2020
DOI: 10.2139/ssrn.3619786
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Spectral Analysis of the Daily Evolution of Deaths Due to COVID-19 in France and in the World Shows a Weekend Effect: Myth or Reality?

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“…Since most common uncertainties are related to the time frame between contagion, sampling, detection and report (temporal misclassification), recovery criteria (PCR or fix quarantine time after which the patient is considered healed), we suggest to perform a data-pretreatment stage, where delayed curves could be corrected to the day of contagion before applying moving averages to smooth trends and estimate their variability while R t . The use of an one-week averaging window is suggested for minimizing the impact of the “weekend-effect” ( 20 ).…”
Section: Methodsmentioning
confidence: 99%
“…Since most common uncertainties are related to the time frame between contagion, sampling, detection and report (temporal misclassification), recovery criteria (PCR or fix quarantine time after which the patient is considered healed), we suggest to perform a data-pretreatment stage, where delayed curves could be corrected to the day of contagion before applying moving averages to smooth trends and estimate their variability while R t . The use of an one-week averaging window is suggested for minimizing the impact of the “weekend-effect” ( 20 ).…”
Section: Methodsmentioning
confidence: 99%
“…These sub-populations interact dynamically with each other, and the spreading modes are not necessarily isotropic [16] . Furthermore, our understanding of viral spread is greatly determined by data availability and quality, which has been proven to have significant delays [11] , weekly modulation [19] , and even weekend effects [5] , [10] .…”
Section: Introductionmentioning
confidence: 99%