论文标题
平坦的Covid-19曲线：全球大流行中的“希腊”案例
Flattening the COVID-19 Curve: The "Greek" case in the Global Pandemic
论文作者
论文摘要
The global crisis caused by the COVID-19 pandemic, in conjunction with the economic consequences and the collapse of health systems, has raised serious concerns in Europe, which is the most affected continent by the pandemic since it recorded 2,388,694 cases and 190,091 deaths (39.6% of the worldwide total), of which 71.7% (136,238) are in the United Kingdom （43,414），意大利（34,708），法国（29,778）和西班牙（28,338）。与其他国家不同，希腊，大约有310例确认病例和每百万的死亡人数约18人，这是对该现象的研究和分析的一个例外。在流行病学和实施术语中，重点介绍了希腊疾病传播的特殊性，本文对希腊的covid-19的时间扩散进行了探索性分析，并提出了一种基于回归量表的模型和预测方法的方法学方法，以基于回归量表的模型和预测总计算法的变化率。此外，它提出了评估和解释疾病传播的社会距离测量方法的混合样条回归和复杂的网络模型。总体方法有助于对公共卫生系统的决策和支持，以及与大流行的斗争。
The global crisis caused by the COVID-19 pandemic, in conjunction with the economic consequences and the collapse of health systems, has raised serious concerns in Europe, which is the most affected continent by the pandemic since it recorded 2,388,694 cases and 190,091 deaths (39.6% of the worldwide total), of which 71.7% (136,238) are in the United Kingdom (43,414), Italy (34,708), France (29,778), and Spain (28,338). Unlike other countries, Greece, with about 310 confirmed cases and 18 deaths per million, is one bright exception in the study and analysis of this phenomenon. Focusing on the peculiarities of the disease spreading in Greece, both in epidemiological and in implementation terms, this paper applies an exploratory analysis of COVID-19 temporal spread in Greece and proposes a methodological approach for the modeling and prediction of the disease based on the Regression Splines algorithm and the change rate of the total infections. Also, it proposes a hybrid spline regression and complex network model of social distance measures evaluating and interpreting the spread of the disease. The overall approach contributes to decision making and support of the public health system and to the fight against the pandemic.
