Academic Journal
Dataset of COVID-19 outbreak and potential predictive features in the USA
| Title: | Dataset of COVID-19 outbreak and potential predictive features in the USA |
|---|---|
| Authors: | Arezoo Haratian, Hadi Fazelinia, Zeinab Maleki, Pouria Ramazi, Hao Wang, Mark A. Lewis, Russell Greiner, David Wishart |
| Source: | Data in Brief, Vol 38, Iss , Pp 107360- (2021) |
| Publisher Information: | Elsevier, 2021. |
| Publication Year: | 2021 |
| Collection: | LCC:Computer applications to medicine. Medical informatics LCC:Science (General) |
| Subject Terms: | COVID-19, Epidemiology, Predictive features, Machine learning, Computer applications to medicine. Medical informatics, R858-859.7, Science (General), Q1-390 |
| More Details: | 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. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2352-3409 |
| Relation: | http://www.sciencedirect.com/science/article/pii/S2352340921006429; https://doaj.org/toc/2352-3409 |
| DOI: | 10.1016/j.dib.2021.107360 |
| Access URL: | https://doaj.org/article/fdb1933041c9469e98a4152dded3e2f4 |
| Accession Number: | edsdoj.fdb1933041c9469e98a4152dded3e2f4 |
| Database: | Directory of Open Access Journals |
| ISSN: | 23523409 |
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| DOI: | 10.1016/j.dib.2021.107360 |
| Published in: | Data in Brief |
| Language: | English |