Linear behavior in Covid19 epidemic as an effect of lockdown.

IF 1.7 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Journal of Mathematics in Industry Pub Date : 2020-01-01 Epub Date: 2020-11-30 DOI:10.1186/s13362-020-00095-z
Dario Bambusi, Antonio Ponno
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引用次数: 4

Abstract

We propose a mechanism explaining the approximately linear growth of Covid19 world total cases as well as the slow linear decrease of the daily new cases (and daily deaths) observed (in average) in USA and Italy. In our explanation, we regard a given population (the whole world or a single nation) as composed by many sub-clusters which, after lockdown, evolve essentially independently. The interaction is modeled by the fact that the outbreak time of the epidemic in a sub-cluster is a random variable with probability density slowly varying in time. The explanation is independent of the law according to which the epidemic evolves in the single sub cluster.

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封锁对covid - 19疫情的影响
我们提出了一种机制来解释covid - 19世界总病例的近似线性增长以及美国和意大利观察到的(平均)每日新病例(和每日死亡人数)的缓慢线性下降。在我们的解释中,我们认为一个给定的人口(整个世界或一个国家)由许多子集群组成,这些子集群在封锁后基本上是独立发展的。这种相互作用是通过一个子集群中流行病的爆发时间是一个概率密度随时间缓慢变化的随机变量来建模的。这种解释独立于流行病在单个子群中演变的规律。
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来源期刊
Journal of Mathematics in Industry
Journal of Mathematics in Industry MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
5.00
自引率
0.00%
发文量
12
审稿时长
13 weeks
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