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

Although with some biases and limitations, self-reported tweet data serves as a valuable complement to clinical data, especially in the postpandemic era dominated by mild cases. Our web-based analytic platform can play a significant role in continuously tracking COVID-19, finding new uncommon symptoms, detecting and monitoring the manifestation of long-term effects, and providing necessary insights to the public and decision-makers.