Nonlinear trend of COVID-19 infection time series

Autor:	Ishiyama, Fumihiko
Rok vydání:	2024
Předmět:	Physics - Physics and Society Quantitative Biology - Populations and Evolution
Zdroj:	Nolta, Volume 14, Issue 2, Pages 165-174, 2023
Druh dokumentu:	Working Paper
DOI:	10.1587/nolta.14.165
Popis:	We have developed a nonlinear method of time series analysis that allows us to obtain multiple nonlinear trends without harmonics from a given set of numerical data. We propose to apply the method to recognize the ongoing status of COVID-19 infection with an analytical equation for nonlinear trends. We found that there is only a single nonlinear trend, and this result justifies the use of a week-based infection growth rate. In addition, the fit with the obtained analytical equation for the nonlinear trend holds for a duration of more than three months for the Delta variant infection time series. The fitting also visualizes the transition to the Omicron variant. Comment: 11 pages, 7 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2404.00866 Zobrazit plný text záznamu View this record from Arxiv