Review: Prediction of number of cases of 2019 novel coronavirus (COVID-19) using social media search index

Home/Review: Prediction of number of cases of 2019 novel coronavirus (COVID-19) using social media search index

Review: Prediction of number of cases of 2019 novel coronavirus (COVID-19) using social media search index

Review: Prediction of number of cases of 2019 novel coronavirus (COVID-19) using social media search index

An estimated 80% of all Internet users search for health information. This study investigated the correlation between the number of new cases of COVID-19 and search index for the Baidu, the most popular search engine in China.

Investigators obtained keyword search trends on Baidu for terms related to suspected COVID-19, including (Chinese words for) dry cough, fever, chest distress, coronavirus, and pneumonia, from 31 December 2019, to 9 February 2020. New suspected cases of COVID-19 data were collected from 20 January 2020 to 9 February 2020.

They found that new suspected COVID-19 case numbers correlated significantly with the lagged series of these search indexes, which were detected 6-9 days earlier than new suspected cases of COVID-19. These findings suggest that search indexes could be early, effective predictors of the number of COVID-19 infections, which would enable governments’ health departments to locate potential and high-risk outbreak areas.

|2020-04-06T14:19:56-04:00April 6th, 2020|COVID-19 Literature|Comments Off on Review: Prediction of number of cases of 2019 novel coronavirus (COVID-19) using social media search index

About the Author: Erika Cheng

Erika Cheng

Get Involved with Indiana CTSI