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. 2021 Mar 23;23(3):e24925. doi: 10.2196/24925

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©Christopher J Lynch, Ross Gore. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 23.03.2021.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

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State-level forecasts’ aggregated median MdAE values and 95% CI. CI ranges are calculated using box plot notch ranges around the median. Statistically significant differences at a P value of .01 are identified by nonoverlapping CI ranges of forecasting methods at each combination of forecast length and look-back length. Units are in terms of COVID-19 cumulative case counts. Y-axis scales differ on each row based on the scale of the contained data. Due to differing assumptions, five of the seven forecasting methods are present for each look-back length as indicated on the x-axis. AR: autoregressive; ARIMA: autoregressive integrated moving average; ARMA: autoregressive moving average; HW: Holt-Winters; MA: moving average; MdAE: median absolute error.