美国新冠肺炎疫情数据集及潜在预测特征
Dataset of COVID-19 outbreak and potential predictive features in the USA.
作者信息
Haratian Arezoo, Fazelinia Hadi, Maleki Zeinab, Ramazi Pouria, Wang Hao, Lewis Mark A, Greiner Russell, Wishart David
机构信息
Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran.
Department of Mathematics and Statistics, Brock University, St. Catharines, ON L2S 3A1, Canada.
出版信息
Data Brief. 2021 Oct;38:107360. doi: 10.1016/j.dib.2021.107360. Epub 2021 Sep 10.
This dataset provides information related to the outbreak of COVID-19 disease in the United States, including data from each of 3142 US counties from the beginning of the outbreak (January 2020) until June 2021. This data is collected from many public online databases and includes the daily number of COVID-19 confirmed cases and deaths, as well as 46 features that may be relevant to the pandemic dynamics: demographic, geographic, climatic, traffic, public-health, social-distancing-policy adherence, and political characteristics of each county. We anticipate many researchers will use this dataset to train models that can predict the spread of COVID-19 and to identify the key driving factors.
该数据集提供了与美国新冠肺炎疫情爆发相关的信息，包括从疫情开始（2020年1月）到2021年6月期间美国3142个县的数据。这些数据是从许多公共在线数据库收集而来的，包括新冠肺炎确诊病例和死亡的每日数量，以及46个可能与疫情动态相关的特征：每个县的人口统计学、地理、气候、交通、公共卫生、社交距离政策遵守情况和政治特征。我们预计许多研究人员将使用这个数据集来训练能够预测新冠肺炎传播的模型，并识别关键驱动因素。
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