Dataset of COVID-19 outbreak and potential predictive features in the USA

被引：4

作者：

Haratian, Arezoo ^{[1
]}

Fazelinia, Hadi ^{[1
]}

Maleki, Zeinab ^{[1
]}

Ramazi, Pouria ^{[2
]}

Wang, Hao ^{[3
]}

Lewis, Mark A. ^{[3
,4
]}

Greiner, Russell ^{[5
,6
]}

Wishart, David ^{[4
,5
]}

机构：

[1] Isfahan Univ Technol, Dept Elect & Comp Engn, Esfahan 8415683111, Iran

[2] Brock Univ, Dept Math & Stat, St Catharines, ON L2S 3A1, Canada

[3] Univ Alberta, Dept Math & Stat Sci, Edmonton, AB T6G 2G1, Canada

[4] Univ Alberta, Dept Biol Sci, Edmonton, AB T6G 2E9, Canada

[5] Univ Alberta, Dept Comp Sci, Edmonton, AB T6G 2E8, Canada

[6] Alberta Machine Intelligence Inst, Edmonton, AB T5J 3B1, Canada

来源：

DATA IN BRIEF | 2021年 / 38卷

关键词：

COVID-19; Epidemiology; Predictive features; Machine learning;

D O I：

10.1016/j.dib.2021.107360

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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. (C) 2021 The Authors. Published by Elsevier Inc.

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页数：14

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