Philip J Turk, William E Anderson, Ryan J Burns, Shih-Hsiung Chou, Thomas E Dobbs, James T Kearns, Seth T Lirette, Maggie Sj McCarter, Hieu M Nguyen, Catherine L Passaretti, Geoffrey A Rose, Casey L Stephens, Jing Zhao, Andrew D McWilliams
BACKGROUND: During the COVID-19 pandemic, analytics and predictive models built on regional data provided timely, accurate monitoring of epidemiological behavior, informing critical planning and decision-making for health system leaders. At Atrium Health, a large, integrated healthcare system in the southeastern United States, a team of statisticians and physicians created a comprehensive forecast and monitoring program that leveraged an array of statistical methods. METHODS: The program utilized the following methodological approaches: (i) exploratory graphics, including time plots of epidemiological metrics with smoothers; (ii) infection prevalence forecasting using a Bayesian epidemiological model with time-varying infection rate; (iii) doubling and halving times computed using changepoints in local linear trend; (iv) death monitoring using combination forecasting with an ensemble of models; (v) effective reproduction number estimation with a Bayesian approach; (vi) COVID-19 patients hospital census monitored via time series models; and (vii) quantified forecast performance...
April 23, 2024: Journal of Infection and Public Health