Enhancing Influenza-Like Illness forecasting: An ensemble approach combining mathematical and deep learning models amidst the COVID-19 pandemic
These findings underscore the power of hybrid forecasting approaches to improve epidemic preparedness and response, providing a flexible data-driven framework that can evolve with changing transmission dynamics and extend to other emerging infectious threats.
Authors
- Amanda Bleichrodt (ORCID: https://orcid.org/0009-0007-2524-369X)
- Kang Hyun Yoon
- Sunmi Lee
- Gerardo Chowell
Institutions
- Georgia State University (US)
- Kyung Hee University (KR)
Publication Details
- Journal
- Epidemics
- Published
- 2026-02-27
- DOI
- https://doi.org/10.1016/j.epidem.2026.100901
- Primary Topic
- COVID-19 epidemiological studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00