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Spectral Processing of COVID-19 Time-Series Data

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Document pages: 7 pages

Abstract: The presence of oscillations in aggregated COVID-19 data not only raisesquestions about the data s accuracy, it hinders understanding of the pandemic.Spectral analysis is used to reveal additional properties of the data, and theoscillations are replicated using sinusoidal resynthesis. The precise behaviorof the seven-day moving average is also discussed, specifically, the cause ofits jaggedness and the phase error it introduces. In comparison, otherfiltering techniques and Fourier processing produce superior smoothing and havezero phase error. Both of these are presented, and they are extended to isolateseveral frequency ranges. This extracts some of the same short-term variabilitythat is resynthesized, and it shows that fluctuations with periods between 8and 21 days are present in U.S. mortality data. These methods have applicationsthat include modeling epidemiological time-series data as well as identifyingless obvious properties of the data.

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