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Model Input and Optimization: Improving the Speed and Accuracy of Our COVID-19 Hospitalization Forecasts

Background: During the COVID-19 pandemic, public-health decision makers have increasingly relied on hospitalization forecasts that are routinely provided, accurate, and based on timely input data to inform pandemic planning. In North Carolina, we adapted an existing agent-based model (ABM) to produc...

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Detalles Bibliográficos
Autores principales:	Rhea, Sarah, Hadley, Emily, Jones, Kasey, Preiss, Alexander, Stoner, Marie, Kery, Caroline, Baumgartner, Peter, Giarrocco, Alex
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Cambridge University Press 2021
Materias:	Covid-19
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9551504/ http://dx.doi.org/10.1017/ash.2021.16

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