When are predictions useful? A new method for evaluating epidemic forecasts

The WCIS provides a pragmatic utility-based characterization of probabilistic predictions. This method is expressly intended to enable practitioners and policymakers who may not have expertise in forecasting but are nevertheless essential partners in epidemic response to use and provide insightful analysis of predictions. We note that the WCIS is intended specifically for retrospective forecast evaluation and should not be used as a minimized penalty in a competitive context as it lacks statistical propriety. Code and data used for our analysis are available at https://github.com/maximilian-marshall/wcis .

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Publication Details

Journal
BMC Global and Public Health
Published
2024-10-03
DOI
https://doi.org/10.1186/s44263-024-00098-7
Citations
1
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.40

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article

When are predictions useful? A new method for evaluating epidemic forecasts

Felix Parker, Lauren A. Gardner, Maximilian Marshall
1 citations
BMC Global and Public Health
COVID-19 epidemiological studies
0.40
article

When are predictions useful? A new method for evaluating epidemic forecasts

Felix Parker, Lauren A. Gardner, Maximilian Marshall
article en
1 citations

Abstract

The WCIS provides a pragmatic utility-based characterization of probabilistic predictions. This method is expressly intended to enable practitioners and policymakers who may not have expertise in forecasting but are nevertheless essential partners in epidemic response to use and provide insightful analysis of predictions. We note that the WCIS is intended specifically for retrospective forecast evaluation and should not be used as a minimized penalty in a competitive context as it lacks statistical propriety. Code and data used for our analysis are available at https://github.com/maximilian-marshall/wcis .

BMC Global and Public HealthVol. 2(1)
Johns Hopkins University (US), Johns Hopkins Medicine (US)
National Science Foundation
Openalex Percentile: Top 41%
COVID-19 epidemiological studies
0.40
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