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可解时滞模型在传染病传播中的应用:以意大利的新冠肺炎疫情为例。

Solvable delay model for epidemic spreading: the case of Covid-19 in Italy.

机构信息

Dipartimento di Fisica e Astronomia "G. Galilei", Università degli Studi di Padova, via F. Marzolo 8, 35131, Padova, Italy.

出版信息

Sci Rep. 2020 Sep 25;10(1):15763. doi: 10.1038/s41598-020-72529-y.

Abstract

We study a simple realistic model for describing the diffusion of an infectious disease on a population of individuals. The dynamics is governed by a single functional delay differential equation, which, in the case of a large population, can be solved exactly, even in the presence of a time-dependent infection rate. This delay model has a higher degree of accuracy than that of the so-called SIR model, commonly used in epidemiology, which, instead, is formulated in terms of ordinary differential equations. We apply this model to describe the outbreak of the new infectious disease, Covid-19, in Italy, taking into account the containment measures implemented by the government in order to mitigate the spreading of the virus and the social costs for the population.

摘要

我们研究了一个简单的现实模型,用于描述传染病在人群中的扩散。动力学由一个单一的函数时滞微分方程控制,在大种群的情况下,即使在感染率随时间变化的情况下,也可以精确求解。与通常在流行病学中使用的所谓 SIR 模型相比,这个时滞模型具有更高的准确性,而 SIR 模型则是用常微分方程来表述的。我们将这个模型应用于描述意大利新传染病 COVID-19 的爆发,考虑到政府为减轻病毒传播和人口的社会成本而实施的遏制措施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e577/7519166/d51e63d7431d/41598_2020_72529_Fig1_HTML.jpg

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