Estimating a continuously varying offset between multivariate time series with application to COVID-19 in the United States

Abstract

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.

arXiv commentFinal version. Minor edits since v1. Equal contribution

References in corpus (20)

• Measuring and testing dependence by correlation of distances
• Spatiotemporal effects of the causal factors on COVID-19 incidences in the contiguous United States
• Accurate closed-form solution of the SIR epidemic model
• COVID-19: Development of a Robust Mathematical Model and Simulation Package with Consideration for Ageing Population and Time Delay for Control Action and Resusceptibility
• Strong correlations between power-law growth of COVID-19 in four continents and the inefficiency of soft quarantine strategies
• Polynomial growth in age-dependent branching processes with diverging reproductive number
• Power-law distribution in the number of confirmed COVID-19 cases
• Spatio-temporal propagation of COVID-19 pandemics
• COVID-19 second wave mortality in Europe and the United States
• On the Emergence of a Power Law in the Distribution of COVID-19 Cases
• Analytic solution of the SEIR epidemic model via asymptotic approximant
• Size and timescale of epidemics in the SIR framework
• COVID-19 in the United States: Trajectories and second surge behavior
• Trends in COVID-19 prevalence and mortality: a year in review
• Hamiltonian structure of compartmental epidemiological models
• Association between COVID-19 cases and international equity indices
• Novel semi-metrics for multivariate change point analysis and anomaly detection
• Decay of distance autocorrelation and Lyapunov exponents
• Efficiency of communities and financial markets during the 2020 pandemic
• A simplified estimate of the Effective Reproduction Number $R_t$ using its relation with the doubling time and application to Italian COVID-19 data

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