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Fig 1.

Number and types of models at each forecast origin for each mortality dataset.

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Fig 2.

Data availability for forecasts of incident COVID-19 deaths.

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Fig 3.

Illustration of interval forecast combining methods that do not rely on past historical accuracy.

Each pair of shapes represents an interval forecast produced by an individual model.

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Table 1.

For incident mortality, 95% interval MIS and MWIS.

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Table 2.

For incident mortality, skill scores for 95% interval MIS and MWIS.

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Table 3.

For incident mortality, average ranks of the 95% interval MIS and MWIS.

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Table 4.

For incident mortality, skill scores for MWIS calculated separately for the first and second halves of the 74-week out-of-sample period.

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Table 5.

For incident mortality, skill scores for MWIS for combining methods applied to forecasts of all models, compartmental models only, and non-compartmental models only.

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Table 6.

For incident mortality, summary statistics of skill scores for individual models.

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Fig 4.

For incident mortality, reliability diagrams showing calibration of the 23 quantiles for the mean, median and inverse score with tuning methods.

The 23 quantiles include all bounds on the interval forecasts and the median.

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Table 7.

For cumulative mortality, 95% interval MIS and MWIS for the 78-week out-of-sample period.

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Table 8.

For cumulative mortality, skill scores for 95% interval MIS and MWIS for the 78-week out-of-sample period.

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Table 9.

For cumulative mortality, average ranks of the 95% interval MIS and MWIS.

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Table 10.

For cumulative mortality, skill scores for MWIS calculated separately for the first and second halves of the 78-week out-of-sample period.

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Table 10 Expand

Table 11.

For cumulative mortality, skill scores for MWIS for combining methods applied to forecasts of all models, compartmental models only, and non-compartmental models only.

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Table 12.

For cumulative mortality, summary statistics of skill scores for individual models, using mean and median combining as benchmark.

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Fig 5.

For cumulative mortality, reliability diagrams showing calibration of the 23 quantiles for the mean, median and inverse score with tuning methods.

The 23 quantiles include all bounds on the interval forecasts and the median.

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Fig 6.

Numbers of reported cumulative deaths in six states where there were noticeable changes in reporting patterns.

Based on reported death counts at multiple data points between 20 June 2020 and 15 January 2022.

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Fig 7.

For incident mortality, MWIS for high, medium and low mortality states for three selected combining methods.

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Fig 8.

For cumulative mortality, MWIS for high, medium and low mortality states for three selected combining methods.

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Fig 9.

Two examples of an outlying set of quantile forecasts of cumulative deaths for one week-ahead from forecast origin for the week ending on 18 July 2020.

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