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Johannes Bracher, Evan L Ray, Tilmann Gneiting, Nicholas G Reich
For practical reasons, many forecasts of case, hospitalization, and death counts in the context of the current Coronavirus Disease 2019 (COVID-19) pandemic are issued in the form of central predictive intervals at various levels. This is also the case for the forecasts collected in the COVID-19 Forecast Hub (https://covid19forecasthub.org/). Forecast evaluation metrics like the logarithmic score, which has been applied in several infectious disease forecasting challenges, are then not available as they require full predictive distributions. This article provides an overview of how established methods for the evaluation of quantile and interval forecasts can be applied to epidemic forecasts in this format. Specifically, we discuss the computation and interpretation of the weighted interval score, which is a proper score that approximates the continuous ranked probability score. It can be interpreted as a generalization of the absolute error to probabilistic forecasts and allows for a decomposition into a measure of sharpness and penalties for over- and underprediction.
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Bracher, J., Ray, E. L., Gneiting, T., & Reich, N. G. (2021). Evaluating epidemic forecasts in an interval format. PLoS Computational Biology, 17(2), e1008618. https://doi.org/10.1371/journal.pcbi.1008618
Bracher, Johannes, et al. "Evaluating epidemic forecasts in an interval format." PLoS Computational Biology, vol. 17, no. 2, 2021, pp. e1008618, https://doi.org/10.1371/journal.pcbi.1008618.
Bracher, Johannes, Evan L Ray, Tilmann Gneiting, and Nicholas G Reich. "Evaluating epidemic forecasts in an interval format." PLoS Computational Biology 17, no. 2 (2021): e1008618. https://doi.org/10.1371/journal.pcbi.1008618.
Bracher J., Ray E. L., Gneiting T. [и др.] Evaluating epidemic forecasts in an interval format // PLoS Computational Biology. — 2021. — Vol. 17, № 2. — P. e1008618. — URL: https://doi.org/10.1371/journal.pcbi.1008618
@article{bracher2021evaluating,
title = {{Evaluating epidemic forecasts in an interval format}},
author = {Johannes Bracher and Evan L Ray and Tilmann Gneiting and Nicholas G Reich},
journal = {PLoS Computational Biology},
year = {2021},
volume = {17},
number = {2},
pages = {e1008618},
doi = {10.1371/journal.pcbi.1008618},
url = {https://doi.org/10.1371/journal.pcbi.1008618}
}TY - JOUR AU - Bracher, Johannes AU - Ray, Evan L AU - Gneiting, Tilmann AU - Reich, Nicholas G TI - Evaluating epidemic forecasts in an interval format JO - PLoS Computational Biology VL - 17 IS - 2 SP - e1008618 PY - 2021 DA - 2021/02/12 DO - 10.1371/journal.pcbi.1008618 UR - https://doi.org/10.1371/journal.pcbi.1008618 ER -
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