Canton Enriquez Daniel, Niembro-Ceceña Jose A, Muñoz Mandujano Martin, Alarcon Daniel, Arcadia Guerrero Jorge, Gonzalez Garcia Ivan, Montes Gutierrez Agueda Areli, Gutierrez-Lopez Alfonso
Facultad de Informatica, Universidad Autonoma de Queretaro, Juriquilla, Queretaro 76230, Mexico.
Facultad de Ingeniería, Universidad Autonoma de Queretaro, Centro Universitario, Queretaro 76010, Mexico.
Data Brief. 2022 Feb;40:107783. doi: 10.1016/j.dib.2021.107783. Epub 2022 Jan 1.
Worldwide, COVID-19 coronavirus disease is spreading rapidly in a second and third wave of infections. In this context of increasing infections, it is critical to know the probability of a specific number of cases being reported. We collated data on new daily confirmed cases of COVID-19 breakouts in: Argentina, Brazil, China, Colombia, France, Germany, India, Indonesia, Iran, Italy, Mexico, Poland, Russia, Spain, U.K., and the United States, from the 20th of January, 2020 to 28th of August 2021. A selected sample of almost ten thousand data is used to validate the proposed models. Generalized Extreme-Value Distribution Type 1-Gumbel and Exponential (1, 2 parameters) models were introduced to analyze the probability of new daily confirmed cases. The data presented in this document for each country provide the daily probability of rate incidence. In addition, the frequencies of historical events expressed as a return period in days of the complete data set is provided.
在全球范围内，新冠病毒疾病（COVID-19）正在第二波和第三波感染中迅速传播。在这种感染不断增加的背景下，了解报告特定数量病例的概率至关重要。我们整理了2020年1月20日至2021年8月28日期间阿根廷、巴西、中国、哥伦比亚、法国、德国、印度、印度尼西亚、伊朗、意大利、墨西哥、波兰、俄罗斯、西班牙、英国和美国每日新增新冠确诊病例的数据。使用近一万个选定样本数据来验证所提出的模型。引入广义极值分布类型1-耿贝尔分布和指数分布（1, 2参数）模型来分析每日新增确诊病例的概率。本文档中每个国家的数据提供了发病率的每日概率。此外，还提供了以完整数据集的天数重现期表示的历史事件频率。
Zotero 插件
