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Accuracy and robustness of US CDC COVID-19 forecasting fashions

In a current examine posted to the medRxiv* preprint server, researchers examined the accuracy of the US Facilities for Illness Management and Prevention (CDC) coronavirus illness 2019 (COVID-19) forecasting fashions.

Study: Accuracy of US CDC COVID-19 Forecasting Models. Image Credit: CROCOTHERY/Shutterstock
Examine: Accuracy of US CDC COVID-19 Forecasting Fashions. Picture Credit score: CROCOTHERY/Shutterstock

Correct predictive modeling of pandemic outcomes performs a essential function in growing methods and insurance policies to curb the extent of the pandemic. Whereas a number of prediction fashions have been thought-about, their accuracy and robustness over time and totally different fashions are unclear.

In regards to the examine

Within the current examine, the researchers analyzed all US CDC COVID-19 forecasting fashions by categorizing them as per mannequin kind and estimating their imply % error over totally different COVID-19 an infection waves.

The crew in contrast a number of US CDC COVID-19 forecasting fashions in response to their quantitative traits by measuring their efficiency over varied intervals. The US CDC compiles COVID-19 case-related weekly forecasts in 4 totally different time intervals, together with one week two weeks, three weeks, and 4 weeks. The fashions make a brand new forecast each week for brand new COVID-19 circumstances incident in every of the 4 subsequent weeks. The forecast horizon was thought-about because the time span for which the forecast was to be ready. The current examine targeted on assessing the efficiency of four-week forecast fashions.

The forecasting fashions had been differentiated into 5 classes specifically, ensemble, epidemiological, hybrid, and machine studying. The crew examined a complete of 51 fashions. The CDC mannequin makes use of an ensemble mannequin and the researchers assessed if this mannequin was extra correct than any particular person mannequin. Imply absolute % error (MAPE) was evaluated and reported for every mannequin studied and the fashions had been in contrast in response to their efficiency in every wave. The crew outlined waves as (1) Wave I: 6 July 2020 to 31 August 2020; (2) Wave II: 1 September 2020 to 14 February 2021; (3) Wave III: 15 February 2021 to 26 July 2021; and (4) Wave IV: 27 July 2021 to 17 January 2022.

The efficiency of the forecasting fashions was calculated in response to two baselines. Baseline-I used to be the ‘CovidHub-Baseline’ (or CDC’s baseline) that evaluated the latest an infection incidence because the median prediction of future horizons. Baseline-II took under consideration the extrapolation of the linear predictor in reported energetic COVID-19 circumstances between two weeks earlier than the date of the forecast. The crew solely thought-about the fashions that had made predictions for at least 25% of the goal dates studied.        


The examine outcomes confirmed that through the first wave of the COVID-19 pandemic, the MAPE values had been 14% for the Columbia_UNC-SurvCon, 17% for the USACE-ERDC_SEIR, and 25% for the CovidAnalytics-DELPHI fashions. Among the many 4 fashions that carried out higher as in comparison with the 2 baselines, three had been epidemiological fashions and one was a hybrid mannequin. The crew additionally inferred that the hybrid fashions carried out higher than the remainder and had the bottom MAPE, adopted by the epidemiological and subsequently the machine studying fashions. In distinction, the ensemble fashions had the best MAPE within the first wave whereas not one of the fashions crossed the brink of the MAPE of baseline-I.

Through the second COVID-19 wave, the IQVIA_ACOE-STAN mannequin carried out the very best with a 5.5% MAPE. A complete of 13 fashions surpassed each the baselines with a MAPE between 5 and 37. The most effective-performing fashions on this wave included 5 ensemble fashions, 4 epidemiological fashions, two machine studying fashions, and two hybrid fashions. Notably, all of the ensemble fashions surpassed the efficiency of the primary baseline with a MAPE of 37%, besides the UVA-Ensemble mannequin. Additionally, a staggering distribution in MAPE values was noticed for the epidemiological fashions. Moreover, versus wave I, the ensemble fashions predicted essentially the most correct forecasts in wave II whereas the hybrid fashions had been the least correct.

Throughout wave III, the efficiency of the ensemble fashions was corresponding to the primary wave. Furthermore, the baselines fashions reported a relatively larger MAPE with the MAPE values at baselines I and II being 74% and 77%, respectively. On this wave, the very best performing mannequin was the USC-SI_kJalpha which had a MAPE of 32%. A complete of 32 fashions confirmed higher efficiency than that of the baseline fashions, together with 12 compartment fashions, three machine studying fashions, 4 hybrid fashions, eight ensemble fashions, and 5 un-categorized fashions.

Within the fourth wave of the pandemic, just a few fashions had a MAPE of 28% whereas the baseline MAPE was 47%. Whereas the ensemble fashions carried out the very best on this time interval, the epidemiological fashions confirmed the best MAPE. The MAPE scores of baseline I and II had been 47% and 48%, respectively.  


To summarize, the examine findings confirmed that there have been no important variations within the accuracy of the totally different CDC COVID-19 forecasting fashions. Moreover, the error price within the fashions elevated over time via the pandemic. The researchers consider that the current examine can function a basis for the event of extra correct and strong forecasting fashions.

*Vital discover

medRxiv publishes preliminary scientific studies that aren’t peer-reviewed and, due to this fact, shouldn’t be thought to be conclusive, information medical follow/health-related conduct, or handled as established info.


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