Determinants of COVID-19 mortality in the United States dataset(BrainX)
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
With the current COVID-19 pandemic, there have been various principal questions left unanswered. In response to these vital questions, many leading health professionals and researchers have brought forward new datasets.
This data set uses several trusted sources to provide reliable information relating to the socioeconomic, racial, weather, healthcare resource utilization and travel data from all of the 50 states of the United States of America including District of Columbia in one dataset. The dataset includes numerous possible determinants of COVID-19 spread and mortality, all organized in a simple spreadsheet.COVID-19 positive rates and mortality in the dataset were obtained from https://covidtracking.com/data. All the data is accurate as of April 30,2020, reported through the sources.
Two researchers collected data from available resources which include governmental and non-governmental sources.(See article and source table references below).
With this dataset, explainable machine learning models showing relationship of these determinants with COVID-19 mortality in the United States cases were created.
Reference: Mathur P, Sethi T, Mathur A, et al. Explainable machine learning models to understand determinants of COVID-19 mortality in the United States. medRxiv. 2020:2020.2005.2023.20110189.(Source table for the dataset is available as supplemental to this article.)
This particular dataset was created for the purpose of continuing research into COVID-19. However, there are many other uses for this large dataset. With information from all 50 states and the District of Columbia, many US statistics can be compared.The data from this dataset can also be used to make new datasets with different purposes.