摘要: 本研究以病例、检测、年龄、住院率和死亡率为输入，考察了 G20 国家的 COVID-19 疫情传播函数之间的关系。研究还显示了各国根据建议的拥挤指数采取的 COVID-19 预防措施的程度。分析了 2020 年 3 月 12 日至 2020 年 5 月 29 日 G20 国家的数据，并从 https://github.com/owid/covid-19 data/blob/master/public/data/owid-covid-data.xlsx 计算了描述性统计数据。面板数据分析用于研究基于所讨论变量的对一次性事件输出值的影响。在检验紧密度指数对死亡人数的影响时，计算出的相关值为 0.7639。据观察，硬度指数每变化一个单位，产量就会增加 7.8017。与这些研究不同，本研究考察了社会因素对病例数量的影响，并使用 R Studio 应用了面板数据分析固定效应模型。同时，还考察了各国采取的措施与病例数量/死亡率之间的关系。

Abstract: In this study, the relationship between the COVID-19 outbreak spreading function, where cases, tests, age, hospitalization rate and mortality were defined as inputs, was examined for G20 countries. It also shows the extent to which countries have taken precautions against COVID-19 with the recommended congestion index. The data of G20 countries between 12.03.2020 and 29.05.2020 were analyzed and descriptive statistics were calculated from https://github.com/owid/covid-19-data/blob/master/public/data/owid- covid-data.xlsx. Panel data analysis is used to investigate the effect on the output value based on the variables in question for an event occurring at once. When examining the effect of the tightness index on the number of deaths, the correlation value was calculated as 0.7639. It has been observed that a one unit change in the hardness index increases production by 7.8017. In our study, unlike these studies, the social factors on the number of cases was examined and Panel Data Analysis Fixed Effects Model was applied using R Studio. At the same time, the relationship between the measures taken by countries and the number of cases / death rates was also examined.