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基于阿曼苏丹国新冠疫情感染临床阶段的SEAMHCRD确定性分区模型。

SEAMHCRD deterministic compartmental model based on clinical stages of infection for COVID-19 pandemic in Sultanate of Oman.

作者信息

Varghese Abraham, Kolamban Shajidmon, Sherimon Vinu, Lacap Eduardo M, Ahmed Saad Salman, Sreedhar Jagath Prasad, Al Harthi Hasina, Al Shuaily Huda Salim

机构信息

Department of Information Technology, Faculty of Mathematics, University of Technology and Applied Sciences, Muscat, Sultanate of Oman.

Department of Information Technology, Faculty of IT, University of Technology and Applied Sciences, Muscat, Sultanate of Oman.

出版信息

Sci Rep. 2021 Jun 7;11(1):11984. doi: 10.1038/s41598-021-91114-5.

Abstract

The present novel coronavirus (COVID-19) infection has engendered a worldwide crisis on an enormous scale within a very short period. The effective solution for this pandemic is to recognize the nature and spread of the disease so that appropriate policies can be framed. Mathematical modelling is always at the forefront to understand and provide an adequate description of the transmission of any disease. In this research work, we have formulated a deterministic compartmental model (SEAMHCRD) including various stages of infection, such as Mild, Moderate, Severe and Critical to study the spreading of COVID-19 and estimated the model parameters by fitting the model with the reported data of ongoing pandemic in Oman. The steady-state, stability and final pandemic size of the model has been proved mathematically. The various transmission as well as transition parameters are estimated during the period from June 4th to July 30th, 2020. Based on the currently estimated parameters, the pandemic size is also predicted for another 100 days. Sensitivity analysis is performed to identify the key model parameters, and the parameter gamma due to contact with the symptomatic moderately infected is found to be more significant in spreading the disease. Accordingly, the corresponding basic reproduction number has also been computed using the Next Generation Matrix (NGM) method. As the value of the basic reproduction number (R) is 0.9761 during the period from June 4th to July 30th, 2020, the disease-free equilibrium is stable. Isolation and tracing the contact of infected individuals are recommended to control the spread of disease.

摘要

当前的新型冠状病毒(COVID-19)感染在极短时间内引发了一场大规模的全球危机。解决这场大流行的有效办法是认清该疾病的本质和传播方式,以便制定适当的政策。数学建模始终处于理解和充分描述任何疾病传播的前沿。在这项研究工作中,我们构建了一个确定性的 compartmental 模型(SEAMHCRD),该模型包含感染的各个阶段,如轻症、中症、重症和危重症,以研究 COVID-19 的传播情况,并通过将该模型与阿曼正在流行的疫情报告数据进行拟合来估计模型参数。从数学上证明了该模型的稳态、稳定性和最终大流行规模。在2020年6月4日至7月30日期间估计了各种传播以及转变参数。基于当前估计的参数,还预测了未来100天的大流行规模。进行了敏感性分析以确定关键模型参数,发现与有症状的中度感染者接触导致的参数 gamma 在疾病传播中更为显著。相应地,还使用下一代矩阵(NGM)方法计算了基本再生数。由于2020年6月4日至7月30日期间基本再生数(R)的值为0.9761,无病平衡点是稳定的。建议对感染者进行隔离并追踪其接触者以控制疾病传播。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb3e/8184795/8be2c055bf06/41598_2021_91114_Fig1_HTML.jpg

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