Traffic-driven spatio-temporal prediction for fine-scale epidemic outbreaks in China
Our proposed approach integrates transportation patterns and human mobility into edge weight calculations to enhance spatial connectivity. This post-lockdown simulation across cities in China offers a fine-grained analytical scale previously unexplored, and the comprehensive analysis provides enhanced insights into epidemic dynamics and transmission patterns, supporting the future public health strategies.
Authors
- Licheng Li (ORCID: https://orcid.org/0000-0002-0886-2292)
- Wei Yan (ORCID: https://orcid.org/0000-0001-9569-9026)
- Rui Wang (ORCID: https://orcid.org/0000-0002-4792-1945)
- Han Li (ORCID: https://orcid.org/0000-0003-1983-5158)
- Jianping Huang (ORCID: https://orcid.org/0000-0002-1138-6151)
- Yingjie Zhao (ORCID: https://orcid.org/0000-0002-8660-6104)
- Xinbo Lian
- Shujuan Hu (ORCID: https://orcid.org/0009-0002-0474-7921)
- Zihan Hao (ORCID: https://orcid.org/0009-0006-7381-6280)
Institutions
- Lanzhou University of Finance and Economics (CN)
- Lanzhou University (CN)
Publication Details
- Journal
- BMC Infectious Diseases
- Published
- 2025-10-13
- DOI
- https://doi.org/10.1186/s12879-025-11708-6
- Primary Topic
- COVID-19 epidemiological studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Chinese Center for Disease Control and Prevention
- National Key Research and Development Program of China