从阶段空间分析大流行病

Olivier Merlo
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引用次数: 0

摘要

在 SIRD 模型的基础上,提出了一个包含时间延迟的新模型,用于描述新型冠状病毒 Sars-CoV-2 大流行的爆发。通过将所有数量表示为易感人群的函数来分析所有数据,而不是通常的时间依赖性。在达到最大感染人数后不久,可以预测德国第一、第二和第三波大流行的死亡总人数,准确率约为 10%。通过在相空间中的演示,可以证明经典的 SEIRD 模型和 SIRD 模型(参数不变)无法准确描述大流行的第一波。
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Analysing pandemics in phase-space
Based on the SIRD-model a new model including time-delay is proposed for a description of the outbreak of the novel coronavirus Sars-CoV-2 pandemic. All data were analysed by representing all quantities as a function of the susceptible population, as opposed to the usual dependence on time. The total number of deaths could be predicted for the first, second and third wave of the pandemic in Germany with an accuracy of about 10\%, shortly after the maximum of infectious people was reached. By using the presentation in phase space, it could be shown that a classical SEIRD- and SIRD-model with constant parameters will not be able to describe the first wave of the pandemic accurately.
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