论文标题
早期对COVID-19爆发进化的预测以及对反应措施有效性的定量评估
Early forecasts of the evolution of the COVID-19 outbreaks and quantitative assessment of the effectiveness of countering measures
论文作者
论文摘要
我们发现，在Covid-19的当前爆发中，新感染的反向分数每日生长的时间演变是通过通用功能准确地描述的，即在我们研究的所有国家中，两参数gumbel累积功能。尽管确定的数据符合数据，但两国之间的两个gumbel参数（甚至在同一国家的不同地区）都不同，这反映了所采用的遏制措施的多样性和功效，但N/DN演变的功能形式似乎是普遍的。在给定区域或国家 /地区拟合的结果似乎在所选时间间隔的变化方面稳定。这使得即使在相对较小的时间段内，也可以从数据数据中稳健地估算两个参数。反过来，这使人们可以通过大量进步和控制良好的置信度，每日新感染的高峰时间，其大小和持续时间（因此全部感染）以及每日新感染减少到预先设定的价值（例如，每天每天2个新的感染）的时间非常有用的时间，这些活动对计划的活动非常有用。我们利用这种形式主义来预测和比较许多国家中Covid-19疾病进化的这些关键特征，并对他们努力计算爆发的努力的成功程度进行定量评估。
We discovered that the time evolution of the inverse fractional daily growth of new infections, N/dN, in the current outbreak of COVID-19 is accurately described by a universal function, namely the two-parameter Gumbel cumulative function, in all countries that we have investigated. While the two Gumbel parameters, as determined bit fits to the data, vary from country to country (and even within different regions of the same country), reflecting the diversity and efficacy of the adopted containment measures, the functional form of the evolution of N/dN appears to be universal. The result of the fit in a given region or country appears to be stable against variations of the selected time interval. This makes it possible to robustly estimate the two parameters from the data data even over relatively small time periods. In turn, this allows one to predict with large advance and well-controlled confidence levels, the time of the peak in the daily new infections, its magnitude and duration (hence the total infections), as well as the time when the daily new infections decrease to a pre-set value (e.g. less than about 2 new infections per day per million people), which can be very useful for planning the reopening of economic and social activities. We use this formalism to predict and compare these key features of the evolution of the COVID-19 disease in a number of countries and provide a quantitative assessment of the degree of success in in their efforts to countain the outbreak.
