Projecting COVID-19 cases and hospital burden in Ohio.
Projecting COVID-19 cases and hospital burden in Ohio.
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DOI：
10.1016/j.jtbi.2022.111404
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发表时间：
2023-03-21
影响因子：
2
通讯作者：
Rempala, Grzegorz A.
中科院分区：
文献类型：
--
作者：
KhudaBukhsh, Wasiur R.;Bastian, Caleb Deen;Wascher, Matthew;Klaus, Colin;Sahai, Saumya Yashmohini;Weir, Mark H.;Kenah, Eben;Root, Elisabeth;Tien, Joseph H.;Rempala, Grzegorz A.
随着2019冠状病毒病（COVID-19）开始在俄亥俄州迅速蔓延，俄亥俄州州立大学（OSU）传染病研究所（IDI）内的生态学、流行病学和人口健康（EEPH）项目主动为俄亥俄州卫生部（ODH）提供流行病建模和决策分析支持。本文描述了OSU/IDI响应建模团队用于预测全州新感染病例以及该州潜在医院负担的方法。该方法有两个组成部分：（1）一个动态生存分析（DSA）为基础的统计方法进行参数推断，全州范围内的预测和不确定性量化。(2)一个地理组成部分，向下项目全州预测计数到潜在的医院负担在整个国家。我们用公开的数据展示了整体方法。该方法的Python实现也公开提供。本手稿是作为“COVID-19建模和未来大流行的准备”主题问题的一部分提交的。
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”.
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影响因子：
2.9
作者：
Bastian, Caleb Deen;Rempala, Grzegorz A.
通讯作者：
Rempala, Grzegorz A.
DOI：
10.1098/rsif.2022.0124
发表时间：
2022-06
期刊：
Journal of the Royal Society, Interface
影响因子：
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作者：
通讯作者：
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影响因子：
3.5
作者：
Eubank, S.;Eckstrand, I;Barrett, C. L.
通讯作者：
Barrett, C. L.
DOI：
10.15585/mmwr.mm6912e2
发表时间：
2020-03-27
期刊：
MMWR. Morbidity and mortality weekly report
影响因子：
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作者：
CDC COVID-19 Response Team
通讯作者：
CDC COVID-19 Response Team
DOI：
10.1098/rspa.1927.0118
发表时间：
1927-08-01
期刊：
PROCEEDINGS OF THE ROYAL SOCIETY OF LONDON SERIES A-CONTAINING PAPERS OF A MATHEMATICAL AND PHYSICAL CHARACTER
影响因子：
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作者：
Kermack, WO;McKendrick, AG
通讯作者：
McKendrick, AG