This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2391) Infodemiology and Infoveillance (1274) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1013) Outbreak and Pandemic Preparedness and Management (1675) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1482) Infoveillance and Social Listening (181)

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

Authors of this article:

Cuihua Shen1 Author Orcid Image ;   Anfan Chen2 Author Orcid Image ;   Chen Luo3 Author Orcid Image ;   Jingwen Zhang1, 4 Author Orcid Image ;   Bo Feng1 Author Orcid Image ;   Wang Liao1 Author Orcid Image
Article Authors Cited by (89) Tweetations (43) Metrics

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