COVID-19 Global Data Atlas

The **COVID-19 Global Data Atlas** is your go-to resource for a comprehensive view of the COVID-19 landscape worldwide. We bring together data from various health authorities, both at the national and international levels to help you make informed decisions, assess trends, and gain valuable insights into the ongoing global impact of the COVID-19 Pandemic.

While general COVID-19 data is available at the global level, additional unique data is often published by various national and local governments, reflecting their local nuances. Our atlas embraces this diversity, offering a more detailed and comprehensive perspective compared to global summaries. We curate a growing collection of specific data sources, ensuring you get a richer understanding of the global picture.

Our goal with this product is to make the data more accessible without sacrificing its authenticity. This involves converting non-tabular data into tables, cleaning up column names, and translating non-English terms. The result is a clear and unembellished representation of original published data.

The dataset is updated daily, although the underlying data sources mostly provide weekly summaries. We aim to provide you with the most up-to-date information while respecting the reporting cadence of the original sources.

**Key Attributes**

While different countries and international agencies provide different data, the following kinds of data are generally available:

- **COVID-19 Case and Test Counts**: Numbers of positive tests for COVID-19, numbers of total tests, numbers of diagnoses, etc.
- **COVID-19 Variants**: Counts of laboratory confirmed cases of specific COVID-19 variants.
- **COVID-19 Vaccinations**: Information on vaccine administrations, including providers and dosages.
- **COVID-19 Predictions**: Forward-looking forecasts from various institutions.
- **Hospitalization and Severity**: Some datasets include hospitalization counts for COVID-19 cases.
- **Regional and Demographic Breakdowns**: Some datasets include fine-grained regional, age, gender, or other demographic breakdowns.

**Sources:**
- [Carnegie Mellon University Delphi COVIDcast project](https://delphi.cmu.edu/)
- [Clinical Trials Transformation Initiative](https://ctti-clinicaltrials.org/)
- [COVID-19 Tracker Canada Project](https://covid19tracker.ca/)
- [European Centre for Disease Prevention and Control](https://www.ecdc.europa.eu/en)
- [Government of Canada Health Infobase](https://health-infobase.canada.ca/)
- [Japan Ministry of Health, Labour, and Welfare](https://www.mhlw.go.jp/index.html)
- [Korean Disease Control and Prevention Agency](https://ncv.kdca.go.kr)
- [Ministerio de Sanidad](sanidad.gob.es)
- [Ministero della Salute](https://www.salute.gov.it/portale/home.html)
- [Our World in Data](https://ourworldindata.org/)
- [Prime Minister's Office of Japan](https://www.kantei.go.jp/)
- [République Française](https://www.data.gouv.fr/fr/)
- [Robert Koch Institut](https://www.rki.de/DE/Home/homepage_node.html)
- [Taiwan National Infections Disease Statistics System](https://nidss.cdc.gov.tw/)
- [The New York Times](https://www.nytimes.com/interactive/2021/us/covid-cases.html)
- [UK Government](https://coronavirus.data.gov.uk/)
- [U.S. Centers for Disease Control and Prevention](https://data.cdc.gov)
- [Yu Group](https://www.stat.berkeley.edu/~yugroup/people.html)