Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63190, first published .
Leveraging Large Language Models for Infectious Disease Surveillance—Using a Web Service for Monitoring COVID-19 Patterns From Self-Reporting Tweets: Content Analysis

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

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

Jiacheng Xie   1, 2 , PhD ;   Ziyang Zhang   1, 2 , MS ;   Shuai Zeng   1, 2 , PhD ;   Joel Hilliard   1 , BSc ;   Guanghui An   2, 3 , MD, PhD ;   Xiaoting Tang   2, 4 , MD, PhD ;   Lei Jiang   1, 2 , PhD ;   Yang Yu   1, 2 , PhD ;   Xiufeng Wan   1, 2, 5, 6 , PhD ;   Dong Xu   1, 2 , PhD

1 Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, United States

2 Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, United States

3 School of Acupuncture-Moxibustion and Tuina, Shanghai University of Traditional Chinese Medicine, Shanghai, China

4 Shanghai Pudong New Area Wanggang Community Health Service Center, Shanghai, China

5 NextGen Center for Influenza and Emerging Infectious Diseases, University of Missouri, Columbia, United States

6 Department of Molecular Microbiology and Immunology, University of Missouri, Columbia, United States

Corresponding Author:

  • Dong Xu, PhD
  • Department of Electrical Engineering and Computer Science
  • University of Missouri
  • 227 Naka Hall
  • Columbia, MO, 65211
  • United States
  • Phone: 1 5738822299
  • Email: xudong@missouri.edu