Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study

By S. M. Ayyoubzadeh, Seyed Mehdi Ayyoubzadeh, H. Zahedi, Mahnaz Ahmadi, Sharareh R. Niakan Kalhori. JMIR Public Health and Surveillance, 2020

330 citations recorded by the source corpus.

Background The recent global outbreak of coronavirus disease (COVID-19) is affecting many countries worldwide. Iran is one of the top 10 most affected countries. Search engines provide useful data from populations, and these data might be useful to analyze epidemics. Utilizing data mining methods on electronic resources’ data might provide a better insight into the COVID-19 outbreak to manage the health crisis in each country and worldwide. Objective This study aimed to predict the incidence of COVID-19 in Iran. Methods Data were obtained from the Google Trends website. Linear regression and long short-term memory (LSTM) models were used to estimate the number of positive COVID-19 cases. All models were evaluated using 10-fold cross-validation, and root mean square error (RMSE) was used as the performance metric. Results The linear regression model predicted the incidence with an RMSE of 7.562 (SD 6.492). The most effective factors besides previous day incidence included the search frequency of handwashing, hand sanitizer, and antiseptic topics. The RMSE of the LSTM model was 27.187 (SD 20.705). Conclusions Data mining algorithms can be employed to predict trends of outbreaks. This prediction might support policymakers and health care managers to plan and allocate health care resources accordingly.

Subfields: Epidemiology, Modeling and Simulation, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/ef6b60b71fb5ac07ad5fb3ddf4f975c3d21740f0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Digital Health Strategies to Fight COVID-19 Worldwide: Challenges, Recommendations, and a Call for Papers (2020, methodology): “Exploiting data such as Google Trends [34], Wikipedia searches, or the Baidu Index and Weibo Index in China has already proved useful.”
Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey (2020, positive): “In the case of other countries like Iran, China, Italy, and South Korea, the Google Trends Data is being used to collect coronavirus related information (Ayyoubzadeh, Ayyoubzadeh, Zahedi, Ahmadi, & Kalhori, 2020; Husnayain, Fuad, & Su, 2020; Strzelecki, 2020).”