A human behavior-based model for respiratory infectious diseases prediction
This research presents an innovative micro-level exposure risk model for respiratory infectious diseases (RIDs), which provides significant insights into the risk of infection. However, it is important to acknowledge certain limitations, including the distinctiveness of the data sources utilized and the insufficient examination of transmission pathways. Subsequent studies should aim to enhance the dataset, fine-tune model parameters, and integrate further transmission pathways to augment both the accuracy and applicability of the model.
Authors
- Hui Ma (ORCID: https://orcid.org/0000-0003-3967-7636)
- Mingcai Li (ORCID: https://orcid.org/0000-0003-3910-6964)
- Nan Zhang (ORCID: https://orcid.org/0000-0003-2092-4334)
- Zhi Chen (ORCID: https://orcid.org/0000-0002-9038-4831)
- Huaguo Zhang (ORCID: https://orcid.org/0000-0002-5331-9926)
- Min Zhu (ORCID: https://orcid.org/0000-0002-4800-4161)
- Zhengwen Ma
Institutions
- Capital Medical University (CN)
- Chinese PLA General Hospital (CN)
- Beijing University of Technology (CN)
- Southern Medical University (CN)
Publication Details
- Journal
- Frontiers in Public Health
- Published
- 2025-04-29
- DOI
- https://doi.org/10.3389/fpubh.2025.1578178
- Citations
- 1
- Primary Topic
- COVID-19 epidemiological studies
- Type
- article
- Field-Weighted Citation Impact
- 1.37