noktada, gerçek zamanlı internet verileri üreten, bireylerin davranışlarına ilişkin bilgi sağlayan ve dijital sağlık çözümleri arasında yer alan Google gibi çevrimiçi arama motorlarının; salgının yayılımının tahmin edilmesinde ve izlenmesinde kullanılabileceği belirtilmektedir. Bu doğrultuda bu çalışmada, Google arama motorunun Türkiye’de Covid-19 salgınının yayılımının tahmin edilmesinde ve izlenmesinde kullanılabilirliğinin incelenmesi amaçlanmıştır. Gereç ve Yöntem: Türkiye’de Google üzerinden Covid-19 belirtileri ile ilgili yapılan aramalara ait Google Trends’ten elde edilen skorlar ile günlük bildirilen Covid-19 vaka sayıları arasındaki gecikmeli ilişki Çapraz Korelasyon analizi ile incelenmiştir. Bulgular: Çalışma sonucunda, Covid-19 belirtileri arasında yer alan “öksürük”, “yüksek ateş”, “nefes darlığı”, “boğaz ağrısı” ve “burun akıntısı” anahtar kelimelerine olan en yüksek ilginin, günlük Covid-19 vaka sayısının pik yapmasından yaklaşık 2-3 hafta önce gerçekleştiği, korelasyon katsayılarının iyi derecede ilişki gösterdiği ve sonuçların istatistiki açıdan anlamlı olduğu tespit edilmiştir. Sonuç: Daha yüksek korelasyon skoruna sahip olan “öksürük”, “yüksek ateş”, “nefes darlığı”, “boğaz ağrısı” ve “burun akıntısı” anahtar kelimeleri Türkiye’de Covid-19 salgınının yayılımının tahmin edilmesinde ve izlenmesinde kullanılabilir. 

Keywords

Dijital sürveyans, Gecikmeli ilişki, Google Trends, Çapraz korelasyon

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