Forecasting COVID-19 Hospital Census: A Multivariate Time-Series Model Based on Local Infection Incidence [open pdf - 620KB]
From the Abstract: "COVID-19 [coronavirus disease 2019] has been one of the most serious global health crises in world history. During the pandemic, health care systems require accurate forecasts for key resources to guide preparation for patient surges. Forecasting the COVID-19 hospital census is among the most important planning decisions to ensure adequate staffing, number of beds, intensive care units, and vital equipment. [...] The goal of this study was to explore the potential utility of local COVID-19 infection incidence data in developing a forecasting model for the COVID-19 hospital census."
Hieu M Nguyen, Philip J Turk, Andrew D McWilliams. Posted here with permission. Document is under a Creative Commons license and requires proper attribution and noncommercial use to be shared: [https://creativecommons.org/licenses/by/4.0/].
JMIR Publications: https://jmirpublications.com/
JMIR Public Health Surveillance (August 04, 2021), v.7 issue 8