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Evaluation of stochastic trajectory-based epidemic models using the energy score
Clara Bay1, Kunpeng Mu1, Guillaume St-Onge2
1Laboratory for the Modeling of Biological and Socio-technical Systems, Network Science Institute, Northeastern University, Boston, MA, USA.
Epidemics
|July 16, 2026
Summary
We introduce the energy score, a new metric for evaluating epidemic models. This score unifies multiple predictions into one measure, improving assessment of model performance for infectious disease forecasting.
Area of Science:
- Epidemiology
- Computational Biology
- Biostatistics
Background:
- Scoring rules are essential for assessing epidemic model accuracy.
- Existing metrics may not adequately capture multivariate time-series prediction performance.
Purpose of the Study:
- Introduce and evaluate the energy score for stochastic trajectory-based epidemic models.
- Compare the energy score's utility against the weighted interval score (WIS).
Main Methods:
- Applied the energy score as a multivariate extension of the continuous ranked probability score (CRPS).
- Analyzed the energy score's performance using data from the Scenario Modeling Hub for the 2023-2024 influenza season.
Main Results:
- The energy score provides a single, unified metric for time-series predictions, assessing calibration and sharpness.
- Demonstrated the energy score's utility in integrating predictions across multiple outcomes.
Conclusions:
- The energy score is a valuable tool for evaluating epidemic models, particularly for complex scenarios.
- It offers a more interpretable metric for comparing diverse model outputs.
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