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

Infodemiology and Infoveillance (1349) JMIR Theme Issue: COVID-19 Special Issue (2452) Infoveillance and Social Listening (209)

Published on in Vol 23, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28876, first published .
Forecasting the COVID-19 Epidemic by Integrating Symptom Search Behavior Into Predictive Models: Infoveillance Study

Forecasting the COVID-19 Epidemic by Integrating Symptom Search Behavior Into Predictive Models: Infoveillance Study

Forecasting the COVID-19 Epidemic by Integrating Symptom Search Behavior Into Predictive Models: Infoveillance Study

Authors of this article:

Alessandro Rabiolo1 Author Orcid Image ;   Eugenio Alladio2 Author Orcid Image ;   Esteban Morales3 Author Orcid Image ;   Andrew Ian McNaught1, 4 Author Orcid Image ;   Francesco Bandello5 Author Orcid Image ;   Abdelmonem A Afifi6 Author Orcid Image ;   Alessandro Marchese5 Author Orcid Image
Article Authors Cited by (17) Tweetations (5) Metrics

Alessandro Rabiolo   1 * , MD ;   Eugenio Alladio   2 * , PhD ;   Esteban Morales   3 , MSc ;   Andrew Ian McNaught   1, 4 , MD ;   Francesco Bandello   5 , MD ;   Abdelmonem A Afifi   6 , PhD ;   Alessandro Marchese   5 , MD

1 Department of Ophthalmology, Gloucestershire Hospitals NHS Foundation Trust, Cheltenham, United Kingdom

2 Department of Chemistry, University of Turin, Turin, Italy

3 Jules Stein Eye Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States

4 School of Health Professions, Faculty of Health, University of Plymouth, Plymouth, United Kingdom

5 Department of Ophthalmology, Vita-Salute University, IRCCS Ospedale San Raffaele Scientific Institute, Milan, Italy

6 Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, United States

*these authors contributed equally

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