论文标题
COVID-19大流行的现象学动力学：调整参数的荟萃分析
Phenomenological dynamics of COVID-19 pandemic: meta-analysis for adjustment parameters
论文作者
论文摘要
我们提出了一种处理COVID的现象学程序，即119个不同国家的政府卫生机构提供的数据。我们没有通过调整这些模型中包含的时间（无独立参数）来拟合数据的（精确或近似）解决方案来拟合数据，而是引入了动态参数，其时间依赖性可以通过现象学在现象学上获得充分的脱离日常提供的日常提供的数据来获得。对于我们考虑的国家，这种现象学方法可以及时正确调整感染（和被删除）个体的数量非常有效。此外，它可以处理一些国家可能会遇到的子流行事件。通过这种方式，我们在不使用基于微分方程的任何先验模型的情况下获得了大流行的演变。
We present a phenomenological procedure of dealing with the COVID--19 data provided by government health agencies of eleven different countries. Instead of using the (exact or approximate) solutions to the SIR (or other) model(s) to fit the data by adjusting the time--independent parameters included in those models, we introduce dynamical parameters whose time--dependence may be phenomenologically obtained by adequately extrapolating a chosen subset of the daily provided data. This phenomenological approach works extremely well to properly adjust the number of infected (and removed) individuals in time, for the countries we consider. Besides, it can handle the sub--epidemic events that some countries may experience. In this way, we obtain the evolution of the pandemic without using any a priori model based on differential equations.
