Leveraging Large Language Models for Infectious Disease Surveillance-Using a Web Service for Monitoring COVID-19 Patterns From Self-Reporting Tweets: Content Analysis.

Background: The emergence of new SARS-CoV-2 variants, the resulting reinfections, and post-COVID-19 condition continue to impact many people's lives. Tracking websites like the one at Johns Hopkins University no longer report the daily confirmed cases, posing challenges to accurately determine the true extent of infections. Many COVID-19 cases with mild symptoms are self-assessed at home and reported on social media, which provides an opportunity to monitor and understand the progression and evolving trends of the disease.