Dataset of COVID-19 outbreak and potential predictive features in the USA
| Autor: | Hao Wang, Hadi Fazelinia, Pouria Ramazi, Zeinab Maleki, Arezoo Haratian, Mark A. Lewis, David S. Wishart, Russell Greiner |
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| Rok vydání: | 2020 |
| Předmět: |
Driving factors
medicine.medical_specialty 2019-20 coronavirus outbreak Science (General) Multidisciplinary Coronavirus disease 2019 (COVID-19) Epidemiology Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Computer applications to medicine. Medical informatics R858-859.7 Predictive features COVID-19 Outbreak Disease Q1-390 Geography Environmental health Machine learning Pandemic medicine Data Article |
| Zdroj: | Data in Brief Data in Brief, Vol 38, Iss, Pp 107360-(2021) |
| Popis: | 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 September 2020. This data is collected from many public online databases and includes the daily number of COVID-19 confirmed cases and deaths, as well as 33 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. |
| Databáze: | OpenAIRE |
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