4.1 Article Data Paper

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

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DATA IN BRIEF
卷 38, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.dib.2021.107360

关键词

COVID-19; Epidemiology; Predictive features; Machine learning

资金

  1. Alberta Innovates [RES0052027]
  2. Pfizer
  3. Isfahan University of Technology [4300/1011]

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This dataset contains information on the COVID-19 outbreak in the United States, covering each of 3142 US counties from January 2020 to June 2021. It includes daily confirmed cases and deaths, as well as 46 features related to demographics, geography, climate, traffic, public health, social distancing policies, and political characteristics of each county. Researchers are expected to use this dataset to build models for predicting the spread of COVID-19 and identifying key driving factors.
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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