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基于马尔可夫转换模型推断和预测 COVID-19 亚谱系的相位转移。

Inference and forecasting phase shift regime of COVID-19 sub-lineages with a Markov-switching model.

机构信息

Freddie Mac , Tysons Corner, Virginia, USA.

Artificial Intelligence and Big-Data Convergence Center, Gil Medical Center, Gachon University College of Medicine , Incheon, South Korea.

出版信息

Microbiol Spectr. 2023 Dec 12;11(6):e0166923. doi: 10.1128/spectrum.01669-23. Epub 2023 Oct 9.

Abstract

Using regime-switching models, we attempted to determine whether there is a link between changes in severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) variants and infection waves, as well as forecasting new SARS-Cov-2 variants. We believe that our study makes a significant contribution to the field because it proposes a new approach for forecasting the ongoing pandemic, and the spread of other infectious diseases, using a statistical model which incorporates unpredictable factors such as human behavior, political factors, and cultural beliefs.

摘要

我们使用了状态转换模型,试图确定严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 变异株的变化与感染浪潮之间是否存在关联,以及预测新的 SARS-CoV-2 变异株。我们相信我们的研究对该领域做出了重要贡献,因为它提出了一种新的方法,使用一种统计模型来预测正在进行的大流行以及其他传染病的传播,该模型纳入了不可预测的因素,如人类行为、政治因素和文化信仰。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e94/10714866/5bccfeea6787/spectrum.01669-23.f001.jpg

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