We test the predictive accuracy of forecasts of the number of COVID-19 fatalities produced by several forecasting teams and collected by the United States Centers for Disease Control and Prevention for the epidemic in the United States. We find three main results. First, at the short horizon (1-week ahead) no forecasting team out performs a simple time-series benchmark. Second, at longer horizons (3- and 4-week ahead)forecasters are more successful and sometimes outperform the benchmark. Third, one of the best performing forecasts is the Ensemble forecast, that combines all available predictions using uniform weights. In view of these results, collecting a wide range of forecasts and combining them in an ensemble forecast may be a superior approach for health authorities, rather than relying on a small number of forecasts.
|Number of pages||17|
|Journal||International journal of forecasting|
|Early online date||4 Mar 2023|
|Publication status||E-pub ahead of print - 4 Mar 2023|
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- Forecast evaluation, Forecasting tests, Epidemic