Retrospective analysis of the possibility of predicting the COVID-19 outbreak from Internet searches and social media data, China, 2020

• Published in: Euro surveillance : bulletin européen sur les maladies transmissibles Vol. 25; no. 10
• Main Authors: Li, Cuilian, Chen, Li Jia, Chen, Xueyu, Zhang, Mingzhi, Pang, Chi Pui, Chen, Haoyu
• Format: Journal Article
• Language: English
• Published: Sweden European Centre for Disease Prevention and Control (ECDC) 12-03-2020
• Subjects: China - epidemiology; Coronavirus Infections - diagnosis; Coronavirus Infections - epidemiology; Coronavirus Infections - transmission; COVID-19; Disease Outbreaks - statistics & numerical data; Humans; Incidence; Internet; Laboratories - statistics & numerical data; Pneumonia, Viral - diagnosis; Pneumonia, Viral - epidemiology; Pneumonia, Viral - transmission; Population Surveillance - methods; Public Health Practice; Rapid Communication; Search Engine - statistics & numerical data; Social Media - statistics & numerical data; Social Media - trends; Web Browser - statistics & numerical data; Web Browser - trends; China; Baidu Index; COVID-19; Google Trends; Internet surveillance; coronavirus; Weibo Index
• ISSN: 1560-7917; 1025-496X; 1560-7917
• DOI: 10.2807/1560-7917.es.2020.25.10.2000199

The peak of Internet searches and social media data about the coronavirus disease 2019 (COVID-19) outbreak occurred 10-14 days earlier than the peak of daily incidences in China. Internet searches and social media data had high correlation with daily incidences, with the maximum r > 0.89 in all correlations. The lag correlations also showed a maximum correlation at 8-12 days for laboratory-confirmed cases and 6-8 days for suspected cases.