论文标题
COVID-19大流行：生长模式，功率定律缩放和饱和度
The COVID-19 pandemic: growth patterns, power law scaling, and saturation
论文作者
论文摘要
由于有效的政府锁定和社会疏远措施，越来越多的国家显示，新的Covid-19感染的数量显着放缓。我们通过本地斜率分析分析了前25个受影响最大的国家的增长行为，并发现了三种不同国家根据锁定协议的严格性遵循的三种不同模式：指数的上升和下降，权力法或逻辑。对于展示电力法增长的国家，我们已经确定了扩展指数。对于表现出强烈的感染率下降的国家，我们推断了感染次数的预期饱和和预期的最终日期。使用了两种不同的外推法（逻辑和抛物线）。两种方法都同意饱和度和结束日期的数量级。用相同的方法分析全球感染率。讨论了这些外推的相关性和准确性。
More and more countries show a significant slowdown in the number of new COVID-19 infections due to effective governmentally instituted lockdown and social distancing measures. We have analyzed the growth behavior of the top 25 most affected countries by means of a local slope analysis and found three distinct patterns that individual countries follow depending on the strictness of the lockdown protocols: exponential rise and fall, power law, or logistic. For countries showing power law growth we have determined the scaling exponents. For countries that showed a strong slowdown in the rate of infections we have extrapolated the expected saturation of the number of infections and the expected final date. Two different extrapolation methods (logistic and parabolic) were used. Both methods agree on the order of magnitude of saturation and end dates. Global infections rates are analyzed with the same methods. The relevance and accuracy of these extrapolations is discussed.
