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Projecting COVID-19 cases and hospital burden in Ohio

KhudaBukhsh, Wasiur R.; Bastian, Caleb Deen; Wascher, Matthew; Klaus, Colin; Sahai, Saumya Yashmohini; Weir, Mark H.; Kenah, Eben; Root, Elisabeth; Tien, Joseph H.; Rempała, Grzegorz A.

Authors

Caleb Deen Bastian

Matthew Wascher

Colin Klaus

Saumya Yashmohini Sahai

Mark H. Weir

Eben Kenah

Elisabeth Root

Joseph H. Tien

Grzegorz A. Rempała



Abstract

As the Coronavirus 2019 disease (COVID-19) started to spread rapidly in the state of Ohio, the Ecology, Epidemiology and Population Health (EEPH) program within the Infectious Diseases Institute (IDI) at The Ohio State University (OSU) took the initiative to offer epidemic modeling and decision analytics support to the Ohio Department of Health (ODH). This paper describes the methodology used by the OSU/IDI response modeling team to predict statewide cases of new infections as well as potential hospital burden in the state. The methodology has two components: (1) A Dynamical Survival Analysis (DSA)-based statistical method to perform parameter inference, statewide prediction and uncertainty quantification. (2) A geographic component that down-projects statewide predicted counts to potential hospital burden across the state. We demonstrate the overall methodology with publicly available data. A Python implementation of the methodology is also made publicly available. This manuscript was submitted as part of a theme issue on “Modelling COVID-19 and Preparedness for Future Pandemics”.

Citation

KhudaBukhsh, W. R., Bastian, C. D., Wascher, M., Klaus, C., Sahai, S. Y., Weir, M. H., …Rempała, G. A. (2023). Projecting COVID-19 cases and hospital burden in Ohio. Journal of Theoretical Biology, 561, Article 111404. https://doi.org/10.1016/j.jtbi.2022.111404

Journal Article Type Article
Acceptance Date Dec 26, 2022
Online Publication Date Jan 13, 2023
Publication Date Mar 21, 2023
Deposit Date Jan 14, 2023
Publicly Available Date Jan 18, 2023
Journal Journal of Theoretical Biology
Print ISSN 0022-5193
Electronic ISSN 1095-8541
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 561
Article Number 111404
DOI https://doi.org/10.1016/j.jtbi.2022.111404
Keywords Applied Mathematics; General Agricultural and Biological Sciences; General Immunology and Microbiology; General Biochemistry, Genetics and Molecular Biology; Modeling and Simulation; General Medicine; Statistics and Probability
Public URL https://nottingham-repository.worktribe.com/output/15940568
Publisher URL https://www.sciencedirect.com/science/article/pii/S0022519322003952?via%3Dihub

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