Optimizing Disease Outbreak Forecast Ensembles
On the basis of historical influenza and COVID-19 forecasts, we found that more than 3 forecast models are needed to ensure robust ensemble accuracy. Additional models can improve ensemble performance, but with diminishing accuracy returns. This understanding will assist with the design of current and future collaborative infectious disease forecasting efforts.
Authors
- Spencer J. Fox (ORCID: https://orcid.org/0000-0003-1969-3778)
- Evan L Ray (ORCID: https://orcid.org/0000-0003-4035-0243)
- Nicholas G Reich (ORCID: https://orcid.org/0000-0003-3503-9899)
- Lauren Ancel Meyers (ORCID: https://orcid.org/0000-0002-5828-8874)
- Minsu Kim
Publication Details
- Journal
- Emerging infectious diseases
- Published
- 2024-08-23
- DOI
- https://doi.org/10.3201/eid3009.240026
- Citations
- 12
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 4.64
Funders
- University of Texas at Austin
- Centers for Disease Control and Prevention