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理解环境传播在 COVID-19 群体免疫和入侵潜力中的作用。

Understanding the Role of Environmental Transmission on COVID-19 Herd Immunity and Invasion Potential.

机构信息

Natural Product Informatics Research Center, Korea Institute of Science and Technology, Gangneung, 25451, South Korea.

Department of Applied Mathematics, University of Rajshahi, Rajshahi, 6205, Bangladesh.

出版信息

Bull Math Biol. 2022 Sep 10;84(10):116. doi: 10.1007/s11538-022-01070-y.

Abstract

COVID-19 is caused by the SARS-CoV-2 virus, which is mainly transmitted directly between humans. However, it is observed that this disease can also be transmitted through an indirect route via environmental fomites. The development of appropriate and effective vaccines has allowed us to target and anticipate herd immunity. Understanding of the transmission dynamics and the persistence of the virus on environmental fomites and their resistive role on indirect transmission of the virus is an important scientific and public health challenge because it is essential to consider all possible transmission routes and route specific transmission strength to accurately quantify the herd immunity threshold. In this paper, we present a mathematical model that considers both direct and indirect transmission modes. Our analysis focuses on establishing the disease invasion threshold, investigating its sensitivity to both transmission routes and isolate route-specific transmission rate. Using the tau-leap algorithm, we perform a stochastic model simulation to address the invasion potential of both transmission routes. Our analysis shows that direct transmission has a higher invasion potential than that of the indirect transmission. As a proof of this concept, we fitted our model with early epidemic data from several countries to uniquely estimate the reproduction numbers associated with direct and indirect transmission upon confirming the identifiability of the parameters. As the indirect transmission possess lower invasion potential than direct transmission, proper estimation and necessary steps toward mitigating it would help reduce vaccination requirement.

摘要

COVID-19 是由 SARS-CoV-2 病毒引起的,主要在人与人之间直接传播。然而,据观察,这种疾病也可以通过环境污染物间接传播。开发合适和有效的疫苗使我们能够针对并预测群体免疫。了解病毒在环境污染物上的传播动力学和持久性及其在病毒间接传播中的抗性作用,是一个重要的科学和公共卫生挑战,因为必须考虑所有可能的传播途径和途径特异性传播强度,以准确量化群体免疫阈值。在本文中,我们提出了一个同时考虑直接和间接传播模式的数学模型。我们的分析侧重于建立疾病入侵阈值,研究其对两种传播途径和分离株特异性传播率的敏感性。我们使用 tau-leap 算法对随机模型进行模拟,以解决两种传播途径的入侵潜力。我们的分析表明,直接传播比间接传播具有更高的入侵潜力。作为这一概念的证明,我们用来自几个国家的早期疫情数据来拟合我们的模型,以独特地估计直接和间接传播的繁殖数,同时确认参数的可识别性。由于间接传播的入侵潜力低于直接传播,因此适当的估计和采取必要措施来减轻它将有助于减少疫苗接种的需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5563/9464131/8876f6da7ce5/11538_2022_1070_Fig1_HTML.jpg

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