Payesh (Apr 2021)
Predicting COVID-19 epidemics using Google search trends
Abstract
Objective (s): Traditional health surveillance systems usually publish reports of infectious disease outbreaks 1 to 2 weeks after onset. The Google Trends shows people search information with a one-day delay. These data can be used to identify and manage epidemics of infectious diseases. The aim of this study was to predict the Covid-19 epidemic using the Google Trends. Methods: This descriptive cross-sectional study was conducted in February 2021. Google Trends data was used to determine how much attention was paid to COVID-19. Data on COVID-19 deaths were obtained from the Iran Ministry of Health. Data were collected and reviewed in the period from February 22, 2020 to January 20, 2021. Data were analyzed using Excel and SPSS soft wares. Results: Simultaneously with the announcement of incidence of COVID-19 in Iran on February 20, the society’s sensitivity to COVID-19 has increased and the search rate for COVID-19 in Google has reached its maximum. Three waves of COVID-19 outbreak have been observed in Iran by the end of December 2020. These three waves were similarly observed in Google trends. In all three COVID-19 waves, the peak of Google search occurred 10 to 20 days before the peak of the number of deaths. Conclusion: The Google Trends can detect the COVID-19 outbreak quicker. Google search data can be used as a complement to the infectious disease surveillance system.
