Published on in Vol 22, No 5 (2020): May

This is a member publication of UC Davis - Shields Library, Davis, CA, USA

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19421, first published .
Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study

Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study

Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study

Cuihua Shen   1 * , PhD ;   Anfan Chen   2 * , PhD ;   Chen Luo   3 , MA ;   Jingwen Zhang   1, 4 , PhD ;   Bo Feng   1 , PhD ;   Wang Liao   1 , PhD

1 Department of Communication, University of California, Davis, Davis, CA, United States

2 Department of Science Communication and Science Policy, University of Science and Technology of China, Hefei, China

3 School of Journalism and Communication, Tsinghua University, Beijing, China

4 Department of Public Health Sciences, University of California, Davis, Davis, CA, United States

*these authors contributed equally

Corresponding Author:

  • Wang Liao, PhD
  • Department of Communication
  • University of California, Davis
  • One Shields Ave
  • Davis, CA
  • United States
  • Phone: 1 5307520966
  • Email: wngliao@ucdavis.edu