论文标题
COVID-19大流行的分形时间增长:准确的自相似模型和紧急结论
The fractal time growth of COVID-19 pandemic: an accurate self-similar model, and urgent conclusions
论文作者
论文摘要
使用维度分析和自相似性假设分析了COVID-19大流行的全球影响的当前可用数据。我们表明,受感染人群的时间序列和影响最大和没有准备的国家的死亡表现出渐近力法行为,与分形网络中信号的传播兼容。我们提出了一个模型,该模型可以预测在遏制前的及时及时的渐近自相似的膨胀,以及在总遏制量度下的最终死亡人数,这是观察到扩张后采取这些措施的延迟的函数。该模型的物理类似于具有分形尺寸为3.75的均匀域中火焰的膨胀。采取遏制措施后,网络的自然分形结构会发生巨大变化,并观察到二次进化。根据中国大流行行为的可用数据,这种演变类似于最终淬火的静态隔离围墙中的均匀燃烧,其特征时间为20.1天。所提出的模型与可用数据非常一致,该数据支持模型中提出的简化假设。还提出了隔离的通用公式作为该延迟的函数。
Current available data of the worldwide impact of the COVID-19 pandemic has been analyzed using dimensional analysis and self-similarity hypotheses. We show that the time series of infected population and deaths of the most impacted and unprepared countries exhibits an asymptotic power law behavior, compatible with the propagation of a signal in a fractal network. We propose a model which predicts an asymptotically self-similar expansion of deaths in time before containment, and the final death toll under total containment measures, as a function of the delay in taking those measures after the expansion is observed. The physics of the model resembles the expansion of a flame in a homogeneous domain with a fractal dimension 3.75. After containment measures are taken, the natural fractal structure of the network is drastically altered and a secondary evolution is observed. This evolution, akin to the homogeneous combustion in a static isolated enclosure with a final quenching, has a characteristic time of 20.1 days, according to available data of the pandemic behavior in China. The proposed model is remarkably consistent with available data, which supports the simplifying hypotheses made in the model. A universal formulation for a quarantine as a function of that delay is also proposed.