Integrating meteorological data and hybrid intelligent models for dengue fever prediction
Our experiment revealed the correlation and lag effect between meteorological factors and the incidence of dengue fever, indicating that meteorological factors have important value in predicting dengue fever. In addition, the hybrid prediction models constructed in this article can accurately predict outbreaks of dengue fever, which can lay a theoretical foundation for the construction of monitoring and early warning systems and improve the ability of relevant government departments to detect and identify dengue fever outbreaks in a timely manner.
Authors
- Yanping Bai
- Ting Xu (ORCID: https://orcid.org/0009-0004-0278-0503)
- Xiuhui Tan (ORCID: https://orcid.org/0000-0003-1596-0891)
- Jing Yang (ORCID: https://orcid.org/0000-0003-3223-2618)
- Rong Cheng
- Yunyun Cheng
Institutions
- North University of China (CN)
- Taiyuan Institute of Technology (CN)
Publication Details
- Journal
- BMC Public Health
- Published
- 2025-04-23
- DOI
- https://doi.org/10.1186/s12889-025-22375-2
- Citations
- 5
- Primary Topic
- Mosquito-borne diseases and control
- Type
- article
- Field-Weighted Citation Impact
- 9.39
Funders
- National Science Foundation
- National Natural Science Foundation of China