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

Journal: JMIR public health and surveillance
Published Date: Apr 14, 2020

Abstract

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.

Authors

  • Seyed Mohammad Ayyoubzadeh
    Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
  • Seyed Mehdi Ayyoubzadeh
    Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada.
  • Hoda Zahedi
    School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
  • Mahnaz Ahmadi
    Department of Pharmaceutics, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Sharareh R Niakan Kalhori
    Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

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