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Abstract：
Complex systems have characteristics that give rise to the emergence of rare and extreme events. This paper addresses an example of such type of crisis, namely the spread of the new Coronavirus disease 2019 (COVID-19). The study deals with the statistical comparison and visualization of country-based real-data for the period December 31, 2019, up to April 12, 2020, and does not intend to address the medical treatment of the disease. Two distinct approaches are considered, the description of the number of infected people across time by means of heuristic models fitting the real-world data, and the comparison of countries based on hierarchical clustering and multidimensional scaling. The computational and mathematical modeling lead to the emergence of patterns, highlighting similarities and differences between the countries, pointing toward the main characteristics of the complex dynamics.
摘要：
复杂系统具有引起罕见和极端事件出现的特征。本文讨论了这种危机的一个例子，即2019年新型冠状病毒病（COVID-19）的传播。该研究涉及2019年12月31日至2020年4月12日期间基于国家的真实数据的统计比较和可视化，并且不打算解决该疾病的医疗问题。考虑了两种不同的方法，通过启发式模型拟合现实世界数据来描述不同时间的感染者数量，以及基于层次聚类和多维缩放的国家比较。计算和数学建模导致了模式的出现，突出国家之间的异同,指向复杂动力学的主要特征。
