Digital Surveillance Through an Online Decision Support Tool for COVID-19 Over One Year of the Pandemic in Italy: Observational Study.

Alberto Eugenio Tozzi Francesco Gesualdo Emanuele Urbani Alessandro Sbenaglia Roberto Ascione Nicola Procopio Ileana Croci Caterina Rizzo

Published in: Journal of medical Internet research (2021)

Temporal trends in the number of online COVID-19 DSS sessions may precede the trend in reported COVID-19 cases through traditional surveillance. The trends in sessions by users with a contact with COVID-19 may better predict reported cases of COVID-19 than sessions by symptomatic users. Data from online DSS may represent a useful supplement to traditional surveillance and support the identification of early warning signals in the COVID-19 pandemic.

Keyphrases

coronavirus disease
sars cov
public health
respiratory syndrome coronavirus
social media
healthcare
machine learning
health information
artificial intelligence
bioinformatics analysis