Estimating a continuously varying offset between multivariate time series with application to COVID-19 in the United States
School of Mathematics and Statistics, University of Melbourne, 3010, Parkville, VIC, Australia
2 Beijing Institute of Mathematical Sciences and Applications, Tsinghua University, 101408, Beijing, China
Accepted: 18 December 2021
Published online: 11 January 2022
This paper introduces new methods to track the offset between two multivariate time series on a continuous basis. We then apply this framework to COVID-19 counts on a state-by-state basis in the United States to determine the progression from cases to deaths as a function of time. Across multiple approaches, we reveal an “up-down-up” pattern in the estimated offset between reported cases and deaths as the pandemic progresses. This analysis could be used to predict imminent increased load on a healthcare system and aid the allocation of additional resources in advance.
© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2022