An ensemble approach improves the prediction of the COVID-19 pandemic in South Korea
No single model performed consistently. While the ensemble models did not always provide the best predictions, a comparison of first-best and second-best models showed that they performed considerably better than the single models. If an ensemble model was not the best performing model, its performance was always not far from the best single model: a look at the mean and variance of the error measures shows that ensemble models provided stable predictions without much variation in their performances compared to single models. These results can be used to inform policymaking during future pandemics.
Authors
- Hanbyul Song
- Bogyeom Lee (ORCID: https://orcid.org/0009-0007-8534-3342)
- Kyulhee Han (ORCID: https://orcid.org/0000-0002-7243-5711)
- Xuwen Hu (ORCID: https://orcid.org/0000-0002-9508-642X)
- Catherine Apio (ORCID: https://orcid.org/0000-0003-0240-794X)
- Zhe Liu (ORCID: https://orcid.org/0000-0001-8587-656X)
- Taewan Goo (ORCID: https://orcid.org/0000-0001-9427-2290)
- Taesung Park (ORCID: https://orcid.org/0000-0002-8294-590X)
- Jiwon Park (ORCID: https://orcid.org/0009-0004-9528-7637)
Institutions
- Seoul National University (KR)
Publication Details
- Journal
- Journal of Global Health
- Published
- 2025-03-27
- DOI
- https://doi.org/10.7189/jogh.15.04079
- Citations
- 1
- Primary Topic
- COVID-19 epidemiological studies
- Type
- article
- Field-Weighted Citation Impact
- 1.37