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Covid-19 Regional Metadata and Recoveries
Patient Health Records & Digital Health
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About
This dataset is designed for Covid-19 forecasting challenges, providing cleaned and compiled metadata from various sources. It offers regional data including geographical coordinates, population metrics, and daily recovery figures. The data is structured to support analysis and prediction models for the pandemic.
Columns
- Province_State: Represents the state or province, with 73% missing values. It includes 67 unique entries, with "Australian Capital Territory" being the most common.
- Country_Region: Denotes the country or region, featuring 187 unique entries, with "China" as the most frequent.
- lat: Latitude coordinate for the region.
- lon: Longitude coordinate for the region.
- continent: The continent where the region is located.
- population: The population of the specified region.
- area: The geographical area of the region.
- density: Population density of the region.
- Date: The specific date for which the data is recorded. Dates range from 22 January 2020 to 10 May 2020.
- Recoveries: The number of Covid-19 cases recovered up to the specified date. Values range from 0 to 216,169, with a mean of 1.14k.
Distribution
The dataset is provided in a CSV format, with the file
region_date_metadata.csv having a size of 740.8 kB. It contains 27.7k valid entries across the Date, Country_Region, and Recoveries columns. The date range spans from 22 January 2020 to 10 May 2020.Usage
This dataset is ideal for developing and testing Covid-19 forecasting models, participating in Covid-19 forecasting competitions, and conducting regional analysis of recovery trends during the pandemic.
Coverage
The dataset provides geographical coverage for various regions, including countries and states, with 187 unique countries and 67 unique states. Data is available for dates ranging from 22 January 2020 to 10 May 2020, with recovery figures specifically recorded up to 8 May 2020.
License
CC0: Public Domain
Who Can Use It
Data scientists, researchers, and public health analysts can utilise this dataset for epidemiological studies, predictive modelling of disease progression, and understanding regional recovery patterns. It is particularly relevant for those involved in Covid-19 forecasting challenges.
Dataset Name Suggestions
- Covid-19 Regional Metadata and Recoveries
- Global Covid-19 Recovered Cases & Regional Data
- Covid-19 Forecasting Data (Regions & Recoveries)
- JHU & Wikipedia Covid-19 Daily Recoveries Dataset
Attributes
Original Data Source: Covid-19 Regional Metadata and Recoveries
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